feat(timeseries): unify element history queries

Result validation bypassed the project-specific GIS transform and called ST_Transform on custom engineering SRIDs. Read project and map coordinates from gis.junctions so every project uses its configured publication transform.

.dockerignore

@@ -0,0 +1,22 @@
+.git
+.github
+.gitea
+__pycache__/
+.pytest_cache/
+.mypy_cache/
+.venv/
+venv/
+build/
+dist/
+package/
+temp/
+data/
+db_inp/
+inp/
+.env
+.env.*
+logs/
+coverage/
+*.pyc
+*.dump
+app/algorithms/pipe_health_prediction/model/my_survival_forest_model_quxi.joblib

.env.example

@@ -1,19 +1,16 @@
 # TJWater Server 环境变量配置模板
 # 复制此文件为 .env 并填写实际值
-ENVIRONMENT="local"
+# CI/CD: 生产环境变量由 Dev 主机的受控 backend.env 注入，不要将完整 .env 保存为 Gitea 仓库密钥。
+ENVIRONMENT="production"
 NETWORK_NAME="tjwater"
 # ============================================
-# 安全配置 (必填)
+# 敏感配置加密 (必填)
 # ============================================
 
-# JWT 密钥 - 用于生成和验证 Token
-# 生成方式: openssl rand -hex 32
-SECRET_KEY=your-secret-key-here-change-in-production-use-openssl-rand-hex-32
-
-# 数据加密密钥 - 用于敏感数据加密
+# Fernet 格式，生产环境必须替换为独立密钥
 # 生成方式: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
-ENCRYPTION_KEY=
-DATABASE_ENCRYPTION_KEY="rJC2VqLg4KrlSq+DGJcYm869q4v5KB2dFAeuQTe0I50="
+# 用于项目数据库 DSN、GeoServer 管理密码等敏感配置
+DATABASE_ENCRYPTION_KEY="replace-with-generated-fernet-key"
 
 # ============================================
 # 数据库配置 (PostgreSQL)
@@ -42,10 +39,52 @@ METADATA_DB_PORT="5432"
 METADATA_DB_USER="tjwater"
 METADATA_DB_PASSWORD="password"
 
+# Per-project synchronous connection pools
+PROJECT_PG_CACHE_SIZE="16"
+PROJECT_TS_CACHE_SIZE="16"
+PROJECT_PG_POOL_MIN_SIZE="0"
+PROJECT_PG_POOL_SIZE="4"
+PROJECT_PG_MAX_OVERFLOW="2"
+PROJECT_TS_POOL_MIN_SIZE="0"
+PROJECT_TS_POOL_MAX_SIZE="4"
+WNDB_SCHEMA_TEMPLATE_DB_NAME="tjwater_v2_schema_template"
+TIMESCALEDB_SCHEMA_TEMPLATE_DB_NAME="tjwater_v2_timescale_template"
+WNDB_TEMP_DB_MAX_COUNT="8"
+
+# ============================================
+# GeoServer 项目供应
+# ============================================
+GEOSERVER_URL="http://localhost:8080/geoserver"
+GEOSERVER_USERNAME="admin"
+GEOSERVER_PASSWORD="password"
+# 留空时分别复用 DB_HOST / DB_PORT / DB_USER / DB_PASSWORD。
+# GeoServer 在容器内运行时，GEOSERVER_DB_HOST 通常应填写数据库服务名。
+GEOSERVER_DB_HOST=""
+GEOSERVER_DB_PORT=""
+GEOSERVER_DB_USER=""
+GEOSERVER_DB_PASSWORD=""
+# 30 天客户端缓存，单位为秒。
+GEOSERVER_CLIENT_CACHE_SECONDS="2592000"
+
 # ============================================
 # Keycloak JWT (可选)
 # ============================================
 KEYCLOAK_PUBLIC_KEY="-----BEGIN PUBLIC KEY-----\n...\n-----END PUBLIC KEY-----"
 KEYCLOAK_ALGORITHM=RS256
 KEYCLOAK_AUDIENCE="account"
+KEYCLOAK_ACCESS_TOKEN_MAX_AGE_SECONDS=900
 
+
+# ============================================
+# Bocha Web Search API
+# ============================================
+BOCHA_API_KEY="sk-your-bocha-api-key"
+BOCHA_WEB_SEARCH_URL="https://api.bochaai.com/v1/web-search"
+BOCHA_WEB_SEARCH_TIMEOUT_SECONDS=30
+
+# ============================================
+# Tianditu Geocoding API
+# ============================================
+TIANDITU_GEOCODER_TOKEN="your-tianditu-geocoder-token"
+TIANDITU_GEOCODER_URL="https://api.tianditu.gov.cn/geocoder"
+TIANDITU_GEOCODER_TIMEOUT_SECONDS=30

.gitea/workflows/package.yml

@@ -0,0 +1,22 @@
+name: Server CI/CD v2
+
+on:
+  push:
+    tags:
+      - "v*"
+  workflow_dispatch: {}
+
+jobs:
+  build-test-publish-and-deploy:
+    uses: OrgTJWater/ci-templates/.gitea/workflows/container-cd.yml@68c8a9855391baa31d31523674f5812cd24ec604
+    with:
+      image_name: gitea.waternetwork.cn/orgtjwater/tjwater-backend
+      dockerfile: Dockerfile
+      build_context: .
+      test_target: test
+      deploy_service: backend
+      deploy_host: 192.168.1.114
+    secrets:
+      REGISTRY_USERNAME: ${{ secrets.REGISTRY_USERNAME }}
+      REGISTRY_PASSWORD: ${{ secrets.REGISTRY_PASSWORD }}
+      DEV_DEPLOY_SSH_KEY: ${{ secrets.DEV_DEPLOY_SSH_KEY }}

.github/copilot-instructions.md

@@ -1,82 +0,0 @@
-# Copilot Instructions for TJWater Server
-
-This repository contains the backend code for the TJWater Server, a water distribution network management system built with FastAPI.
-
-## High-Level Architecture
-
-The application follows a layered architecture:
-
-- **Entry Point**: `app/main.py` initializes the FastAPI application, database connections (PostgreSQL & TimescaleDB), and middleware.
-- **API Layer**: `app/api/v1` contains the route handlers.
-- **Service Layer**: `app/services` contains business logic and orchestration.
-- **Infrastructure Layer**: `app/infra` handles database connections (`db`), audit logging (`audit`), and external integrations.
-- **Domain Layer**: `app/domain` likely contains core domain models.
-- **Native/Algorithms**: `app/native` and `app/algorithms` handle specialized water network calculations (possibly using EPANET/WNTR).
-
-## Build, Test, and Run Commands
-
-### Environment Setup
-
-- Dependencies are listed in `requirements.txt`.
-- Configuration is managed via environment variables (see `.env.example` if available, or `app/core/config.py`).
-- **Important**: Ensure `.env` is configured with correct database credentials for both PostgreSQL and TimescaleDB.
-
-If first time setting up, you may want to create a Conda environment:
-
-```bash
-conda create -n server python=3.12
-conda activate server
-pip install uv
-uv pip install -r requirements.txt
-conda install -c conda-forge pymetis
-```
-
-### Running the Server
-
-The preferred way to run the server locally is using the helper script which sets up the Python path correctly:
-
-```bash
-conda activate server
-python scripts/run_server.py
-```
-
-Alternatively, you can run directly with uvicorn (ensure PYTHONPATH includes the root):
-
-```bash
-conda activate server
-uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
-```
-
-### Running Tests
-
-Use `pytest` to run tests. The `tests/conftest.py` handles path setup.
-
-```bash
-# Run all tests
-pytest
-
-# Run a specific test file
-pytest tests/unit/test_specific_file.py
-
-# Run a specific test case
-pytest tests/unit/test_specific_file.py::test_function_name
-```
-
-### Building (Optional)
-
-The project includes scripts to compile Python modules to `.pyd` files using Cython (see `scripts/build_pyd.py`). This is likely for distribution/performance but not required for standard development.
-
-## Key Conventions
-
-- **Async/Await**: The codebase heavily uses `async` and `await` for I/O operations, especially database interactions.
-- **Database Management**:
-  - Connections are managed globally in `app.infra.db` and initialized in `lifespan` (app/main.py).
-  - Use `app.infra.db.dynamic_manager` for project-specific database connections (multi-tenancy/dynamic projects).
-- **Pydantic**: extensively used for data validation and settings management.
-- **Scripts**: The `scripts/` directory contains many utility scripts for maintenance, data processing, and server management. Check there before writing new operational scripts.
-- **Water Network Modeling**: Interactions with water network models often involve `epanet` or `wntr` libraries. Be aware of domain-specific terminology (nodes, links, junctions, tanks).
-
-## Code Style
-
-- Follow standard PEP 8 guidelines.
-- No specific linter configuration was found, so default to standard Python formatting.

.github/workflows/build-package.yml

@@ -1,128 +0,0 @@
-name: Build And Package
-
-on:
-  push:
-    tags:
-      - "v*"
-
-jobs:
-  build-package:
-    runs-on: ${{ matrix.os }}
-    env:
-      FORCE_JAVASCRIPT_ACTIONS_TO_NODE24: true
-    strategy:
-      fail-fast: false
-      matrix:
-        os: [ubuntu-latest, windows-latest]
-
-    steps:
-      - name: Checkout source
-        uses: actions/checkout@v5
-
-      - name: Setup Python
-        uses: actions/setup-python@v6
-        with:
-          python-version: "3.12"
-
-      - name: Install system build tools
-        if: runner.os == 'Linux'
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential
-
-      - name: Install compile dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install cython setuptools wheel
-
-      - name: Run Cython compile
-        run: |
-          python scripts/compile.py
-
-      - name: Prepare package and archive
-        run: |
-          python - <<'PY'
-          import os
-          import shutil
-          import tarfile
-          import zipfile
-          import sys
-          from pathlib import Path
-
-          root = Path.cwd()
-          package_dir = root / "package"
-          dist_dir = root / "dist"
-
-          for d in [package_dir, dist_dir]:
-            if d.exists():
-              shutil.rmtree(d)
-            d.mkdir(parents=True, exist_ok=True)
-
-          # Define directories with compiled artifacts
-          compile_dirs = ["app/services", "app/native/wndb", "app/algorithms"]
-          # Global ignore list
-          ignore_names = {
-            ".git",
-            ".github",
-            "__pycache__",
-            ".pytest_cache",
-            ".mypy_cache",
-            ".venv",
-            "venv",
-            "temp",
-            "tests",
-            "package",
-            "dist",
-          }
-
-          def ignore_func(directory, names):
-            rel_dir = os.path.relpath(directory, root).replace("\\", "/")
-            is_in_compile_path = any(rel_dir.startswith(d) for d in compile_dirs)
-            
-            ignored = []
-            for name in names:
-              if name in ignore_names or name.endswith(".pyc"):
-                ignored.append(name)
-              # Exclude source .py files only in compiled directories
-              elif is_in_compile_path and name.endswith(".py"):
-                ignored.append(name)
-            return ignored
-
-          for item in root.iterdir():
-            if item.name in ignore_names:
-              continue
-            target = package_dir / item.name
-            if item.is_dir():
-              shutil.copytree(item, target, ignore=ignore_func)
-            else:
-              shutil.copy2(item, target)
-
-          # Safety guard: ensure no .github directory remains
-          github_paths = [p for p in package_dir.rglob(".github") if p.is_dir()]
-          for p in github_paths:
-            shutil.rmtree(p, ignore_errors=True)
-
-          sha = os.environ["GITHUB_SHA"]
-          run_os = os.environ["RUNNER_OS"].lower()
-
-          if run_os == "windows":
-            archive_path = dist_dir / f"tjwater-server-{run_os}-{sha}.zip"
-            with zipfile.ZipFile(archive_path, "w", compression=zipfile.ZIP_DEFLATED) as zf:
-              for f in package_dir.rglob("*"):
-                if f.is_file():
-                  zf.write(f, f.relative_to(package_dir))
-          else:
-            archive_path = dist_dir / f"tjwater-server-{run_os}-{sha}.tar.gz"
-            with tarfile.open(archive_path, "w:gz") as tf:
-              tf.add(package_dir, arcname=".")
-
-          print(f"Archive created: {archive_path}")
-          PY
-        shell: bash
-
-      - name: Upload package artifact
-        uses: actions/upload-artifact@v5
-        with:
-          name: tjwater-server-package-${{ runner.os }}
-          path: dist/*
-          retention-days: 14

.gitignore

@@ -6,4 +6,5 @@ build/
 .env
 *.dump
 .vscode/
-app/algorithms/health/model/my_survival_forest_model_quxi.joblib
+app/algorithms/pipe_health_prediction/model/my_survival_forest_model_quxi.joblib
+/inp/

AGENTS.md

@@ -0,0 +1,38 @@
+# Repository Guidelines
+
+## Project Structure & Module Organization
+
+This repository contains the TJWater Python backend. Main application code lives in `app/`: API routes under `app/api`, authentication in `app/auth`, configuration in `app/core`, database and repository code in `app/infra`, domain models/schemas in `app/domain`, and business logic in `app/services` and `app/algorithms`.
+
+Tests are under `tests/`, split into `tests/unit`, `tests/api`, and `tests/auth`. SQL and sample assets are stored in `resources/`; deployment files are in `Dockerfile`, `.gitea/workflows/package.yml`, and `infra/docker/docker-compose.yml`. Local data directories such as `db_inp/`, `temp/`, `data/`, and `.env` are ignored and should not be committed.
+
+## Build, Test, and Development Commands
+
+Use the existing conda environment when available:
+
+```bash
+conda run -n server python -m pytest tests/unit tests/auth -q
+conda run -n server uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
+docker build -t tjwater-server:local .
+docker compose -f infra/docker/docker-compose.yml config
+```
+
+`pytest` runs backend tests. `uvicorn` starts the FastAPI app locally. `docker build` verifies the container image. `docker compose config` validates compose syntax and variable expansion.
+
+## Coding Style & Naming Conventions
+
+Use Python 3.12, four-space indentation, type hints for new public functions, and explicit imports. Keep API endpoint modules grouped by domain under `app/api/v1/endpoints`. Use `snake_case` for files, functions, and variables; `PascalCase` for classes and Pydantic models. Prefer existing repository/service patterns in `app/infra/db` and `app/services` over introducing new abstractions.
+
+## Testing Guidelines
+
+The project uses `pytest`. Name test files `test_*.py` and test functions `test_*`. Keep unit tests isolated with fakes or monkeypatching from `tests/conftest.py`. Some existing tests depend on local data outside the repository; avoid adding new tests that require untracked files. For API changes, add or update tests in `tests/api`.
+
+## Commit & Pull Request Guidelines
+
+History uses a mix of Conventional Commit prefixes and concise Chinese messages, for example `feat(api): add Tianditu geocoding` or `fix(auth): validate project context`. Prefer `feat(scope): ...`, `fix(scope): ...`, or a clear Chinese summary.
+
+Pull requests should describe the behavior change, list verification commands, mention configuration or migration impacts, and link related issues. Include API examples or screenshots only when they clarify user-facing behavior.
+
+## Security & Configuration Tips
+
+Do not commit `.env`, database dumps, generated caches, or local project data. Use `.env.example` as the configuration template. CI/CD only uses Gitea repository secrets `REGISTRY_USERNAME`, `REGISTRY_PASSWORD`, and `DEV_DEPLOY_SSH_KEY`; production application settings are injected on the Dev host.

AUTHENTICATION_AND_USER_MANAGEMENT.md

@@ -0,0 +1,117 @@
+# TJWater Authentication and Metadata Management
+
+## Ownership
+
+Keycloak owns login identity, credentials, token issuance, and token expiry.
+TJWater metadata stores only business snapshots and authorization data:
+
+- `users.keycloak_id` is the stable identity binding.
+- `users.username`, `users.email`, and `users.last_login_at` are Keycloak claim caches.
+- `users.role`, `users.is_active`, and `users.is_superuser` control TJWater system access.
+- `user_project_membership.project_role` controls project access.
+
+The backend does not accept passwords, does not issue local JWTs, and does not
+trust frontend-supplied user IDs.
+
+## Fixed Project RBAC
+
+Project roles are stored directly in
+`user_project_membership.project_role`; there is no separate role table or
+user-defined permission editor in this delivery.
+
+| Role | Main access |
+| --- | --- |
+| `modeler` | Model upload/import, simulation, burst, risk, and optimization analysis |
+| `dispatcher` | SCADA cleaning, simulation and burst analysis |
+| `auditor` | Project read access and project-scoped audit logs |
+| `viewer` | WebGIS and read-only risk results |
+
+Legacy `owner`, `admin`, and `member` values remain supported for existing
+records. The backend is the authorization boundary; the frontend uses
+`GET /api/v1/access/context` only to hide unavailable menus and guard routes.
+System admins receive environment, membership, and global-audit permissions,
+but still need a project membership for project business APIs.
+
+## Login Snapshot Refresh
+
+Every authenticated metadata-user resolution validates the Keycloak access token
+and reads `sub`, `preferred_username`, and `email` claims. The
+backend finds `users` by `keycloak_id = sub`, rejects inactive or missing users,
+then refreshes `username`, `email`, and `last_login_at`.
+
+This keeps local display data current without changing the identity binding.
+There is no Keycloak webhook requirement; second-level user or permission sync is
+out of scope unless explicitly requested later.
+
+## Admin APIs
+
+All admin APIs require metadata admin access: `users.is_superuser = true` or
+`users.role = 'admin'`.
+
+User and membership management:
+
+- `GET /api/v1/admin/me`
+- `POST /api/v1/admin/users/sync`
+- `POST /api/v1/admin/users/sync/batch`
+- `GET /api/v1/admin/users`
+- `GET /api/v1/admin/users/{user_id}`
+- `PATCH /api/v1/admin/users/{user_id}`
+- `GET /api/v1/admin/projects/{project_id}/members`
+- `POST /api/v1/admin/projects/{project_id}/members`
+- `PATCH /api/v1/admin/projects/{project_id}/members/{user_id}`
+- `DELETE /api/v1/admin/projects/{project_id}/members/{user_id}`
+
+Project configuration:
+
+- `GET /api/v1/admin/projects`
+- `POST /api/v1/admin/projects`
+- `PATCH /api/v1/admin/projects/{project_id}`
+- `GET /api/v1/admin/projects/{project_id}/databases`
+- `PUT /api/v1/admin/projects/{project_id}/databases`
+- `DELETE /api/v1/admin/projects/{project_id}/databases/{db_role}`
+- `POST /api/v1/admin/projects/{project_id}/databases/{db_role}/health`
+
+## Secret Handling
+
+Admins submit plaintext DSNs only through HTTPS admin APIs. Operators should not
+write encrypted columns manually.
+
+- `project_databases.dsn_encrypted` is encrypted with `DATABASE_ENCRYPTION_KEY`.
+- Admin responses return only `has_dsn`.
+- Audit logs record whether a secret was updated, but never store plaintext DSNs
+  or other secrets.
+
+Generate the database encryption key with:
+
+```bash
+python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
+```
+
+Keep keys stable for the lifetime of encrypted metadata. Rotating a key requires
+decrypting with the old key and re-encrypting with the new key.
+
+## Metadata Schema Patches
+
+Apply metadata patches in order:
+
+1. `resources/sql/004_metadata_auth_management.sql`
+2. `resources/sql/005_metadata_project_configuration.sql`
+3. `resources/sql/006_metadata_rbac_roles.sql`
+
+`004` creates Keycloak-backed metadata users and project memberships. `005`
+creates project and project database routing tables with uniqueness, role/type,
+and pool-size constraints. `006` extends existing membership constraints with
+the fixed delivery roles.
+
+## Frontend System Management
+
+`/system-admin` is shown only when `GET /api/v1/access/context` returns
+`environment.manage`. The page lets admins maintain metadata users, project
+members, projects, project database routing for `biz_data` and `iot_data`, and
+connection health checks. This replaces direct SQL editing for normal project
+onboarding.
+
+Hydraulic model authoring is outside the Web application. Models are prepared
+in the desktop modeling client and uploaded/imported by an authorized modeler;
+the system administrator configures the project environment and database
+routing.

BACKEND_NAMING_AUDIT.md

@@ -0,0 +1,77 @@
+# Backend Naming Audit
+
+DOC-003 audit for the internal `TJWaterServerBinary` backend.
+
+## Scope
+
+Reviewed FastAPI route decorators under `app/api/v1/endpoints`, router prefixes in `app/api/v1/router.py`, and public request/response schema fields in `app/api` and `app/domain`.
+
+The backend is mounted only under `/api/v1` from `app/main.py`; the old no-prefix router include remains commented out.
+
+## Current Good Surface
+
+These newer routes already follow the naming rule for public HTTP paths:
+
+- Metadata/admin: `/api/v1/admin/projects`, `/api/v1/admin/users/sync`, `/api/v1/admin/projects/{project_id}/members`
+- Audit: `/api/v1/audit/logs`, `/api/v1/audit/logs/count`
+- Agent auth: `/api/v1/agent/auth/context`
+- Business APIs: `/api/v1/burst-detection/detect`, `/api/v1/burst-location/locate`, `/api/v1/leakage/identify`
+- Time-series APIs: `/api/v1/scada/by-ids-time-range`, `/api/v1/scada/by-ids-field-time-range`, `/api/v1/composite/clean-scada`
+- Project data APIs: `/api/v1/scada-info`, `/api/v1/scheme-list`, `/api/v1/burst-locate-result`
+- Web integrations: `/api/v1/web-search`, `/api/v1/geocode`
+
+Path template parameters such as `{project_id}`, `{user_id}`, `{device_id}`, `{scheme_name}`, and `{link_id}` intentionally remain `snake_case`.
+
+## Legacy URL Categories
+
+### Keep With Compatibility
+
+These now have `kebab-case` aliases. The frontend has been migrated to the replacement paths; keep the old paths as deprecated compatibility aliases for Agent planning, tests, customer scripts, or external callers:
+
+| Current URL | Suggested replacement |
+| --- | --- |
+| `/api/v1/openproject/` | `/api/v1/projects/open` |
+| `/api/v1/project_info/` | `/api/v1/project-info` |
+| `/api/v1/getallschemes/` | `/api/v1/schemes` |
+| `/api/v1/getallsensorplacements/` | `/api/v1/sensor-placement-schemes` |
+| `/api/v1/sensorplacementscheme/create` | `/api/v1/sensor-placement-schemes` |
+| `/api/v1/burst_analysis/` | `/api/v1/burst-analysis` |
+| `/api/v1/valve_isolation_analysis/` | `/api/v1/valve-isolation-analysis` |
+| `/api/v1/flushing_analysis/` | `/api/v1/flushing-analysis` |
+| `/api/v1/contaminant_simulation/` | `/api/v1/contaminant-simulation` |
+| `/api/v1/runsimulationmanuallybydate/` | `/api/v1/simulations/run-by-date` |
+
+### Broad Legacy Surface
+
+These route groups expose many command-style concatenated paths. They should not be copied into new work; replace only when a caller migration is planned:
+
+- Project lifecycle: `listprojects`, `createproject`, `deleteproject`, `isprojectopen`, `closeproject`, `copyproject`, `importinp`, `exportinp`, `readinp`, `dumpinp`, `lockproject`, `unlockproject`
+- Network object CRUD: `addjunction`, `getjunctionelevation`, `setpipediameter`, `getvalvesetting`, and similar junction/pipe/pump/tank/reservoir/valve routes
+- Region/DMA/VD commands: `calculatedistrictmeteringareaforregion`, `getdistrictmeteringarea`, `generatevirtualdistrict`, and related routes
+- SCADA native CRUD: `getscadadevice`, `setscadadevicedata`, `cleanscadaelement`, and related routes
+- Snapshot/synchronization utilities: `takesnapshotforoperation`, `syncwithserver`
+- Advanced simulation endpoints with underscore paths: `pressure_regulation`, `daily_scheduling_analysis`, `network_update`, `pressure_sensor_placement_kmeans`
+
+### Direct Cleanup Candidates
+
+These are likely safe only after confirming no caller uses them:
+
+- `/api/v1/test_dict/`: development/test utility in `misc.py`.
+- `/api/v1/takenapshotforcurrentoperation`: typo compatibility path; keep deprecated if any client may still call it.
+- `/api/v1/getpumpenergyproperties//` and `/api/v1/setpumpenergyproperties//`: double-slash paths in options endpoints.
+
+## Field Naming
+
+Most public JSON, query, and SSE fields are already `snake_case`, including `project_id`, `user_id`, `scheme_name`, `scheme_type`, `start_time`, `end_time`, `device_ids`, `session_id`, and `request_id`.
+
+Known legacy exception:
+
+- `BurstAnalysis.burst_ID` in `app/api/v1/endpoints/simulation.py` should become `burst_id` on a new API contract. Preserve `burst_ID` only for the legacy body shape.
+
+Headers keep standard HTTP casing:
+
+- `X-Project-Id`
+
+## Recommendation
+
+Do not rename existing legacy routes in place. For each active legacy route, keep the new `kebab-case` alias as the documented path, keep the old route marked deprecated, migrate remaining Agent/customer/script callers, then remove only after a documented compatibility window.

Dockerfile

@@ -1,25 +1,42 @@
-FROM continuumio/miniconda3:latest
+FROM condaforge/miniforge3:latest AS base
 
 WORKDIR /app
 
+ENV PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple \
+    PIP_TRUSTED_HOST=pypi.tuna.tsinghua.edu.cn \
+    UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
+
 # 安装 Python 3.12 和 pymetis (通过 conda-forge 避免编译问题)
-RUN conda install -y -c conda-forge python=3.12 pymetis && \
-    conda clean -afy
+RUN mamba install -y python=3.12 pymetis && \
+    mamba clean -afy
 
 COPY requirements.txt .
-RUN pip install uv
+RUN pip install --no-cache-dir uv
 RUN uv pip install --system --no-cache-dir -r requirements.txt
 
-# 将代码放入子目录 'app'，将数据放入子目录 'db_inp'
-# 这样临时文件默认会生成在 /app 下，而代码在 /app/app 下，实现了分离
+# 本地数据目录和环境变量在运行时通过 Compose 挂载或注入，
+# 不应进入镜像构建上下文。
 COPY app ./app
-COPY db_inp ./db_inp
-COPY temp ./temp
-COPY .env .
+COPY contracts ./contracts
+COPY infra ./infra
+COPY resources ./resources
+RUN python -c "from pathlib import Path; from zipfile import ZipFile; model_dir = Path('app/algorithms/pipe_health_prediction/model'); zip_path = model_dir / 'my_survival_forest_model_quxi.zip'; joblib_name = 'my_survival_forest_model_quxi.joblib'; joblib_path = model_dir / joblib_name; assert zip_path.exists(), f'Model archive not found: {zip_path}'; archive = ZipFile(zip_path); archive.extract(joblib_name, model_dir); archive.close(); assert joblib_path.exists(), f'Model file not extracted: {joblib_path}'" && \
+    rm -f app/algorithms/pipe_health_prediction/model/my_survival_forest_model_quxi.zip
+RUN mkdir -p db_inp temp data inp
 
 # 设置 PYTHONPATH 以便 uvicorn 找到 app 模块
 ENV PYTHONPATH=/app
 
+FROM base AS test
+COPY scripts ./scripts
+COPY tests ./tests
+RUN python -m compileall -q app && \
+    python -c "import app.main" && \
+    python scripts/check_openapi.py && \
+    pytest -q tests
+
+FROM base AS runner
+
 EXPOSE 8000
 
 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "4"]

README.md

@@ -0,0 +1,108 @@
+# TJWaterServerBinary 内部后端
+
+`TJWaterServerBinary` 是 TJWater 内部版 Python 后端，基于 FastAPI 提供认证、项目、管网、模拟、爆管、漏损、SCADA 和地图服务集成能力。该仓库用于内部开发和完整功能维护。
+
+## 技术栈
+
+- Python 3.12
+- FastAPI / Uvicorn
+- Pydantic / SQLAlchemy / psycopg
+- PostgreSQL、PostGIS、TimescaleDB
+- WNTR、EPANET、Cython、科学计算与空间分析依赖
+- pytest
+
+## 目录结构
+
+```text
+app/main.py           FastAPI 入口
+app/api/              HTTP API 路由
+app/auth/             认证和权限上下文
+app/core/             配置、日志和基础设施初始化
+app/domain/           领域模型和 Pydantic schema
+app/infra/            数据库、EPANET 和外部集成
+app/services/         业务服务编排
+app/algorithms/       管网算法、模拟、爆管、漏损、清洗和健康分析
+app/native/           本地管网数据读写与转换
+tests/                后端测试
+resources/            SQL、模板和示例资源
+infra/docker/         Docker Compose 编排
+```
+
+## 本地开发
+
+推荐使用已有 conda 环境：
+
+```bash
+conda run -n server python -m pytest tests/unit tests/auth -q
+conda run -n server uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
+```
+
+如需要进入环境：
+
+```bash
+conda activate server
+```
+
+## 常用命令
+
+```bash
+conda run -n server python -m pytest tests -q
+conda run -n server python scripts/run_server.py
+docker build -t tjwater-server:local .
+docker compose -f infra/docker/docker-compose.yml config
+```
+
+- `pytest`：运行自动化测试。
+- `scripts/run_server.py`：使用项目脚本启动服务。
+- `docker build`：构建后端镜像。
+- `docker compose config`：检查 compose 配置和变量展开。
+
+## 开发规范
+
+- Python 文件、函数、变量、Pydantic 字段、JSON body 字段和 query 参数使用 `snake_case`。
+- Python 类和 Pydantic 模型使用 `PascalCase`。
+- 新 HTTP 路径使用 `kebab-case`，例如 `/api/v1/pressure-status/analyze`。
+- 优先复用现有 FastAPI/service/repository 边界。
+- 不要把临时数据、数据库 dump、日志或本地运行产物纳入提交。
+
+## 项目数据库路由
+
+项目级 REST 请求通过 `X-Project-Id` 解析元数据中的数据库配置：
+
+- `biz_data` DSN 用于管网业务数据。每个物理业务库使用同名 `_template` 数据库，通过逻辑订阅只同步 `network` schema；模拟临时库从该项目模板克隆。`WNDB_SCHEMA_TEMPLATE_DB_NAME`（当前为 `tjwater_v2_schema_template`）仅用于创建空业务库和 INP 导入暂存库。
+- `iot_data` DSN 用于 TimescaleDB，始终使用元数据配置的完整 DSN，不再从项目代码推导数据库名。
+- 元数据、业务库和 TimescaleDB 可以部署在同一主机，也可以分别部署。
+
+完整新建供水项目使用 `POST /api/v1/admin/project-provisions`，以
+`multipart/form-data` 同时提交 `name`、小写 `code`、可选的
+`description`、`gs_workspace`、`map_zoom` 和 INP `file`。工作流会按顺序完成：
+
+1. EPANET 校验 INP，并从空结构模板创建业务库、导入模型；
+2. 创建同名 `_template`，复制 32 张 `network` 表并建立逻辑订阅；
+3. 从 `TIMESCALEDB_SCHEMA_TEMPLATE_DB_NAME` 创建空时序库；
+4. 创建 GeoServer 工作空间、PostGIS 数据存储和 7 个 GIS 图层，将客户端缓存设为 `GEOSERVER_CLIENT_CACHE_SECONDS`；
+5. 最后在一个元数据事务中写入项目、两条加密数据库路由和创建者成员关系，并将项目设为 `active`。
+
+基础设施任一步失败时按 GeoServer、时序库、管网模板、业务库的逆序清理；元数据提交失败也执行同样清理。旧 `POST /admin/projects` 仅保留给已经由外部流程创建好的资源登记使用，并已标记为 deprecated。
+
+使用模板复制或临时方案库的模拟功能时，`biz_data` 账号必须具备数据库创建和删除权限；只有显式删除项目时才会终止该项目的现有数据库会话，普通复制不会主动中断复制源会话。
+
+## 测试与发布
+
+提交前根据改动范围运行最小有效测试：
+
+```bash
+conda run -n server python -m pytest tests/unit tests/auth -q
+```
+
+发布镜像前建议运行：
+
+```bash
+docker build -t tjwater-server:local .
+```
+
+Gitea 包工作流位于 `.gitea/workflows/package.yml`，通常由 tag 触发构建、推送镜像并通知部署 webhook。
+
+## 安全规则
+
+不要提交 `.env`、客户数据、数据库 dump、日志、生成缓存、`db_inp/`、`temp/`、`data/` 或本地密钥。CI/CD 凭据应放在 Gitea secrets 和仓库变量中。

app/algorithms/__init__.py

@@ -1,36 +1,5 @@
-from app.algorithms.cleaning import flow_data_clean, pressure_data_clean
-from app.algorithms.sensor import (
-    pressure_sensor_placement_sensitivity,
-    pressure_sensor_placement_kmeans,
-)
-from app.algorithms.isolation.valve import valve_isolation_analysis
-from app.algorithms.leakage import LeakageIdentifier
-from app.algorithms.health import PipelineHealthAnalyzer
-from app.algorithms.burst_location import run_burst_location
-from app.algorithms.simulation.scenarios import (
-    convert_to_local_unit,
-    burst_analysis,
-    valve_close_analysis,
-    flushing_analysis,
-    contaminant_simulation,
-    age_analysis,
-    pressure_regulation,
-)
+"""Pure water-network calculation packages.
 
-__all__ = [
-    "flow_data_clean",
-    "pressure_data_clean",
-    "pressure_sensor_placement_sensitivity",
-    "pressure_sensor_placement_kmeans",
-    "convert_to_local_unit",
-    "burst_analysis",
-    "valve_close_analysis",
-    "flushing_analysis",
-    "contaminant_simulation",
-    "age_analysis",
-    "pressure_regulation",
-    "valve_isolation_analysis",
-    "LeakageIdentifier",
-    "PipelineHealthAnalyzer",
-    "run_burst_location",
-]
+Application workflows belong in :mod:`app.services`; database and external
+system access belongs in :mod:`app.infra` or :mod:`app.native`.
+"""

app/algorithms/burst_detection/__init__.py

@@ -1,3 +1,3 @@
-from app.algorithms.burst_detection.burst_detector import BurstDetector
+from app.algorithms.burst_detection.pressure_anomaly import PressureAnomalyDetector
 
-__all__ = ["BurstDetector"]
+__all__ = ["PressureAnomalyDetector"]

app/algorithms/burst_detection/pressure_anomaly.py

@@ -17,7 +17,7 @@ PressureDataInput = (
 IGNORED_OBSERVATION_COLUMNS = {"time", "timestamp", "datetime", "date"}
 
 
-class BurstDetector:
+class PressureAnomalyDetector:
     """FFT + IsolationForest based burst detection for daily aligned pressure data."""
 
     def __init__(

app/algorithms/burst_localization/__init__.py

@@ -0,0 +1,3 @@
+from .pipeline import run_burst_location
+
+__all__ = ["run_burst_location"]

app/algorithms/burst_localization/candidate_ranking.py

@@ -11,13 +11,13 @@ import networkx as nx
 import numpy as np
 import pandas as pd
 
-from .leak_simulator import cal_signature_pipe_multi_pf
-from .network_partitioner import (
+from .leak_signature import cal_signature_pipe_multi_pf
+from .topology_partitioning import (
     cal_group_num,
     metis_grouping_pipe_weight,
     visualize_metis_partition,
 )
-from .similarity_calculator import (
+from .similarity_metrics import (
     adjust_ratio,
     cal_similarity_all_multi_new_sq_improve_double_lzr,
     decode_mode,
@@ -769,4 +769,3 @@ def DN_search_multi_simple_add_flow_count_new(
         final_candidates_csv,
     )
 
-

app/algorithms/burst_localization/pipeline.py

@@ -1,5 +1,3 @@
-import argparse
-import json
 import logging
 from multiprocessing import cpu_count
 from pathlib import Path
@@ -7,12 +5,12 @@ from typing import Any, Iterable
 
 import pandas as pd
 
-from app.algorithms.burst_location import leak_simulator
+from app.algorithms.burst_localization import leak_signature
 
-from .burst_locator import (
+from .candidate_ranking import (
     DN_search_multi_simple_add_flow_count_new,
 )
-from .network_model import (
+from .topology_model import (
     _build_node_pipe_maps,
     cal_node_coordinate,
     construct_graph,
@@ -26,35 +24,6 @@ DEFAULT_N_WORKERS = max(1, min(cpu_count() - 1, 4))
 logger = logging.getLogger(__name__)
 
 
-def _read_id_list_json(path):
-    if path is None:
-        return None
-    data = json.loads(Path(path).read_text(encoding="utf-8"))
-    if isinstance(data, list):
-        return [str(item) for item in data]
-    if isinstance(data, dict):
-        if "ids" in data and isinstance(data["ids"], list):
-            return [str(item) for item in data["ids"]]
-        raise ValueError(f"ID JSON must be list or dict with key 'ids': {path}")
-    raise ValueError(f"Unsupported ID JSON format: {path}")
-
-
-def _read_series_csv(path):
-    if path is None:
-        return None
-    df = pd.read_csv(path)
-    if df.shape[1] < 2:
-        raise ValueError(f"CSV must contain at least two columns (id,value): {path}")
-    if {"id", "value"}.issubset(df.columns):
-        id_col, value_col = "id", "value"
-    else:
-        id_col, value_col = df.columns[0], df.columns[1]
-    series = pd.Series(
-        df[value_col].values, index=df[id_col].astype(str).values, dtype=float
-    )
-    return series
-
-
 def _align_scada_series(
     series: pd.Series, ids: Iterable[str], series_name: str
 ) -> pd.Series:
@@ -121,7 +90,7 @@ def run_burst_location(
     basic_pressure: float = 10.0,
     n_workers: int = DEFAULT_N_WORKERS,
     partition_on_full_graph: bool = True,
-    visualize_partition: bool = True,
+    visualize_partition: bool = False,
     visualize_pause_seconds: float = 0.3,
     final_candidates_csv_path: (
         str | None
@@ -159,7 +128,7 @@ def run_burst_location(
         pipe_diameter,
     ) = read_inf_inp(wn)
 
-    candidate_pipe, _ = leak_simulator.cal_possible_pipe(
+    candidate_pipe, _ = leak_signature.cal_possible_pipe(
         burst_leakage, all_pipe, pipe_diameter
     )
 
@@ -267,76 +236,3 @@ def run_burst_location(
         "final_candidates_csv": final_candidates_csv,
         "stage_timing_seconds": stage_timing,
     }
-
-
-def _parse_args():
-    parser = argparse.ArgumentParser(description="爆管定位主函数入口")
-    parser.add_argument("--wn-inp", required=True, help="EPANET inp 文件路径")
-    parser.add_argument(
-        "--pressure-ids-json", required=True, help="压力SCADA ID列表 JSON 文件"
-    )
-    parser.add_argument(
-        "--flow-ids-json", default=None, help="（可选）流量SCADA ID列表 JSON 文件"
-    )
-    parser.add_argument(
-        "--burst-pressure-csv", required=True, help="爆管时压力 CSV（id,value）"
-    )
-    parser.add_argument(
-        "--normal-pressure-csv", required=True, help="正常时压力 CSV（id,value）"
-    )
-    parser.add_argument(
-        "--burst-flow-csv", default=None, help="（可选）爆管时流量 CSV（id,value）"
-    )
-    parser.add_argument(
-        "--normal-flow-csv", default=None, help="（可选）正常时流量 CSV（id,value）"
-    )
-    parser.add_argument(
-        "--burst-leakage", type=float, required=True, help="爆管漏损流量"
-    )
-    parser.add_argument(
-        "--min-dpressure",
-        type=float,
-        default=2.0,
-        help="（可选）最小压降阈值，默认 2.0",
-    )
-    parser.add_argument(
-        "--basic-pressure",
-        type=float,
-        default=10.0,
-        help="（可选）基础服务压力，默认 10.0",
-    )
-    parser.add_argument(
-        "--n-workers",
-        type=int,
-        default=DEFAULT_N_WORKERS,
-        help="（可选）特征中心模拟进程数，默认 max(1, min(cpu_count()-1, 4))",
-    )
-    parser.add_argument(
-        "--final-candidates-csv-path",
-        default="temp/burst_location/final_round_candidates.csv",
-        help="（可选）最后一轮候选管道明细 CSV 输出路径",
-    )
-    return parser.parse_args()
-
-
-def main():
-    args = _parse_args()
-    result = run_burst_location(
-        wn_inp_path=args.wn_inp,
-        pressure_scada_ids=_read_id_list_json(args.pressure_ids_json),
-        burst_pressure=_read_series_csv(args.burst_pressure_csv),
-        normal_pressure=_read_series_csv(args.normal_pressure_csv),
-        burst_leakage=args.burst_leakage,
-        flow_scada_ids=_read_id_list_json(args.flow_ids_json),
-        burst_flow=_read_series_csv(args.burst_flow_csv),
-        normal_flow=_read_series_csv(args.normal_flow_csv),
-        min_dpressure=args.min_dpressure,
-        basic_pressure=args.basic_pressure,
-        n_workers=args.n_workers,
-        final_candidates_csv_path=args.final_candidates_csv_path,
-    )
-    print(json.dumps(result, ensure_ascii=False))
-
-
-if __name__ == "__main__":
-    main()

app/algorithms/burst_localization/synthetic_observations.py

@@ -6,7 +6,7 @@ import random
 import numpy as np
 import pandas as pd
 
-from .leak_simulator import simple_add_leak, simple_recover_wn, simple_simulation_pf
+from .leak_signature import simple_add_leak, simple_recover_wn, simple_simulation_pf
 
 
 def add_noise_pd(data, noise_type, noise_para):
@@ -195,4 +195,3 @@ def change_para_of_wn(wn, pipe_roughness_change):
         pipe.roughness = pipe_roughness_change[pipe_name]
     return wn
 
-

app/algorithms/burst_location/__init__.py

@@ -1,3 +0,0 @@
-from .burst_location import run_burst_location
-
-__all__ = ["run_burst_location"]

app/algorithms/cleaning/__init__.py

@@ -1,59 +0,0 @@
-import os
-
-from app.algorithms.cleaning import flow as _flow_module
-from app.algorithms.cleaning import pressure as _pressure_module
-
-
-############################################################
-# 流量监测数据清洗   ***卡尔曼滤波法***
-############################################################
-# 2025/08/21 hxyan
-
-
-def flow_data_clean(input_csv_file: str) -> str:
-    """
-    读取 input_csv_path 中的每列时间序列，使用一维 Kalman 滤波平滑并用预测值替换基于 3σ 检测出的异常点。
-    保存输出为：<input_filename>_cleaned.xlsx（与输入同目录），并返回输出文件的绝对路径。如有同名文件存在，则覆盖。
-    :param: input_csv_file: 输入的 CSV 文件明或路径
-    :return: 输出文件的绝对路径
-    """
-
-    # 提供的 input_csv_path 绝对路径，以下为 默认脚本目录下同名 CSV 文件，构建绝对路径，可根据情况修改
-    # 使用 algorithms 根目录保持与原 data_cleaning.py 一致的行为
-    script_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-    input_csv_path = os.path.join(script_dir, input_csv_file)
-
-    # 检查文件是否存在
-    if not os.path.exists(input_csv_path):
-        raise FileNotFoundError(f"指定的文件不存在: {input_csv_path}")
-    # 调用 clean_flow_data_kf 函数进行数据清洗
-    out_xlsx_path = _flow_module.clean_flow_data_kf(input_csv_path)
-    print("清洗后的数据已保存到:", out_xlsx_path)
-
-
-############################################################
-# 压力监测数据清洗   ***kmean++法***
-############################################################
-# 2025/08/21 hxyan
-
-
-def pressure_data_clean(input_csv_file: str) -> str:
-    """
-    读取 input_csv_path 中的每列时间序列，使用Kmean++清洗数据。
-    保存输出为：<input_filename>_cleaned.xlsx（与输入同目录），并返回输出文件的绝对路径。如有同名文件存在，则覆盖。
-    原始数据在 sheet 'raw_pressure_data'，处理后数据在 sheet 'cleaned_pressusre_data'。
-    :param input_csv_path: 输入的 CSV 文件路径
-    :return: 输出文件的绝对路径
-    """
-
-    # 提供的 input_csv_path 绝对路径，以下为 默认脚本目录下同名 CSV 文件，构建绝对路径，可根据情况修改
-    # 使用 algorithms 根目录保持与原 data_cleaning.py 一致的行为
-    script_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-    input_csv_path = os.path.join(script_dir, input_csv_file)
-
-    # 检查文件是否存在
-    if not os.path.exists(input_csv_path):
-        raise FileNotFoundError(f"指定的文件不存在: {input_csv_path}")
-    # 调用 clean_pressure_data_km 函数进行数据清洗
-    out_xlsx_path = _pressure_module.clean_pressure_data_km(input_csv_path)
-    print("清洗后的数据已保存到:", out_xlsx_path)

app/algorithms/cleaning/pressure.py

@@ -1,283 +0,0 @@
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-from sklearn.cluster import KMeans
-from sklearn.impute import SimpleImputer
-import os
-
-from app.algorithms._utils import fill_time_gaps
-
-
-def clean_pressure_data_km(
-    input_csv_path: str, show_plot: bool = False, fill_gaps: bool = True
-) -> str:
-    """
-    读取输入 CSV，基于 KMeans 检测异常并用滚动平均修复。输出为 <input_basename>_cleaned.xlsx（同目录）。
-    原始数据在 sheet 'raw_pressure_data'，处理后数据在 sheet 'cleaned_pressusre_data'。
-    返回输出文件的绝对路径。
-
-    Args:
-        input_csv_path: CSV 文件路径
-        show_plot: 是否显示可视化
-        fill_gaps: 是否先补齐时间缺口（默认 True）
-    """
-    # 读取 CSV
-    input_csv_path = os.path.abspath(input_csv_path)
-    data = pd.read_csv(input_csv_path, header=0, index_col=None, encoding="utf-8")
-
-    # 补齐时间缺口（如果数据包含 time 列）
-    if fill_gaps and "time" in data.columns:
-        data = fill_time_gaps(
-            data, time_col="time", freq="1min", short_gap_threshold=10
-        )
-
-    # 分离时间列和数值列
-    time_col_data = None
-    if "time" in data.columns:
-        time_col_data = data["time"]
-        data = data.drop(columns=["time"])
-    # 标准化
-    data_norm = (data - data.mean()) / data.std()
-
-    # 聚类与异常检测
-    k = 3
-    kmeans = KMeans(n_clusters=k, init="k-means++", n_init=50, random_state=42)
-    clusters = kmeans.fit_predict(data_norm)
-    centers = kmeans.cluster_centers_
-
-    distances = np.linalg.norm(data_norm.values - centers[clusters], axis=1)
-    threshold = distances.mean() + 3 * distances.std()
-
-    anomaly_pos = np.where(distances > threshold)[0]
-    anomaly_indices = data.index[anomaly_pos]
-
-    anomaly_details = {}
-    for pos in anomaly_pos:
-        row_norm = data_norm.iloc[pos]
-        cluster_idx = clusters[pos]
-        center = centers[cluster_idx]
-        diff = abs(row_norm - center)
-        main_sensor = diff.idxmax()
-        anomaly_details[data.index[pos]] = main_sensor
-
-    # 修复：滚动平均（窗口可调）
-    data_rolled = data.rolling(window=13, center=True, min_periods=1).mean()
-    data_repaired = data.copy()
-    for pos in anomaly_pos:
-        label = data.index[pos]
-        sensor = anomaly_details[label]
-        data_repaired.loc[label, sensor] = data_rolled.loc[label, sensor]
-
-    # 可选可视化（使用位置作为 x 轴）
-    plt.rcParams["font.sans-serif"] = ["SimHei"]
-    plt.rcParams["axes.unicode_minus"] = False
-
-    if show_plot and len(data.columns) > 0:
-        n = len(data)
-        time = np.arange(n)
-        plt.figure(figsize=(12, 8))
-        for col in data.columns:
-            plt.plot(time, data[col].values, marker="o", markersize=3, label=col)
-        for pos in anomaly_pos:
-            sensor = anomaly_details[data.index[pos]]
-            plt.plot(pos, data.iloc[pos][sensor], "ro", markersize=8)
-        plt.xlabel("时间点（序号）")
-        plt.ylabel("压力监测值")
-        plt.title("各传感器折线图（红色标记主要异常点）")
-        plt.legend()
-        plt.show()
-
-        plt.figure(figsize=(12, 8))
-        for col in data_repaired.columns:
-            plt.plot(
-                time, data_repaired[col].values, marker="o", markersize=3, label=col
-            )
-        for pos in anomaly_pos:
-            sensor = anomaly_details[data.index[pos]]
-            plt.plot(pos, data_repaired.iloc[pos][sensor], "go", markersize=8)
-        plt.xlabel("时间点（序号）")
-        plt.ylabel("修复后压力监测值")
-        plt.title("修复后各传感器折线图（绿色标记修复值）")
-        plt.legend()
-        plt.show()
-
-    # 保存到 Excel：两个 sheet
-    input_dir = os.path.dirname(os.path.abspath(input_csv_path))
-    input_base = os.path.splitext(os.path.basename(input_csv_path))[0]
-    output_filename = f"{input_base}_cleaned.xlsx"
-    output_path = os.path.join(input_dir, output_filename)
-
-    # 如果原始数据包含时间列，将其添加回结果
-    data_for_save = data.copy()
-    data_repaired_for_save = data_repaired.copy()
-    if time_col_data is not None:
-        data_for_save.insert(0, "time", time_col_data)
-        data_repaired_for_save.insert(0, "time", time_col_data)
-
-    if os.path.exists(output_path):
-        os.remove(output_path)  # 覆盖同名文件
-    with pd.ExcelWriter(output_path, engine="openpyxl") as writer:
-        data_for_save.to_excel(writer, sheet_name="raw_pressure_data", index=False)
-        data_repaired_for_save.to_excel(
-            writer, sheet_name="cleaned_pressusre_data", index=False
-        )
-
-    # 返回输出文件的绝对路径
-    return os.path.abspath(output_path)
-
-
-def clean_pressure_data_df_km(data: pd.DataFrame, show_plot: bool = False) -> dict:
-    """
-    接收一个 DataFrame 数据结构，使用KMeans聚类检测异常并用滚动平均修复。
-    返回清洗后的字典数据结构。
-
-    Args:
-        data: 输入 DataFrame（可包含 time 列）
-        show_plot: 是否显示可视化
-    """
-    # 使用传入的 DataFrame
-    data = data.copy()
-
-    # 补齐时间缺口（如果启用且数据包含 time 列）
-    data_filled = fill_time_gaps(
-        data, time_col="time", freq="1min", short_gap_threshold=10
-    )
-
-    # 保存 time 列用于最后合并
-    time_col_series = None
-    if "time" in data_filled.columns:
-        time_col_series = data_filled["time"]
-
-    # 移除 time 列用于后续清洗
-    data_filled = data_filled.drop(columns=["time"])
-
-    # 标准化（使用填充后的数据）
-    data_norm = (data_filled - data_filled.mean()) / data_filled.std()
-
-    # 添加：处理标准化后的 NaN（例如，标准差为0的列），防止异常数据，时间段内所有数据都相同导致计算结果为 NaN
-    imputer = SimpleImputer(
-        strategy="constant", fill_value=0, keep_empty_features=True
-    )  # 用 0 填充 NaN，包括全 NaN，并保留空特征
-    data_norm = pd.DataFrame(
-        imputer.fit_transform(data_norm),
-        columns=data_norm.columns,
-        index=data_norm.index,
-    )
-
-    # 聚类与异常检测
-    k = 3
-    kmeans = KMeans(n_clusters=k, init="k-means++", n_init=50, random_state=42)
-    clusters = kmeans.fit_predict(data_norm)
-    centers = kmeans.cluster_centers_
-
-    distances = np.linalg.norm(data_norm.values - centers[clusters], axis=1)
-    threshold = distances.mean() + 3 * distances.std()
-
-    anomaly_pos = np.where(distances > threshold)[0]
-    anomaly_indices = data_filled.index[anomaly_pos]
-
-    anomaly_details = {}
-    for pos in anomaly_pos:
-        row_norm = data_norm.iloc[pos]
-        cluster_idx = clusters[pos]
-        center = centers[cluster_idx]
-        diff = abs(row_norm - center)
-        main_sensor = diff.idxmax()
-        anomaly_details[data_filled.index[pos]] = main_sensor
-
-    # 修复：滚动平均（窗口可调）
-    data_rolled = data_filled.rolling(window=13, center=True, min_periods=1).mean()
-    data_repaired = data_filled.copy()
-    for pos in anomaly_pos:
-        label = data_filled.index[pos]
-        sensor = anomaly_details[label]
-        data_repaired.loc[label, sensor] = data_rolled.loc[label, sensor]
-
-    # 可选可视化（使用位置作为 x 轴）
-    plt.rcParams["font.sans-serif"] = ["SimHei"]
-    plt.rcParams["axes.unicode_minus"] = False
-
-    if show_plot and len(data.columns) > 0:
-        n = len(data)
-        time = np.arange(n)
-        n_filled = len(data_filled)
-        time_filled = np.arange(n_filled)
-        plt.figure(figsize=(12, 8))
-        for col in data.columns:
-            plt.plot(
-                time, data[col].values, marker="o", markersize=3, label=col, alpha=0.5
-            )
-        for col in data_filled.columns:
-            plt.plot(
-                time_filled,
-                data_filled[col].values,
-                marker="x",
-                markersize=3,
-                label=f"{col}_filled",
-                linestyle="--",
-            )
-        for pos in anomaly_pos:
-            sensor = anomaly_details[data_filled.index[pos]]
-            plt.plot(pos, data_filled.iloc[pos][sensor], "ro", markersize=8)
-        plt.xlabel("时间点（序号）")
-        plt.ylabel("压力监测值")
-        plt.title("各传感器折线图（红色标记主要异常点，虚线为0值填充后）")
-        plt.legend()
-        plt.show()
-
-        plt.figure(figsize=(12, 8))
-        for col in data_repaired.columns:
-            plt.plot(
-                time_filled, data_repaired[col].values, marker="o", markersize=3, label=col
-            )
-        for pos in anomaly_pos:
-            sensor = anomaly_details[data_filled.index[pos]]
-            plt.plot(pos, data_repaired.iloc[pos][sensor], "go", markersize=8)
-        plt.xlabel("时间点（序号）")
-        plt.ylabel("修复后压力监测值")
-        plt.title("修复后各传感器折线图（绿色标记修复值）")
-        plt.legend()
-        plt.show()
-
-    # 将 time 列添加回结果
-    if time_col_series is not None:
-        data_repaired.insert(0, "time", time_col_series)
-
-    # 返回清洗后的字典
-    return data_repaired
-
-
-# 测试
-# if __name__ == "__main__":
-#     # 默认使用脚本目录下的 pressure_raw_data.csv
-#     script_dir = os.path.dirname(os.path.abspath(__file__))
-#     default_csv = os.path.join(script_dir, "pressure_raw_data.csv")
-#     out_path = clean_pressure_data_km(default_csv, show_plot=False)
-#     print("保存路径：", out_path)
-
-# 测试 clean_pressure_data_dict_km 函数
-if __name__ == "__main__":
-    import random
-
-    # 读取 szh_pressure_scada.csv 文件
-    script_dir = os.path.dirname(os.path.abspath(__file__))
-    csv_path = os.path.join(script_dir, "szh_pressure_scada.csv")
-    data = pd.read_csv(csv_path, header=0, index_col=None, encoding="utf-8")
-
-    # 排除 Time 列，随机选择 5 列
-    columns_to_exclude = ["Time"]
-    available_columns = [col for col in data.columns if col not in columns_to_exclude]
-    selected_columns = random.sample(available_columns, 5)
-
-    # 将选中的列转换为字典
-    data_dict = {col: data[col].tolist() for col in selected_columns}
-
-    print("选中的列:", selected_columns)
-    print("原始数据长度:", len(data_dict[selected_columns[0]]))
-
-    # 调用函数进行清洗
-    cleaned_dict = clean_pressure_data_df_km(data_dict, show_plot=True)
-
-    print("清洗后的字典键:", list(cleaned_dict.keys()))
-    print("清洗后的数据长度:", len(cleaned_dict[selected_columns[0]]))
-    print("测试完成：函数运行正常")

app/algorithms/demand_allocation/__init__.py

@@ -0,0 +1,5 @@
+"""Demand allocation calculations."""
+
+from .pipe_length_weighted import allocate_demand_by_pipe_length
+
+__all__ = ["allocate_demand_by_pipe_length"]

app/algorithms/demand_allocation/pipe_length_weighted.py

@@ -0,0 +1,36 @@
+"""Pipe-length-weighted demand allocation.
+
+This module deliberately accepts plain topology data and performs no database
+or file access. Application services are responsible for loading topology.
+"""
+
+from typing import Any, Mapping
+
+
+def allocate_demand_by_pipe_length(
+    demand: float,
+    topology_nodes: Mapping[str, Mapping[str, Any]],
+    topology_links: Mapping[str, Mapping[str, Any]],
+) -> dict[str, float]:
+    """Allocate total demand to junctions by half of each incident link length."""
+
+    if not topology_nodes or not topology_links or demand == 0.0:
+        return {}
+
+    total_link_length = sum(
+        abs(float(link["length"])) for link in topology_links.values()
+    )
+    if total_link_length <= 0.0:
+        return {}
+
+    demand_per_length = demand / total_link_length
+    result: dict[str, float] = {}
+    for node_id, node in topology_nodes.items():
+        if node["type"] != "junction":
+            continue
+        incident_length = sum(
+            abs(float(topology_links[link_id]["length"]))
+            for link_id in node["links"]
+        )
+        result[node_id] = incident_length * demand_per_length * 0.5
+    return result

app/algorithms/dma_leakage_estimation/__init__.py

@@ -0,0 +1,3 @@
+from app.algorithms.dma_leakage_estimation.genetic_optimizer import DmaLeakageOptimizer
+
+__all__ = ["DmaLeakageOptimizer"]

app/algorithms/dma_leakage_estimation/genetic_optimizer.py

@@ -3,7 +3,6 @@ import numpy as np
 import pandas as pd
 import os
 import time
-import argparse
 from multiprocessing import Pool, cpu_count
 from typing import Any, List, Dict, Union
 
@@ -70,7 +69,7 @@ def _worker_init(
 
 def _worker_evaluate(raw_ratios: np.ndarray) -> float:
     d = _worker_data
-    effective_ratio_map = LeakageIdentifier._effective_area_ratios(
+    effective_ratio_map = DmaLeakageOptimizer._effective_area_ratios(
         raw_ratios,
         d["area_ids"],
         d["nodes_by_area"],
@@ -121,13 +120,15 @@ def _worker_evaluate(raw_ratios: np.ndarray) -> float:
         _cleanup_temp_files(prefix)
 
 
-class LeakageIdentifier:
-    FLOW_UNIT_TO_M3S = {
-        "m3/s": 1.0,
-        "m3/h": 1.0 / 3600.0,
-        "L/s": 1.0 / 1000.0,
-        "L/min": 1.0 / 60000.0,
-    }
+class DmaLeakageOptimizer:
+    FLOW_UNIT_TO_M3S = {
+        "m3/s": 1.0,
+        "m³/s": 1.0,
+        "m3/h": 1.0 / 3600.0,
+        "m³/h": 1.0 / 3600.0,
+        "L/s": 1.0 / 1000.0,
+        "L/min": 1.0 / 60000.0,
+    }
 
     @classmethod
     def _flow_to_m3s(cls, value: float, unit: str) -> float:
@@ -541,7 +542,7 @@ class LeakageProblem(Problem):
         leak_ratios = x
 
         # 将漏损分布归一化
-        effective_ratio_map = LeakageIdentifier._effective_area_ratios(
+        effective_ratio_map = DmaLeakageOptimizer._effective_area_ratios(
             leak_ratios,
             self.area_ids,
             self.nodes_by_area,
@@ -603,51 +604,6 @@ class LeakageProblem(Problem):
 
     def close(self) -> None:
         if self._pool is not None:
-            self._pool.close()
-            self._pool.join()
-            self._pool = None
-
-
-def main() -> int:
-    parser = argparse.ArgumentParser(description="漏损区域识别")
-    parser.add_argument("--inp", required=True, help=".inp 文件路径")
-    parser.add_argument("--map", help="节点-区域映射 CSV 路径")
-    parser.add_argument("--scada", help="SCADA 压力 CSV 路径 (观测数据)")
-    parser.add_argument("--sensors", help="传感器节点 ID 列表 (逗号分隔)")
-    parser.add_argument("--output", default="Results", help="输出目录")
-
-    parser.add_argument("--pop_size", type=int, default=50, help="种群大小")
-    parser.add_argument("--max_gen", type=int, default=100, help="最大代数")
-    parser.add_argument("--duration", type=float, default=24, help="模拟时长(小时)")
-    parser.add_argument("--q_sum", type=float, default=0.241, help="总漏损流量")
-    parser.add_argument(
-        "--q_sum_unit",
-        default="m3/s",
-        choices=list(LeakageIdentifier.FLOW_UNIT_TO_M3S.keys()),
-        help="q_sum 输入单位（建议与现场习惯一致，内部统一换算为 m3/s）",
-    )
-
-    args = parser.parse_args()
-
-    if not args.map or not args.scada or not args.sensors:
-        parser.error("--map、--scada、--sensors 为必填")
-
-    q_sum_m3s = LeakageIdentifier._flow_to_m3s(args.q_sum, args.q_sum_unit)
-
-    sensors = [sensor.strip() for sensor in args.sensors.split(",") if sensor.strip()]
-    identifier = LeakageIdentifier(
-        args.inp, sensors, args.map, duration=args.duration, q_sum=q_sum_m3s
-    )
-
-    identifier.run_identification(
-        args.scada,
-        args.output,
-        pop_size=args.pop_size,
-        max_gen=args.max_gen,
-        output_flow_unit=args.q_sum_unit,
-    )
-    return 0
-
-
-if __name__ == "__main__":
-    raise SystemExit(main())
+            self._pool.close()
+            self._pool.join()
+            self._pool = None

app/algorithms/dma_leakage_estimation/topology_partitioning.py

@@ -0,0 +1,206 @@
+"""Pure topology partitioning used by DMA leakage estimation."""
+
+import math
+from collections import deque
+from typing import Any, Iterable, Mapping
+
+import numpy as np
+
+
+def build_dma_partitions(
+    sensor_nodes: list[str],
+    node_coords: Mapping[str, Mapping[str, Any]],
+    link_entries: Iterable[str],
+    dma_count: int | None,
+) -> tuple[dict[str, str], list[dict[str, Any]]]:
+    """Assign every topology node to a sensor-seeded virtual DMA."""
+
+    all_nodes = list(node_coords)
+    if not all_nodes:
+        raise ValueError("管网中未获取到可分区节点。")
+    available_sensors = [node for node in sensor_nodes if node in node_coords]
+    if not available_sensors:
+        raise ValueError("无可用压力传感器，无法生成虚拟分区。")
+
+    area_count = _resolve_dma_count(dma_count, available_sensors, all_nodes)
+    sensor_area_map = _cluster_sensors_to_areas(
+        available_sensors, node_coords, area_count
+    )
+    adjacency = _build_adjacency(link_entries, all_nodes)
+    distance_by_sensor = {
+        sensor: _bfs_distances(adjacency, sensor) for sensor in available_sensors
+    }
+
+    assignment_count = {sensor: 0 for sensor in available_sensors}
+    area_map: dict[str, str] = {}
+    for node_id in sorted(all_nodes):
+        sensor = _choose_sensor_for_node(
+            node_id,
+            available_sensors,
+            node_coords,
+            distance_by_sensor,
+            assignment_count,
+        )
+        assignment_count[sensor] += 1
+        area_map[node_id] = sensor_area_map[sensor]
+
+    return area_map, _build_area_meta(area_map, sensor_area_map)
+
+
+def _resolve_dma_count(
+    dma_count: int | None, sensor_nodes: list[str], all_nodes: list[str]
+) -> int:
+    if dma_count is None:
+        return min(len(sensor_nodes), len(all_nodes))
+    if dma_count <= 0:
+        raise ValueError("dma_count 必须大于 0。")
+    if dma_count > len(all_nodes):
+        raise ValueError("dma_count 不能大于可分区节点数量。")
+    if dma_count > len(sensor_nodes):
+        raise ValueError("dma_count 不能大于可用传感器数量。")
+    return dma_count
+
+
+def _cluster_sensors_to_areas(
+    sensor_nodes: list[str],
+    node_coords: Mapping[str, Mapping[str, Any]],
+    area_count: int,
+) -> dict[str, str]:
+    if area_count >= len(sensor_nodes):
+        return {sensor: str(index + 1) for index, sensor in enumerate(sensor_nodes)}
+
+    points = np.array(
+        [
+            [float(node_coords[sensor]["x"]), float(node_coords[sensor]["y"])]
+            for sensor in sensor_nodes
+        ],
+        dtype=float,
+    )
+    centers = points[:area_count].copy()
+    labels = np.full(points.shape[0], -1, dtype=int)
+    for _ in range(20):
+        distances_squared = (
+            (points[:, None, :] - centers[None, :, :]) ** 2
+        ).sum(axis=2)
+        next_labels = distances_squared.argmin(axis=1)
+        if np.array_equal(labels, next_labels):
+            break
+        labels = next_labels
+        for index in range(area_count):
+            cluster_points = points[labels == index]
+            if cluster_points.size > 0:
+                centers[index] = cluster_points.mean(axis=0)
+    labels = _restore_empty_area_labels(labels, points, centers, area_count)
+    return {
+        sensor: str(int(labels[index]) + 1)
+        for index, sensor in enumerate(sensor_nodes)
+    }
+
+
+def _restore_empty_area_labels(
+    labels: np.ndarray,
+    points: np.ndarray,
+    centers: np.ndarray,
+    area_count: int,
+) -> np.ndarray:
+    """Keep every requested area represented when coordinates are degenerate."""
+
+    labels = labels.copy()
+    for missing_area in sorted(set(range(area_count)) - set(labels.tolist())):
+        area_sizes = {
+            area: int(np.count_nonzero(labels == area)) for area in range(area_count)
+        }
+        donor_area = max(
+            (area for area, size in area_sizes.items() if size > 1),
+            key=lambda area: (area_sizes[area], -area),
+        )
+        donor_indices = np.flatnonzero(labels == donor_area)
+        replacement_index = max(
+            (int(index) for index in donor_indices),
+            key=lambda index: (
+                float(np.sum((points[index] - centers[donor_area]) ** 2)),
+                index,
+            ),
+        )
+        labels[replacement_index] = missing_area
+        centers[missing_area] = points[replacement_index]
+    return labels
+
+
+def _build_adjacency(
+    link_entries: Iterable[str], all_nodes: list[str]
+) -> dict[str, set[str]]:
+    adjacency: dict[str, set[str]] = {node: set() for node in all_nodes}
+    for link in link_entries:
+        parts = str(link).split(":")
+        if len(parts) < 4:
+            continue
+        node1, node2 = parts[-2], parts[-1]
+        if node1 in adjacency and node2 in adjacency:
+            adjacency[node1].add(node2)
+            adjacency[node2].add(node1)
+    return adjacency
+
+
+def _bfs_distances(adjacency: Mapping[str, set[str]], start: str) -> dict[str, int]:
+    distances = {start: 0}
+    queue: deque[str] = deque([start])
+    while queue:
+        node = queue.popleft()
+        for neighbor in adjacency.get(node, set()):
+            if neighbor in distances:
+                continue
+            distances[neighbor] = distances[node] + 1
+            queue.append(neighbor)
+    return distances
+
+
+def _choose_sensor_for_node(
+    node_id: str,
+    sensors: list[str],
+    node_coords: Mapping[str, Mapping[str, Any]],
+    distance_by_sensor: Mapping[str, Mapping[str, int]],
+    assignment_count: Mapping[str, int],
+) -> str:
+    min_distance: int | None = None
+    candidates: list[str] = []
+    for sensor in sensors:
+        distance = distance_by_sensor.get(sensor, {}).get(node_id)
+        if distance is None:
+            continue
+        if min_distance is None or distance < min_distance:
+            min_distance = distance
+            candidates = [sensor]
+        elif distance == min_distance:
+            candidates.append(sensor)
+    if not candidates:
+        node_coord = node_coords[node_id]
+        return min(
+            sensors,
+            key=lambda sensor: math.hypot(
+                float(node_coord["x"]) - float(node_coords[sensor]["x"]),
+                float(node_coord["y"]) - float(node_coords[sensor]["y"]),
+            ),
+        )
+    return min(candidates, key=lambda sensor: (assignment_count[sensor], sensor))
+
+
+def _build_area_meta(
+    area_map: Mapping[str, str], sensor_area_map: Mapping[str, str]
+) -> list[dict[str, Any]]:
+    nodes_by_area: dict[str, list[str]] = {}
+    for node_id, area_id in area_map.items():
+        nodes_by_area.setdefault(area_id, []).append(node_id)
+    sensors_by_area: dict[str, list[str]] = {}
+    for sensor, area_id in sensor_area_map.items():
+        sensors_by_area.setdefault(area_id, []).append(sensor)
+
+    return [
+        {
+            "area_id": area_id,
+            "sensor_nodes": sorted(sensors_by_area.get(area_id, [])),
+            "node_ids": sorted(nodes_by_area[area_id]),
+            "node_count": len(nodes_by_area[area_id]),
+        }
+        for area_id in sorted(nodes_by_area, key=int)
+    ]

app/algorithms/health/__init__.py

@@ -1,3 +0,0 @@
-from app.algorithms.health.analyzer import PipelineHealthAnalyzer
-
-__all__ = ["PipelineHealthAnalyzer"]

app/algorithms/isolation/__init__.py

@@ -1,3 +0,0 @@
-from app.algorithms.isolation.valve import valve_isolation_analysis
-
-__all__ = ["valve_isolation_analysis"]

app/algorithms/isolation/valve.py

@@ -1,165 +0,0 @@
-from collections import defaultdict, deque
-from functools import lru_cache
-from typing import Any
-
-from app.services.tjnetwork import (
-    get_network_link_nodes,
-    is_node,
-    get_link_properties,
-)
-
-
-VALVE_LINK_TYPE = "valve"
-
-
-def _parse_link_entry(link_entry: str) -> tuple[str, str, str, str]:
-    parts = link_entry.split(":", 3)
-    if len(parts) != 4:
-        raise ValueError(f"Invalid link entry format: {link_entry}")
-    return parts[0], parts[1], parts[2], parts[3]
-
-
-@lru_cache(maxsize=16)
-def _get_network_topology(network: str):
-    """
-    解析并缓存网络拓扑，大幅减少重复的 API 调用和字符串解析开销。
-    返回:
-    - pipe_adj: 永久连通的管道/泵邻接表 (dict[str, set])
-    - all_valves: 所有阀门字典 {id: (n1, n2)}
-    - link_lookup: 链路快速查表 {id: (n1, n2, type)} 用于快速定位事故点
-    - node_set: 所有已知节点集合
-    """
-    pipe_adj = defaultdict(set)
-    all_valves = {}
-    link_lookup = {}
-    node_set = set()
-
-    # 此处假设 get_network_link_nodes 获取全网数据
-    for link_entry in get_network_link_nodes(network):
-        link_id, link_type, node1, node2 = _parse_link_entry(link_entry)
-        link_type_name = str(link_type).lower()
-
-        link_lookup[link_id] = (node1, node2, link_type_name)
-        node_set.add(node1)
-        node_set.add(node2)
-
-        if link_type_name == VALVE_LINK_TYPE:
-            all_valves[link_id] = (node1, node2)
-        else:
-            # 只有非阀门（管道/泵）才进入永久连通图
-            pipe_adj[node1].add(node2)
-            pipe_adj[node2].add(node1)
-
-    return pipe_adj, all_valves, link_lookup, node_set
-
-
-def valve_isolation_analysis(
-    network: str, accident_elements: str | list[str], disabled_valves: list[str] = None
-) -> dict[str, Any]:
-    """
-    关阀搜索/分析：基于拓扑结构确定事故隔离所需关阀。
-    :param network: 模型名称
-    :param accident_elements: 事故点（节点或管道/泵/阀门ID），可以是单个ID字符串或ID列表
-    :param disabled_valves: 故障/无法关闭的阀门ID列表
-    :return: dict，包含受影响节点、必须关闭阀门、可选阀门等信息
-    """
-    if disabled_valves is None:
-        disabled_valves_set = set()
-    else:
-        disabled_valves_set = set(disabled_valves)
-
-    if isinstance(accident_elements, str):
-        target_elements = [accident_elements]
-    else:
-        target_elements = accident_elements
-
-    # 1. 获取缓存拓扑 (极快，无 IO)
-    pipe_adj, all_valves, link_lookup, node_set = _get_network_topology(network)
-
-    # 2. 确定起点，优先查表避免 API 调用
-    start_nodes = set()
-    for element in target_elements:
-        if element in node_set:
-            start_nodes.add(element)
-        elif element in link_lookup:
-            n1, n2, _ = link_lookup[element]
-            start_nodes.add(n1)
-            start_nodes.add(n2)
-        else:
-            # 仅当缓存中没找到时（极少见），才回退到慢速 API
-            if is_node(network, element):
-                start_nodes.add(element)
-            else:
-                props = get_link_properties(network, element)
-                n1, n2 = props.get("node1"), props.get("node2")
-                if n1 and n2:
-                    start_nodes.add(n1)
-                    start_nodes.add(n2)
-                else:
-                    raise ValueError(
-                        f"Accident element {element} invalid or missing endpoints"
-                    )
-
-    # 3. 处理故障阀门 (构建临时增量图)
-    # 我们不修改 cached pipe_adj，而是建立一个 extra_adj
-    extra_adj = defaultdict(list)
-    boundary_valves = {}  # 当前有效的边界阀门
-
-    for vid, (n1, n2) in all_valves.items():
-        if vid in disabled_valves_set:
-            # 故障阀门：视为连通管道
-            extra_adj[n1].append(n2)
-            extra_adj[n2].append(n1)
-        else:
-            # 正常阀门：视为潜在边界
-            boundary_valves[vid] = (n1, n2)
-
-    # 4. BFS 搜索 (叠加 pipe_adj 和 extra_adj)
-    affected_nodes: set[str] = set()
-    queue = deque(start_nodes)
-    while queue:
-        node = queue.popleft()
-        if node in affected_nodes:
-            continue
-        affected_nodes.add(node)
-
-        # 遍历永久管道邻居
-        if node in pipe_adj:
-            for neighbor in pipe_adj[node]:
-                if neighbor not in affected_nodes:
-                    queue.append(neighbor)
-
-        # 遍历故障阀门带来的额外邻居
-        if node in extra_adj:
-            for neighbor in extra_adj[node]:
-                if neighbor not in affected_nodes:
-                    queue.append(neighbor)
-
-    # 5. 结果聚合
-    must_close_valves: list[str] = []
-    optional_valves: list[str] = []
-
-    for valve_id, (n1, n2) in boundary_valves.items():
-        in_n1 = n1 in affected_nodes
-        in_n2 = n2 in affected_nodes
-        if in_n1 and in_n2:
-            optional_valves.append(valve_id)
-        elif in_n1 or in_n2:
-            must_close_valves.append(valve_id)
-
-    must_close_valves.sort()
-    optional_valves.sort()
-
-    result = {
-        "accident_elements": target_elements,
-        "disabled_valves": disabled_valves,
-        "affected_nodes": sorted(affected_nodes),
-        "must_close_valves": must_close_valves,
-        "optional_valves": optional_valves,
-        "isolatable": len(must_close_valves) > 0,
-    }
-
-    if len(target_elements) == 1:
-        result["accident_element"] = target_elements[0]
-
-    return result

app/algorithms/leakage/__init__.py

@@ -1,3 +0,0 @@
-from app.algorithms.leakage.identifier import LeakageIdentifier
-
-__all__ = ["LeakageIdentifier"]

app/algorithms/pipe_health_prediction/__init__.py

@@ -0,0 +1,5 @@
+from app.algorithms.pipe_health_prediction.survival_predictor import (
+    PipeHealthSurvivalPredictor,
+)
+
+__all__ = ["PipeHealthSurvivalPredictor"]

app/algorithms/pipe_health_prediction/survival_predictor.py

@@ -4,7 +4,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 
 
-class PipelineHealthAnalyzer:
+class PipeHealthSurvivalPredictor:
     """
     管道健康分析器类，使用随机生存森林模型预测管道的生存概率。
 
@@ -28,11 +28,6 @@ class PipelineHealthAnalyzer:
                 "model",
                 "my_survival_forest_model_quxi.joblib",
             )
-        # 确保 model 目录存在
-        model_dir = os.path.dirname(model_path)
-        if model_dir and not os.path.exists(model_dir):
-            os.makedirs(model_dir, exist_ok=True)
-
         if not os.path.exists(model_path):
             raise FileNotFoundError(f"模型文件未找到: {model_path}")
 
@@ -102,7 +97,7 @@ class PipelineHealthAnalyzer:
 
 # 调用说明示例
 """
-在其他项目中使用PipelineHealthAnalyzer类的步骤：
+在其他项目中使用 PipeHealthSurvivalPredictor 类的步骤：
 
 1. 安装依赖（在requirements.txt中添加）：
    joblib==1.5.0
@@ -112,34 +107,29 @@ class PipelineHealthAnalyzer:
    matplotlib==3.9.4
 
 2. 导入类：
-   from pipeline_health_analyzer import PipelineHealthAnalyzer
+   from survival_predictor import PipeHealthSurvivalPredictor
 
 3. 初始化分析器（替换为实际模型路径）：
-   analyzer = PipelineHealthAnalyzer(model_path='path/to/my_survival_forest_model3-10.joblib')
+   predictor = PipeHealthSurvivalPredictor(model_path='path/to/model.joblib')
 
-4. 准备数据（pandas DataFrame，包含9个特征列）：
+4. 准备数据（pandas DataFrame，包含4个特征列）：
    import pandas as pd
    data = pd.DataFrame({
        'Material': [1, 2],  # 示例数据
        'Diameter': [100, 150],
        'Flow Velocity': [1.5, 2.0],
-       'Pressure': [50, 60],
-       'Temperature': [20, 25],
-       'Precipitation': [0.1, 0.2],
-       'Location': [1, 2],
-       'Structural Defects': [0, 1],
-       'Functional Defects': [0, 0]
+       'Pressure': [50, 60]
    })
 
 5. 进行预测：
-   survival_funcs = analyzer.predict_survival(data)
+   survival_funcs = predictor.predict_survival(data)
 
 6. 查看结果（每个样本的生存概率随时间变化）：
    for i, sf in enumerate(survival_funcs):
        print(f"样本 {i+1}: 时间点: {sf.x[:5]}..., 生存概率: {sf.y[:5]}...")
 
 7. 可视化（可选）：
-   analyzer.plot_survival(survival_funcs, save_path='survival_plot.png')
+   predictor.plot_survival(survival_funcs, save_path='survival_plot.png')
 
 注意：
 - 数据格式必须匹配特征列表，特征值为数值型。

app/algorithms/pressure_sensor_placement/__init__.py

@@ -0,0 +1 @@
+"""Pressure sensor placement calculation implementations."""

app/algorithms/pressure_sensor_placement/kmeans_placement.py

@@ -0,0 +1,96 @@
+import matplotlib.pyplot as plt
+import numpy as np
+import sklearn.cluster
+import wntr
+
+
+class KMeansPlacement:
+    def __init__(self, wn, num_monitors: int, min_diameter_mm: float):
+        self.cluster_num = num_monitors
+        self.wn = wn
+        self.monitor_nodes: list[str] = []
+        self.coords: list[tuple[float, float]] = []
+        self.candidate_nodes: list[str] = []
+        self.min_diameter_mm = min_diameter_mm
+
+    def get_junctions_coordinates(self) -> None:
+        eligible_nodes: set[str] = set()
+        junction_names = set(self.wn.junction_name_list)
+        for pipe_name in self.wn.pipe_name_list:
+            pipe = self.wn.get_link(pipe_name)
+            if float(pipe.diameter) * 1000 < self.min_diameter_mm:
+                continue
+            eligible_nodes.update(
+                node_id
+                for node_id in (pipe.start_node_name, pipe.end_node_name)
+                if node_id in junction_names
+            )
+
+        for junction_name in self.wn.junction_name_list:
+            if junction_name not in eligible_nodes:
+                continue
+            junction = self.wn.get_node(junction_name)
+            self.candidate_nodes.append(junction_name)
+            self.coords.append(junction.coordinates)
+
+    def select_monitoring_points(self) -> list[str]:
+        if not self.coords:
+            self.get_junctions_coordinates()
+        if self.cluster_num <= 0:
+            raise ValueError("sensor_count must be greater than zero")
+        if self.cluster_num > len(self.candidate_nodes):
+            raise ValueError("符合最小管径条件的候选节点数量少于请求的监测点数量")
+        coords = np.array(self.coords)
+        coordinate_span = coords.max(axis=0) - coords.min(axis=0)
+        coordinate_span[coordinate_span == 0] = 1.0
+        coords_normalized = (coords - coords.min(axis=0)) / coordinate_span
+        kmeans = sklearn.cluster.KMeans(n_clusters=self.cluster_num, random_state=42)
+        kmeans.fit(coords_normalized)
+
+        selected_indices: set[int] = set()
+        for cluster_index, center in enumerate(kmeans.cluster_centers_):
+            cluster_indices = np.flatnonzero(kmeans.labels_ == cluster_index)
+            available_indices = [
+                int(index)
+                for index in cluster_indices
+                if int(index) not in selected_indices
+            ]
+            if not available_indices:
+                available_indices = [
+                    index
+                    for index in range(len(self.candidate_nodes))
+                    if index not in selected_indices
+                ]
+            nearest_index = min(
+                available_indices,
+                key=lambda index: (
+                    float(np.sum((coords_normalized[index] - center) ** 2)),
+                    index,
+                ),
+            )
+            selected_indices.add(nearest_index)
+            nearest_node = self.candidate_nodes[nearest_index]
+            self.monitor_nodes.append(nearest_node)
+
+        return self.monitor_nodes
+
+    def visualize_network(self) -> None:
+        """Visualize network with monitoring points."""
+        wntr.graphics.plot_network(
+            self.wn,
+            node_attribute=self.monitor_nodes,
+            node_size=30,
+            title="Optimal sensor",
+        )
+        plt.show()
+
+
+def optimize_sensor_placement(
+    network_model: wntr.network.WaterNetworkModel,
+    sensor_count: int,
+    min_diameter_mm: float,
+) -> list[str]:
+    """Select sensor nodes from an already loaded network model."""
+
+    placement = KMeansPlacement(network_model, sensor_count, min_diameter_mm)
+    return placement.select_monitoring_points()

app/algorithms/pressure_sensor_placement/sensitivity_placement.py

@@ -0,0 +1,905 @@
+"""Pressure sensor placement based on scalable sensitivity analysis.
+
+The original implementation expanded a sparse water network into several dense
+``node x node``, ``node x pipe``, and ``pipe x pipe`` matrices.  That made the
+memory requirement quadratic and the explicit matrix inverse cubic in time.
+
+This module keeps one algorithm for every network size:
+
+* run EPANET once and reuse the first hydraulic state;
+* keep incidence and hydraulic graphs sparse;
+* estimate the row-wise L1 pressure sensitivity with deterministic Cauchy
+  projections and one sparse factorization;
+* estimate total directed hydraulic distance from a deterministic spatial
+  coreset without materialising an all-pairs distance matrix;
+* balance sensitivity score with geographic and pipe-network coverage without
+  materialising candidate-to-candidate distances.
+
+The random seed and sample counts are fixed, so the same model and request
+produce the same placement on every run.
+"""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from time import perf_counter
+
+import numpy as np
+import wntr
+from scipy.sparse import csr_matrix, eye
+from scipy.sparse.csgraph import connected_components, dijkstra
+from scipy.sparse.linalg import splu
+from sklearn.cluster import MiniBatchKMeans
+
+
+logger = logging.getLogger(__name__)
+
+_RANDOM_SEED = 42
+_SENSITIVITY_PROJECTIONS = 256
+_HYDRAULIC_LANDMARKS = 256
+_PROJECTION_BLOCK_SIZE = 16
+_DIJKSTRA_BLOCK_SIZE = 16
+_HEADLOSS_EPSILON = 1e-10
+_DIAMETER_TOLERANCE_MM = 1e-9
+_COVERAGE_ELIGIBILITY_RATIO = 0.70
+_COVERAGE_EDGE_EPSILON = 1e-9
+
+
+@dataclass(frozen=True)
+class _PreparedNetwork:
+    """Sparse data required by the placement pipeline."""
+
+    node_names: tuple[str, ...]
+    full_node_indices: np.ndarray
+    candidate_indices: np.ndarray
+    coordinates: np.ndarray
+    incidence: csr_matrix
+    conductance: np.ndarray
+    roughness_response: np.ndarray
+    distance_graph: csr_matrix
+    coverage_graph: csr_matrix
+
+
+@dataclass(frozen=True)
+class _CandidatePool:
+    """Aligned candidate arrays consumed by the placement stage."""
+
+    full_indices: np.ndarray
+    coordinates: np.ndarray
+    names: np.ndarray
+    scores: np.ndarray
+
+
+def _run_hydraulic_simulation(
+    wn: wntr.network.WaterNetworkModel,
+):
+    """Run only the initial EPANET state without shared ``temp.*`` files."""
+
+    original_duration = wn.options.time.duration
+    try:
+        # Every downstream calculation reads ``iloc[0]``.  Running an extended
+        # simulation only allocates unused time-series results, which is
+        # especially expensive for daily models with tens of thousands of
+        # nodes.  Restore the caller's model even when EPANET fails.
+        wn.options.time.duration = 0
+        with TemporaryDirectory(prefix="tjwater-sensitivity-") as temp_dir:
+            file_prefix = str(Path(temp_dir) / "simulation")
+            return wntr.sim.EpanetSimulator(wn).run_sim(file_prefix=file_prefix)
+    finally:
+        wn.options.time.duration = original_duration
+
+
+def _excluded_elements(
+    wn: wntr.network.WaterNetworkModel,
+) -> tuple[set[str], set[str]]:
+    """Return nodes that cannot host sensors and source-connected pipes.
+
+    Reservoirs, tanks, pump/valve endpoints, and the junction immediately next
+    to a reservoir or tank are treated as hydraulic boundary nodes.  Pipes
+    connected directly to a source are removed from the perturbation set, as
+    in the legacy algorithm.
+    """
+
+    source_nodes = set(wn.reservoir_name_list) | set(wn.tank_name_list)
+    excluded_nodes = set(source_nodes)
+    source_pipes: set[str] = set()
+
+    for pipe_name, pipe in wn.pipes():
+        endpoints = {pipe.start_node_name, pipe.end_node_name}
+        if endpoints & source_nodes:
+            source_pipes.add(pipe_name)
+            excluded_nodes.update(endpoints)
+
+    for _link_name, link in list(wn.pumps()) + list(wn.valves()):
+        excluded_nodes.add(link.start_node_name)
+        excluded_nodes.add(link.end_node_name)
+
+    return excluded_nodes, source_pipes
+
+
+def _minimum_weight_csr(
+    rows: list[int],
+    columns: list[int],
+    weights: list[float],
+    *,
+    shape: tuple[int, int],
+) -> csr_matrix:
+    """Build a CSR graph while retaining the lightest parallel edge."""
+
+    if not rows:
+        return csr_matrix(shape, dtype=np.float64)
+
+    row_array = np.asarray(rows, dtype=np.int64)
+    column_array = np.asarray(columns, dtype=np.int64)
+    weight_array = np.asarray(weights, dtype=np.float64)
+    order = np.lexsort((column_array, row_array))
+    row_array = row_array[order]
+    column_array = column_array[order]
+    weight_array = weight_array[order]
+
+    group_start = np.empty(len(row_array), dtype=bool)
+    group_start[0] = True
+    group_start[1:] = (row_array[1:] != row_array[:-1]) | (
+        column_array[1:] != column_array[:-1]
+    )
+    starts = np.flatnonzero(group_start)
+    minimum_weights = np.minimum.reduceat(weight_array, starts)
+    return csr_matrix(
+        (minimum_weights, (row_array[starts], column_array[starts])),
+        shape=shape,
+    )
+
+
+def _node_coordinates(
+    wn: wntr.network.WaterNetworkModel,
+    node_names: tuple[str, ...],
+) -> np.ndarray:
+    coordinate_series = wn.query_node_attribute("coordinates")
+    coordinates = np.asarray(
+        [coordinate_series.loc[node_name] for node_name in node_names],
+        dtype=np.float64,
+    )
+    if coordinates.ndim != 2 or coordinates.shape[1] < 2:
+        raise ValueError("管网节点缺少二维坐标，无法进行监测点空间布置")
+    coordinates = coordinates[:, :2]
+    if not np.isfinite(coordinates).all():
+        raise ValueError("管网节点坐标包含非有限值，无法进行监测点空间布置")
+    return coordinates
+
+
+def _build_coverage_graph(
+    wn: wntr.network.WaterNetworkModel,
+    results,
+    full_node_index: dict[str, int],
+) -> csr_matrix:
+    """Build the active undirected physical graph used to spread sensors."""
+
+    status_series = results.link["status"].iloc[0]
+    rows: list[int] = []
+    columns: list[int] = []
+    weights: list[float] = []
+
+    for link_name, link in wn.links():
+        if float(status_series.loc[link_name]) <= 0:
+            continue
+
+        start = full_node_index[link.start_node_name]
+        end = full_node_index[link.end_node_name]
+        # Pipes carry their physical length.  Pumps and valves are point
+        # devices, so a tiny positive length preserves connectivity without
+        # dominating shortest-path distance.
+        weight = max(
+            float(getattr(link, "length", 0.0)),
+            _COVERAGE_EDGE_EPSILON,
+        )
+        rows.extend((start, end))
+        columns.extend((end, start))
+        weights.extend((weight, weight))
+
+    return _minimum_weight_csr(
+        rows,
+        columns,
+        weights,
+        shape=(len(full_node_index), len(full_node_index)),
+    )
+
+
+def _prepare_network(
+    wn: wntr.network.WaterNetworkModel,
+    results,
+    *,
+    min_diameter: int,
+) -> _PreparedNetwork:
+    excluded_nodes, source_pipes = _excluded_elements(wn)
+    full_node_names = tuple(wn.node_name_list)
+    full_node_index = {
+        node_name: index for index, node_name in enumerate(full_node_names)
+    }
+    node_names = tuple(
+        node_name for node_name in full_node_names if node_name not in excluded_nodes
+    )
+    if not node_names:
+        raise ValueError("管网中没有可参与灵敏度分析的节点")
+
+    node_index = {node_name: index for index, node_name in enumerate(node_names)}
+    full_node_indices = np.asarray(
+        [full_node_index[node_name] for node_name in node_names],
+        dtype=np.int64,
+    )
+    coordinates = _node_coordinates(wn, node_names)
+
+    flow_series = results.link["flowrate"].iloc[0]
+    headloss_series = results.link["headloss"].iloc[0]
+    head_series = results.node["head"].iloc[0]
+
+    candidate_nodes: set[str] = set()
+    for _pipe_name, pipe in wn.pipes():
+        diameter_mm = float(pipe.diameter) * 1000.0
+        if diameter_mm + _DIAMETER_TOLERANCE_MM < min_diameter:
+            continue
+        if pipe.start_node_name in node_index:
+            candidate_nodes.add(pipe.start_node_name)
+        if pipe.end_node_name in node_index:
+            candidate_nodes.add(pipe.end_node_name)
+
+    incidence_rows: list[int] = []
+    incidence_columns: list[int] = []
+    incidence_values: list[float] = []
+    conductance: list[float] = []
+    roughness_response: list[float] = []
+    distance_rows: list[int] = []
+    distance_columns: list[int] = []
+    distance_weights: list[float] = []
+
+    kept_pipe_count = 0
+    for pipe_name, pipe in wn.pipes():
+        if pipe_name in source_pipes:
+            continue
+
+        start_name = pipe.start_node_name
+        end_name = pipe.end_node_name
+        if start_name not in node_index and end_name not in node_index:
+            continue
+
+        flow = float(flow_series.loc[pipe_name])
+        absolute_flow = abs(flow)
+        headloss = abs(float(headloss_series.loc[pipe_name]))
+        roughness = float(pipe.roughness)
+        if roughness <= 0:
+            raise ValueError(f"管道 {pipe_name} 的粗糙度必须大于 0")
+
+        orientation = -1.0 if flow < 0 else 1.0
+        if start_name in node_index:
+            incidence_rows.append(node_index[start_name])
+            incidence_columns.append(kept_pipe_count)
+            incidence_values.append(-orientation)
+        if end_name in node_index:
+            incidence_rows.append(node_index[end_name])
+            incidence_columns.append(kept_pipe_count)
+            incidence_values.append(orientation)
+
+        conductance.append(
+            absolute_flow / (1.852 * headloss + _HEADLOSS_EPSILON)
+        )
+        roughness_response.append(absolute_flow / roughness)
+
+        if flow > 0:
+            upstream_name, downstream_name = start_name, end_name
+        else:
+            upstream_name, downstream_name = end_name, start_name
+        hydraulic_weight = (
+            abs(float(head_series.loc[start_name]) - float(head_series.loc[end_name]))
+            * float(pipe.length)
+        )
+        distance_rows.append(full_node_index[upstream_name])
+        distance_columns.append(full_node_index[downstream_name])
+        distance_weights.append(hydraulic_weight)
+        kept_pipe_count += 1
+
+    if kept_pipe_count == 0:
+        raise ValueError("管网中没有可用于灵敏度分析的管道")
+
+    incidence = csr_matrix(
+        (
+            np.asarray(incidence_values, dtype=np.float64),
+            (
+                np.asarray(incidence_rows, dtype=np.int64),
+                np.asarray(incidence_columns, dtype=np.int64),
+            ),
+        ),
+        shape=(len(node_names), kept_pipe_count),
+    )
+    conductance_array = np.asarray(conductance, dtype=np.float64)
+    response_array = np.asarray(roughness_response, dtype=np.float64)
+    if not np.isfinite(conductance_array).all() or not np.isfinite(
+        response_array
+    ).all():
+        raise ValueError("水力结果产生了非有限灵敏度系数")
+
+    distance_graph = _minimum_weight_csr(
+        distance_rows,
+        distance_columns,
+        distance_weights,
+        shape=(len(full_node_names), len(full_node_names)),
+    )
+    coverage_graph = _build_coverage_graph(wn, results, full_node_index)
+    candidate_indices = np.asarray(
+        [
+            index
+            for index, node_name in enumerate(node_names)
+            if node_name in candidate_nodes
+        ],
+        dtype=np.int64,
+    )
+
+    return _PreparedNetwork(
+        node_names=node_names,
+        full_node_indices=full_node_indices,
+        candidate_indices=candidate_indices,
+        coordinates=coordinates,
+        incidence=incidence,
+        conductance=conductance_array,
+        roughness_response=response_array,
+        distance_graph=distance_graph,
+        coverage_graph=coverage_graph,
+    )
+
+
+def _axis_normalized_coordinates(coordinates: np.ndarray) -> np.ndarray:
+    """Scale each axis independently for MiniBatchKMeans."""
+
+    minimum = coordinates.min(axis=0)
+    span = np.ptp(coordinates, axis=0)
+    span[span == 0] = 1.0
+    return (coordinates - minimum) / span
+
+
+def _isotropic_coordinates(coordinates: np.ndarray) -> np.ndarray:
+    """Normalize coordinates without distorting the network aspect ratio."""
+
+    minimum = coordinates.min(axis=0)
+    scale = float(np.max(np.ptp(coordinates, axis=0), initial=0.0))
+    if scale == 0:
+        scale = 1.0
+    return (coordinates - minimum) / scale
+
+
+def _cluster_labels(
+    coordinates: np.ndarray,
+    cluster_count: int,
+    *,
+    random_seed: int,
+) -> tuple[np.ndarray, np.ndarray]:
+    """Cluster coordinates deterministically with one implementation at all sizes."""
+
+    normalized = _axis_normalized_coordinates(coordinates)
+    if cluster_count == 1:
+        return np.zeros(len(coordinates), dtype=np.int64), normalized[[0]]
+    if cluster_count >= len(coordinates):
+        return np.arange(len(coordinates), dtype=np.int64), normalized.copy()
+
+    model = MiniBatchKMeans(
+        n_clusters=cluster_count,
+        random_state=random_seed,
+        n_init=3,
+        batch_size=min(len(coordinates), max(1024, cluster_count * 3)),
+        max_iter=100,
+        max_no_improvement=20,
+        reassignment_ratio=0.0,
+    )
+    labels = model.fit_predict(normalized).astype(np.int64, copy=False)
+    return labels, np.asarray(model.cluster_centers_, dtype=np.float64)
+
+
+def _estimate_log_pressure_sensitivity(prepared: _PreparedNetwork) -> np.ndarray:
+    """Estimate each row's L1 sensitivity using streaming Cauchy projections."""
+
+    weighted_incidence = prepared.incidence.multiply(prepared.conductance)
+    laplacian = (weighted_incidence @ prepared.incidence.T).tocsc()
+    diagonal = np.asarray(laplacian.diagonal(), dtype=np.float64)
+    diagonal_scale = float(np.max(np.abs(diagonal), initial=0.0))
+    if diagonal_scale == 0:
+        raise ValueError("水力雅可比矩阵为空，无法计算压力灵敏度")
+
+    regularization = diagonal_scale * np.sqrt(np.finfo(np.float64).eps)
+    laplacian = laplacian + eye(
+        laplacian.shape[0], format="csc", dtype=np.float64
+    ) * regularization
+    factor = splu(
+        laplacian,
+        permc_spec="MMD_AT_PLUS_A",
+        diag_pivot_thresh=0.0,
+        options={"SymmetricMode": True},
+    )
+
+    random = np.random.default_rng(_RANDOM_SEED)
+    log_absolute_sum = np.zeros(len(prepared.node_names), dtype=np.float64)
+    projection_count = 0
+    float_epsilon = np.finfo(np.float64).eps
+    float_tiny = np.finfo(np.float64).tiny
+
+    while projection_count < _SENSITIVITY_PROJECTIONS:
+        block_size = min(
+            _PROJECTION_BLOCK_SIZE,
+            _SENSITIVITY_PROJECTIONS - projection_count,
+        )
+        uniform = random.random((prepared.incidence.shape[1], block_size))
+        np.clip(uniform, float_epsilon, 1.0 - float_epsilon, out=uniform)
+        cauchy_projection = np.tan(np.pi * (uniform - 0.5))
+        projected_response = prepared.incidence @ (
+            prepared.roughness_response[:, None] * cauchy_projection
+        )
+        solution = factor.solve(np.asarray(projected_response, dtype=np.float64))
+        log_absolute_sum += np.log(
+            np.maximum(np.abs(solution), float_tiny)
+        ).sum(axis=1)
+        projection_count += block_size
+
+    # For a standard Cauchy variable E[log(abs(X))] is zero.  Therefore this
+    # streaming geometric mean estimates log(||row||_1) without retaining the
+    # node-by-projection matrix.  A finite-sample bias is common to all rows and
+    # does not affect ranking.
+    return log_absolute_sum / _SENSITIVITY_PROJECTIONS
+
+
+def _landmark_coreset(prepared: _PreparedNetwork) -> tuple[np.ndarray, np.ndarray]:
+    landmark_count = min(_HYDRAULIC_LANDMARKS, len(prepared.node_names))
+    labels, centers = _cluster_labels(
+        prepared.coordinates,
+        landmark_count,
+        random_seed=_RANDOM_SEED + 1,
+    )
+    normalized = _axis_normalized_coordinates(prepared.coordinates)
+    landmarks: list[int] = []
+    weights: list[float] = []
+
+    for label in np.unique(labels):
+        members = np.flatnonzero(labels == label)
+        center = centers[int(label)]
+        squared_distance = np.square(normalized[members] - center).sum(axis=1)
+        landmarks.append(int(members[int(np.argmin(squared_distance))]))
+        weights.append(float(len(members)))
+
+    return (
+        np.asarray(landmarks, dtype=np.int64),
+        np.asarray(weights, dtype=np.float64),
+    )
+
+
+def _estimate_hydraulic_distance_sums(prepared: _PreparedNetwork) -> np.ndarray:
+    """Estimate outbound distance sums without an all-pairs distance matrix."""
+
+    landmark_indices, landmark_weights = _landmark_coreset(prepared)
+    full_landmark_indices = prepared.full_node_indices[landmark_indices]
+    reversed_graph = prepared.distance_graph.transpose().tocsr()
+    distance_sums = np.zeros(len(prepared.node_names), dtype=np.float64)
+
+    for start in range(0, len(landmark_indices), _DIJKSTRA_BLOCK_SIZE):
+        stop = min(start + _DIJKSTRA_BLOCK_SIZE, len(landmark_indices))
+        distances = dijkstra(
+            reversed_graph,
+            directed=True,
+            indices=full_landmark_indices[start:stop],
+            return_predecessors=False,
+        )
+        distances = np.atleast_2d(distances)[:, prepared.full_node_indices]
+        # The legacy matrix represented unreachable pairs as zero.  Retaining
+        # that convention prevents disconnected branches from receiving an
+        # artificial infinite score.
+        distances[~np.isfinite(distances)] = 0.0
+        distance_sums += landmark_weights[start:stop] @ distances
+
+    return distance_sums
+
+
+def _build_candidate_pool(
+    prepared: _PreparedNetwork,
+    log_sensitivity: np.ndarray,
+    hydraulic_distance_sums: np.ndarray,
+) -> _CandidatePool:
+    candidate_indices = prepared.candidate_indices
+    candidate_distance = hydraulic_distance_sums[candidate_indices]
+    with np.errstate(divide="ignore", invalid="ignore"):
+        scores = log_sensitivity[candidate_indices] + np.log(candidate_distance)
+    scores = np.nan_to_num(
+        scores,
+        nan=-np.inf,
+        neginf=-np.inf,
+        posinf=np.finfo(np.float64).max,
+    )
+    return _CandidatePool(
+        full_indices=prepared.full_node_indices[candidate_indices],
+        coordinates=_isotropic_coordinates(prepared.coordinates[candidate_indices]),
+        names=np.asarray(
+            [prepared.node_names[index] for index in candidate_indices],
+            dtype=str,
+        ),
+        scores=scores,
+    )
+
+
+def _highest_scoring_position(
+    names: np.ndarray,
+    scores: np.ndarray,
+    positions: np.ndarray,
+) -> int:
+    """Return the best position, breaking score ties by node name."""
+
+    order = np.lexsort((names[positions], -scores[positions]))
+    return int(positions[order[0]])
+
+
+def _relative_gap(
+    distances: np.ndarray,
+    available: np.ndarray,
+) -> np.ndarray:
+    """Normalize available distances to their current finite maximum."""
+
+    maximum = float(np.max(distances[available], initial=0.0))
+    if not np.isfinite(maximum) or maximum <= np.finfo(np.float64).eps:
+        return np.zeros(len(distances), dtype=np.float64)
+    return distances / maximum
+
+
+def _eligible_gap_positions(
+    relative_gap: np.ndarray,
+    available: np.ndarray,
+) -> np.ndarray:
+    """Return positions within the configured fraction of the largest gap."""
+
+    maximum = float(np.max(relative_gap[available], initial=0.0))
+    if maximum <= np.finfo(np.float64).eps:
+        return np.flatnonzero(available)
+    threshold = _COVERAGE_ELIGIBILITY_RATIO * maximum
+    return np.flatnonzero(
+        available & (relative_gap >= threshold - np.finfo(np.float64).eps)
+    )
+
+
+def _allocate_component_quotas(
+    coverage_graph: csr_matrix,
+    candidate_full_indices: np.ndarray,
+    candidate_scores: np.ndarray,
+    *,
+    sensor_num: int,
+) -> tuple[np.ndarray, np.ndarray]:
+    """Allocate sensor counts by active pipe length with candidate caps."""
+
+    component_count, node_components = connected_components(
+        coverage_graph,
+        directed=False,
+        return_labels=True,
+    )
+    candidate_components = node_components[candidate_full_indices]
+    capacities = np.bincount(
+        candidate_components,
+        minlength=component_count,
+    ).astype(np.int64, copy=False)
+
+    # The graph is symmetric.  Summed row weights count every physical edge
+    # twice, hence the division by two after aggregation by component.
+    node_lengths = np.asarray(coverage_graph.sum(axis=1)).ravel()
+    component_lengths = np.bincount(
+        node_components,
+        weights=node_lengths,
+        minlength=component_count,
+    ) / 2.0
+    component_best_scores = np.full(component_count, -np.inf, dtype=np.float64)
+    np.maximum.at(
+        component_best_scores,
+        candidate_components,
+        candidate_scores,
+    )
+
+    active_components = np.flatnonzero(capacities)
+    quotas = np.zeros(component_count, dtype=np.int64)
+    if len(active_components) > sensor_num:
+        order = np.lexsort(
+            (
+                active_components,
+                -component_best_scores[active_components],
+                -component_lengths[active_components],
+            )
+        )
+        quotas[active_components[order[:sensor_num]]] = 1
+        return candidate_components, quotas
+
+    quotas[active_components] = 1
+    remaining = sensor_num - len(active_components)
+    while remaining > 0:
+        available = active_components[
+            quotas[active_components] < capacities[active_components]
+        ]
+        if len(available) == 0:
+            raise ValueError("连通区域中的候选节点不足，无法分配监测点名额")
+
+        weights = component_lengths[available]
+        if float(weights.sum()) <= 0:
+            weights = (capacities[available] - quotas[available]).astype(
+                np.float64,
+                copy=False,
+            )
+        ideal = remaining * weights / float(weights.sum())
+        whole = np.minimum(
+            np.floor(ideal).astype(np.int64),
+            capacities[available] - quotas[available],
+        )
+        whole_count = int(whole.sum())
+        if whole_count:
+            quotas[available] += whole
+            remaining -= whole_count
+            continue
+
+        fractional = ideal - np.floor(ideal)
+        order = np.lexsort(
+            (
+                available,
+                -component_best_scores[available],
+                -weights,
+                -fractional,
+            )
+        )
+        for component in available[order]:
+            quotas[component] += 1
+            remaining -= 1
+            if remaining == 0:
+                break
+
+    return candidate_components, quotas
+
+
+def _select_component_positions(
+    coverage_graph: csr_matrix,
+    candidates: _CandidatePool,
+    component_positions: np.ndarray,
+    existing_positions: list[int],
+    *,
+    quota: int,
+) -> list[int]:
+    """Select one component's sensors with score-aware farthest-first search."""
+
+    local_coordinates = candidates.coordinates[component_positions]
+    local_names = candidates.names[component_positions]
+    local_scores = candidates.scores[component_positions]
+    nearest_geographic = np.full(len(component_positions), np.inf)
+    nearest_topological = np.full(len(component_positions), np.inf)
+
+    for position in existing_positions:
+        nearest_geographic = np.minimum(
+            nearest_geographic,
+            np.linalg.norm(
+                local_coordinates - candidates.coordinates[position],
+                axis=1,
+            ),
+        )
+
+    if existing_positions:
+        all_local = np.ones(len(component_positions), dtype=bool)
+        seed_eligible = _eligible_gap_positions(
+            _relative_gap(nearest_geographic, all_local),
+            all_local,
+        )
+    else:
+        seed_eligible = np.arange(len(component_positions), dtype=np.int64)
+
+    seed = _highest_scoring_position(
+        local_names,
+        local_scores,
+        seed_eligible,
+    )
+    selected_local = [seed]
+    remaining = np.ones(len(component_positions), dtype=bool)
+    remaining[seed] = False
+
+    while len(selected_local) < quota:
+        newest = selected_local[-1]
+        geographic_distance = np.linalg.norm(
+            local_coordinates - local_coordinates[newest],
+            axis=1,
+        )
+        nearest_geographic = np.minimum(
+            nearest_geographic,
+            geographic_distance,
+        )
+
+        source = int(candidates.full_indices[component_positions[newest]])
+        topological_distance = dijkstra(
+            coverage_graph,
+            directed=False,
+            indices=source,
+            return_predecessors=False,
+        )[candidates.full_indices[component_positions]]
+        nearest_topological = np.minimum(
+            nearest_topological,
+            topological_distance,
+        )
+
+        coverage_gap = np.maximum(
+            _relative_gap(nearest_geographic, remaining),
+            _relative_gap(nearest_topological, remaining),
+        )
+        eligible_local = _eligible_gap_positions(coverage_gap, remaining)
+        next_local = _highest_scoring_position(
+            local_names,
+            local_scores,
+            eligible_local,
+        )
+        selected_local.append(next_local)
+        remaining[next_local] = False
+
+    return [int(component_positions[position]) for position in selected_local]
+
+
+def _geographic_coverage_metrics(
+    candidate_coordinates: np.ndarray,
+    selected_positions: list[int],
+) -> tuple[float, float, float]:
+    normalized = _isotropic_coordinates(candidate_coordinates)
+    nearest = np.full(len(normalized), np.inf)
+    for position in selected_positions:
+        nearest = np.minimum(
+            nearest,
+            np.linalg.norm(normalized - normalized[position], axis=1),
+        )
+
+    selected_coordinates = normalized[selected_positions]
+    if len(selected_positions) < 2:
+        minimum_gap = 0.0
+    else:
+        pairwise = np.linalg.norm(
+            selected_coordinates[:, None, :] - selected_coordinates[None, :, :],
+            axis=2,
+        )
+        np.fill_diagonal(pairwise, np.inf)
+        minimum_gap = float(pairwise.min())
+    return (
+        float(nearest.max()),
+        float(np.quantile(nearest, 0.95)),
+        minimum_gap,
+    )
+
+
+def _select_sensor_nodes(
+    prepared: _PreparedNetwork,
+    log_sensitivity: np.ndarray,
+    hydraulic_distance_sums: np.ndarray,
+    *,
+    sensor_num: int,
+) -> list[str]:
+    candidate_indices = prepared.candidate_indices
+    if len(candidate_indices) < sensor_num:
+        raise ValueError(
+            "满足最小管径要求的候选节点少于请求的监测点数量："
+            f"候选 {len(candidate_indices)} 个，请求 {sensor_num} 个"
+        )
+
+    candidates = _build_candidate_pool(
+        prepared,
+        log_sensitivity,
+        hydraulic_distance_sums,
+    )
+    candidate_components, component_quotas = _allocate_component_quotas(
+        prepared.coverage_graph,
+        candidates.full_indices,
+        candidates.scores,
+        sensor_num=sensor_num,
+    )
+    selected_positions: list[int] = []
+    quota_components = np.flatnonzero(component_quotas)
+    component_order = np.lexsort(
+        (quota_components, -component_quotas[quota_components])
+    )
+    for component in quota_components[component_order]:
+        component_positions = np.flatnonzero(candidate_components == component)
+        selected_positions.extend(
+            _select_component_positions(
+                prepared.coverage_graph,
+                candidates,
+                component_positions,
+                selected_positions,
+                quota=int(component_quotas[component]),
+            )
+        )
+
+    selected_array = np.asarray(selected_positions, dtype=np.int64)
+    selected_order = np.lexsort(
+        (
+            candidates.names[selected_array],
+            -candidates.scores[selected_array],
+        )
+    )
+    selected_positions = selected_array[selected_order].tolist()
+    maximum_radius, p95_radius, minimum_gap = _geographic_coverage_metrics(
+        prepared.coordinates[candidate_indices],
+        selected_positions,
+    )
+    logger.info(
+        "Sensitivity placement coverage: components=%d max_radius=%.6f "
+        "p95_radius=%.6f min_sensor_gap=%.6f",
+        int(np.count_nonzero(component_quotas)),
+        maximum_radius,
+        p95_radius,
+        minimum_gap,
+    )
+    return [str(candidates.names[position]) for position in selected_positions]
+
+
+def optimize_sensor_placement(
+    wn: wntr.network.WaterNetworkModel,
+    sensor_num: int,
+    min_diameter: int,
+) -> list[str]:
+    """Return deterministic pressure monitoring nodes for a loaded network.
+
+    ``min_diameter`` is expressed in millimetres, matching the HTTP contract.
+    A node is a valid installation candidate when at least one incident pipe
+    meets the threshold.  All valid hydraulic nodes still participate in the
+    sensitivity calculation so small pipes continue to influence the result.
+    """
+
+    if sensor_num <= 0:
+        raise ValueError("监测点数量必须大于 0")
+    if min_diameter < 0:
+        raise ValueError("最小管径不能小于 0")
+
+    total_started = perf_counter()
+    simulation_started = total_started
+    results = _run_hydraulic_simulation(wn)
+    simulation_seconds = perf_counter() - simulation_started
+
+    preparation_started = perf_counter()
+    prepared = _prepare_network(wn, results, min_diameter=min_diameter)
+    preparation_seconds = perf_counter() - preparation_started
+
+    sensitivity_started = perf_counter()
+    log_sensitivity = _estimate_log_pressure_sensitivity(prepared)
+    sensitivity_seconds = perf_counter() - sensitivity_started
+
+    distance_started = perf_counter()
+    hydraulic_distance_sums = _estimate_hydraulic_distance_sums(prepared)
+    distance_seconds = perf_counter() - distance_started
+
+    selection_started = perf_counter()
+    selected = _select_sensor_nodes(
+        prepared,
+        log_sensitivity,
+        hydraulic_distance_sums,
+        sensor_num=sensor_num,
+    )
+    selection_seconds = perf_counter() - selection_started
+
+    logger.info(
+        "Sensitivity placement completed: nodes=%d pipes=%d candidates=%d "
+        "sensors=%d seconds=%.3f "
+        "(simulation=%.3f preparation=%.3f sensitivity=%.3f "
+        "distance=%.3f selection=%.3f)",
+        len(prepared.node_names),
+        prepared.incidence.shape[1],
+        len(prepared.candidate_indices),
+        len(selected),
+        perf_counter() - total_started,
+        simulation_seconds,
+        preparation_seconds,
+        sensitivity_seconds,
+        distance_seconds,
+        selection_seconds,
+    )
+    return selected
+
+
+def optimize_sensor_placement_from_inp(
+    inp_path: str | Path,
+    sensor_num: int,
+    min_diameter: int,
+) -> list[str]:
+    """Load an EPANET INP model and run the unified placement algorithm."""
+
+    wn = wntr.network.WaterNetworkModel(str(inp_path))
+    return optimize_sensor_placement(
+        wn,
+        sensor_num=sensor_num,
+        min_diameter=min_diameter,
+    )

app/algorithms/scada_cleaning/__init__.py

@@ -0,0 +1,6 @@
+"""SCADA time-series cleaning algorithms."""
+
+from .flow_series import clean_flow_data_df_kf
+from .pressure_series import clean_pressure_data_df_km
+
+__all__ = ["clean_flow_data_df_kf", "clean_pressure_data_df_km"]

app/algorithms/scada_cleaning/flow_series.py

@@ -142,11 +142,13 @@ def clean_flow_data_kf(
     return os.path.abspath(output_path)
 
 
-def clean_flow_data_df_kf(data: pd.DataFrame, show_plot: bool = False) -> dict:
+def clean_flow_data_df_kf(
+    data: pd.DataFrame, show_plot: bool = False
+) -> pd.DataFrame:
     """
     接收一个 DataFrame 数据结构，使用一维 Kalman 滤波平滑并用预测值替换基于 IQR 检测出的异常点。
     区分合理的0值（流量转换）和异常的0值（连续多个0或孤立0）。
-    返回完整的清洗后的字典数据结构。
+    返回完整的清洗后 DataFrame。
 
     Args:
         data: 输入 DataFrame（可包含 time 列）
@@ -305,42 +307,3 @@ def clean_flow_data_df_kf(data: pd.DataFrame, show_plot: bool = False) -> dict:
 
     # 返回完整的修复后字典
     return cleaned_data
-
-
-# # 测试
-# if __name__ == "__main__":
-#     # 默认：脚本目录下同名 CSV 文件
-#     script_dir = os.path.dirname(os.path.abspath(__file__))
-#     default_csv = os.path.join(script_dir, "pipe_flow_data_to_clean2.0.csv")
-#     out = clean_flow_data_kf(default_csv)
-#     print("清洗后的数据已保存到:", out)
-
-# 测试 clean_flow_data_dict 函数
-if __name__ == "__main__":
-    import random
-
-    # 读取 szh_flow_scada.csv 文件
-    script_dir = os.path.dirname(os.path.abspath(__file__))
-    csv_path = os.path.join(script_dir, "szh_flow_scada.csv")
-    data = pd.read_csv(csv_path, header=0, index_col=None, encoding="utf-8")
-
-    # 排除 Time 列，随机选择 5 列
-    columns_to_exclude = ["Time"]
-    available_columns = [col for col in data.columns if col not in columns_to_exclude]
-    selected_columns = random.sample(available_columns, 1)
-
-    # 将选中的列转换为字典
-    data_dict = {col: data[col].tolist() for col in selected_columns}
-
-    print("选中的列:", selected_columns)
-    print("原始数据长度:", len(data_dict[selected_columns[0]]))
-
-    # 调用函数进行清洗
-    cleaned_dict = clean_flow_data_df_kf(data_dict, show_plot=True)
-    # 将清洗后的字典写回 CSV
-    out_csv = os.path.join(script_dir, f"{selected_columns[0]}_clean.csv")
-    pd.DataFrame(cleaned_dict).to_csv(out_csv, index=False, encoding="utf-8-sig")
-    print("已保存清洗结果到:", out_csv)
-    print("清洗后的字典键:", list(cleaned_dict.keys()))
-    print("清洗后的数据长度:", len(cleaned_dict[selected_columns[0]]))
-    print("测试完成：函数运行正常")

app/algorithms/scada_cleaning/pressure_series.py

@@ -0,0 +1,543 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+import os
+
+ID_LIKE_COLUMNS = {
+    "id",
+    "device_id",
+    "node_id",
+    "sensor_id",
+    "monitor_id",
+    "junction_id",
+}
+
+
+def _normalize_time_frame(data: pd.DataFrame) -> pd.DataFrame:
+    """返回按时间排序的副本，并尽量将 time 列解析为时间类型。"""
+    data = data.copy()
+    if "time" in data.columns:
+        data["time"] = pd.to_datetime(data["time"], errors="coerce")
+        data = data.sort_values(["time"]).reset_index(drop=True)
+    return data
+
+
+def _select_pressure_columns(data: pd.DataFrame) -> tuple[list[str], list[str]]:
+    """区分需要清洗的数值列与需要原样保留的列。"""
+    value_cols: list[str] = []
+    keep_cols: list[str] = []
+    for col in data.columns:
+        if col == "time":
+            continue
+        col_key = col.lower()
+        if col_key in ID_LIKE_COLUMNS or col_key.endswith("_id"):
+            keep_cols.append(col)
+            continue
+        numeric = pd.to_numeric(data[col], errors="coerce")
+        if numeric.notna().sum() == 0 or numeric.nunique(dropna=True) <= 1:
+            keep_cols.append(col)
+        else:
+            value_cols.append(col)
+    return value_cols, keep_cols
+
+
+def _robust_scale(values: pd.Series) -> float:
+    """基于 MAD 计算稳健尺度。"""
+    series = pd.to_numeric(values, errors="coerce").dropna()
+    if series.empty:
+        return 1.0
+    median = series.median()
+    mad = (series - median).abs().median()
+    if pd.notna(mad) and mad > 0:
+        return float(1.4826 * mad)
+    iqr = series.quantile(0.75) - series.quantile(0.25)
+    if pd.notna(iqr) and iqr > 0:
+        return float(iqr / 1.349)
+    std = series.std()
+    if pd.notna(std) and std > 0:
+        return float(std)
+    return 1.0
+
+
+def _shrink_toward_baseline(observed: float, baseline: float, scale: float) -> float:
+    """把观测值向基线值收缩，scale 越小，修复越强。"""
+    if pd.isna(observed):
+        return baseline
+    if pd.isna(baseline):
+        return observed
+    diff = observed - baseline
+    weight = scale / (abs(diff) + scale)
+    return float(baseline + diff * weight)
+
+
+def _infer_time_frequency(time_values: pd.Series | pd.Index) -> pd.Timedelta:
+    """从时间序列中推断采样频率，失败时默认 15 分钟。"""
+    parsed = pd.to_datetime(pd.Series(time_values), errors="coerce").dropna().sort_values()
+    if len(parsed) < 2:
+        return pd.Timedelta(minutes=15)
+
+    diffs = parsed.diff().dropna()
+    diffs = diffs[diffs > pd.Timedelta(0)]
+    if diffs.empty:
+        return pd.Timedelta(minutes=15)
+
+    mode = diffs.mode()
+    return mode.iloc[0] if not mode.empty else diffs.median()
+
+
+def _build_local_pressure_baseline(series: pd.Series) -> pd.Series:
+    """基于局部插值与中值滤波构造平滑基线。"""
+    baseline = _safe_time_interpolate(series)
+    baseline = baseline.rolling(window=5, center=True, min_periods=1).median()
+    baseline = _safe_time_interpolate(baseline)
+    return baseline.ffill().bfill()
+
+
+def _build_seasonal_pressure_baseline(series: pd.Series) -> pd.Series:
+    """按一天内的同一时刻构造季节性基线，适合日周期压力数据。"""
+    if not isinstance(series.index, pd.DatetimeIndex):
+        return pd.Series(np.nan, index=series.index, dtype=float)
+
+    slot_labels = pd.Series(series.index.strftime("%H:%M:%S"), index=series.index)
+    return series.groupby(slot_labels).transform("median")
+
+
+def _detect_pressure_spikes(series: pd.Series, local_baseline: pd.Series) -> pd.Series:
+    """识别单点异常上升/下降尖峰，避免过度修正正常波动。"""
+    residual = series - local_baseline
+    neighbor_center = (series.shift(1) + series.shift(-1)) / 2
+    curvature = series - neighbor_center
+
+    residual_scale = max(_robust_scale(residual), 1e-6)
+    curvature_scale = max(_robust_scale(curvature), 1e-6)
+    direction_flip = ((series - series.shift(1)) * (series.shift(-1) - series) < 0).fillna(False)
+
+    return (
+        residual.abs() > 3.5 * residual_scale
+    ) & (
+        curvature.abs() > 3.0 * curvature_scale
+    ) & direction_flip
+
+
+def _fill_pressure_gaps(
+    original: pd.Series,
+    repaired: pd.Series,
+    local_baseline: pd.Series,
+    seasonal_baseline: pd.Series,
+) -> pd.Series:
+    """短缺口用局部插值，长缺口优先使用同一时刻的季节性轨迹。"""
+    missing_mask = original.isna()
+    if not missing_mask.any():
+        return repaired
+
+    gap_groups = (missing_mask != missing_mask.shift(fill_value=False)).cumsum()
+    gap_lengths = missing_mask.groupby(gap_groups).transform("sum").where(missing_mask, 0)
+
+    filled = repaired.copy()
+    short_gap_mask = missing_mask & (gap_lengths < 4)
+    long_gap_mask = missing_mask & ~short_gap_mask
+
+    filled[short_gap_mask] = local_baseline[short_gap_mask]
+    long_gap_fill = seasonal_baseline.where(seasonal_baseline.notna(), local_baseline)
+    filled[long_gap_mask] = long_gap_fill[long_gap_mask]
+    return filled
+
+
+def _clean_pressure_series(series: pd.Series) -> pd.Series:
+    """清洗单个压力时间序列。"""
+    series = pd.to_numeric(series, errors="coerce").astype(float)
+    local_baseline = _build_local_pressure_baseline(series)
+    spike_mask = _detect_pressure_spikes(series, local_baseline)
+
+    repaired = series.copy()
+    repaired[spike_mask] = local_baseline[spike_mask]
+
+    seasonal_baseline = _build_seasonal_pressure_baseline(repaired)
+    repaired = _fill_pressure_gaps(series, repaired, local_baseline, seasonal_baseline)
+
+    if repaired.isna().any():
+        repaired = repaired.where(repaired.notna(), local_baseline)
+    return repaired.ffill().bfill()
+
+
+def _format_time_column(data: pd.DataFrame) -> pd.DataFrame:
+    """统一输出时间格式，方便下游直接按 ISO 字符串解析。"""
+    if "time" not in data.columns:
+        return data
+
+    formatted = data.copy()
+    time_values = pd.to_datetime(formatted["time"], errors="coerce")
+    if time_values.isna().all():
+        return formatted
+
+    if time_values.dt.tz is not None:
+        time_strings = time_values.dt.strftime("%Y-%m-%dT%H:%M:%S%z")
+        time_strings = time_strings.str.replace(
+            r"([+-]\d{2})(\d{2})$",
+            r"\1:\2",
+            regex=True,
+        )
+    else:
+        time_strings = time_values.dt.strftime("%Y-%m-%dT%H:%M:%S")
+
+    formatted["time"] = time_strings.where(time_values.notna(), formatted["time"])
+    return formatted
+
+
+def _expand_snapshot_time_grid(data: pd.DataFrame, freq: pd.Timedelta) -> pd.DataFrame:
+    """仅补齐时间轴，不提前填充值，避免长缺口丢失原始形状特征。"""
+    expanded = data.copy()
+    expanded["time"] = pd.to_datetime(expanded["time"], errors="coerce")
+    expanded = expanded.dropna(subset=["time"]).sort_values("time")
+    if expanded.empty:
+        return data
+
+    indexed = expanded.set_index("time")
+    full_index = pd.date_range(indexed.index.min(), indexed.index.max(), freq=freq)
+    indexed = indexed.reindex(full_index)
+    indexed.index.name = "time"
+    return indexed.reset_index()
+
+
+def _safe_datetime_index(values: pd.Series | pd.Index | list[object]) -> pd.DatetimeIndex | None:
+    """尽量把时间值标准化为 DatetimeIndex；失败则返回 None。"""
+    parsed = pd.to_datetime(values, errors="coerce")
+    try:
+        datetime_index = pd.DatetimeIndex(parsed)
+    except (TypeError, ValueError):
+        return None
+
+    if datetime_index.isna().all():
+        return None
+    return datetime_index
+
+
+def _safe_time_interpolate(series: pd.Series) -> pd.Series:
+    """仅在索引确实是 DatetimeIndex 时使用 time interpolation。"""
+    if isinstance(series.index, pd.DatetimeIndex):
+        return series.interpolate(method="time", limit_direction="both")
+    return series.interpolate(limit_direction="both")
+
+
+def _detect_long_form_identifier(data: pd.DataFrame, value_cols: list[str], keep_cols: list[str]) -> str | None:
+    """识别 time/id/value 长表结构。"""
+    if "time" not in data.columns or len(value_cols) != 1:
+        return None
+
+    identifier_candidates = [
+        col
+        for col in keep_cols
+        if col.lower() in ID_LIKE_COLUMNS or col.lower().endswith("_id")
+    ]
+    if len(identifier_candidates) != 1:
+        return None
+    if not data["time"].duplicated().any():
+        return None
+    return identifier_candidates[0]
+
+
+def _clean_long_form_pressure(
+    data: pd.DataFrame,
+    value_col: str,
+    identifier_col: str,
+    keep_cols: list[str],
+    fill_gaps: bool,
+) -> pd.DataFrame:
+    """按测点拆分 long-form 压力数据，再逐列清洗后恢复原结构。"""
+    data = _normalize_time_frame(data)
+    wide_df = (
+        data[[identifier_col, "time", value_col]]
+        .pivot(index="time", columns=identifier_col, values=value_col)
+        .reset_index()
+    )
+
+    sensor_cols = [col for col in wide_df.columns if col != "time"]
+    cleaned_wide = _clean_snapshot_pressure(wide_df, sensor_cols, keep_cols=[], fill_gaps=fill_gaps)
+
+    cleaned_long = cleaned_wide.melt(
+        id_vars="time",
+        var_name=identifier_col,
+        value_name=value_col,
+    )
+
+    passthrough_cols = [col for col in keep_cols if col != identifier_col]
+    if passthrough_cols:
+        metadata = data[[identifier_col] + passthrough_cols].drop_duplicates(subset=[identifier_col])
+        cleaned_long = cleaned_long.merge(metadata, on=identifier_col, how="left")
+
+    try:
+        cleaned_long[identifier_col] = cleaned_long[identifier_col].astype(data[identifier_col].dtype)
+    except (TypeError, ValueError):
+        pass
+
+    cleaned_long = cleaned_long.sort_values(["time", identifier_col]).reset_index(drop=True)
+    ordered_cols = ["time", identifier_col] + passthrough_cols + [value_col]
+    cleaned_long = cleaned_long[[col for col in ordered_cols if col in cleaned_long.columns]]
+    return cleaned_long
+
+
+def _build_time_slot_frame(
+    data: pd.DataFrame, value_col: str, expected_slots: int
+) -> pd.DataFrame:
+    """把重复时间点整理成 time x slot 的矩阵。"""
+    grouped = data.groupby("time", sort=True)
+    times = list(grouped.groups.keys())
+    slot_frame = pd.DataFrame(index=pd.Index(times, name="time"), columns=range(expected_slots), dtype=float)
+
+    for time_value, group in grouped:
+        values = pd.to_numeric(group[value_col], errors="coerce").tolist()
+        for slot_idx, value in enumerate(values[:expected_slots]):
+            slot_frame.loc[time_value, slot_idx] = value
+    return slot_frame
+
+
+def _slot_baseline(slot_frame: pd.DataFrame) -> pd.DataFrame:
+    """对每个槽位做时间插值和平滑，得到基线轨迹。"""
+    baseline = pd.DataFrame(index=slot_frame.index, columns=slot_frame.columns, dtype=float)
+    for col in slot_frame.columns:
+        series = slot_frame[col].astype(float)
+        series = _safe_time_interpolate(series)
+        series = series.rolling(window=5, center=True, min_periods=1).median()
+        series = _safe_time_interpolate(series).ffill().bfill()
+        baseline[col] = series
+    return baseline
+
+
+def _choose_insertion_position(
+    observed: list[float], baseline_row: pd.Series, expected_slots: int
+) -> int:
+    """为少一个观测值的时间组选择最合理的插入位置。"""
+    missing_count = expected_slots - len(observed)
+    if missing_count <= 0:
+        return 0
+
+    best_pos = 0
+    best_cost = float("inf")
+    for insert_pos in range(expected_slots):
+        cost = 0.0
+        obs_idx = 0
+        for slot_idx in range(expected_slots):
+            if slot_idx == insert_pos:
+                continue
+            obs_value = observed[obs_idx]
+            base_value = float(baseline_row.iloc[slot_idx])
+            if pd.notna(obs_value) and pd.notna(base_value):
+                cost += abs(obs_value - base_value)
+            obs_idx += 1
+        if cost < best_cost:
+            best_cost = cost
+            best_pos = insert_pos
+    return best_pos
+
+
+def _clean_repeated_timestamp_pressure(
+    data: pd.DataFrame, value_col: str, keep_cols: list[str]
+) -> pd.DataFrame:
+    """针对同一时间点重复采样的压力数据进行修复。"""
+    data = _normalize_time_frame(data)
+    grouped_sizes = data.groupby("time").size()
+    if grouped_sizes.empty:
+        return data
+
+    expected_slots = int(grouped_sizes.mode().iloc[0]) if not grouped_sizes.mode().empty else int(grouped_sizes.max())
+    expected_slots = max(expected_slots, int(grouped_sizes.max()))
+    slot_frame = _build_time_slot_frame(data, value_col, expected_slots)
+    baseline_frame = _slot_baseline(slot_frame)
+
+    residuals = slot_frame - baseline_frame
+    slot_scales = {
+        col: max(_robust_scale(residuals[col]), 1e-6) for col in residuals.columns
+    }
+
+    cleaned_rows: list[dict[str, object]] = []
+    grouped = data.groupby("time", sort=True)
+    for time_value, group in grouped:
+        observed_values = pd.to_numeric(group[value_col], errors="coerce").tolist()
+        baseline_row = baseline_frame.loc[time_value]
+        insert_pos = _choose_insertion_position(observed_values, baseline_row, expected_slots)
+
+        cleaned_values: list[float] = []
+        obs_idx = 0
+        for slot_idx in range(expected_slots):
+            if slot_idx == insert_pos and len(observed_values) < expected_slots:
+                cleaned_values.append(float(baseline_row.iloc[slot_idx]))
+                continue
+
+            if obs_idx >= len(observed_values):
+                cleaned_values.append(float(baseline_row.iloc[slot_idx]))
+                continue
+
+            observed = observed_values[obs_idx]
+            baseline = float(baseline_row.iloc[slot_idx])
+            cleaned_values.append(
+                _shrink_toward_baseline(observed, baseline, slot_scales.get(slot_idx, 1.0))
+            )
+            obs_idx += 1
+
+        # 其余字段原样保留；常量列（如 id）直接复制第一条记录即可
+        template_row = group.iloc[0].to_dict()
+        for slot_idx, cleaned_value in enumerate(cleaned_values):
+            row = dict(template_row)
+            row["time"] = time_value
+            row[value_col] = cleaned_value
+            cleaned_rows.append(row)
+
+    cleaned_df = pd.DataFrame(cleaned_rows)
+    cleaned_df = cleaned_df.sort_values(["time"]).reset_index(drop=True)
+    ordered_cols = ["time"] + keep_cols + [value_col]
+    ordered_cols = [col for col in ordered_cols if col in cleaned_df.columns]
+    remaining_cols = [col for col in cleaned_df.columns if col not in ordered_cols]
+    cleaned_df = cleaned_df[ordered_cols + remaining_cols]
+    return _format_time_column(cleaned_df)
+
+
+def _clean_snapshot_pressure(
+    data: pd.DataFrame, value_cols: list[str], keep_cols: list[str], fill_gaps: bool
+) -> pd.DataFrame:
+    """针对单条时间序列或多列快照数据进行稳健修复。"""
+    data = _normalize_time_frame(data)
+    if fill_gaps and "time" in data.columns:
+        freq = _infer_time_frequency(data["time"])
+        data = _expand_snapshot_time_grid(data, freq)
+        data["time"] = pd.to_datetime(data["time"], errors="coerce")
+        data = data.sort_values(["time"]).reset_index(drop=True)
+
+    cleaned_df = data.copy()
+    time_index = (
+        _safe_datetime_index(cleaned_df["time"])
+        if "time" in cleaned_df.columns
+        else None
+    )
+    if time_index is None:
+        time_index = pd.RangeIndex(start=0, stop=len(cleaned_df))
+    for col in value_cols:
+        series = pd.Series(
+            pd.to_numeric(cleaned_df[col], errors="coerce").to_numpy(),
+            index=time_index,
+            dtype=float,
+        )
+        cleaned_df[col] = _clean_pressure_series(series).to_numpy()
+
+    ordered_cols = ["time"] + keep_cols + value_cols
+    ordered_cols = [col for col in ordered_cols if col in cleaned_df.columns]
+    remaining_cols = [col for col in cleaned_df.columns if col not in ordered_cols]
+    cleaned_df = cleaned_df[ordered_cols + remaining_cols]
+    return _format_time_column(cleaned_df)
+
+
+def clean_pressure_data_km(
+    input_csv_path: str, show_plot: bool = False, fill_gaps: bool = True
+) -> str:
+    """
+    读取输入 CSV，基于时间结构进行稳健修复。输出为 <input_basename>_cleaned.xlsx（同目录）。
+    原始数据在 sheet 'raw_pressure_data'，处理后数据在 sheet 'cleaned_pressusre_data'。
+    返回输出文件的绝对路径。
+
+    Args:
+        input_csv_path: CSV 文件路径
+        show_plot: 是否显示可视化
+        fill_gaps: 是否先补齐时间缺口（默认 True）
+    """
+    # 读取 CSV
+    input_csv_path = os.path.abspath(input_csv_path)
+    data = pd.read_csv(input_csv_path, header=0, index_col=None, encoding="utf-8")
+    data = _normalize_time_frame(data)
+    value_cols, keep_cols = _select_pressure_columns(data)
+    has_repeated_time = "time" in data.columns and data["time"].duplicated().any()
+    identifier_col = _detect_long_form_identifier(data, value_cols, keep_cols)
+
+    if identifier_col is not None:
+        data_repaired = _clean_long_form_pressure(
+            data,
+            value_cols[0],
+            identifier_col,
+            keep_cols,
+            fill_gaps,
+        )
+    elif has_repeated_time and len(value_cols) == 1:
+        data_repaired = _clean_repeated_timestamp_pressure(data, value_cols[0], keep_cols)
+    else:
+        data_repaired = _clean_snapshot_pressure(data, value_cols, keep_cols, fill_gaps)
+
+    # 可选可视化（只展示首个数值列）
+    plt.rcParams["font.sans-serif"] = ["SimHei"]
+    plt.rcParams["axes.unicode_minus"] = False
+    if show_plot and value_cols:
+        plot_col = value_cols[0]
+        if "time" in data_repaired.columns:
+            x = pd.to_datetime(data_repaired["time"], errors="coerce")
+        else:
+            x = np.arange(len(data_repaired))
+        plt.figure(figsize=(12, 6))
+        plt.plot(x, pd.to_numeric(data_repaired[plot_col], errors="coerce"), label="cleaned")
+        plt.xlabel("时间" if "time" in data_repaired.columns else "序号")
+        plt.ylabel("压力监测值")
+        plt.title(f"{plot_col} 清洗结果")
+        plt.legend()
+        plt.show()
+
+    # 保存到 Excel：两个 sheet
+    input_dir = os.path.dirname(os.path.abspath(input_csv_path))
+    input_base = os.path.splitext(os.path.basename(input_csv_path))[0]
+    output_filename = f"{input_base}_cleaned.xlsx"
+    output_path = os.path.join(input_dir, output_filename)
+
+    # 如果原始数据包含时间列，将其添加回结果
+    data_for_save = data.copy()
+    data_repaired_for_save = data_repaired.copy()
+
+    if os.path.exists(output_path):
+        os.remove(output_path)  # 覆盖同名文件
+    with pd.ExcelWriter(output_path, engine="openpyxl") as writer:
+        data_for_save.to_excel(writer, sheet_name="raw_pressure_data", index=False)
+        data_repaired_for_save.to_excel(
+            writer, sheet_name="cleaned_pressusre_data", index=False
+        )
+
+    # 返回输出文件的绝对路径
+    return os.path.abspath(output_path)
+
+
+def clean_pressure_data_df_km(data: pd.DataFrame, show_plot: bool = False) -> pd.DataFrame:
+    """
+    接收一个 DataFrame 数据结构，使用时间感知的稳健修复方法清洗压力数据。
+    返回清洗后的 DataFrame。
+
+    Args:
+        data: 输入 DataFrame（可包含 time 列）
+        show_plot: 是否显示可视化
+    """
+    # 使用传入的 DataFrame
+    data = data.copy()
+    data = _normalize_time_frame(data)
+    value_cols, keep_cols = _select_pressure_columns(data)
+    has_repeated_time = "time" in data.columns and data["time"].duplicated().any()
+    identifier_col = _detect_long_form_identifier(data, value_cols, keep_cols)
+
+    if identifier_col is not None:
+        data_repaired = _clean_long_form_pressure(
+            data,
+            value_cols[0],
+            identifier_col,
+            keep_cols,
+            fill_gaps=True,
+        )
+    elif has_repeated_time and len(value_cols) == 1:
+        data_repaired = _clean_repeated_timestamp_pressure(data, value_cols[0], keep_cols)
+    else:
+        data_repaired = _clean_snapshot_pressure(data, value_cols, keep_cols, fill_gaps=True)
+
+    if show_plot and value_cols:
+        plt.rcParams["font.sans-serif"] = ["SimHei"]
+        plt.rcParams["axes.unicode_minus"] = False
+        plot_col = value_cols[0]
+        x = pd.to_datetime(data_repaired["time"], errors="coerce") if "time" in data_repaired.columns else np.arange(len(data_repaired))
+        plt.figure(figsize=(12, 6))
+        plt.plot(x, pd.to_numeric(data_repaired[plot_col], errors="coerce"), label="cleaned")
+        plt.xlabel("时间" if "time" in data_repaired.columns else "序号")
+        plt.ylabel("压力监测值")
+        plt.title(f"{plot_col} 清洗结果")
+        plt.legend()
+        plt.show()
+
+    return data_repaired

app/algorithms/sensor/__init__.py

@@ -1,91 +0,0 @@
-import psycopg
-
-from app.algorithms.sensor import kmeans as kmeans_sensor
-from app.algorithms.sensor import sensitivity
-from app.core.config import get_pgconn_string
-from app.services.tjnetwork import dump_inp
-
-
-def pressure_sensor_placement_sensitivity(
-    name: str, scheme_name: str, sensor_number: int, min_diameter: int, username: str
-) -> None:
-    """
-    基于改进灵敏度法进行压力监测点优化布置
-    :param name: 数据库名称
-    :param scheme_name: 监测优化布置方案名称
-    :param sensor_number: 传感器数目
-    :param min_diameter: 最小管径
-    :param username: 用户名
-    :return:
-    """
-    sensor_location = sensitivity.get_ID(
-        name=name, sensor_num=sensor_number, min_diameter=min_diameter
-    )
-    try:
-        conn_string = get_pgconn_string(db_name=name)
-        with psycopg.connect(conn_string) as conn:
-            with conn.cursor() as cur:
-                sql = """
-                        INSERT INTO sensor_placement (scheme_name, sensor_number, min_diameter, username, sensor_location)
-                        VALUES (%s, %s, %s, %s, %s)
-                    """
-
-                cur.execute(
-                    sql,
-                    (
-                        scheme_name,
-                        sensor_number,
-                        min_diameter,
-                        username,
-                        sensor_location,
-                    ),
-                )
-            conn.commit()
-            print("方案信息存储成功！")
-    except Exception as e:
-        print(f"存储方案信息时出错：{e}")
-
-
-# 2025/08/21
-# 基于kmeans聚类法进行压力监测点优化布置
-def pressure_sensor_placement_kmeans(
-    name: str, scheme_name: str, sensor_number: int, min_diameter: int, username: str
-) -> None:
-    """
-    基于聚类法进行压力监测点优化布置
-    :param name: 数据库名称（注意，此处数据库名称也是inp文件名称，inp文件与pg库名要一样）
-    :param scheme_name: 监测优化布置方案名称
-    :param sensor_number: 传感器数目
-    :param min_diameter: 最小管径
-    :param username: 用户名
-    :return:
-    """
-    # dump_inp
-    inp_name = f"./db_inp/{name}.db.inp"
-    dump_inp(name, inp_name, "2")
-    sensor_location = kmeans_sensor.kmeans_sensor_placement(
-        name=name, sensor_num=sensor_number, min_diameter=min_diameter
-    )
-    try:
-        conn_string = get_pgconn_string(db_name=name)
-        with psycopg.connect(conn_string) as conn:
-            with conn.cursor() as cur:
-                sql = """
-                        INSERT INTO sensor_placement (scheme_name, sensor_number, min_diameter, username, sensor_location)
-                        VALUES (%s, %s, %s, %s, %s)
-                    """
-
-                cur.execute(
-                    sql,
-                    (
-                        scheme_name,
-                        sensor_number,
-                        min_diameter,
-                        username,
-                        sensor_location,
-                    ),
-                )
-            conn.commit()
-            print("方案信息存储成功！")
-    except Exception as e:
-        print(f"存储方案信息时出错：{e}")

app/algorithms/sensor/kmeans.py

@@ -1,109 +0,0 @@
-import wntr
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import sklearn.cluster
-import os
-
-
-
-class QD_KMeans(object):
-    def __init__(self, wn, num_monitors):
-        # self.inp = inp
-        self.cluster_num = num_monitors # 聚类中心个数，也即测压点个数
-        self.wn=wn
-        self.monitor_nodes = []
-        self.coords = []
-        self.junction_nodes = {}  # Added missing initialization
-
-
-    def get_junctions_coordinates(self):
-       
-        for junction_name in self.wn.junction_name_list: 
-            junction = self.wn.get_node(junction_name)
-            self.junction_nodes[junction_name] = junction.coordinates
-            self.coords.append(junction.coordinates )
-
-        # print(f"Total junctions: {self.junction_coordinates}")   
-
-    def select_monitoring_points(self):
-        if not self.coords:  # Add check if coordinates are collected
-            self.get_junctions_coordinates()
-        coords = np.array(self.coords)
-        coords_normalized = (coords - coords.min(axis=0)) / (coords.max(axis=0) - coords.min(axis=0))
-        kmeans = sklearn.cluster.KMeans(n_clusters= self.cluster_num, random_state=42)
-        kmeans.fit(coords_normalized) 
-
-        for center in kmeans.cluster_centers_:
-            distances = np.sum((coords_normalized - center) ** 2, axis=1)
-            nearest_node = self.wn.junction_name_list[np.argmin(distances)]
-            self.monitor_nodes.append(nearest_node)  
-
-        return self.monitor_nodes
-    
-
-    def visualize_network(self):
-        """Visualize network with monitoring points"""
-        ax=wntr.graphics.plot_network(self.wn,   
-                               node_attribute=self.monitor_nodes,  
-                               node_size=30,  
-                               title='Optimal sensor') 
-        plt.show() 
-
-
-    
-    
-def kmeans_sensor_placement(name: str, sensor_num: int, min_diameter: int) -> list:
-    inp_name = f'./db_inp/{name}.db.inp'
-    wn= wntr.network.WaterNetworkModel(inp_name)
-    wn_cluster=QD_KMeans(wn, sensor_num)
-
-    # Select monitoring pointse
-    sensor_ids= wn_cluster.select_monitoring_points()
-
-    # wn_cluster.visualize_network()
-
-    return sensor_ids
-
-
-     
-if __name__ == "__main__":
-    #sensorindex = get_ID(name='suzhouhe_2024_cloud_0817', sensor_num=30, min_diameter=500)
-    sensorindex = kmeans_sensor_placement(name='szh', sensor_num=50, min_diameter=300)
-    print(sensorindex)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-

app/algorithms/sensor/sensitivity.py

@@ -1,653 +0,0 @@
-# 改进灵敏度法
-import networkx
-import numpy as np
-import pandas
-import wntr
-import pandas as pd
-import copy
-import matplotlib.pyplot as plt
-import networkx as nx
-from sklearn.cluster import KMeans
-from wntr.epanet.toolkit import EpanetException
-from numpy.linalg import slogdet
-import random
-from matplotlib.lines import Line2D
-from sklearn.cluster import SpectralClustering
-import libpysal as ps
-from spopt.region import Skater
-from shapely.geometry import Point
-import geopandas as gpd
-from sklearn.metrics import pairwise_distances
-import app.services.project_info as project_info
-
-# 2025/03/12
-# Step1: 获取节点坐标
-def getCoor(wn: wntr.network.WaterNetworkModel) -> pandas.DataFrame:
-    """
-    获取管网模型的节点坐标
-    :param wn: 由wntr生成的模型
-    :return: 节点坐标
-    """
-    # site: pandas.Series
-    #   index：节点名称（wn.node_name_list）
-    #   values：每个节点的坐标，格式为 tuple（如 (x, y) 或 (x, y, z)）
-    site = wn.query_node_attribute('coordinates')
-    # Coor: pandas.Series
-    #   index：与site相同（节点名称）。
-    #   values：坐标转换为numpy.ndarray（如array([10.5, 20.3])）
-    Coor = site.apply(lambda x: np.array(x))  # 将节点坐标转换为numpy数组
-    # x, y: list[float]
-    x = []  # 存储所有节点的 x 坐标
-    y = []  # 存储所有节点的 y 坐标
-    for i in range(0, len(Coor)):
-        x.append(Coor.values[i][0])  # 将 x 坐标存入 x 列表。
-        y.append(Coor.values[i][1])  # 将 y 坐标存入 y 列表
-    # xy: dict[str, list], x、y 坐标的字典
-    xy = {'x': x, 'y': y}
-    # Coor_node: pandas.DataFrame, 存储节点 x, y 坐标的 DataFrame
-    Coor_node = pd.DataFrame(xy, index=wn.node_name_list, columns=['x', 'y'])
-    return Coor_node
-
-
-# 2025/03/12
-# Step2: KMeans 聚类
-# 将节点用kmeans根据坐标分为k组，存入字典g
-def kgroup(coor: pandas.DataFrame, knum: int) -> dict[int, list[str]]:
-    """
-    使用KMeans聚类，将节点坐标分组
-    :param coor: 存储所有节点的坐标数据
-    :param knum: 需要分成的聚类数
-    :return: 聚类结果字典
-    """
-    g = {}
-    # estimator: sklearn.cluster.KMeans,KMeans 聚类模型
-    estimator = KMeans(n_clusters=knum)
-    estimator.fit(coor)
-    # label_pred: numpy.ndarray（int）,每个点的类别标签
-    label_pred = estimator.labels_
-    for i in range(0, knum):
-        g[i] = coor[label_pred == i].index.tolist()
-    return g
-
-
-def skater_partition(G, n_clusters):
-    """
-    使用 SKATER 算法对输入的无向图 G 进行区域划分，
-    保证每个划分区域在图论意义上是连通的，
-    同时依据节点坐标的空间信息进行划分。
-
-    参数:
-        G: networkx.Graph
-            带有节点坐标属性（键为 'pos'）的无向图。
-        n_clusters: int
-            希望划分的区域数量。
-
-    返回:
-        groups: dict
-            字典形式的聚类结果，键为区域编号，值为该区域内的节点列表。
-    """
-    # 1. 获取所有节点坐标，假设每个节点都有 'pos' 属性
-    pos = nx.get_node_attributes(G, 'pos')
-    nodes = list(G.nodes())
-    # 构造坐标数组：每行为 [x, y]
-    coords = np.array([pos[node] for node in nodes])
-
-    # 2. 构造 GeoDataFrame：创建 DataFrame 并生成 geometry 列
-    df = pd.DataFrame(coords, columns=['x', 'y'], index=nodes)
-    # 利用 shapely 的 Point 构造空间位置
-    df['geometry'] = df.apply(lambda row: Point(row['x'], row['y']), axis=1)
-    gdf = gpd.GeoDataFrame(df, geometry='geometry')
-
-    # 3. 构造空间权重矩阵，使用 4 近邻方法（k=4，可根据实际情况调整）
-    w = ps.weights.KNN.from_array(coords, k=4)
-    w.transform = 'R'
-
-    # 4. 调用 SKATER：新版本 API 要求传入 gdf, w 以及 attrs_name（这里使用 'x' 和 'y' 作为属性）
-    skater = Skater(gdf, w, attrs_name=['x', 'y'], n_clusters=n_clusters)
-    skater.solve()
-
-    # 5. 获取聚类标签，构造成字典格式
-    labels = skater.labels_
-    groups = {}
-    for label, node in zip(labels, nodes):
-        groups.setdefault(label, []).append(node)
-
-    return groups
-
-
-def spectral_partition(G, n_clusters):
-    """
-    利用谱聚类算法对图 G 进行分区：
-      1. 根据所有节点的空间坐标计算欧氏距离矩阵；
-      2. 利用高斯核函数构造相似度矩阵；
-      3. 使用 SpectralClustering 进行归一化割，返回分区结果。
-
-    参数:
-        G: networkx.Graph
-            每个节点需要有 'pos' 属性，其值为 (x, y) 坐标。
-        n_clusters: int
-            希望划分的聚类数目。
-
-    返回:
-        groups: dict
-            键为聚类标签，值为该聚类对应的节点列表。
-    """
-    # 1. 获取节点空间坐标，注意保证每个节点都有 'pos' 属性
-    pos_dict = nx.get_node_attributes(G, 'pos')
-    nodes = list(G.nodes())
-    coords = np.array([pos_dict[node] for node in nodes])
-
-    # 2. 计算节点之间的欧氏距离矩阵
-    D = pairwise_distances(coords, metric='euclidean')
-
-    # 3. 计算 sigma 值：这里取所有距离的均值，当然也可以根据实际情况调整
-    sigma = np.mean(D)
-
-    # 4. 构造相似度矩阵：使用高斯核函数
-    #    A(i, j) = exp( -d(i,j)^2 / (2*sigma^2) )
-    A = np.exp(- (D ** 2) / (2 * sigma ** 2))
-
-    # 5. 使用谱聚类进行图分区
-    clustering = SpectralClustering(n_clusters=n_clusters,
-                                    affinity='precomputed',
-                                    random_state=0)
-    labels = clustering.fit_predict(A)
-
-    # 6. 构造字典形式的分区结果
-    groups = {}
-    for label, node in zip(labels, nodes):
-        groups.setdefault(label, []).append(node)
-
-    return groups
-
-# 2025/03/12
-# Step3: wn_func类，水力计算
-# wn_func 主要用于计算：
-#     水力距离（hydraulic length）：即节点之间的水力阻力。
-#     灵敏度分析（sensitivity analysis）：用于优化测压点的布置。
-# 一些与水力相关的函数，包括 CtoS：求水力距离,stafun：求状态函数F
-# # diff：求F对P的导数，返回灵敏度矩阵A
-# # sensitivity：返回灵敏度和总灵敏度
-class wn_func(object):
-
-    # Step3.1: 初始化
-    def __init__(self, wn: wntr.network.WaterNetworkModel, min_diameter: int):
-        """
-        获取管网模型信息
-        :param wn: 由wntr生成的模型
-        :param min_diameter: 安装的最小管径
-        """
-        # self.results: wntr.sim.results.SimulationResults,仿真结果，包含压力、流量、水头等数据
-        self.results = wntr.sim.EpanetSimulator(wn).run_sim()  # 存储运行结果
-        self.wn = wn
-        # self.q：pandas.DataFrame,管道流量，索引为时间步长，列为管道名称
-        self.q = self.results.link['flowrate']
-        # ReservoirIndex / Tankindex: list[str],水库 / 水箱节点名称列表
-        ReservoirIndex = wn.reservoir_name_list
-        Tankindex = wn.tank_name_list
-        # 删除水库节点，删除与直接水库相连的虚拟管道
-        # self.pipes: list[str],所有管道的名称
-        self.pipes = wn.pipe_name_list
-        # self.nodes: list[str],所有节点的名称
-        self.nodes = wn.node_name_list
-        # self.coordinates：pandas.Series,节点坐标，索引为节点名，值为 (x, y) 坐标的 tuple
-        self.coordinates = wn.query_node_attribute('coordinates')
-        # allpumps / allvalves: list[str],所有泵/阀门名称列表
-        allpumps = wn.pump_name_list
-        allvalves = wn.valve_name_list
-        # pumpstnode / pumpednode / valvestnode / valveednode: list[str],存储泵和阀门 起终点节点的名称
-        pumpstnode = []
-        pumpednode = []
-        valvestnode = []
-        valveednode = []
-        # Reservoirpipe / Reservoirednode: list[str],记录与水库相关的管道和节点
-        Reservoirpipe = []
-        Reservoirednode = []
-        for pump in allpumps:
-            pumpstnode.append(wn.links[pump].start_node.name)
-            pumpednode.append(wn.links[pump].end_node.name)
-        for valve in allvalves:
-            valvestnode.append(wn.links[valve].start_node.name)
-            valveednode.append(wn.links[valve].end_node.name)
-        for pipe in self.pipes:
-            if wn.links[pipe].start_node.name in ReservoirIndex:
-                Reservoirpipe.append(pipe)
-                Reservoirednode.append(wn.links[pipe].end_node.name)
-            if wn.links[pipe].start_node.name in Tankindex:
-                Reservoirpipe.append(pipe)
-                Reservoirednode.append(wn.links[pipe].end_node.name)
-            if wn.links[pipe].end_node.name in Tankindex:
-                Reservoirpipe.append(pipe)
-                Reservoirednode.append(wn.links[pipe].start_node.name)
-        # 泵的起终点、tank、reservoir
-        # self.delnodes: list[str],需要删除的节点（包括水库、泵、阀门连接的节点）
-        self.delnodes = list(
-            set(ReservoirIndex).union(Tankindex, pumpstnode, pumpednode, valvestnode, valveednode, Reservoirednode))
-        # 泵、起终点为tank、reservoir的管道
-        # self.delpipes: list[str],需要删除的管道（包括水库、泵、阀门连接的管道）
-        self.delpipes = list(set(wn.pump_name_list).union(wn.valve_name_list).union(Reservoirpipe))
-        self.pipes = [pipe for pipe in wn.pipe_name_list if pipe not in self.delpipes]
-        # self.L: list[float],所有管道的长度（以米为单位）
-        self.L = wn.query_link_attribute('length')[self.pipes].tolist()
-        self.n = len(self.nodes)
-        self.m = len(self.pipes)
-        # self.unit_headloss: list[float],单位水头损失（headloss 数据的第一行，单位：米/km）
-        self.unit_headloss = self.results.link['headloss'].iloc[0, :].tolist()
-        ##
-        self.delnodes1 = list(set(ReservoirIndex).union(Tankindex))
-
-        # === 改动新增部分：筛选管径小于 min_diameter 的管道节点 ===
-        self.less_than_min_diameter_junction_list = []
-        for pipe in self.pipes:
-            diameter = wn.links[pipe].diameter
-            if diameter < min_diameter:
-                start_node = wn.links[pipe].start_node.name
-                end_node = wn.links[pipe].end_node.name
-                self.less_than_min_diameter_junction_list.extend([start_node, end_node])
-        # 去重
-        self.less_than_min_diameter_junction_list = list(set(self.less_than_min_diameter_junction_list))
-
-    # Step3.2: 计算水力距离
-    def CtoS(self):
-        """
-        计算水力距离矩阵
-        :return:
-        """
-        # 水力距离：当行索引对应的节点为控制点时，列索引对应的节点距离控制点的（路径*水头损失）的最小值
-        # nodes：list[str]（节点名称）
-        nodes = copy.deepcopy(self.nodes)
-        # pipes：list[str]（管道名称）
-        pipes = self.pipes
-        wn = self.wn
-        # n / m：int（节点数 / 管道数）
-        n = self.n
-        m = self.m
-        s1 = [0] * m
-        q = self.q
-        L = self.L
-        # H1：pandas.DataFrame,水头数据，索引为时间步长，列为节点名
-        H1 = self.results.node['head'].T
-        # hh：list[float],计算管道两端水头之差
-        hh = []
-        # 水头损失
-        for p in pipes:
-            h1 = self.wn.links[p].start_node.name
-            h1 = H1.loc[str(h1)]
-            h2 = self.wn.links[p].end_node.name
-            h2 = H1.loc[str(h2)]
-            hh.append(abs(h1 - h2))
-        hh = np.array(hh)
-        # headloss：pandas.DataFrame,管道水头损失矩阵
-        headloss = pd.DataFrame(hh, index=pipes).T
-        # s1:管道阻力系数，s2：将管道阻力系数与管道的起始节点和终止节点对应
-        hf = pd.DataFrame(np.array([0] * (n ** 2)).reshape(n, n), index=nodes, columns=nodes, dtype=float)
-        weightL = pd.DataFrame(np.array([0] * (n ** 2)).reshape(n, n), index=nodes, columns=nodes, dtype=float)
-        # s2为对应管道起始节点与终止节点的粗糙度系数矩阵，index代表起始节点，columns代表终止节点
-        G = nx.DiGraph()
-        for i in range(0, m):
-            pipe = pipes[i]
-            a = wn.links[pipe].start_node.name
-            b = wn.links[pipe].end_node.name
-            if q.loc[0, pipe] > 0:
-                hf.loc[a, b] = headloss.loc[0, pipe]
-                weightL.loc[a, b] = headloss.loc[0, pipe] * L[i]
-                G.add_weighted_edges_from([(a, b, weightL.loc[a, b])])
-
-            else:
-                hf.loc[b, a] = headloss.loc[0, pipe]
-                weightL.loc[b, a] = headloss.loc[0, pipe] * L[i]
-                G.add_weighted_edges_from([(b, a, weightL.loc[b, a])])
-
-        hydraulicL = pd.DataFrame(np.array([0] * (n ** 2)).reshape(n, n), index=nodes, columns=nodes, dtype=float)
-
-        for a in nodes:
-            if a in G.nodes:
-                d = nx.shortest_path_length(G, source=a, weight='weight')
-                for b in list(d.keys()):
-                    hydraulicL.loc[a, b] = d[b]
-
-        hydraulicL = hydraulicL.drop(self.delnodes)
-        hydraulicL = hydraulicL.drop(self.delnodes, axis=1)
-
-        # 求加权水力距离
-        return hydraulicL, G
-
-    # Step3.3: 计算灵敏度矩阵
-    # 获取关系矩阵
-    def get_Conn(self):
-        """
-        计算管网连接关系矩阵
-        :return:
-        """
-        m = self.wn.num_links
-        n = self.wn.num_nodes
-        p = self.wn.num_pumps
-        v = self.wn.num_valves
-
-        self.nonjunc_index = []
-        self.non_link_index = []
-        for r in self.wn.reservoirs():
-            self.nonjunc_index.append(r[0])
-        for t in self.wn.tanks():
-            self.nonjunc_index.append(t[0])
-        # Conn：numpy.matrix，节点-管道连接矩阵，起点 -1，终点 1
-        Conn = np.mat(np.zeros([n, m - p - v]))  # 节点和管道的关系矩阵，行为节点，列为管道，起点为-1，终点为1
-        # NConn：numpy.matrix，节点-节点连接矩阵，有管道相连的地方设为 1
-        NConn = np.mat(np.zeros([n, n]))  # 节点之间的关系，之间有管道为1，反之为0
-        # pipes：list[str]，去除泵和阀门的管道列表
-        pipes = [pipe for pipe in self.wn.pipes() if pipe not in self.wn.pumps() and pipe not in self.wn.valves()]
-        for pipe_name, pipe in pipes:
-            start = self.wn.node_name_list.index(pipe.start_node_name)
-            end = self.wn.node_name_list.index(pipe.end_node_name)
-            p_index = self.wn.link_name_list.index(pipe_name)
-            Conn[start, p_index] = -1
-            Conn[end, p_index] = 1
-            NConn[start, end] = 1
-            NConn[end, start] = 1
-        self.A = Conn
-        link_name_list = [link for link in self.wn.link_name_list if
-                          link not in self.wn.pump_name_list and link not in self.wn.valve_name_list]
-        self.A2 = pd.DataFrame(self.A, index=self.wn.node_name_list, columns=link_name_list)
-        self.A2 = self.A2.drop(self.delnodes)
-        for pipe in self.delpipes:
-            if pipe not in self.wn.pump_name_list and pipe not in self.wn.valve_name_list:
-                self.A2 = self.A2.drop(columns=pipe)
-        self.junc_list = self.A2.index
-        self.A2 = np.mat(self.A2)  # 节点管道关系
-        self.A3 = NConn
-
-    def Jaco(self, hL: pandas.DataFrame):
-        """
-        计算灵敏度矩阵（节点压力对粗糙度变化的响应）
-        :param hL: 水力距离矩阵
-        :return:
-        """
-        # global result
-        # A：numpy.matrix, 节点-管道关系矩阵
-        A = self.A2
-        wn = self.wn
-
-        try:
-            result = wntr.sim.EpanetSimulator(wn).run_sim()
-        except EpanetException:
-            pass
-        finally:
-            h = result.link['headloss'][self.pipes].values[0]
-            q = result.link['flowrate'][self.pipes].values[0]
-            l = self.wn.query_link_attribute('length')[self.pipes]
-            C = self.wn.query_link_attribute('roughness')[self.pipes]
-            # headloss：numpy.ndarray,水头损失数组
-            headloss = np.array(h)
-            # 调整流量方向
-            for i in range(0, len(q)):
-                if q[i] < 0:
-                    A[:, i] = -A[:, i]
-            # q：numpy.ndarray,流量数组
-            q = np.abs(q)
-            # 两个灵敏度矩阵
-            # B / S：numpy.matrix,灵敏度计算的中间矩阵
-            B = np.mat(np.diag(q / ((1.852 * headloss) + 1e-10)))
-            S = np.mat(np.diag(q / C))
-            # X：numpy.matrix, 灵敏度矩阵
-            X = A * B * A.T
-            try:
-                det = np.linalg.det(X)
-            except RuntimeError as e:
-                sign, logdet = slogdet(X)   # 防止溢出
-                det = sign * np.exp(logdet)
-            if det != 0:
-                J_H_Cw = X.I * A * S
-                # J_H_Q = -X.I
-                J_q_Cw = S - B * A.T * X.I * A * S  # 去掉了delnodes和delpipes
-                # J_q_Q = B * A.T * X.I
-            else:  # 当X不可逆
-                J_H_Cw = np.linalg.pinv(X) @ A @ S
-                # J_H_Q = -np.linalg.pinv(X)
-                J_q_Cw = S - B * A.T * np.linalg.pinv(X) * A * S
-                # J_q_Q = B * A.T * np.linalg.pinv(X)
-
-            Sen_pressure = []
-            S_pressure = np.abs(J_H_Cw).sum(axis=1).tolist()  # 修改为绝对值
-            for ss in S_pressure:
-                Sen_pressure.append(ss[0])
-            # 求总灵敏度
-            SS_pressure = copy.deepcopy(hL)
-            for i in range(0, len(Sen_pressure)):
-                SS_pressure.iloc[i, :] = SS_pressure.iloc[i, :] * Sen_pressure[i]
-            SS = copy.deepcopy(hL)
-            for i in range(0, len(Sen_pressure)):
-                SS.iloc[i, :] = SS.iloc[i, :] * Sen_pressure[i]
-            # SS[i,j]:节点nodes[i]的灵敏度*该节点到nodes[j]的水力距离
-            return SS
-
-
-# 2025/03/12
-# Step4: 传感器布置优化
-# Sensorplacement
-# weight：分配权重
-# sensor：传感器布置的位置
-class Sensorplacement(wn_func):
-    """
-    Sensorplacement 类继承了 wn_func 类，并且用于计算和优化传感器布置的位置。
-    """
-    def __init__(self, wn: wntr.network.WaterNetworkModel, sensornum: int, min_diameter: int):
-        """
-
-        :param wn: 由wntr生成的模型
-        :param sensornum: 传感器的数量
-        :param min_diameter: 安装的最小管径
-        """
-        wn_func.__init__(self, wn, min_diameter=min_diameter)
-        self.sensornum = sensornum
-
-    # 1.某个节点到所有节点的加权距离之和
-    # 2.某个节点到该组内所有节点的加权距离之和
-    def sensor(self, SS: pandas.DataFrame, G: networkx.Graph, group: dict[int, list[str]]):
-        """
-        sensor 方法是用来根据灵敏度矩阵 SS 和加权图 G 来确定传感器布置位置的
-        :param SS: 灵敏度矩阵，每个节点的行和列代表不同节点，矩阵元素表示节点间的灵敏度。SS.iloc[i, :] 表示第 i 行对应节点 i 到所有其他节点的灵敏度
-        :param G: 加权图，表示管网的拓扑结构，每个节点通过管道连接。图的边的权重通常是根据水力距离或者流量等计算的
-        :param group: 节点分组，字典的键是分组编号，值是该组的节点名称列表
-        :return:
-        """
-        # 传感器布置个数以及位置
-        # W = self.weight()
-        n = self.n - len(self.delnodes)
-        nodes = copy.deepcopy(self.nodes)
-        for node in self.delnodes:
-            nodes.remove(node)
-        # sumSS：list[float],每个节点到其他节点的灵敏度之和。SS.iloc[i, :] 返回第 i 个节点与所有其他节点的灵敏度值，sum(SS.iloc[i, :]) 计算这些灵敏度值的总和。
-        sumSS = []
-        for i in range(0, n):
-            sumSS.append(sum(SS.iloc[i, :]))
-        # 一个整数范围，表示每个节点的索引，用作sumSS_ DataFrame的索引
-        indices = range(0, n)
-        # sumSS_：pandas.DataFrame,将 sumSS 转换成 DataFrame 格式，并且将节点的总灵敏度保存到 CSV 文件 sumSS_data.csv 中
-        sumSS_ = pd.DataFrame(np.array(sumSS), index=indices)
-        # sumSS_.to_csv('sumSS_data.csv')  # 存储节点总灵敏度
-
-        # sumSS：pandas.DataFrame,sumSS 被转换为 DataFrame 类型，并且按总灵敏度（即灵敏度之和）降序排列。此时，sumSS 是按节点的灵敏度之和排序的 DataFrame
-        sumSS = pd.DataFrame(np.array(sumSS), index=nodes)
-        sumSS = sumSS.sort_values(by=[0], ascending=[False])
-        # sensorindex：list[str],用于存储根据灵敏度排序选出的传感器位置的节点名称,存储根据总灵敏度排序的节点列表，用于传感器布置
-        sensorindex = []
-        # sensorindex_2：list[str],用于存储每组内根据灵敏度排序选出的传感器位置的节点名称,存储每个组内根据灵敏度排序选择的传感器节点
-        sensorindex_2 = []
-        # group_S：dict[int, pandas.DataFrame],存储每个组内的灵敏度矩阵
-        group_S = {}
-        # group_sumSS：dict[int, list[float]],存储每个组内节点的总灵敏度，值为每个组内节点灵敏度之和的列表
-        group_sumSS = {}
-
-        # 改动
-        for i in range(0, len(group)):
-            for node in self.delnodes:
-                # 这里的group[i]是每个组的节点列表，代码首先去除已经被标记为删除的节点self.delnodes
-                if node in group[i]:
-                    group[i].remove(node)
-            group_S[i] = SS.loc[group[i], group[i]]
-            # 对每个组内的节点，计算组内节点的总灵敏度（group_sumSS[i]）。它将每个组内节点的灵敏度值相加，并且按灵敏度降序排序
-            group_sumSS[i] = []
-            for j in range(0, len(group[i])):
-                group_sumSS[i].append(sum(group_S[i].iloc[j, :]))
-            group_sumSS[i] = pd.DataFrame(np.array(group_sumSS[i]), index=group[i])
-            group_sumSS[i] = group_sumSS[i].sort_values(by=[0], ascending=[False])
-            for node in self.less_than_min_diameter_junction_list:
-                # 这里的group_sumSS[i]是每个分组的灵敏度节点排序列表，去除已经被标记为删除的节点self.less_than_min_diameter_junction_list
-                if node in group_sumSS[i]:
-                    group_sumSS[i].remove(node)
-        pass
-
-        # 1.选sumSS最大的节点，然后把这个节点所在的那个组删掉，就可以不再从这个组选点。再重新排序选sumSS最大的;
-        # 2.在每组内选group_sumSS最大的节点
-        # 在这个循环中，首先选择灵敏度最高的节点Smaxnode并添加到sensorindex。然后根据灵敏度排序，删除已选的节点并继续选择下一个灵敏度最大的节点。这个过程用于选择传感器的位置
-        sensornum = self.sensornum
-        for i in range(0, sensornum):
-            # Smaxnode：str,最大灵敏度节点，sumSS.index[0] 表示灵敏度最高的节点
-            Smaxnode = sumSS.index[0]
-            sensorindex.append(Smaxnode)
-            sensorindex_2.append(group_sumSS[i].index[0])
-
-            for key, value in group.items():
-                if Smaxnode in value:
-                    sumSS = sumSS.drop(index=group[key])
-                    continue
-
-            sumSS = sumSS.sort_values(by=[0], ascending=[False])
-
-        return sensorindex, sensorindex_2
-
-
-# 2025/03/13
-def get_ID(name: str, sensor_num: int, min_diameter: int) -> list[str]:
-    """
-    获取布置测压点的坐标,初始测压点布置根据灵敏度来布置，计算初始情况下的校准过程的error
-    :param name: 数据库名称
-    :param sensor_num: 测压点数目
-    :param min_diameter: 安装的最小管径
-    :return: 测压点节点ID
-    """
-    # inp_file_real：str,输入文件名，表示原始水力模型文件的路径,该文件格式为 EPANET 输入文件（.inp），包含管网的结构信息、节点、管道、泵等数据
-    inp_file_real = f'./db_inp/{name}.db.inp'
-    # sensornum：int,需要布置的传感器数量
-    # sensornum = sensor_num
-    # wn_real：wntr.network.WaterNetworkModel,加载 EPANET 水力模型
-    wn_real = wntr.network.WaterNetworkModel(inp_file_real)  # 真实粗糙度的原始管网
-    # sim_real：wntr.sim.EpanetSimulator,创建一个水力仿真器对象
-    sim_real = wntr.sim.EpanetSimulator(wn_real)
-    # results_real：wntr.sim.results.SimulationResults,运行仿真并返回结果
-    results_real = sim_real.run_sim()
-
-    # real_C：list[float]，包含所有管道粗糙度的列表
-    real_C = wn_real.query_link_attribute('roughness').tolist()
-    # wn_fun1：wn_func（继承自 object），创建 wn_func 类的实例，传入 wn_real 水力模型对象。wn_func 用于计算管网相关的水力属性，比如水力距离、灵敏度等
-    wn_fun1 = wn_func(wn_real, min_diameter=min_diameter)
-    # nodes：list[str]，管网的节点名称列表
-    nodes = wn_fun1.nodes
-    # delnodes：list[str]，被删除的节点（如水库、泵、阀门连接的节点等）
-    delnodes = wn_fun1.delnodes
-    # Coor_node：pandas.DataFrame
-    Coor_node = getCoor(wn_real)
-    Coor_node = Coor_node.drop(wn_fun1.delnodes)
-    nodes = [node for node in wn_fun1.nodes if node not in delnodes]
-    # coordinates：pandas.Series，存储所有节点的坐标，类型为 Series，索引为节点名称，值为 (x, y) 坐标对
-    coordinates = wn_fun1.coordinates
-
-    # 随机产生监测点
-    # junctionnum：int，nodes 的长度，表示节点的数量
-    junctionnum = len(nodes)
-    # random_numbers：list[int]，使用 random.sample 随机选择 sensornum（20）个节点的编号。它返回一个不重复的随机编号列表
-    # random_numbers = random.sample(range(junctionnum), sensor_num)
-    # for i in range(sensor_num):
-    #     # print(random_numbers[i])
-
-    wn_fun1.get_Conn()
-    # hL：pandas.DataFrame，水力距离矩阵，表示每个节点到其他节点的水力阻力
-    # G：networkx.DiGraph，加权有向图，表示管网的拓扑结构，节点之间的边带有权重
-    hL, G = wn_fun1.CtoS()
-    # SS：pandas.DataFrame，灵敏度矩阵，表示每个节点对管网变化（如粗糙度、流量等）的响应
-    SS = wn_fun1.Jaco(hL)
-    # group：dict[int, list[str]]，使用 kgroup 函数将节点按坐标分成若干组，每组包含的节点数不一定相同。group 是一个字典，键为分组编号，值为节点名列表
-
-    G1 = wn_real.to_graph()
-    G1 = G1.to_undirected()  # 变为无向图
-
-    group = kgroup(Coor_node, sensor_num)
-    # group = skater_partition(G1, sensor_num)
-    # group = spectral_partition(G1, sensor_num)
-
-    # print(group)
-    # --------------------- 保存 group 数据 ---------------------
-    # 将 group 数据转换为一个“长格式”的 DataFrame，
-    # 每一行记录一个节点及其所属的分组
-    # group_data = []
-    # for group_id, node_list in group.items():
-    #     for node in node_list:
-    #         group_data.append({"Group": group_id, "Node": node})
-    #
-    # df_group = pd.DataFrame(group_data)
-    #
-    # # 保存为 Excel 文件，文件名为 "group.xlsx"；index=False 表示不保存行索引
-    # df_group.to_excel("group.xlsx", index=False)
-
-    # wn_fun：Sensorplacement（继承自wn_func）
-    # 创建Sensorplacement类的实例，传入水力网络模型wn_real和传感器数量sensornum。Sensorplacement用于计算和布置传感器
-    wn_fun = Sensorplacement(wn_real, sensor_num, min_diameter=min_diameter)
-    wn_fun.__dict__.update(wn_fun1.__dict__)
-    # sensorindex：list[str]，初始传感器布置位置的节点名称
-    # sensorindex_2：list[str]，根据分组选择的传感器位置
-    sensorindex, sensorindex_2 = wn_fun.sensor(SS, G, group)  # 初始的sensorindex
-    # print(str(sensor_num), "个测压点，测压点位置：", sensorindex)
-
-
-    # 重新打开数据库
-    # if is_project_open(name=name):
-    #     close_project(name=name)
-    # open_project(name=name)
-    # for node_id in sensorindex :
-    #     sensor_coord[node_id] = get_node_coord(name=name, node_id=node_id)
-    # close_project(name=name)
-    # print(sensor_coord)
-    # # 分区画图
-    # colorlist = ['lightpink', 'coral', 'rosybrown', 'olive', 'powderblue', 'lightskyblue', 'steelblue', 'peachpuff','brown','silver','indigo','lime','gold','violet','maroon','navy','teal','magenta','cyan',
-    #              'burlywood', 'tan', 'slategrey', 'thistle', 'lightseagreen', 'lightgreen', 'red','blue','yellow','orange','purple','grey','green','pink','lightblue','beige','chartreuse','turquoise','lavender','fuchsia','coral']
-    # G = wn_real.to_graph()
-    # G = G.to_undirected()  # 变为无向图
-    # pos = nx.get_node_attributes(G, 'pos')
-    # pass
-    #
-    # for i in range(0, sensor_num):
-    #     ax = plt.gca()
-    #     ax.set_title(inp_file_real + str(sensor_num))
-    #     nodes = nx.draw_networkx_nodes(G, pos, nodelist=group[i], node_color=colorlist[i], node_size=10)
-    # nodes = nx.draw_networkx_nodes(G, pos,
-    #                                nodelist=sensorindex_2, node_color='red', node_size=70, node_shape='*'
-    #                                )
-    # edges = nx.draw_networkx_edges(G, pos)
-    # ax.spines['top'].set_visible(False)
-    # ax.spines['right'].set_visible(False)
-    # ax.spines['bottom'].set_visible(False)
-    # ax.spines['left'].set_visible(False)
-    # plt.savefig(inp_file_real + str(sensor_num) + ".png", dpi=300)
-    # plt.show()
-    #
-    # wntr.graphics.plot_network(wn_real, node_attribute=sensorindex_2, node_size=50, node_labels=False,
-    #                            title=inp_file_real + '_Projetion' + str(sensor_num))
-    # plt.savefig(inp_file_real + '_S' + str(sensor_num) + ".png", dpi=300)
-    # plt.show()
-    return sensorindex
-
-
-if __name__ == '__main__':
-    sensorindex = get_ID(name=project_info.name, sensor_num=20, min_diameter=300)
-
-    print(sensorindex)
-    # 将 sensor_coord 字典转换为 DataFrame，
-    # 使用 orient='index' 表示字典的键作为 DataFrame 的行索引，
-    # 数据中每个键对应的 value 是一个子字典，其键 'x' 和 'y' 成为 DataFrame 的列名
-    # df_sensor_coord = pd.DataFrame.from_dict(sensor_coord, orient='index')
-    #
-    # # 将索引名称设为 'Node'
-    # df_sensor_coord.index.name = 'Node'
-    #
-    # # 保存到 Excel 文件
-    # df_sensor_coord.to_excel("sensor_coord.xlsx", index=True)

app/algorithms/simulation/__init__.py

@@ -1,19 +0,0 @@
-from app.algorithms.simulation.scenarios import (
-    convert_to_local_unit,
-    burst_analysis,
-    valve_close_analysis,
-    flushing_analysis,
-    contaminant_simulation,
-    age_analysis,
-    pressure_regulation,
-)
-
-__all__ = [
-    "convert_to_local_unit",
-    "burst_analysis",
-    "valve_close_analysis",
-    "flushing_analysis",
-    "contaminant_simulation",
-    "age_analysis",
-    "pressure_regulation",
-]

app/algorithms/simulation/runner.py

@@ -1,876 +0,0 @@
-import numpy as np
-from app.services.tjnetwork import (
-    ChangeSet,
-    close_project,
-    copy_project,
-    delete_project,
-    get_pattern,
-    get_patterns,
-    get_pump,
-    get_reservoir,
-    get_status,
-    get_tank,
-    get_time,
-    have_project,
-    is_project_open,
-    open_project,
-    read_all,
-    run_project,
-    set_pattern,
-    set_status,
-    set_tank,
-    set_time,
-)
-# from get_real_status import *
-from datetime import datetime,timedelta
-from math import modf
-import json
-import pytz
-import requests
-import time
-import app.services.project_info as project_info
-
-url_path = 'http://10.101.15.16:9000/loong'  # 内网
-# url_path = 'http://183.64.62.100:9057/loong'  # 外网
-url_real = url_path + '/api/mpoints/realValue'
-url_hist = url_path + '/api/curves/data'
-
-PATTERN_TIME_STEP=15.0
-DN_900_ID='2498'
-DN_500_ID='3854'
-DN_1000_ID='3853'
-H_RESSURE='2510'
-L_PRESURE='2514'
-H_TANK='4780'
-L_TANK='4854'
-
-H_REGION_1='SA_ZBBDJSCP000002'
-H_REGION_2='' #to do
-L_REGION_1='SA_ZBBDTJSC000001'
-L_REGION_2='SA_R00003'
-
-# reservoir basic height
-RESERVOIR_BASIC_HEIGHT = float(250.35)
-
-# regions
-regions = ['hp', 'lp']
-regions_demand_patterns = {'hp': ['DN900', 'DN500'], 'lp': ['DN1000']}  # 出厂水量近似表示用水量
-regions_patterns = {'hp': ['ChuanYiJiXiao', 'BeiQuanHuaYuan', 'ZhuangYuanFuDi', 'JingNingJiaYuan',
-                           '308', 'JiaYinYuan', 'XinChengGuoJi', 'YiJingBeiChen', 'ZhongYangXinDu',
-                           'XinHaiJiaYuan', 'DongFengJie', 'DingYaXinYu', 'ZiYunTai', 'XieMaGuangChang',
-                           'YongJinFu', 'BianDianZhan', 'BeiNanDaDao', 'TianShengLiJie', 'XueYuanXiaoQu',
-                           'YunHuaLu', 'GaoJiaQiao', 'LuZuoFuLuXiaDuan', 'TianRunCheng', 'CaoJiaBa',
-                           'PuLingChang', 'QiLongXiaoQu', 'TuanXiao',
-                           'TuanShanBaoZhongShiHua', 'XieMa', 'BeiWenQuanJiuHaoErQi', 'LaiYinHuSiQi',
-                           'DN500', 'DN900'],
-                    'lp': ['PanXiMingDu', 'WanKeJinYuHuaFuGaoCeng', 'KeJiXiao',
-                           'LuGouQiao', 'LongJiangHuaYuan', 'LaoQiZhongDui', 'ShiYanCun', 'TianQiDaSha',
-                           'TianShengPaiChuSuo', 'TianShengShangPin', 'JiaoTang', 'RenMinHuaYuan',
-                           'TaiJiBinJiangYiQi', 'TianQiHuaYuan', 'TaiJiBinJiangErQi', '122Zhong',
-                           'WanKeJinYuHuaFuYangFang', 'ChengBeiCaiShiKou', 'WenXingShe', 'YueLiangTianBBGJCZ',
-                           'YueLiangTian', 'YueLiangTian200', 'ChengTaoChang', 'HuoCheZhan', 'LiangKu', 'QunXingLu',
-                           'JiuYuanErTongYiYuan', 'TangDouHua', 'TaiJiBinJiangErQi(SanJi)',
-                           'ZhangDouHua', 'JinYunXiaoQuDN400',
-                           'DN1000']}
-
-# nodes
-monitor_single_patterns = ['ChuanYiJiXiao', 'BeiQuanHuaYuan', 'ZhuangYuanFuDi', 'JingNingJiaYuan',
-                           '308', 'JiaYinYuan', 'XinChengGuoJi', 'YiJingBeiChen', 'ZhongYangXinDu',
-                           'XinHaiJiaYuan', 'DongFengJie', 'DingYaXinYu', 'ZiYunTai', 'XieMaGuangChang',
-                           'YongJinFu', 'PanXiMingDu', 'WanKeJinYuHuaFuGaoCeng', 'KeJiXiao',
-                           'LuGouQiao', 'LongJiangHuaYuan', 'LaoQiZhongDui', 'ShiYanCun', 'TianQiDaSha',
-                           'TianShengPaiChuSuo', 'TianShengShangPin', 'JiaoTang', 'RenMinHuaYuan',
-                           'TaiJiBinJiangYiQi', 'TianQiHuaYuan', 'TaiJiBinJiangErQi', '122Zhong',
-                           'WanKeJinYuHuaFuYangFang']
-monitor_single_patterns_id = {'ChuanYiJiXiao': '7338', 'BeiQuanHuaYuan': '7315', 'ZhuangYuanFuDi': '7316',
-                              'JingNingJiaYuan': '7528', '308': '8272', 'JiaYinYuan': '7304',
-                              'XinChengGuoJi': '7325', 'YiJingBeiChen': '7328', 'ZhongYangXinDu': '7329',
-                              'XinHaiJiaYuan': '9138', 'DongFengJie': '7302', 'DingYaXinYu': '7331',
-                              'ZiYunTai': '7420,9059', 'XieMaGuangChang': '7326', 'YongJinFu': '9059',
-                              'PanXiMingDu': '7320', 'WanKeJinYuHuaFuGaoCeng': '7419',
-                              'KeJiXiao': '7305', 'LuGouQiao': '7306', 'LongJiangHuaYuan': '7318',
-                              'LaoQiZhongDui': '9075', 'ShiYanCun': '7309', 'TianQiDaSha': '7323',
-                              'TianShengPaiChuSuo': '7335', 'TianShengShangPin': '7324', 'JiaoTang': '7332',
-                              'RenMinHuaYuan': '7322', 'TaiJiBinJiangYiQi': '7333', 'TianQiHuaYuan': '8235',
-                              'TaiJiBinJiangErQi': '7334', '122Zhong': '7314', 'WanKeJinYuHuaFuYangFang': '7418'}
-
-monitor_unity_patterns = ['BianDianZhan', 'BeiNanDaDao', 'TianShengLiJie', 'XueYuanXiaoQu',
-                          'YunHuaLu', 'GaoJiaQiao', 'LuZuoFuLuXiaDuan', 'TianRunCheng',
-                          'CaoJiaBa', 'PuLingChang', 'QiLongXiaoQu', 'TuanXiao',
-                          'ChengBeiCaiShiKou', 'WenXingShe', 'YueLiangTianBBGJCZ',
-                          'YueLiangTian', 'YueLiangTian200',
-                          'ChengTaoChang', 'HuoCheZhan', 'LiangKu', 'QunXingLu',
-                          'TuanShanBaoZhongShiHua', 'XieMa', 'BeiWenQuanJiuHaoErQi', 'LaiYinHuSiQi',
-                          'JiuYuanErTongYiYuan', 'TangDouHua', 'TaiJiBinJiangErQi(SanJi)',
-                          'ZhangDouHua', 'JinYunXiaoQuDN400',
-                          'DN500', 'DN900', 'DN1000']
-monitor_unity_patterns_id = {'BianDianZhan': '7339', 'BeiNanDaDao': '7319', 'TianShengLiJie': '8242',
-                             'XueYuanXiaoQu': '7327', 'YunHuaLu': '7312', 'GaoJiaQiao': '7340',
-                             'LuZuoFuLuXiaDuan': '7343', 'TianRunCheng': '7310', 'CaoJiaBa': '7300',
-                             'PuLingChang': '7307', 'QiLongXiaoQu': '7321', 'TuanXiao': '8963',
-                             'ChengBeiCaiShiKou': '7330', 'WenXingShe': '7311',
-                             'YueLiangTianBBGJCZ': '7313', 'YueLiangTian': '7313', 'YueLiangTian200': '7313',
-                             'ChengTaoChang': '7301', 'HuoCheZhan': '7303',
-                             'LiangKu': '7296', 'QunXingLu': '7308',
-                             'DN500': '3854', 'DN900': '2498', 'DN1000': '3853'}
-monitor_patterns = monitor_single_patterns + monitor_unity_patterns
-monitor_patterns_id = {**monitor_single_patterns_id, **monitor_unity_patterns_id}
-# pumps
-pumps_name = ['1#', '2#', '3#', '4#', '5#', '6#', '7#']
-pumps = ['PU00000', 'PU00001', 'PU00002', 'PU00003', 'PU00004', 'PU00005', 'PU00006']
-variable_frequency_pumps = ['PU00004', 'PU00005', 'PU00006']
-pumps_id = {'PU00000': '2747', 'PU00001': '2776', 'PU00002': '2730', 'PU00003': '2787',
-            'PU00004': '2500', 'PU00005': '2502', 'PU00006': '2504'}
-# reservoirs
-reservoirs = ['ZBBDJSCP000002', 'R00003']
-reservoirs_id = {'ZBBDJSCP000002': '2497', 'R00003': '2571'}
-# tanks
-tanks = ['ZBBDTJSC000002', 'ZBBDTJSC000001']
-tanks_id = {'ZBBDTJSC000002': '4780', 'ZBBDTJSC000001': '9774'}
-
-
-class DataLoader:
-    """数据加载器"""
-    def __init__(self, project_name, start_time: datetime, end_time: datetime,
-                 pumps_control: dict = None, tank_initial_level_control: dict = None,
-                 region_demand_control: dict = None, downloading_prohibition: bool = False):
-        self.project_name = project_name  # 数据库名
-        self.current_time = self.round_time(datetime.now(pytz.timezone('Asia/Shanghai')), 1)  # 圆整至整分钟
-        self.current_round_time = self.round_time(self.current_time, int(PATTERN_TIME_STEP))
-        self.updating_data_flag = True \
-            if self.current_round_time == self.round_time(start_time, int(PATTERN_TIME_STEP)) \
-            else False  # 判断是否从当前时刻开始模拟(是否更新最新监测数据)
-        self.downloading_prohibition = downloading_prohibition  # 是否禁止下载数据(默认False: 允许下载)
-        self.updating_data_flag = False if self.downloading_prohibition else self.updating_data_flag
-        self.pattern_start_index = get_pattern_index(
-            self.round_time(start_time, int(PATTERN_TIME_STEP)).strftime("%Y-%m-%d %H:%M:%S"))  # pattern起始索引
-        self.pattern_end_index = get_pattern_index(
-            self.round_time(end_time, int(PATTERN_TIME_STEP)).strftime("%Y-%m-%d %H:%M:%S"))  # pattern结束索引
-        self.pattern_index_list = list(range(self.pattern_start_index, self.pattern_end_index + 1))  # pattern索引列表
-        self.download_id = self.get_download_id()  # 数据下载接口id '7338,7315,7316,...'
-        self.current_time_download_data = dict(
-            zip(self.download_id.split(','),
-                [np.nan]*len(list(self.download_id.split(','))))
-        )  # {id(str): value(float)}
-        self.current_time_download_data_flag = dict(
-            zip(self.download_id.split(','),
-                [False]*len(list(self.download_id.split(','))))
-        )  # 下载数据是否具备实时性, {id(str): flag(bool)}
-        self.old_flow_data = self.init_dict_of_list(dict(
-            zip(monitor_patterns,
-                [[np.nan]] * (len(monitor_patterns)))
-        ))  # {pattern_name(str): flow(float)}
-        self.old_pattern_factor = self.init_dict_of_list(dict(
-            zip(monitor_patterns,
-                [[np.nan]] * (len(monitor_patterns)))
-        ))  # {pattern_name(str): [pattern_factor(float)]}
-        self.new_flow_data = self.init_dict_of_list(dict(
-            zip(monitor_patterns,
-                [[np.nan]] * (len(monitor_patterns)))
-        ))  # {pattern_name(str): flow(float)}
-        self.new_pattern_factor = self.init_dict_of_list(dict(
-            zip(monitor_patterns,
-                [[np.nan]] * (len(monitor_patterns)))
-        ))  # {pattern_name(str): [pattern_factor(float)]}
-        self.reservoir_data = dict(zip(reservoirs, [np.nan]*len(reservoirs)))  # {reservoir_name(str): level(float)}
-        self.tank_data = dict(zip(tanks, [np.nan] * len(tanks)))  # {tank_name(str): level(float)}
-        self.pump_data = self.init_dict_of_list(
-            dict(zip(pumps, [[np.nan]]*len(pumps))))  # {pump_name(str): [frequency(float)]}
-        self.pump_control = pumps_control  # {pump_name(str): [frequency(float)]}
-        self.tank_initial_level_control = tank_initial_level_control  # {tank_name(str): level(float)}
-        self.region_demand_current = dict(zip(regions, [0]*len(regions)))  # {region_name(str): total_demand(float)}
-        self.region_demand_control = region_demand_control  # {region_name(str): total_demand(float)}
-        self.region_demand_control_factor = dict(
-            zip(regions, [1]*len(regions)))  # 区域流量控制系数(用于调整用水量), {region_name(str): factor(float)}
-
-    def load_data(self):
-        """生成数据集"""
-        self.download_data()  # 下载实时数据
-        self.get_old_pattern_and_flow()  # 读取历史记录pattern信息
-        self.cal_demand_convert_factor()  # 计算用水量转换系数(设定用水量时)
-        self.set_new_flow()  # 设置'更新'流量
-        self.set_new_pattern_factor()  # 设置'更新'pattern factors
-        self.set_reservoirs()  # 设置清水池
-        self.set_tanks()  # 设置调节池
-        self.set_pumps()  # 设置水泵
-        return self.pattern_start_index
-
-    def download_data(self):
-        """下载数据"""
-        if self.updating_data_flag is True:
-            print('{} -- Start downloading data.'.format(
-                datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
-            data_wait_flag = True
-            while data_wait_flag:
-                try:
-                    newest_data_time = self.download_real_data(self.download_id)  # 获取实时数据
-                except Exception as e:
-                    print('{}\nWaiting for real data.'.format(e))
-                    time.sleep(1)
-                else:
-                    print('{} -- Downloading data ok. Newest timestamp: {}.'.format(
-                        datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
-                        newest_data_time.strftime('%Y-%m-%d %H:%M:%S')))
-                    data_wait_flag = False
-
-    def cal_current_region_demand(self):
-        """计算区域当前用水量"""
-        if self.updating_data_flag is True:
-            for region in self.region_demand_current.keys():
-                total_demand = 0
-                for pipe in regions_demand_patterns[region]:
-                    total_demand += self.current_time_download_data[monitor_patterns_id[pipe]]  # 出厂流量
-                self.region_demand_current[region] = total_demand
-
-    def cal_history_region_demand(self, pattern_index_list):
-        """计算区域历史用水量(对应记录的pattern)"""
-        old_demand = {}
-        for region in regions:
-            total_demand = 0
-            for pipe_pattern_name in regions_demand_patterns[region]:
-                old_flows, old_patterns = self.get_history_pattern_info(self.project_name, pipe_pattern_name)
-                for idx in pattern_index_list:
-                    total_demand += old_flows[idx] / 4  # 15分钟水量
-            old_demand[region] = total_demand
-        return old_demand
-
-    def cal_demand_convert_factor(self):
-        """计算用水量转换系数(设定用水量时)"""
-        self.cal_current_region_demand()  # 计算区域当前时刻用水量
-        old_demand_moment = self.cal_history_region_demand([self.pattern_start_index])  # 计算区域目标时刻总用水量
-        old_demand_period = self.cal_history_region_demand(self.pattern_index_list)  # 计算区域目标时段总用水量
-        for region in regions:
-            self.region_demand_control_factor[region] \
-                = (self.region_demand_current[region] / 4) / old_demand_moment[region] \
-                if self.updating_data_flag is True else 1
-            self.region_demand_control_factor[region] = self.region_demand_control[region] / old_demand_period[region] \
-                if (self.region_demand_control is not None) and (region in self.region_demand_control.keys()) \
-                else self.region_demand_control_factor[region]
-
-    def get_old_pattern_and_flow(self):
-        """获取所有pattern的选定时段的历史记录的pattern和flow"""
-        for idx in monitor_patterns:  # 遍历patterns
-            old_flows, old_patterns = self.get_history_pattern_info(self.project_name, idx)
-            for pattern_idx in self.pattern_index_list:
-                old_flow_data = old_flows[pattern_idx]
-                old_pattern_factor = old_patterns[pattern_idx]
-                if pattern_idx == self.pattern_start_index:  # 起始时刻
-                    self.old_flow_data[idx][0] = old_flow_data
-                    self.old_pattern_factor[idx][0] = old_pattern_factor
-                else:
-                    self.old_flow_data[idx].append(old_flow_data)
-                    self.old_pattern_factor[idx].append(old_pattern_factor)
-
-    def set_new_flow(self):
-        """计算模拟时段新流量(相较于历史记录)"""
-        for idx in self.new_flow_data.keys():  # 遍历patterns
-            region_name = None
-            for region in regions_patterns.keys():
-                if idx in regions_patterns[region]:
-                    region_name = region  # pattern所属分区
-                    break
-            # 实时流量
-            if self.updating_data_flag is True:
-                if idx in monitor_unity_patterns[-3:]:  # 出水管流量
-                    self.new_flow_data[idx][0] = self.current_time_download_data[monitor_patterns_id[idx]]
-                else:  # 其余流量
-                    self.new_flow_data[idx][0] \
-                                    = self.region_demand_control_factor[region_name] * self.old_flow_data[idx][0]
-                # if idx == 'ZiYunTai':
-                #     idx_a, idx_b = monitor_patterns_id[idx].split(',')
-                #     self.new_flow_data[idx][0] \
-                #         = self.current_time_download_data[idx_a] - self.current_time_download_data[idx_b]
-                # else:
-                #     self.new_flow_data[idx][0] = self.current_time_download_data[monitor_patterns_id[idx]]
-                # for data_id in monitor_patterns_id[idx].split(','):
-                #     if (self.current_time_download_data_flag[data_id] is False) \
-                #             and (idx not in [pipe for pipe_list in regions_demand_patterns.values()
-                #                              for pipe in pipe_list]):  # 无法获取实时数据
-                #         self.new_flow_data[idx][0] \
-                #             = self.region_demand_control_factor[region_name] * self.old_flow_data[idx][0]
-                #         break
-            # 根据设定用水量修改新流量
-            if (self.region_demand_control is not None) \
-                    and (region_name in self.region_demand_control.keys()):
-                for pattern_idx in self.pattern_index_list:
-                    if pattern_idx == self.pattern_start_index:  # 起始时刻
-                        self.new_flow_data[idx][0] \
-                            = self.region_demand_control_factor[region_name] * self.old_flow_data[idx][0]
-                    else:
-                        self.new_flow_data[idx].append(
-                            self.region_demand_control_factor[region_name]
-                            * self.old_flow_data[idx][self.pattern_index_list.index(pattern_idx)]
-                        )
-
-    def set_new_pattern_factor(self):
-        """更新计算选定时段(设定用水量)/时刻的pattern factor"""
-        pattern_index_list = self.pattern_index_list \
-            if self.region_demand_control is not None \
-            else [self.pattern_start_index]
-        for idx in monitor_patterns:  # 遍历patterns
-            for pattern_idx in pattern_index_list:  # 遍历需要修改的pattern(index)
-                pattern_idx_cls = pattern_index_list.index(pattern_idx)  # 转换index(类表存储结构)
-                old_flow_data = self.old_flow_data[idx][pattern_idx_cls]
-                old_pattern_factor = self.old_pattern_factor[idx][pattern_idx_cls]
-                if pattern_idx_cls == 0:  # 起始时刻
-                    if idx in monitor_single_patterns:
-                        if not np.isnan(self.new_flow_data[idx][0]):
-                            self.new_pattern_factor[idx][0] = (self.new_flow_data[idx][0] * 1000 / 3600)  # m3/h to L/s
-                    if idx in monitor_unity_patterns:
-                        if not np.isnan(self.new_flow_data[idx][0]):
-                            self.new_pattern_factor[idx][0] \
-                                = old_pattern_factor * self.new_flow_data[idx][0] / old_flow_data
-                else:
-                    if idx in monitor_single_patterns:
-                        if len(self.new_flow_data[idx]) > pattern_idx_cls:
-                            self.new_pattern_factor[idx].append(
-                                (self.new_flow_data[idx][pattern_idx_cls] * 1000 / 3600))  # m3/h to L/s
-                    if idx in monitor_unity_patterns:
-                        if len(self.new_flow_data[idx]) > pattern_idx_cls:
-                            self.new_pattern_factor[idx].append(
-                                old_pattern_factor
-                                * self.new_flow_data[idx][pattern_idx_cls]
-                                / old_flow_data)
-
-    def set_reservoirs(self):
-        """设置清水池"""
-        if self.updating_data_flag is True:
-            for idx in self.reservoir_data.keys():
-                if self.current_time_download_data_flag[reservoirs_id[idx]] is False:  # 无法获取实时数据
-                    print('There is no current data of reservoir: {}.'.format(idx))
-                else:
-                    self.reservoir_data[idx] \
-                        = self.current_time_download_data[reservoirs_id[idx]] + RESERVOIR_BASIC_HEIGHT
-
-    def set_tanks(self):
-        """设置调节池"""
-        for idx in self.tank_data.keys():
-            if self.updating_data_flag is True:
-                if self.current_time_download_data_flag[tanks_id[idx]] is False:  # 无法获取实时数据
-                    print('There is no current data of tank: {}.'.format(idx))
-                else:
-                    self.tank_data[idx] = self.current_time_download_data[tanks_id[idx]]
-            self.tank_data[idx] = self.tank_initial_level_control[idx] \
-                if (self.tank_initial_level_control is not None) and (idx in self.tank_initial_level_control) \
-                else self.tank_data[idx]
-
-    def set_pumps(self):
-        """设置水泵"""
-        for idx in self.pump_data.keys():
-            if self.updating_data_flag is True:
-                if self.current_time_download_data_flag[pumps_id[idx]] is False:  # 无法获取实时数据
-                    print('There is no current data of pump: {}.'.format(idx))
-                    if (self.pump_control is not None) and (idx in self.pump_control.keys()):
-                        self.pump_data[idx] = self.pump_control[idx]
-                else:
-                    self.pump_data[idx] = [self.current_time_download_data[pumps_id[idx]]]
-                    if (self.pump_control is not None) and (idx in self.pump_control.keys()):
-                        self.pump_data[idx] = self.pump_data[idx] + self.pump_control[idx] \
-                            if len(self.pump_control[idx]) < len(self.pattern_index_list) \
-                            else self.pump_control[idx]  # 水泵设定
-            else:
-                if (self.pump_control is not None) and (idx in self.pump_control.keys()):
-                    self.pump_data[idx] = self.pump_control[idx]
-            self.pump_data[idx] \
-                = list(np.array(self.pump_data[idx]) / 50) \
-                if idx in variable_frequency_pumps else self.pump_data[idx]
-
-    def set_valves(self):
-        """设置阀门"""
-        pass
-
-    def download_real_data(self, ids: str):
-        """加载实时数据"""
-        # 数据接口的地址
-        global url_real
-        # 设置GET请求的参数
-        params = {'ids': ids}
-        # 发送GET请求获取数据
-        response = requests.get(url_real, params=params)
-        # 检查响应状态码，200表示请求成功
-        if response.status_code == 200:
-            newest_data_time = None  # 下载记录数据的最新时间
-            # 解析响应的JSON数据
-            data = response.json()
-            for realValue in data:  # 取出逐个id的数据
-                data_time = convert_utc_to_bj(realValue['datadt'])  # datetime
-                self.current_time_download_data[str(realValue['id'])] \
-                    = float(realValue['realValue'])  # {id(str): value(float)}
-                if data_time > self.current_round_time.replace(tzinfo=None) - timedelta(minutes=5):  # 下载数据为实时数据
-                    self.current_time_download_data_flag[str(realValue['id'])] = True
-                if newest_data_time is None:
-                    newest_data_time = data_time
-                else:
-                    newest_data_time = data_time if data_time > newest_data_time else newest_data_time  # 更新最新时间
-            if newest_data_time <= self.current_round_time.replace(tzinfo=None) - timedelta(minutes=5):  # 最新记录时间早于当前时间
-                warning_text = 'There is no current data with newest timestamp: {}.'.format(
-                        newest_data_time.strftime('%Y-%m-%d %H:%M:%S'))
-                delta_time = self.current_round_time.replace(tzinfo=None) - newest_data_time
-                if delta_time < timedelta(minutes=PATTERN_TIME_STEP):  # 时间接近(可等待再次下载)
-                    raise Exception(warning_text)
-                else:
-                    print(warning_text)
-                    self.updating_data_flag = False
-            else:
-                for idx in monitor_unity_patterns[-3:]:  # 出水管流量
-                    if self.current_time_download_data_flag[monitor_patterns_id[idx]] is False:  # 无法获取出水管流量的实时数据
-                        print('There is no current data of outflow: {}.'.format(idx))
-                        self.updating_data_flag = False
-            if self.updating_data_flag is False:
-                print('Abandon updating data with downloaded data.')
-            return newest_data_time
-        else:
-            # 如果请求不成功，打印错误信息
-            print("请求失败，状态码:", response.status_code)
-            raise ConnectionError('Cannot download data.')
-
-    @ staticmethod
-    def init_dict_of_list(dict_of_list):
-        """初始化值为列表的字典(重新生成列表地址, 防止指向同一列表)"""
-        for idx in dict_of_list.keys():
-            dict_of_list[idx] = dict_of_list[idx].copy()
-        return dict_of_list
-
-    @ staticmethod
-    def get_download_id():
-        """生成下载数据项的id"""
-        # id_list = (list(monitor_single_patterns_id.values())
-        #            + list(monitor_unity_patterns_id.values())
-        #            + list(tanks_id.values())
-        #            + list(reservoirs_id.values())
-        #            + list(pumps_id.values()))
-        id_list = (list(monitor_unity_patterns_id.values())[-3:]
-                   + list(tanks_id.values())
-                   + list(reservoirs_id.values())
-                   + list(pumps_id.values()))
-        id_list = sorted(set(id_list), key=id_list.index)
-        if None in id_list:
-            id_list.remove(None)
-        return ','.join(id_list)
-
-    @ staticmethod
-    def get_history_pattern_info(project_name, pattern_name):
-        """读取选定pattern的保存的历史pattern信息(flow, factor)"""
-        factors_list = []
-        flow_list = []
-        patterns_info = read_all(project_name,
-                                 f"select * from history_patterns_flows where id = '{pattern_name}' order by _order")
-        for item in patterns_info:
-            flow_list.append(float(item['flow']))
-            factors_list.append(float(item['factor']))
-        return flow_list, factors_list
-
-    @ staticmethod
-    def judge_time(current_time, time_index_list):
-        """时间判断"""
-        current_index \
-            = time_index_list.index(current_time) if (current_time in time_index_list) else None
-        return current_index
-
-    @staticmethod
-    def get_time_index_list(start_time: datetime, end_time: datetime, step: int):
-        """生成时间索引"""
-        time_index_list = []  # 时间索引[str]
-        time_index = start_time
-        while time_index <= end_time:
-            time_index_list.append(time_index)
-            time_index += timedelta(minutes=step)
-        return time_index_list
-
-    @ staticmethod
-    def round_time(time_: datetime, interval=5):
-        """时间向下取整到整n分钟(北京时间): 四舍六入五留双/向下取整"""
-        # return datetime.fromtimestamp(round(time_.timestamp() / (60 * interval)) * (60 * interval))
-        return datetime.fromtimestamp(int((time_.timestamp()) // (60 * interval)) * (60 * interval))
-
-
-def convert_utc_to_bj(utc_time_str):
-    """将utc时间(str)转换成北京时间(datetime)"""
-    # 解析UTC时间字符串为datetime对象
-    utc_time = datetime.strptime(utc_time_str, '%Y-%m-%dT%H:%M:%SZ')
-    # 设定UTC时区
-    utc_timezone = pytz.timezone('UTC')
-    # 转换为北京时间
-    beijing_timezone = pytz.timezone('Asia/Shanghai')
-    beijing_time = utc_time.replace(tzinfo=utc_timezone).astimezone(beijing_timezone).replace(tzinfo=None)
-    return beijing_time
-
-
-def get_datetime(cur_datetime:str):
-    str_format = "%Y-%m-%d %H:%M:%S"
-    return datetime.strptime(cur_datetime, str_format)
-
-
-def get_strftime(cur_datetime: datetime):
-    str_format = "%Y-%m-%d %H:%M:%S"
-    return cur_datetime.strftime(str_format)
-
-
-def step_time(cur_datetime:str, step=5):
-    str_format="%Y-%m-%d %H:%M:%S"
-    dt=datetime.strptime(cur_datetime,str_format)
-    dt=dt+timedelta(minutes=step)
-    return datetime.strftime(dt,str_format)
-
-
-def get_pattern_index(cur_datetime:str)->int:
-    str_format="%Y-%m-%d %H:%M:%S"
-    dt=datetime.strptime(cur_datetime,str_format)
-    hr=dt.hour
-    mnt=dt.minute
-    i=int((hr*60+mnt)/PATTERN_TIME_STEP)
-    return i
-
-def get_pattern_index_str(cur_datetime:str)->str:
-    i=get_pattern_index(cur_datetime)
-    [minN,hrN]=modf(i*PATTERN_TIME_STEP/60)
-    minN_str=str(int(minN*60))
-    minN_str=minN_str.zfill(2)
-    hrN_str=str(int(hrN))
-    hrN_str=hrN_str.zfill(2)
-    str_i='{}:{}:00'.format(hrN_str,minN_str)
-    return str_i
-
-
-def from_seconds_to_clock (secs: int)->str:
-    hrs=int(secs/3600)
-    minutes=int((secs-hrs*3600)/60)
-    seconds=(secs-hrs*3600-minutes*60)
-    hrs_str=str(hrs).zfill(2)
-    minutes_str=str(minutes).zfill(2)
-    seconds_str=str(seconds).zfill(2)
-    str_clock='{}:{}:{}'.format(hrs_str,minutes_str,seconds_str)
-    return str_clock
-
-def from_clock_to_seconds (clock: str)->int:
-    str_format="%Y-%m-%d %H:%M:%S"
-    dt=datetime.strptime(clock,str_format)
-    hr=dt.hour
-    mnt=dt.minute
-    seconds=dt.second
-    return hr*3600+mnt*60+seconds
-
-def from_clock_to_seconds_2 (clock: str)->int:
-    str_format="%H:%M:%S"
-    dt=datetime.strptime(clock,str_format)
-    hr=dt.hour
-    mnt=dt.minute
-    seconds=dt.second
-    return hr*3600+mnt*60+seconds
-
-
-def from_clock_to_seconds_3 (clock: str)->int:
-    str_format = "%H:%M" # 更新时间格式以适应 "小时:分钟" 格式
-    dt = datetime.strptime(clock,str_format)
-    hr = dt.hour
-    mnt = dt.minute
-    seconds = dt.second
-    return hr * 3600 + mnt * 60
-
-
-###convert datetimestring 
-##"XXXX-XX-XXT00:00:00Z" ->"XXXX-XX-XX 00:00:00"
-def trim_time_flag(url_date_time:str)->str:
-    str_datetime=str.replace(url_date_time,'T',' ')
-    str_datetime=str.replace(str_datetime,'Z','')
-    return str_datetime
-
-# 单时间步长模拟
-def run_simulation(name:str,start_datetime:str,end_datetime:str=None, duration:int=900)->str:
-    if(is_project_open(name)):
-        close_project(name)
-    open_project(name)
-    #get_current_data(cur_datetime)
-    #extract the patternindex from datetime
-    #e.g. 0: the first time step for 00:00-00:14; 1: the second step for 00:15-00:30
-    start_datetime=trim_time_flag(start_datetime)
-    if(end_datetime!=None):
-        end_datetime=trim_time_flag(end_datetime)
-
-   
-    
-    ## redistribute the basedemand according to the currentTotalQ and the base_totalQ
-    # step 1. get_real _data
-    if end_datetime==None or start_datetime==end_datetime:
-        end_datetime=step_time(start_datetime)
-        
-    # # ids=['2498','3854','3853','2510','2514','4780','4854']
-    # # real_data=get_real_data(ids,start_datetime,end_datetime)
-    # print(datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d %H:%M:%S")+"--获取实时数据完毕\n")
-    # #step 2. re-distribute the real q to base demand of the node region_sa by region_sa
-    # regions=get_all_service_area_ids(name)
-    # total_demands={}
-    # for region in regions:
-    #     total_demands[region]=get_total_base_demand(name,region)
-    # region_demand_factor={}
-    # #Region_ID:SA_ZBBDJSCP000002 高区;SA_R00003+SA_ZBBDTJSC000001 低区
-    # H_region_real_demands=real_data[DN_900_ID][start_datetime]+real_data[DN_500_ID][start_datetime]
-    # L_region_real_demands=real_data[DN_1000_ID][start_datetime]
-    # factor_H_zone=H_region_real_demands/total_demands[H_REGION_1]/3.6 #3.6: m3/h->L/s
-    # factor_L_zone=L_region_real_demands/(total_demands[L_REGION_1]+total_demands[L_REGION_2])/3.6
-    # print(datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d %H:%M:%S")+"--流量因子计算完毕完毕\n")
-    # for region in regions:
-    #     region_nodes=get_nodes_in_region(name,region)
-    #     factor=1
-    #     if region==H_REGION_1 or H_REGION_2:
-    #         factor=factor_H_zone
-    #     else:
-    #         factor=factor_L_zone
-    #
-    #     for node in region_nodes:
-    #         d=get_demand(name,node)
-    #         for r in d['demands']:
-    #             r['demand']=factor*r['demand']
-    #         cs=ChangeSet()
-    #         cs.append(d)
-    #         set_demand(name,cs)
-    #
-    # #
-    # #
-    # print(datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d %H:%M:%S")+"--节点流量重分配完毕\n")
-    
-    #step 3. set pattern index to the current time,and set duration to 300 secs
-    # 
-    str_pattern_start=get_pattern_index_str(start_datetime)
-    dic_time=get_time(name)
-    dic_time['PATTERN START']=str_pattern_start
-   
-    if duration !=None:
-        dic_time['DURATION']=from_seconds_to_clock(duration)
-    else:
-        dic_time['DURATION']=dic_time['HYDRAULIC TIMESTEP']
-    cs=ChangeSet()
-    cs.operations.append(dic_time)
-    set_time(name,cs)
-    
-    # step4. run simulation and save the result to name-time.out for download
-    #inp_file = 'inp\\'+name+'.inp'
-    #db_name=name
-    #dump_inp(db_name,inp_file,'2')
-    # result=run_inp(db_name)
-    result=run_project(name)
-    #json string format
-    # simulation_result, output, report
-    result_data=json.loads(result)
-    #print(result_data['simulation_result'])
-    print(datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d %H:%M:%S")+'run finished successfully\n')
-    #print(result_data['report'])
-    return result
-
-
-# 在线模拟
-def run_simulation_ex(name: str, simulation_type: str, start_datetime: str,
-                      end_datetime: str = None, duration: int = 0,
-                      pump_control: dict[str, list] = None, tank_initial_level_control: dict[str, float] = None,
-                      region_demand_control: dict[str, float] = None, valve_control: dict[str, dict] = None,
-                      downloading_prohibition: bool = False) -> str:
-    time_cost_start = time.perf_counter()
-    print('{} -- Hydraulic simulation started.'.format(
-        datetime.now(pytz.timezone('Asia/Shanghai')).strftime('%Y-%m-%d %H:%M:%S')))
-
-    if is_project_open(name):
-        close_project(name)
-
-    if simulation_type.upper() == 'REALTIME':  # 实时模拟(修改原数据库)
-        name_c = name
-    elif simulation_type.upper() == 'EXTENDED':  # 扩展模拟(复制数据库)
-        name_c = '_'.join([name, 'c'])
-        if have_project(name_c):
-            if is_project_open(name_c):
-                close_project(name_c)
-            delete_project(name_c)
-        copy_project(name, name_c)  # 备份项目
-    else:
-        raise Exception('Incorrect simulation type, choose in (realtime, extended)')
-
-    open_project(name_c)
-
-    # 时间处理
-    # extract the pattern index from datetime
-    # e.g. 0: the first time step for 00:00-00:14; 1: the second step for 00:15-00:30
-    # start_datetime = get_strftime(convert_utc_to_bj(start_datetime))
-    start_datetime = trim_time_flag(start_datetime)
-    if end_datetime is not None:
-        # end_datetime = get_strftime(convert_utc_to_bj(end_datetime))
-        end_datetime = trim_time_flag(end_datetime)
-
-    # pump name转化/输入值规范化
-    if pump_control is not None:
-        for key in list(pump_control.keys()):
-            pump_control[key] = [pump_control[key]] if type(pump_control[key]) is not list else pump_control[key]
-            pump_control[pumps[pumps_name.index(key)]] = pump_control.pop(key)
-
-    # 重新分配节点(nodes)水量
-    # 1) (single)base_demand_new=1, pattern_new=real_data
-    # 2) (unity)base_demand_new=base_demand_old, pattern_new=factor*pattern_old(factor=flow_new/flow_old)
-    # 获取需水量数据
-    # a) 历史pattern对应水量(读取保存数据库)
-    # b) 实时水量(数据接口下载)
-
-    # 修改node demand = 1, pattern factor *= demand(monitor single patterns对应node)
-    # nodes = get_nodes(name_c)  # nodes
-    # for node_name in nodes:  # 遍历nodes
-    #     demands_dict = get_demand(name_c, node_name)  # {'demands':[{'demand':, 'pattern':}]}
-    #     for demands in demands_dict['demands']:
-    #         if (demands['pattern'] in monitor_single_patterns) and (demands['demand'] != 1):  # 1)
-    #             pattern = get_pattern(name_c, demands['pattern'])
-    #             pattern['factors'] = list(demands['demand'] * np.array(pattern['factors']))  # 修改pattern
-    #             cs = ChangeSet()
-    #             cs.append(pattern)
-    #             set_pattern(name_c, cs)
-    #             demands_dict['demands'][
-    #                 demands_dict['demands'].index(demands)
-    #             ]['demand'] = 1  # 修改demand
-    #     cs = ChangeSet()
-    #     cs.append(demands_dict)
-    #     set_demand(name_c, cs)
-
-    start_time = get_datetime(start_datetime)  # datetime
-    end_time = get_datetime(end_datetime) \
-        if end_datetime is not None \
-        else get_datetime(start_datetime) + timedelta(seconds=duration)  # datetime
-    # modify_pattern_start_index = get_pattern_index(start_datetime)  # 待修改pattern的起始索引(int)
-
-    dataset_loader = DataLoader(project_name=name_c,
-                                start_time=start_time, end_time=end_time,
-                                pumps_control=pump_control, tank_initial_level_control=tank_initial_level_control,
-                                region_demand_control=region_demand_control,
-                                downloading_prohibition=downloading_prohibition)  # 实例化数据加载器
-    modify_index \
-        = dataset_loader.load_data()  # 加载数据(index: 需要修改pattern的factor index, None: 无需修改除水泵和调节池外pattern)
-    new_patterns \
-        = dataset_loader.new_pattern_factor  # {name: float,}  pattern factor(实时: 更新, 其他: 保持/更新(设定用水量时))
-    tank_init_level = dataset_loader.tank_data  # {name: float,}  调节池初始液位(实时: 更新, 其他: 保持/更新(设定液位时))
-    reservoir_level = dataset_loader.reservoir_data  # {name: float,}  水库液位(实时: 更新, 其他: 保持)
-    pump_freq = dataset_loader.pump_data  # {name: [float,]}  水泵频率(实时: 更新, 其他: 保持/更新(设定状态时))
-    print(datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d %H:%M:%S") + " -- Loading data ok.\n")
-
-    pattern_name_list = get_patterns(name_c)  # 所有pattern
-    # 修改node pattern/demand
-    # nodes = get_nodes(name_c)  # nodes
-    # for node_name in nodes:  # 遍历nodes
-    #     demands_dict = get_demand(name_c, node_name)  # {'demands':[{'demand':, 'pattern':}]}
-    #     for demands in demands_dict['demands']:
-    #         if demands['pattern'] in monitor_single_patterns:  # 1)
-    #             demands_dict['demands'][
-    #                 demands_dict['demands'].index(demands)
-    #             ]['demand'] = 1  # 修改demand
-    #             pattern = get_pattern(name_c, demands['pattern'])
-    #             pattern['factors'][modify_index] = flow_new[demands['pattern']]  # 修改pattern
-    #             cs = ChangeSet()
-    #             cs.append(pattern)
-    #             set_pattern(name_c, cs)
-    #             if demands['pattern'] in pattern_name_list:
-    #                 pattern_name_list.remove(demands['pattern'])  # 移出待修改pattern列表
-    #         else:  # 2)
-    #             continue
-    #     cs = ChangeSet()
-    #     cs.append(demands_dict)
-    #     set_demand(name_c, cs)
-    for pattern_name in monitor_patterns:  # 遍历patterns
-        if not np.isnan(new_patterns[pattern_name][0]):
-            pattern = get_pattern(name_c, pattern_name)
-            pattern['factors'][modify_index:
-                               modify_index + len(new_patterns[pattern_name])] \
-                = new_patterns[pattern_name]
-            cs = ChangeSet()
-            cs.append(pattern)
-            set_pattern(name_c, cs)
-            if pattern_name in pattern_name_list:
-                pattern_name_list.remove(pattern_name)  # 移出待修改pattern列表
-
-    # 修改清水池(reservoir)液位pattern
-    for reservoir_name in reservoirs:  # 遍历reservoirs
-        if (not np.isnan(reservoir_level[reservoir_name])) and (reservoir_level[reservoir_name] != 0):
-            reservoir_pattern = get_pattern(name_c, get_reservoir(name_c, reservoir_name)['pattern'])
-            reservoir_pattern['factors'][modify_index] = reservoir_level[reservoir_name]
-            cs = ChangeSet()
-            cs.append(reservoir_pattern)
-            set_pattern(name_c, cs)
-            if reservoir_pattern['id'] in pattern_name_list:
-                pattern_name_list.remove(reservoir_pattern['id'])  # 移出待修改pattern列表
-
-    # 修改调节池(tank)初始液位
-    for tank_name in tanks:  # 遍历tanks
-        if (not np.isnan(tank_init_level[tank_name])) and (tank_init_level[tank_name] != 0):
-            tank = get_tank(name_c, tank_name)
-            tank['init_level'] = tank_init_level[tank_name]
-            cs = ChangeSet()
-            cs.append(tank)
-            set_tank(name_c, cs)
-
-    # 修改水泵(pump)pattern
-    for pump_name in pumps:  # 遍历pumps
-        if not np.isnan(pump_freq[pump_name][0]):
-            pump_pattern = get_pattern(name_c, get_pump(name_c, pump_name)['pattern'])
-            pump_pattern['factors'][modify_index
-                                    :modify_index + len(pump_freq[pump_name])] \
-                = pump_freq[pump_name]
-            cs = ChangeSet()
-            cs.append(pump_pattern)
-            set_pattern(name_c, cs)
-            if pump_pattern['id'] in pattern_name_list:
-                pattern_name_list.remove(pump_pattern['id'])  # 移出待修改pattern列表
-    # 修改阀门(valve)status和setting
-    if valve_control is not None:
-        for valve in valve_control.keys():
-            status = get_status(name_c, valve)
-            if 'status' in valve_control[valve].keys():
-                status['status'] = valve_control[valve]['status']
-            if 'setting' in valve_control[valve].keys():
-                status['setting'] = valve_control[valve]['setting']
-            if 'k' in valve_control[valve].keys():
-                valve_k = valve_control[valve]['k']
-                if valve_k == 0:
-                    status['status'] = 'CLOSED'
-                else:
-                    status['setting'] = 0.1036 * pow(valve_k, -3.105)
-            cs = ChangeSet()
-            cs.append(status)
-            set_status(name_c, cs)
-
-    print('Finish demands amending, unmodified patterns: {}.'.format(pattern_name_list))
-
-    # 修改时间信息
-    str_pattern_start = get_pattern_index_str(
-        DataLoader.round_time(start_time, int(PATTERN_TIME_STEP)).strftime("%Y-%m-%d %H:%M:%S"))
-    dic_time = get_time(name_c)
-    dic_time['PATTERN START'] = str_pattern_start
-
-    if duration is not None:
-        dic_time['DURATION'] = from_seconds_to_clock(duration)
-    else:
-        dic_time['DURATION'] = dic_time['HYDRAULIC TIMESTEP']
-    cs = ChangeSet()
-    cs.operations.append(dic_time)
-    set_time(name_c, cs)
-
-    # 运行并返回结果
-    result = run_project(name_c)
-
-    time_cost_end = time.perf_counter()
-    print('{} -- Hydraulic simulation finished, cost time: {:.2f} s.'.format(
-        datetime.now(pytz.timezone('Asia/Shanghai')).strftime('%Y-%m-%d %H:%M:%S'),
-        time_cost_end - time_cost_start))
-
-    close_project(name_c)
-
-    return result
-
-
-if __name__ == '__main__':
-    # if get_current_data()==True:
-    #     tQ=get_current_total_Q()
-    #     print(f"the current tQ is {tQ}\n")
-    # data=get_hist_data(ids,conver_beingtime_to_ucttime('2024-04-10 15:05:00'),conver_beingtime_to_ucttime('2024-04-10 15:10:00'))
-    # open_project("beibeizone")
-    # read_inp("beibeizone","beibeizone-export_nochinese.inp")
-    # run_simulation("beibeizone","2024-04-01T08:00:00Z")
-    # read_inp('bb_server', 'model20_en.inp')
-    run_simulation_ex(
-        name=project_info.name, simulation_type='extended', start_datetime='2024-11-09T02:30:00Z',
-        # end_datetime='2024-05-30T16:00:00Z',
-        # duration=0,
-        # pump_control={'PU00006': [45, 40]}
-        # region_demand_control={'hp': 6000, 'lp': 2000}
-    )

app/algorithms/valve_isolation/__init__.py

@@ -0,0 +1,3 @@
+from app.algorithms.valve_isolation.topology_search import valve_isolation_analysis
+
+__all__ = ["valve_isolation_analysis"]

app/algorithms/valve_isolation/topology_search.py

@@ -0,0 +1,103 @@
+"""Topology-only valve isolation search."""
+
+from collections import defaultdict, deque
+from typing import Any, Iterable
+
+
+VALVE_LINK_TYPE = "valve"
+
+
+def _parse_link_entry(link_entry: str) -> tuple[str, str, str, str]:
+    parts = link_entry.split(":", 3)
+    if len(parts) != 4:
+        raise ValueError(f"Invalid link entry format: {link_entry}")
+    return parts[0], parts[1], parts[2], parts[3]
+
+
+def valve_isolation_analysis(
+    link_entries: Iterable[str],
+    accident_elements: str | list[str],
+    disabled_valves: list[str] | None = None,
+) -> dict[str, Any]:
+    """Determine boundary valves and affected nodes from a topology snapshot."""
+
+    disabled_valves_set = set(disabled_valves or [])
+    target_elements = (
+        [accident_elements]
+        if isinstance(accident_elements, str)
+        else accident_elements
+    )
+
+    pipe_adj: dict[str, set[str]] = defaultdict(set)
+    all_valves: dict[str, tuple[str, str]] = {}
+    link_lookup: dict[str, tuple[str, str, str]] = {}
+    node_set: set[str] = set()
+    for link_entry in link_entries:
+        link_id, link_type, node1, node2 = _parse_link_entry(link_entry)
+        link_type_name = str(link_type).lower()
+        link_lookup[link_id] = (node1, node2, link_type_name)
+        node_set.update((node1, node2))
+        if link_type_name == VALVE_LINK_TYPE:
+            all_valves[link_id] = (node1, node2)
+        else:
+            pipe_adj[node1].add(node2)
+            pipe_adj[node2].add(node1)
+
+    start_nodes: set[str] = set()
+    for element in target_elements:
+        if element in node_set:
+            start_nodes.add(element)
+        elif element in link_lookup:
+            node1, node2, _ = link_lookup[element]
+            start_nodes.update((node1, node2))
+        else:
+            raise ValueError(f"Accident element {element} was not found in topology")
+
+    extra_adj: dict[str, list[str]] = defaultdict(list)
+    boundary_valves: dict[str, tuple[str, str]] = {}
+    for valve_id, (node1, node2) in all_valves.items():
+        if valve_id in disabled_valves_set:
+            extra_adj[node1].append(node2)
+            extra_adj[node2].append(node1)
+        else:
+            boundary_valves[valve_id] = (node1, node2)
+
+    affected_nodes: set[str] = set()
+    queue = deque(start_nodes)
+    while queue:
+        node = queue.popleft()
+        if node in affected_nodes:
+            continue
+        affected_nodes.add(node)
+        queue.extend(pipe_adj.get(node, set()) - affected_nodes)
+        queue.extend(
+            neighbor
+            for neighbor in extra_adj.get(node, ())
+            if neighbor not in affected_nodes
+        )
+
+    must_close_valves: list[str] = []
+    optional_valves: list[str] = []
+    for valve_id, (node1, node2) in boundary_valves.items():
+        node1_affected = node1 in affected_nodes
+        node2_affected = node2 in affected_nodes
+        if node1_affected and node2_affected:
+            optional_valves.append(valve_id)
+        elif node1_affected or node2_affected:
+            must_close_valves.append(valve_id)
+
+    must_close_valves.sort()
+    optional_valves.sort()
+    isolatable = bool(must_close_valves)
+    result: dict[str, Any] = {
+        "accident_elements": target_elements,
+        "disabled_valves": disabled_valves,
+        "affected_nodes": sorted(affected_nodes) if isolatable else [],
+        "affected_node_count": len(affected_nodes),
+        "must_close_valves": must_close_valves,
+        "optional_valves": optional_valves,
+        "isolatable": isolatable,
+    }
+    if len(target_elements) == 1:
+        result["accident_element"] = target_elements[0]
+    return result

app/api/pagination.py

@@ -0,0 +1,14 @@
+from __future__ import annotations
+
+from collections.abc import Iterable
+from typing import Generic, TypeVar
+
+T = TypeVar("T")
+
+
+class PaginatedList(list[T], Generic[T]):
+    """A page of items carrying the total count from its data source."""
+
+    def __init__(self, items: Iterable[T], *, total: int) -> None:
+        super().__init__(items)
+        self.total = total

app/api/problem_details.py

@@ -0,0 +1,109 @@
+from __future__ import annotations
+
+from typing import Any
+from uuid import uuid4
+
+from fastapi import FastAPI, HTTPException, Request
+from fastapi.exceptions import RequestValidationError
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel, Field
+
+from app.native.wndb.core.database import MaterializedViewRefreshAfterCommitError
+
+
+class ProblemDetails(BaseModel):
+    """RFC 9457 compatible error response used by the REST contract."""
+
+    type: str
+    title: str
+    status: int
+    detail: str
+    instance: str
+    code: str
+    trace_id: str
+    errors: list[dict[str, Any]] = Field(default_factory=list)
+
+
+def _trace_id(request: Request) -> str:
+    return request.headers.get("X-Request-Id") or str(uuid4())
+
+
+def _problem_response(
+    request: Request,
+    *,
+    status_code: int,
+    title: str,
+    detail: str,
+    code: str,
+    errors: list[dict[str, Any]] | None = None,
+) -> JSONResponse:
+    problem = ProblemDetails(
+        type=f"https://tjwater.example/problems/{code.replace('_', '-')}",
+        title=title,
+        status=status_code,
+        detail=detail,
+        instance=request.url.path,
+        code=code,
+        trace_id=_trace_id(request),
+        errors=errors or [],
+    )
+    return JSONResponse(
+        status_code=status_code,
+        content=problem.model_dump(mode="json"),
+        media_type="application/problem+json",
+    )
+
+
+def install_problem_details_handlers(app: FastAPI) -> None:
+    @app.exception_handler(MaterializedViewRefreshAfterCommitError)
+    async def materialized_view_refresh_error_handler(
+        request: Request,
+        exc: MaterializedViewRefreshAfterCommitError,
+    ) -> JSONResponse:
+        response = _problem_response(
+            request,
+            status_code=503,
+            title="Materialized view refresh failed",
+            detail=(
+                f"Project {exc.project!r} changes were committed, but GIS query "
+                "views could not be refreshed. Do not repeat the write blindly."
+            ),
+            code="materialized_view_refresh_failed_after_commit",
+        )
+        response.headers["X-TJWater-Changes-Committed"] = "true"
+        return response
+
+    @app.exception_handler(RequestValidationError)
+    async def validation_error_handler(
+        request: Request,
+        exc: RequestValidationError,
+    ) -> JSONResponse:
+        return _problem_response(
+            request,
+            status_code=422,
+            title="Validation error",
+            detail="Request validation failed",
+            code="validation_error",
+            errors=exc.errors(),
+        )
+
+    @app.exception_handler(HTTPException)
+    async def http_error_handler(request: Request, exc: HTTPException) -> JSONResponse:
+        detail = exc.detail if isinstance(exc.detail, str) else str(exc.detail)
+        code_by_status = {
+            401: "unauthenticated",
+            403: "forbidden",
+            404: "not_found",
+            409: "conflict",
+            422: "validation_error",
+            503: "dependency_unavailable",
+        }
+        return _problem_response(
+            request,
+            status_code=exc.status_code,
+            title=code_by_status.get(exc.status_code, "request_error")
+            .replace("_", " ")
+            .title(),
+            detail=detail,
+            code=code_by_status.get(exc.status_code, "request_error"),
+        )

app/api/v1/endpoints/access.py

@@ -0,0 +1,39 @@
+from fastapi import APIRouter, Depends, Header
+
+from app.auth.metadata_dependencies import (
+    get_current_metadata_user,
+    get_metadata_repository,
+)
+from app.auth.permissions import resolve_permissions
+from app.auth.project_dependencies import resolve_project_context
+from app.domain.schemas.access import AccessContextResponse
+from app.infra.db.metadb.repositories.metadata_repository import MetadataRepository
+
+router = APIRouter()
+
+
+@router.get("/access-context", response_model=AccessContextResponse)
+async def get_access_context(
+    x_project_id: str | None = Header(default=None, alias="X-Project-Id"),
+    current_user=Depends(get_current_metadata_user),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> AccessContextResponse:
+    project_context = (
+        await resolve_project_context(x_project_id, current_user, metadata_repo)
+        if x_project_id
+        else None
+    )
+    permissions = resolve_permissions(
+        project_role=project_context.project_role if project_context else None,
+        system_role=current_user.role,
+        is_superuser=current_user.is_superuser,
+    )
+    return AccessContextResponse(
+        user_id=current_user.id,
+        username=current_user.username,
+        system_role=current_user.role,
+        is_system_admin=current_user.is_superuser or current_user.role == "admin",
+        project_id=project_context.project_id if project_context else None,
+        project_role=project_context.project_role if project_context else None,
+        permissions=sorted(permissions),
+    )

app/api/v1/endpoints/admin_metadata.py

@@ -0,0 +1,702 @@
+from typing import List
+from uuid import UUID
+
+from fastapi import APIRouter, Depends, HTTPException, Path, Query, Response, status
+from sqlalchemy import text
+from sqlalchemy.engine.url import make_url
+from sqlalchemy.exc import IntegrityError, SQLAlchemyError
+from sqlalchemy.ext.asyncio import create_async_engine
+
+from app.auth.metadata_dependencies import (
+    get_current_metadata_admin,
+    get_metadata_repository,
+)
+from app.core.audit import AuditAction, log_audit_event
+from app.domain.schemas.admin_metadata import (
+    AdminProjectCreateRequest,
+    AdminProjectResponse,
+    AdminProjectUpdateRequest,
+    MetadataUsersBatchSyncRequest,
+    MetadataUserResponse,
+    MetadataUserSyncRequest,
+    MetadataUserSyncResult,
+    MetadataUserUpdateRequest,
+    ProjectDatabaseHealthResponse,
+    ProjectDatabaseHealthRequest,
+    ProjectDatabaseResponse,
+    ProjectDatabaseUpsertRequest,
+    ProjectDbRole,
+    ProjectMemberCreateRequest,
+    ProjectMemberResponse,
+    ProjectMemberUpdateRequest,
+)
+from app.infra.db.metadb import models
+from app.infra.db.metadb.repositories.metadata_repository import (
+    MetadataRepository,
+    ProjectDbRouting,
+)
+
+router = APIRouter()
+
+
+def _project_response(project: models.Project) -> AdminProjectResponse:
+    return AdminProjectResponse(
+        project_id=project.id,
+        name=project.name,
+        code=project.code,
+        description=project.description,
+        gs_workspace=project.gs_workspace,
+        map_extent=project.map_extent,
+        status=project.status,
+        created_at=project.created_at,
+        updated_at=project.updated_at,
+    )
+
+
+def _project_database_response(
+    record: models.ProjectDatabase,
+) -> ProjectDatabaseResponse:
+    return ProjectDatabaseResponse(
+        id=record.id,
+        project_id=record.project_id,
+        db_role=record.db_role,
+        db_type=record.db_type,
+        pool_min_size=record.pool_min_size,
+        pool_max_size=record.pool_max_size,
+        has_dsn=bool(record.dsn_encrypted),
+    )
+
+
+def _database_audit_payload(payload: ProjectDatabaseUpsertRequest) -> dict:
+    return {
+        "db_role": payload.db_role,
+        "db_type": _db_type_for_role(payload.db_role),
+        "pool_min_size": payload.pool_min_size,
+        "pool_max_size": payload.pool_max_size,
+        "dsn_updated": payload.dsn is not None,
+    }
+
+
+def _to_async_sqlalchemy_url(dsn: str) -> str:
+    parsed = make_url(dsn)
+    if parsed.drivername in {"postgresql", "postgres"}:
+        parsed = parsed.set(drivername="postgresql+psycopg")
+    return parsed.render_as_string(hide_password=False)
+
+
+def _db_type_for_role(db_role: str) -> str:
+    if db_role == "iot_data":
+        return "timescaledb"
+    return "postgresql"
+
+
+def _status_for_config_value_error(exc: ValueError) -> int:
+    if "DATABASE_ENCRYPTION_KEY" in str(exc):
+        return status.HTTP_503_SERVICE_UNAVAILABLE
+    return status.HTTP_400_BAD_REQUEST
+
+
+async def _check_database_connection(routing: ProjectDbRouting) -> None:
+    engine = create_async_engine(
+        _to_async_sqlalchemy_url(routing.dsn),
+        pool_size=1,
+        max_overflow=0,
+        pool_pre_ping=True,
+    )
+    try:
+        async with engine.connect() as conn:
+            await conn.execute(text("SELECT 1"))
+    finally:
+        await engine.dispose()
+
+
+def _database_health_error_detail(exc: Exception) -> str:
+    message = str(exc)
+    lower_message = message.lower()
+    if "password authentication failed" in lower_message:
+        return "连通性测试失败：用户名或密码错误，请检查 DSN 中的账号密码。"
+    if "connection refused" in lower_message:
+        return "连通性测试失败：目标主机或端口拒绝连接，请检查地址、端口和服务状态。"
+    if "timeout" in lower_message or "timed out" in lower_message:
+        return "连通性测试失败：连接超时，请检查网络、防火墙和数据库服务状态。"
+    if "could not translate host name" in lower_message or "name or service not known" in lower_message:
+        return "连通性测试失败：数据库主机名无法解析，请检查 DSN 中的主机地址。"
+    first_line = message.splitlines()[0] if message else exc.__class__.__name__
+    return f"连通性测试失败：{first_line}"
+
+
+async def _upsert_and_audit_metadata_user(
+    payload: MetadataUserSyncRequest,
+    *,
+    current_user,
+    metadata_repo: MetadataRepository,
+    response_status: int,
+) -> MetadataUserResponse:
+    user = await metadata_repo.upsert_user_from_keycloak(
+        keycloak_id=payload.keycloak_id,
+        username=payload.username,
+        email=str(payload.email),
+        role=payload.role,
+        is_active=payload.is_active,
+    )
+    await log_audit_event(
+        action=AuditAction.UPDATE,
+        user_id=current_user.id,
+        resource_type="metadata_user",
+        resource_id=str(user.id),
+        request_data=payload.model_dump(mode="json"),
+        response_status=response_status,
+        session=metadata_repo.session,
+    )
+    return MetadataUserResponse.model_validate(user)
+
+
+@router.get("/admin/users/me", response_model=MetadataUserResponse)
+async def get_metadata_admin_me(
+    current_user=Depends(get_current_metadata_admin),
+) -> MetadataUserResponse:
+    return MetadataUserResponse.model_validate(current_user)
+
+
+@router.post("/admin/user-syncs", response_model=MetadataUserResponse)
+async def sync_metadata_user(
+    payload: MetadataUserSyncRequest,
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> MetadataUserResponse:
+    try:
+        return await _upsert_and_audit_metadata_user(
+            payload,
+            current_user=current_user,
+            metadata_repo=metadata_repo,
+            response_status=status.HTTP_200_OK,
+        )
+    except IntegrityError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="User keycloak_id, username, or email conflicts with an existing user",
+        ) from exc
+    except SQLAlchemyError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Metadata database error: {exc}",
+        ) from exc
+
+
+
+@router.post("/admin/user-syncs/batches", response_model=List[MetadataUserSyncResult])
+async def sync_metadata_users_batch(
+    payload: MetadataUsersBatchSyncRequest,
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> List[MetadataUserSyncResult]:
+    results: list[MetadataUserSyncResult] = []
+    for item in payload.users:
+        try:
+            user = await _upsert_and_audit_metadata_user(
+                item,
+                current_user=current_user,
+                metadata_repo=metadata_repo,
+                response_status=status.HTTP_200_OK,
+            )
+        except IntegrityError as exc:
+            results.append(
+                MetadataUserSyncResult(
+                    keycloak_id=item.keycloak_id,
+                    success=False,
+                    error="User keycloak_id, username, or email conflicts with an existing user",
+                )
+            )
+            await metadata_repo.session.rollback()
+        except SQLAlchemyError as exc:
+            results.append(
+                MetadataUserSyncResult(
+                    keycloak_id=item.keycloak_id,
+                    success=False,
+                    error=f"Metadata database error: {exc}",
+                )
+            )
+            await metadata_repo.session.rollback()
+        else:
+            results.append(
+                MetadataUserSyncResult(
+                    keycloak_id=item.keycloak_id,
+                    success=True,
+                    user=user,
+                )
+            )
+    return results
+
+
+@router.get("/admin/users", response_model=List[MetadataUserResponse])
+async def list_metadata_users(
+    skip: int = Query(0, ge=0),
+    limit: int = Query(100, ge=1, le=1000),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> List[MetadataUserResponse]:
+    users = await metadata_repo.list_users(skip=skip, limit=limit)
+    return [MetadataUserResponse.model_validate(user) for user in users]
+
+
+@router.get("/admin/projects", response_model=List[AdminProjectResponse])
+async def list_admin_projects(
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> List[AdminProjectResponse]:
+    projects = await metadata_repo.list_project_records()
+    return [_project_response(project) for project in projects]
+
+
+@router.post(
+    "/admin/projects",
+    response_model=AdminProjectResponse,
+    status_code=status.HTTP_201_CREATED,
+    deprecated=True,
+    summary="仅登记已有项目元数据",
+    description=(
+        "仅用于登记已经由外部流程完整创建的资源。新项目应调用 "
+        "POST /admin/project-provisions。"
+    ),
+)
+async def create_admin_project(
+    payload: AdminProjectCreateRequest,
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> AdminProjectResponse:
+    try:
+        project = await metadata_repo.create_project(
+            name=payload.name,
+            code=payload.code,
+            description=payload.description,
+            gs_workspace=payload.gs_workspace,
+            map_extent=payload.map_extent,
+            status=payload.status,
+            creator_user_id=current_user.id,
+        )
+    except IntegrityError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="Project code or workspace conflicts with an existing project",
+        ) from exc
+    except SQLAlchemyError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Metadata database error: {exc}",
+        ) from exc
+
+    await log_audit_event(
+        action=AuditAction.CREATE,
+        user_id=current_user.id,
+        project_id=project.id,
+        resource_type="project",
+        resource_id=str(project.id),
+        request_data=payload.model_dump(mode="json"),
+        response_status=status.HTTP_201_CREATED,
+        session=metadata_repo.session,
+    )
+    return _project_response(project)
+
+
+@router.patch(
+    "/admin/projects/{project_id}",
+    response_model=AdminProjectResponse,
+)
+async def update_admin_project(
+    payload: AdminProjectUpdateRequest,
+    project_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> AdminProjectResponse:
+    updates = payload.model_dump(mode="json", exclude_unset=True)
+    try:
+        project = await metadata_repo.update_project(project_id, updates=updates)
+    except IntegrityError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="Project code or workspace conflicts with an existing project",
+        ) from exc
+    except SQLAlchemyError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Metadata database error: {exc}",
+        ) from exc
+    if project is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Project not found")
+
+    await log_audit_event(
+        action=AuditAction.UPDATE,
+        user_id=current_user.id,
+        project_id=project.id,
+        resource_type="project",
+        resource_id=str(project.id),
+        request_data=updates,
+        response_status=status.HTTP_200_OK,
+        session=metadata_repo.session,
+    )
+    return _project_response(project)
+
+
+@router.get(
+    "/admin/projects/{project_id}/databases",
+    response_model=List[ProjectDatabaseResponse],
+)
+async def list_project_databases(
+    project_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> List[ProjectDatabaseResponse]:
+    project = await metadata_repo.get_project_by_id(project_id)
+    if project is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Project not found")
+    records = await metadata_repo.list_project_databases(project_id)
+    return [_project_database_response(record) for record in records]
+
+
+@router.put(
+    "/admin/projects/{project_id}/databases",
+    response_model=ProjectDatabaseResponse,
+)
+async def upsert_project_database(
+    payload: ProjectDatabaseUpsertRequest,
+    project_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> ProjectDatabaseResponse:
+    project = await metadata_repo.get_project_by_id(project_id)
+    if project is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Project not found")
+    try:
+        routing = (
+            ProjectDbRouting(
+                project_id=project_id,
+                db_role=payload.db_role,
+                db_type=_db_type_for_role(payload.db_role),
+                dsn=payload.dsn,
+                pool_min_size=payload.pool_min_size,
+                pool_max_size=payload.pool_max_size,
+            )
+            if payload.dsn
+            else await metadata_repo.get_project_db_routing(project_id, payload.db_role)
+        )
+        if routing is None:
+            raise ValueError("dsn is required when creating project database config")
+        await _check_database_connection(routing)
+    except ValueError as exc:
+        raise HTTPException(
+            status_code=_status_for_config_value_error(exc),
+            detail=str(exc),
+        ) from exc
+    except Exception as exc:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=_database_health_error_detail(exc),
+        ) from exc
+
+    try:
+        record = await metadata_repo.upsert_project_database_config(
+            project_id,
+            db_role=payload.db_role,
+            db_type=_db_type_for_role(payload.db_role),
+            dsn=payload.dsn,
+            pool_min_size=payload.pool_min_size,
+            pool_max_size=payload.pool_max_size,
+        )
+    except IntegrityError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="Project database role conflicts with an existing config",
+        ) from exc
+    except SQLAlchemyError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Metadata database error: {exc}",
+        ) from exc
+
+    await log_audit_event(
+        action=AuditAction.CONFIG_CHANGE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="project_database",
+        resource_id=payload.db_role,
+        request_data=_database_audit_payload(payload),
+        response_status=status.HTTP_200_OK,
+        session=metadata_repo.session,
+    )
+    return _project_database_response(record)
+
+
+@router.delete(
+    "/admin/projects/{project_id}/databases/{db_role}",
+    status_code=status.HTTP_204_NO_CONTENT,
+)
+async def delete_project_database(
+    project_id: UUID = Path(...),
+    db_role: ProjectDbRole = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> None:
+    removed = await metadata_repo.delete_project_database_config(project_id, db_role)
+    if not removed:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Project database config not found",
+        )
+    await log_audit_event(
+        action=AuditAction.CONFIG_CHANGE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="project_database",
+        resource_id=db_role,
+        request_data={"deleted": True},
+        response_status=status.HTTP_204_NO_CONTENT,
+        session=metadata_repo.session,
+    )
+
+
+@router.post(
+    "/admin/projects/{project_id}/databases/{db_role}/health-checks",
+    response_model=ProjectDatabaseHealthResponse,
+)
+async def check_project_database_health(
+    response: Response,
+    project_id: UUID = Path(...),
+    db_role: ProjectDbRole = Path(...),
+    payload: ProjectDatabaseHealthRequest | None = None,
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> ProjectDatabaseHealthResponse:
+    dsn_to_test = payload.dsn if payload and payload.dsn else None
+    if dsn_to_test:
+        routing = ProjectDbRouting(
+            project_id=project_id,
+            db_role=db_role,
+            db_type=_db_type_for_role(db_role),
+            dsn=dsn_to_test,
+            pool_min_size=1,
+            pool_max_size=1,
+        )
+    else:
+        try:
+            routing = await metadata_repo.get_project_db_routing(project_id, db_role)
+        except ValueError as exc:
+            raise HTTPException(
+                status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+                detail=f"Project database routing DSN is invalid: {exc}",
+            ) from exc
+        if routing is None:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail="Project database config not found",
+            )
+
+    try:
+        await _check_database_connection(routing)
+    except Exception as exc:  # health endpoint should return diagnostic status
+        response.status_code = status.HTTP_503_SERVICE_UNAVAILABLE
+        return ProjectDatabaseHealthResponse(
+            project_id=project_id,
+            db_role=db_role,
+            db_type=routing.db_type,
+            ok=False,
+            detail=_database_health_error_detail(exc),
+        )
+    return ProjectDatabaseHealthResponse(
+        project_id=project_id,
+        db_role=db_role,
+        db_type=routing.db_type,
+        ok=True,
+        detail="连通性测试通过",
+    )
+
+
+@router.get("/admin/users/{user_id}", response_model=MetadataUserResponse)
+async def get_metadata_user(
+    user_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> MetadataUserResponse:
+    user = await metadata_repo.get_user_by_id(user_id)
+    if user is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="User not found")
+    return MetadataUserResponse.model_validate(user)
+
+
+@router.patch("/admin/users/{user_id}", response_model=MetadataUserResponse)
+async def update_metadata_user(
+    payload: MetadataUserUpdateRequest,
+    user_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> MetadataUserResponse:
+    updates = payload.model_dump(mode="json", exclude_unset=True)
+    if user_id == current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Users cannot modify themselves",
+        )
+    user = await metadata_repo.update_user_admin(
+        user_id,
+        updates=updates,
+    )
+    if user is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="User not found")
+
+    await log_audit_event(
+        action=AuditAction.UPDATE,
+        user_id=current_user.id,
+        resource_type="metadata_user",
+        resource_id=str(user.id),
+        request_data=updates,
+        response_status=status.HTTP_200_OK,
+        session=metadata_repo.session,
+    )
+    return MetadataUserResponse.model_validate(user)
+
+
+@router.get(
+    "/admin/projects/{project_id}/members",
+    response_model=List[ProjectMemberResponse],
+)
+async def list_project_members(
+    project_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> List[ProjectMemberResponse]:
+    project = await metadata_repo.get_project_by_id(project_id)
+    if project is None:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Project not found"
+        )
+    members = await metadata_repo.list_project_members(project_id)
+    return [ProjectMemberResponse(**member.__dict__) for member in members]
+
+
+@router.post(
+    "/admin/projects/{project_id}/members",
+    response_model=ProjectMemberResponse,
+    status_code=status.HTTP_201_CREATED,
+)
+async def add_project_member(
+    payload: ProjectMemberCreateRequest,
+    project_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> ProjectMemberResponse:
+    if payload.user_id == current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Users cannot modify their own project membership",
+        )
+    project = await metadata_repo.get_project_by_id(project_id)
+    if project is None:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Project not found"
+        )
+    user = await metadata_repo.get_user_by_id(payload.user_id)
+    if user is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="User not found")
+    existing = await metadata_repo.get_project_membership(project_id, payload.user_id)
+    if existing is not None:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="User is already a project member",
+        )
+
+    membership = await metadata_repo.add_project_member(
+        project_id, payload.user_id, payload.project_role
+    )
+    await log_audit_event(
+        action=AuditAction.PERMISSION_CHANGE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="project_member",
+        resource_id=str(payload.user_id),
+        request_data=payload.model_dump(mode="json"),
+        response_status=status.HTTP_201_CREATED,
+        session=metadata_repo.session,
+    )
+    return ProjectMemberResponse(
+        id=membership.id,
+        user_id=membership.user_id,
+        project_id=membership.project_id,
+        project_role=membership.project_role,
+        username=user.username,
+        email=user.email,
+        is_active=user.is_active,
+    )
+
+
+@router.patch(
+    "/admin/projects/{project_id}/members/{user_id}",
+    response_model=ProjectMemberResponse,
+)
+async def update_project_member(
+    payload: ProjectMemberUpdateRequest,
+    project_id: UUID = Path(...),
+    user_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> ProjectMemberResponse:
+    if user_id == current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Users cannot modify their own project membership",
+        )
+    user = await metadata_repo.get_user_by_id(user_id)
+    if user is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="User not found")
+    membership = await metadata_repo.update_project_member_role(
+        project_id, user_id, payload.project_role
+    )
+    if membership is None:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Project member not found"
+        )
+    await log_audit_event(
+        action=AuditAction.PERMISSION_CHANGE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="project_member",
+        resource_id=str(user_id),
+        request_data=payload.model_dump(mode="json"),
+        response_status=status.HTTP_200_OK,
+        session=metadata_repo.session,
+    )
+    return ProjectMemberResponse(
+        id=membership.id,
+        user_id=membership.user_id,
+        project_id=membership.project_id,
+        project_role=membership.project_role,
+        username=user.username,
+        email=user.email,
+        is_active=user.is_active,
+    )
+
+
+@router.delete("/admin/projects/{project_id}/members/{user_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def remove_project_member(
+    project_id: UUID = Path(...),
+    user_id: UUID = Path(...),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> None:
+    if user_id == current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Users cannot modify their own project membership",
+        )
+    removed = await metadata_repo.remove_project_member(project_id, user_id)
+    if not removed:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Project member not found"
+        )
+    await log_audit_event(
+        action=AuditAction.PERMISSION_CHANGE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="project_member",
+        resource_id=str(user_id),
+        response_status=status.HTTP_204_NO_CONTENT,
+        session=metadata_repo.session,
+    )

app/api/v1/endpoints/agent_auth.py

@@ -0,0 +1,53 @@
+from datetime import datetime, timezone
+
+from fastapi import APIRouter, Depends
+from pydantic import BaseModel
+
+from app.auth.keycloak_dependencies import get_current_keycloak_payload
+from app.auth.metadata_dependencies import get_current_metadata_user
+from app.auth.project_dependencies import (
+    ProjectContext,
+    get_project_context,
+)
+from app.auth.permissions import permissions_for_context
+
+router = APIRouter()
+
+
+class AgentAuthContextResponse(BaseModel):
+    user_id: str
+    keycloak_sub: str
+    username: str
+    role: str
+    is_superuser: bool
+    project_id: str
+    network: str
+    project_role: str
+    permissions: list[str]
+    token_expires_at: str | None = None
+
+
+@router.get("/agent-auth-context", response_model=AgentAuthContextResponse)
+async def get_agent_auth_context(
+    ctx: ProjectContext = Depends(get_project_context),
+    current_user=Depends(get_current_metadata_user),
+    keycloak_payload: dict = Depends(get_current_keycloak_payload),
+) -> AgentAuthContextResponse:
+    exp = keycloak_payload.get("exp")
+    token_expires_at = (
+        datetime.fromtimestamp(exp, tz=timezone.utc).isoformat()
+        if isinstance(exp, int)
+        else None
+    )
+    return AgentAuthContextResponse(
+        user_id=str(current_user.id),
+        keycloak_sub=str(current_user.keycloak_id),
+        username=current_user.username,
+        role=current_user.role,
+        is_superuser=current_user.is_superuser,
+        project_id=str(ctx.project_id),
+        network=ctx.project_code,
+        project_role=ctx.project_role,
+        permissions=sorted(permissions_for_context(ctx)),
+        token_expires_at=token_expires_at,
+    )

app/api/v1/endpoints/audit.py

@@ -1,56 +1,53 @@
-"""
-审计日志 API 接口
-
-仅管理员可访问
-"""
-
-from typing import List, Optional
-from uuid import UUID
 from datetime import datetime
-from fastapi import APIRouter, Depends, Query, Path
-from app.domain.schemas.audit import AuditLogResponse
-from app.infra.db.metadb.repositories.audit_repository import AuditRepository
+from typing import Literal
+from uuid import UUID
+
+from fastapi import APIRouter, Depends, Query, Request, status
+from pydantic import BaseModel
+from sqlalchemy.ext.asyncio import AsyncSession
+
 from app.auth.metadata_dependencies import (
     get_current_metadata_admin,
     get_current_metadata_user,
 )
+from app.api.pagination import PaginatedList
+from app.core.audit import AuditAction, log_audit_event
+from app.domain.schemas.audit import AuditLogResponse
 from app.infra.db.metadb.database import get_metadata_session
-from sqlalchemy.ext.asyncio import AsyncSession
+from app.infra.db.metadb.repositories.audit_repository import AuditRepository
 
 router = APIRouter()
 
 
+class SessionAuditEventRequest(BaseModel):
+    event: Literal["login", "logout"]
+
+
 async def get_audit_repository(
     session: AsyncSession = Depends(get_metadata_session),
 ) -> AuditRepository:
-    """获取审计日志仓储"""
     return AuditRepository(session)
 
 
 @router.get(
-    "/logs",
+    "/audit-logs",
     summary="查询审计日志",
     description="查询审计日志（仅管理员）",
-    response_model=List[AuditLogResponse],
+    response_model=list[AuditLogResponse],
 )
 async def get_audit_logs(
-    user_id: Optional[UUID] = Query(None, description="按用户ID过滤"),
-    project_id: Optional[UUID] = Query(None, description="按项目ID过滤"),
-    action: Optional[str] = Query(None, description="按操作类型过滤"),
-    resource_type: Optional[str] = Query(None, description="按资源类型过滤"),
-    start_time: Optional[datetime] = Query(None, description="开始时间"),
-    end_time: Optional[datetime] = Query(None, description="结束时间"),
+    user_id: UUID | None = Query(None, description="按用户ID过滤"),
+    project_id: UUID | None = Query(None, description="按项目ID过滤"),
+    action: str | None = Query(None, description="按操作类型过滤"),
+    resource_type: str | None = Query(None, description="按资源类型过滤"),
+    start_time: datetime | None = Query(None, description="开始时间"),
+    end_time: datetime | None = Query(None, description="结束时间"),
     skip: int = Query(0, ge=0, description="跳过记录数"),
     limit: int = Query(100, ge=1, le=1000, description="限制记录数"),
-    current_user=Depends(get_current_metadata_admin),
+    _current_user=Depends(get_current_metadata_admin),
     audit_repo: AuditRepository = Depends(get_audit_repository),
-) -> List[AuditLogResponse]:
-    """
-    查询审计日志
-
-    支持按用户、时间、操作类型等条件过滤，仅管理员可访问
-    """
-    logs = await audit_repo.get_logs(
+) -> list[AuditLogResponse]:
+    items = await audit_repo.get_logs(
         user_id=user_id,
         project_id=project_id,
         action=action,
@@ -60,29 +57,32 @@ async def get_audit_logs(
         skip=skip,
         limit=limit,
     )
-    return logs
+    total = await audit_repo.get_log_count(
+        user_id=user_id,
+        project_id=project_id,
+        action=action,
+        resource_type=resource_type,
+        start_time=start_time,
+        end_time=end_time,
+    )
+    return PaginatedList(items, total=total)
 
 
 @router.get(
-    "/logs/count",
+    "/audit-logs/count",
     summary="获取审计日志总数",
     description="获取审计日志总数（仅管理员）",
 )
 async def get_audit_logs_count(
-    user_id: Optional[UUID] = Query(None, description="按用户ID过滤"),
-    project_id: Optional[UUID] = Query(None, description="按项目ID过滤"),
-    action: Optional[str] = Query(None, description="按操作类型过滤"),
-    resource_type: Optional[str] = Query(None, description="按资源类型过滤"),
-    start_time: Optional[datetime] = Query(None, description="开始时间"),
-    end_time: Optional[datetime] = Query(None, description="结束时间"),
-    current_user=Depends(get_current_metadata_admin),
+    user_id: UUID | None = Query(None, description="按用户ID过滤"),
+    project_id: UUID | None = Query(None, description="按项目ID过滤"),
+    action: str | None = Query(None, description="按操作类型过滤"),
+    resource_type: str | None = Query(None, description="按资源类型过滤"),
+    start_time: datetime | None = Query(None, description="开始时间"),
+    end_time: datetime | None = Query(None, description="结束时间"),
+    _current_user=Depends(get_current_metadata_admin),
     audit_repo: AuditRepository = Depends(get_audit_repository),
 ) -> dict:
-    """
-    获取审计日志总数
-
-    获取符合条件的审计日志的总数，仅管理员可访问
-    """
     count = await audit_repo.get_log_count(
         user_id=user_id,
         project_id=project_id,
@@ -94,27 +94,42 @@ async def get_audit_logs_count(
     return {"count": count}
 
 
+@router.post("/audit-events", status_code=status.HTTP_204_NO_CONTENT)
+async def record_session_event(
+    payload: SessionAuditEventRequest,
+    request: Request,
+    current_user=Depends(get_current_metadata_user),
+    session: AsyncSession = Depends(get_metadata_session),
+) -> None:
+    await log_audit_event(
+        action=AuditAction.LOGIN if payload.event == "login" else AuditAction.LOGOUT,
+        user_id=current_user.id,
+        resource_type="session",
+        resource_id=str(current_user.keycloak_id),
+        ip_address=request.client.host if request.client else None,
+        request_method=request.method,
+        request_path=request.url.path,
+        response_status=status.HTTP_204_NO_CONTENT,
+        session=session,
+    )
+
+
 @router.get(
-    "/logs/my",
+    "/audit-logs/mine",
     summary="查询我的审计日志",
     description="查询当前用户的审计日志",
-    response_model=List[AuditLogResponse],
+    response_model=list[AuditLogResponse],
 )
 async def get_my_audit_logs(
-    action: Optional[str] = Query(None, description="按操作类型过滤"),
-    start_time: Optional[datetime] = Query(None, description="开始时间"),
-    end_time: Optional[datetime] = Query(None, description="结束时间"),
+    action: str | None = Query(None, description="按操作类型过滤"),
+    start_time: datetime | None = Query(None, description="开始时间"),
+    end_time: datetime | None = Query(None, description="结束时间"),
     skip: int = Query(0, ge=0, description="跳过记录数"),
     limit: int = Query(100, ge=1, le=1000, description="限制记录数"),
     current_user=Depends(get_current_metadata_user),
     audit_repo: AuditRepository = Depends(get_audit_repository),
-) -> List[AuditLogResponse]:
-    """
-    查询当前用户的审计日志
-
-    普通用户只能查看自己的操作记录
-    """
-    logs = await audit_repo.get_logs(
+) -> list[AuditLogResponse]:
+    items = await audit_repo.get_logs(
         user_id=current_user.id,
         action=action,
         start_time=start_time,
@@ -122,4 +137,10 @@ async def get_my_audit_logs(
         skip=skip,
         limit=limit,
     )
-    return logs
+    total = await audit_repo.get_log_count(
+        user_id=current_user.id,
+        action=action,
+        start_time=start_time,
+        end_time=end_time,
+    )
+    return PaginatedList(items, total=total)

app/api/v1/endpoints/auth.py

@@ -1,190 +0,0 @@
-from typing import Annotated
-from datetime import timedelta
-from fastapi import APIRouter, Depends, HTTPException, status
-from fastapi.security import OAuth2PasswordRequestForm
-from app.core.config import settings
-from app.core.security import create_access_token, create_refresh_token, verify_password
-from app.domain.schemas.user import UserCreate, UserResponse, UserLogin, Token
-from app.infra.db.metadb.repositories.user_repository import UserRepository
-from app.auth.dependencies import get_user_repository, get_current_active_user
-from app.domain.schemas.user import UserInDB
-import logging
-
-logger = logging.getLogger(__name__)
-
-router = APIRouter()
-
-
-@router.post(
-    "/register", response_model=UserResponse, status_code=status.HTTP_201_CREATED
-)
-async def register(
-    user_data: UserCreate, user_repo: UserRepository = Depends(get_user_repository)
-) -> UserResponse:
-    """
-    用户注册
-
-    创建新用户账号
-    """
-    # 检查用户名和邮箱是否已存在
-    if await user_repo.user_exists(username=user_data.username):
-        raise HTTPException(
-            status_code=status.HTTP_400_BAD_REQUEST,
-            detail="Username already registered",
-        )
-
-    if await user_repo.user_exists(email=user_data.email):
-        raise HTTPException(
-            status_code=status.HTTP_400_BAD_REQUEST, detail="Email already registered"
-        )
-
-    # 创建用户
-    try:
-        user = await user_repo.create_user(user_data)
-        if not user:
-            raise HTTPException(
-                status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-                detail="Failed to create user",
-            )
-        return UserResponse.model_validate(user)
-    except Exception as e:
-        logger.error(f"Error during user registration: {e}")
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="Registration failed",
-        )
-
-
-@router.post("/login", response_model=Token)
-async def login(
-    form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> Token:
-    """
-    用户登录（OAuth2 标准格式）
-
-    返回 JWT Access Token 和 Refresh Token
-    """
-    # 验证用户（支持用户名或邮箱登录）
-    user = await user_repo.get_user_by_username(form_data.username)
-    if not user:
-        # 尝试用邮箱登录
-        user = await user_repo.get_user_by_email(form_data.username)
-
-    if not user or not verify_password(form_data.password, user.hashed_password):
-        raise HTTPException(
-            status_code=status.HTTP_401_UNAUTHORIZED,
-            detail="Incorrect username or password",
-            headers={"WWW-Authenticate": "Bearer"},
-        )
-
-    if not user.is_active:
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN, detail="Inactive user account"
-        )
-
-    # 生成 Token
-    access_token = create_access_token(subject=user.username)
-    refresh_token = create_refresh_token(subject=user.username)
-
-    return Token(
-        access_token=access_token,
-        refresh_token=refresh_token,
-        token_type="bearer",
-        expires_in=settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
-    )
-
-
-@router.post("/login/simple", response_model=Token)
-async def login_simple(
-    username: str,
-    password: str,
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> Token:
-    """
-    简化版登录接口（保持向后兼容）
-
-    直接使用 username 和 password 参数
-    """
-    # 验证用户
-    user = await user_repo.get_user_by_username(username)
-    if not user:
-        user = await user_repo.get_user_by_email(username)
-
-    if not user or not verify_password(password, user.hashed_password):
-        raise HTTPException(
-            status_code=status.HTTP_401_UNAUTHORIZED,
-            detail="Incorrect username or password",
-        )
-
-    if not user.is_active:
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN, detail="Inactive user account"
-        )
-
-    # 生成 Token
-    access_token = create_access_token(subject=user.username)
-    refresh_token = create_refresh_token(subject=user.username)
-
-    return Token(
-        access_token=access_token,
-        refresh_token=refresh_token,
-        token_type="bearer",
-        expires_in=settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
-    )
-
-
-@router.get("/me", response_model=UserResponse)
-async def get_current_user_info(
-    current_user: UserInDB = Depends(get_current_active_user),
-) -> UserResponse:
-    """
-    获取当前登录用户信息
-    """
-    return UserResponse.model_validate(current_user)
-
-
-@router.post("/refresh", response_model=Token)
-async def refresh_token(
-    refresh_token: str, user_repo: UserRepository = Depends(get_user_repository)
-) -> Token:
-    """
-    刷新 Access Token
-
-    使用 Refresh Token 获取新的 Access Token
-    """
-    from jose import jwt, JWTError
-
-    credentials_exception = HTTPException(
-        status_code=status.HTTP_401_UNAUTHORIZED,
-        detail="Could not validate refresh token",
-        headers={"WWW-Authenticate": "Bearer"},
-    )
-
-    try:
-        payload = jwt.decode(
-            refresh_token, settings.SECRET_KEY, algorithms=[settings.ALGORITHM]
-        )
-        username: str = payload.get("sub")
-        token_type: str = payload.get("type")
-
-        if username is None or token_type != "refresh":
-            raise credentials_exception
-
-    except JWTError:
-        raise credentials_exception
-
-    # 验证用户仍然存在且激活
-    user = await user_repo.get_user_by_username(username)
-    if not user or not user.is_active:
-        raise credentials_exception
-
-    # 生成新的 Access Token
-    new_access_token = create_access_token(subject=user.username)
-
-    return Token(
-        access_token=new_access_token,
-        refresh_token=refresh_token,  # 保持原 refresh token
-        token_type="bearer",
-        expires_in=settings.ACCESS_TOKEN_EXPIRE_MINUTES * 60,
-    )

app/api/v1/endpoints/burst_detection.py

@@ -1,13 +1,13 @@
 from datetime import datetime
 from typing import Any
+from uuid import UUID
 
-from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
+from fastapi import APIRouter, Depends, HTTPException, Body
 from pydantic import BaseModel, Field
+from starlette.concurrency import run_in_threadpool
 
 from app.auth.keycloak_dependencies import get_current_keycloak_username
 from app.services.burst_detection import (
-    get_burst_detection_scheme_detail,
-    list_burst_detection_schemes,
     run_burst_detection,
 )
 
@@ -30,17 +30,26 @@ class BurstDetectionRequest(BaseModel):
     points_per_day: int = Field(1440, description="每天的数据点数")
     mu: int = Field(100, description="异常值检测的参数")
     iforest_params: dict[str, Any] | None = Field(None, description="隔离森林算法参数")
+    target_time: datetime | None = Field(
+        None,
+        description="目标侦测时刻；为空时自动使用最近一个完整的监测时刻",
+    )
+    sampling_interval_minutes: int | None = Field(
+        None,
+        ge=1,
+        le=1440,
+        description="采样间隔（分钟）；为空时根据压力 SCADA 传输频率自动推断",
+    )
     scada_start: datetime | None = Field(None, description="SCADA数据起始时间")
     scada_end: datetime | None = Field(None, description="SCADA数据结束时间")
     sensor_nodes: list[str] | None = Field(None, description="传感器节点列表")
     scheme_name: str | None = Field(None, description="方案名称")
     data_source: str = Field("monitoring", description="数据来源：monitoring（监测）或simulation（模拟）")
-    simulation_scheme_name: str | None = Field(None, description="模拟方案名称")
-    simulation_scheme_type: str | None = Field(None, description="模拟方案类型")
+    simulation_run_id: UUID | None = Field(None, description="分析模拟运行 ID")
 
 
 @router.post(
-    "/detect/",
+    "/burst-detections",
     summary="执行爆管检测",
     description="基于压力观测数据和其他参数执行爆管检测分析"
 )
@@ -65,67 +74,10 @@ async def detect_burst(
         HTTPException: 当处理过程中发生错误时
     """
     try:
-        return run_burst_detection(**data.model_dump(), username=username)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/",
-    summary="查询爆管检测方案列表",
-    description="获取指定网络的所有爆管检测方案"
-)
-async def query_burst_detection_schemes(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    query_date: datetime | None = Query(None, description="查询日期（可选）"),
-) -> list[dict[str, Any]]:
-    """
-    获取爆管检测方案列表。
-    
-    查询指定网络的所有已配置的爆管检测方案，
-    可按日期进行筛选。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        query_date: 查询日期（可选）
-        
-    Returns:
-        爆管检测方案列表
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return list_burst_detection_schemes(network=network, query_date=query_date)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/{scheme_name}",
-    summary="获取爆管检测方案详情",
-    description="获取指定爆管检测方案的详细信息"
-)
-async def query_burst_detection_scheme_detail(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    scheme_name: str = Path(..., description="爆管检测方案名称"),
-) -> dict[str, Any]:
-    """
-    获取爆管检测方案详情。
-    
-    查询指定爆管检测方案的完整配置和参数信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        scheme_name: 爆管检测方案名称
-        
-    Returns:
-        包含方案详情的字典
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return get_burst_detection_scheme_detail(network=network, scheme_name=scheme_name)
+        return await run_in_threadpool(
+            run_burst_detection,
+            **data.model_dump(),
+            username=username,
+        )
     except Exception as exc:
         raise HTTPException(status_code=400, detail=str(exc))

app/api/v1/endpoints/burst_location.py

@@ -2,14 +2,14 @@ from typing import Any
 from datetime import datetime
 
 from typing import Literal
+from uuid import UUID
 
-from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
+from fastapi import APIRouter, Depends, HTTPException, Body
 from pydantic import BaseModel, Field
+from starlette.concurrency import run_in_threadpool
 
 from app.auth.keycloak_dependencies import get_current_keycloak_username
 from app.services.burst_location import (
-    get_burst_location_scheme_detail,
-    list_burst_location_schemes,
     run_burst_location_by_network,
 )
 
@@ -29,16 +29,17 @@ class BurstLocationRequest(BaseModel):
     normal_flow: dict[str, float] | list[dict[str, Any]] | None = Field(None, description="正常时的流量数据")
     min_dpressure: float = Field(2.0, description="最小压力差（bar）")
     basic_pressure: float = Field(10.0, description="基准压力（bar）")
-    scada_burst_start: datetime | None = Field(None, description="SCADA爆管开始时间")
-    scada_burst_end: datetime | None = Field(None, description="SCADA爆管结束时间")
+    scada_burst_start: datetime | None = Field(None, description="爆管/模拟方案开始时间")
+    scada_burst_end: datetime | None = Field(None, description="爆管/模拟方案结束时间")
+    scada_normal_start: datetime | None = Field(None, description="监测数据正常工况开始时间")
+    scada_normal_end: datetime | None = Field(None, description="监测数据正常工况结束时间")
     use_scada_flow: bool = Field(False, description="是否使用SCADA流量数据")
-    scheme_name: str | None = Field(None, description="方案名称")
-    simulation_scheme_name: str | None = Field(None, description="模拟方案名称")
-    simulation_scheme_type: str | None = Field(None, description="模拟方案类型")
+    scheme_name: str | None = Field(None, description="爆管定位运行名称")
+    simulation_run_id: UUID | None = Field(None, description="分析模拟运行 ID")
 
 
 @router.post(
-    "/locate/",
+    "/burst-locations",
     summary="执行爆管定位",
     description="基于压力和流量数据定位管网中的爆管位置"
 )
@@ -63,67 +64,10 @@ async def locate_burst(
         HTTPException: 当数据类型或值不正确时
     """
     try:
-        return run_burst_location_by_network(**data.model_dump(), username=username)
+        return await run_in_threadpool(
+            run_burst_location_by_network,
+            **data.model_dump(),
+            username=username,
+        )
     except (TypeError, ValueError) as exc:
         raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/",
-    summary="查询爆管定位方案列表",
-    description="获取指定网络的所有爆管定位方案"
-)
-async def query_burst_schemes(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    query_date: datetime | None = Query(None, description="查询日期（可选）")
-) -> list[dict[str, Any]]:
-    """
-    获取爆管定位方案列表。
-    
-    查询指定网络的所有已配置的爆管定位方案，
-    可按日期进行筛选。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        query_date: 查询日期（可选）
-        
-    Returns:
-        爆管定位方案列表
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return list_burst_location_schemes(network=network, query_date=query_date)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/{scheme_name}",
-    summary="获取爆管定位方案详情",
-    description="获取指定爆管定位方案的详细信息"
-)
-async def query_burst_scheme_detail(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    scheme_name: str = Path(..., description="爆管定位方案名称")
-) -> dict[str, Any]:
-    """
-    获取爆管定位方案详情。
-    
-    查询指定爆管定位方案的完整配置和参数信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        scheme_name: 爆管定位方案名称
-        
-    Returns:
-        包含方案详情的字典
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return get_burst_location_scheme_detail(network=network, scheme_name=scheme_name)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))

app/api/v1/endpoints/cache.py

@@ -1,57 +0,0 @@
-from fastapi import APIRouter, Query
-from app.infra.cache.redis_client import redis_client
-
-router = APIRouter()
-
-@router.post("/clearrediskey/", summary="清除单个缓存键", description="根据键名清除单个Redis缓存")
-async def fastapi_clear_redis_key(key: str = Query(..., description="缓存键名")):
-    """
-    清除单个缓存键
-    
-    根据指定的键名删除Redis中对应的缓存
-    """
-    redis_client.delete(key)
-    return True
-
-
-@router.post("/clearrediskeys/", summary="清除匹配的缓存键", description="根据模式清除匹配的Redis缓存键")
-async def fastapi_clear_redis_keys(keys: str = Query(..., description="缓存键模式（支持通配符）")):
-    """
-    清除匹配的缓存键
-    
-    根据指定的模式删除Redis中所有匹配的缓存键
-    """
-    # delete keys contains the key
-    matched_keys = redis_client.keys(f"*{keys}*")
-    if matched_keys:
-        redis_client.delete(*matched_keys)
-
-    return True
-
-
-@router.post("/clearallredis/", summary="清除所有缓存", description="清空整个Redis数据库的所有缓存")
-async def fastapi_clear_all_redis():
-    """
-    清除所有缓存
-    
-    清空Redis数据库中的所有缓存键值对
-    """
-    redis_client.flushdb()
-    return True
-
-
-@router.get("/queryredis/", summary="查询缓存键列表", description="获取Redis中所有的缓存键")
-async def fastapi_query_redis():
-    """
-    查询缓存键列表
-    
-    获取Redis数据库中所有的缓存键列表
-    """
-    # Helper to decode bytes to str for JSON response if needed, 
-    # but original just returned keys (which might be bytes in redis-py unless decode_responses=True)
-    # create_redis_client usually sets decode_responses=False by default.
-    # We will assume user handles bytes or we should decode. 
-    # Original just returned redis_client.keys("*")
-    keys = redis_client.keys("*")
-    # Clean output for API
-    return [k.decode('utf-8') if isinstance(k, bytes) else k for k in keys]

app/api/v1/endpoints/components/controls.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     get_control,
     get_control_schema,
@@ -13,58 +13,58 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getcontrolschema/", summary="获取控制架构", description="获取网络中控制对象的架构定义")
-async def fastapi_get_control_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/control", summary="获取控制架构", description="获取网络中控制对象的架构定义")
+def fastapi_get_control_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取控制架构。
     
     返回指定网络中控制对象的属性架构定义。
     """
     return get_control_schema(network)
 
-@router.get("/getcontrolproperties/", summary="获取控制属性", description="获取指定网络中的控制属性信息")
-async def fastapi_get_control_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/controls/properties", summary="获取控制属性", description="获取指定网络中的控制属性信息")
+def fastapi_get_control_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取控制属性。
     
     返回指定网络中的控制对象属性信息。
     """
     return get_control(network)
 
-@router.post("/setcontrolproperties/", response_model=None, summary="设置控制属性", description="更新指定网络中的控制属性")
-async def fastapi_set_control_properties(
+@router.patch("/controls/properties", response_model=None, summary="设置控制属性", description="更新指定网络中的控制属性")
+def fastapi_set_control_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置控制属性。
     
     更新指定网络中的控制属性值。
     """
-    props = await req.json()
+    props = payload
     return set_control(network, ChangeSet(props))
 
-@router.get("/getruleschema/", summary="获取规则架构", description="获取网络中规则对象的架构定义")
-async def fastapi_get_rule_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/rule-schemas", summary="获取规则架构", description="获取网络中规则对象的架构定义")
+def fastapi_get_rule_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取规则架构。
     
     返回指定网络中规则对象的属性架构定义。
     """
     return get_rule_schema(network)
 
-@router.get("/getruleproperties/", summary="获取规则属性", description="获取指定网络中的规则属性信息")
-async def fastapi_get_rule_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/rule-properties", summary="获取规则属性", description="获取指定网络中的规则属性信息")
+def fastapi_get_rule_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取规则属性。
     
     返回指定网络中的规则对象属性信息。
     """
     return get_rule(network)
 
-@router.post("/setruleproperties/", response_model=None, summary="设置规则属性", description="更新指定网络中的规则属性")
-async def fastapi_set_rule_properties(
+@router.patch("/rule-properties", response_model=None, summary="设置规则属性", description="更新指定网络中的规则属性")
+def fastapi_set_rule_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置规则属性。
     
     更新指定网络中的规则属性值。
     """
-    props = await req.json()
+    props = payload
     return set_rule(network, ChangeSet(props))

app/api/v1/endpoints/components/curves.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_curve,
     delete_curve,
@@ -14,32 +14,32 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getcurveschema", summary="获取曲线架构", description="获取网络中曲线对象的架构定义")
-async def fastapi_get_curve_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/curve", summary="获取曲线架构", description="获取网络中曲线对象的架构定义")
+def fastapi_get_curve_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取曲线架构。
     
     返回指定网络中曲线对象的属性架构定义。
     """
     return get_curve_schema(network)
 
-@router.post("/addcurve/", response_model=None, summary="添加曲线", description="在网络中添加一条新的曲线")
-async def fastapi_add_curve(
+@router.post("/curves", response_model=None, summary="添加曲线", description="在网络中添加一条新的曲线")
+def fastapi_add_curve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     curve: str = Query(..., description="曲线ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加曲线。
     
     在指定网络中创建一条新的曲线，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     ps = {
         "id": curve,
     } | props
     return add_curve(network, ChangeSet(ps))
 
-@router.post("/deletecurve/", response_model=None, summary="删除曲线", description="从网络中删除指定的曲线")
-async def fastapi_delete_curve(
+@router.delete("/curves", response_model=None, summary="删除曲线", description="从网络中删除指定的曲线")
+def fastapi_delete_curve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     curve: str = Query(..., description="曲线ID")
 ) -> ChangeSet:
@@ -50,8 +50,8 @@ async def fastapi_delete_curve(
     ps = {"id": curve}
     return delete_curve(network, ChangeSet(ps))
 
-@router.get("/getcurveproperties/", summary="获取曲线属性", description="获取指定曲线的属性信息")
-async def fastapi_get_curve_properties(
+@router.get("/curves/properties", summary="获取曲线属性", description="获取指定曲线的属性信息")
+def fastapi_get_curve_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     curve: str = Query(..., description="曲线ID")
 ) -> dict[str, Any]:
@@ -61,30 +61,30 @@ async def fastapi_get_curve_properties(
     """
     return get_curve(network, curve)
 
-@router.post("/setcurveproperties/", response_model=None, summary="设置曲线属性", description="更新指定曲线的属性")
-async def fastapi_set_curve_properties(
+@router.patch("/curves/properties", response_model=None, summary="设置曲线属性", description="更新指定曲线的属性")
+def fastapi_set_curve_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     curve: str = Query(..., description="曲线ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置曲线属性。
     
     更新指定曲线的属性值。
     """
-    props = await req.json()
+    props = payload
     ps = {"id": curve} | props
     return set_curve(network, ChangeSet(ps))
 
-@router.get("/getcurves/", summary="获取所有曲线", description="获取网络中的所有曲线列表")
-async def fastapi_get_curves(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
+@router.get("/curves", summary="获取所有曲线", description="获取网络中的所有曲线列表")
+def fastapi_get_curves(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
     """获取所有曲线。
     
     返回指定网络中的所有曲线ID列表。
     """
     return get_curves(network)
 
-@router.get("/iscurve/", summary="检查曲线存在性", description="检查指定的曲线是否存在")
-async def fastapi_is_curve(
+@router.get("/curves/existence", summary="检查曲线存在性", description="检查指定的曲线是否存在")
+def fastapi_is_curve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     curve: str = Query(..., description="曲线ID")
 ) -> bool:

app/api/v1/endpoints/components/options.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     get_energy,
     get_energy_schema,
@@ -19,72 +19,72 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/gettimeschema", summary="获取时间选项架构", description="获取网络中时间选项的架构定义")
-async def fastapi_get_time_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/time", summary="获取时间选项架构", description="获取网络中时间选项的架构定义")
+def fastapi_get_time_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取时间选项架构。
     
     返回指定网络中时间相关选项的属性架构定义。
     """
     return get_time_schema(network)
 
-@router.get("/gettimeproperties/", summary="获取时间选项属性", description="获取指定网络中的时间选项属性信息")
-async def fastapi_get_time_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/network-options/time", summary="获取时间选项属性", description="获取指定网络中的时间选项属性信息")
+def fastapi_get_time_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取时间选项属性。
     
     返回指定网络中的时间相关选项属性。
     """
     return get_time(network)
 
-@router.post("/settimeproperties/", response_model=None, summary="设置时间选项属性", description="更新指定网络中的时间选项属性")
-async def fastapi_set_time_properties(
+@router.patch("/time-properties", response_model=None, summary="设置时间选项属性", description="更新指定网络中的时间选项属性")
+def fastapi_set_time_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置时间选项属性。
     
     更新指定网络中的时间相关选项属性值。
     """
-    props = await req.json()
+    props = payload
     return set_time(network, ChangeSet(props))
 
-@router.get("/getenergyschema/", summary="获取能耗选项架构", description="获取网络中能耗选项的架构定义")
-async def fastapi_get_energy_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/energy", summary="获取能耗选项架构", description="获取网络中能耗选项的架构定义")
+def fastapi_get_energy_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取能耗选项架构。
     
     返回指定网络中能耗相关选项的属性架构定义。
     """
     return get_energy_schema(network)
 
-@router.get("/getenergyproperties/", summary="获取能耗选项属性", description="获取指定网络中的能耗选项属性信息")
-async def fastapi_get_energy_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/network-options/energy", summary="获取能耗选项属性", description="获取指定网络中的能耗选项属性信息")
+def fastapi_get_energy_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取能耗选项属性。
     
     返回指定网络中的能耗相关选项属性。
     """
     return get_energy(network)
 
-@router.post("/setenergyproperties/", response_model=None, summary="设置能耗选项属性", description="更新指定网络中的能耗选项属性")
-async def fastapi_set_energy_properties(
+@router.patch("/energy-properties", response_model=None, summary="设置能耗选项属性", description="更新指定网络中的能耗选项属性")
+def fastapi_set_energy_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置能耗选项属性。
     
     更新指定网络中的能耗相关选项属性值。
     """
-    props = await req.json()
+    props = payload
     return set_energy(network, ChangeSet(props))
 
-@router.get("/getpumpenergyschema/", summary="获取泵能耗选项架构", description="获取网络中泵能耗选项的架构定义")
-async def fastapi_get_pump_energy_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/pump-energy", summary="获取泵能耗选项架构", description="获取网络中泵能耗选项的架构定义")
+def fastapi_get_pump_energy_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取泵能耗选项架构。
     
     返回指定网络中泵能耗相关选项的属性架构定义。
     """
     return get_pump_energy_schema(network)
 
-@router.get("/getpumpenergyproperties//", summary="获取泵能耗属性", description="获取指定泵的能耗属性信息")
-async def fastapi_get_pump_energy_proeprties(
+@router.get("/network-options/pump-energy", summary="获取泵能耗属性", description="获取指定泵的能耗属性信息")
+def fastapi_get_pump_energy_proeprties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="泵ID")
 ) -> dict[str, Any]:
@@ -94,44 +94,44 @@ async def fastapi_get_pump_energy_proeprties(
     """
     return get_pump_energy(network, pump)
 
-@router.get("/setpumpenergyproperties//", response_model=None, summary="设置泵能耗属性", description="更新指定泵的能耗属性")
-async def fastapi_set_pump_energy_properties(
+@router.patch("/network-options/pump-energy", response_model=None, summary="设置泵能耗属性", description="更新指定泵的能耗属性")
+def fastapi_set_pump_energy_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="泵ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置泵能耗属性。
     
     更新指定泵的能耗相关属性值。
     """
-    props = await req.json()
+    props = payload
     ps = {"id": pump} | props
     return set_pump_energy(network, ChangeSet(ps))
 
-@router.get("/getoptionschema/", summary="获取选项架构", description="获取网络中选项对象的架构定义")
-async def fastapi_get_option_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/option", summary="获取选项架构", description="获取网络中选项对象的架构定义")
+def fastapi_get_option_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取选项架构。
     
     返回指定网络中选项对象的属性架构定义。
     """
     return get_option_v3_schema(network)
 
-@router.get("/getoptionproperties/", summary="获取选项属性", description="获取指定网络中的选项属性信息")
-async def fastapi_get_option_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/network-options", summary="获取选项属性", description="获取指定网络中的选项属性信息")
+def fastapi_get_option_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取选项属性。
     
     返回指定网络中的选项对象属性信息。
     """
     return get_option_v3(network)
 
-@router.post("/setoptionproperties/", response_model=None, summary="设置选项属性", description="更新指定网络中的选项属性")
-async def fastapi_set_option_properties(
+@router.patch("/network-options", response_model=None, summary="设置选项属性", description="更新指定网络中的选项属性")
+def fastapi_set_option_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置选项属性。
     
     更新指定网络中的选项属性值。
     """
-    props = await req.json()
+    props = payload
     return set_option_v3(network, ChangeSet(props))

app/api/v1/endpoints/components/patterns.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_pattern,
     delete_pattern,
@@ -14,32 +14,32 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getpatternschema", summary="获取模式架构", description="获取网络中模式对象的架构定义")
-async def fastapi_get_pattern_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/pattern", summary="获取模式架构", description="获取网络中模式对象的架构定义")
+def fastapi_get_pattern_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取模式架构。
     
     返回指定网络中模式对象的属性架构定义。
     """
     return get_pattern_schema(network)
 
-@router.post("/addpattern/", response_model=None, summary="添加模式", description="在网络中添加一个新的模式")
-async def fastapi_add_pattern(
+@router.post("/patterns", response_model=None, summary="添加模式", description="在网络中添加一个新的模式")
+def fastapi_add_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pattern: str = Query(..., description="模式ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加模式。
     
     在指定网络中创建一个新的模式，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     ps = {
         "id": pattern,
     } | props
     return add_pattern(network, ChangeSet(ps))
 
-@router.post("/deletepattern/", response_model=None, summary="删除模式", description="从网络中删除指定的模式")
-async def fastapi_delete_pattern(
+@router.delete("/patterns", response_model=None, summary="删除模式", description="从网络中删除指定的模式")
+def fastapi_delete_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pattern: str = Query(..., description="模式ID")
 ) -> ChangeSet:
@@ -50,8 +50,8 @@ async def fastapi_delete_pattern(
     ps = {"id": pattern}
     return delete_pattern(network, ChangeSet(ps))
 
-@router.get("/getpatternproperties/", summary="获取模式属性", description="获取指定模式的属性信息")
-async def fastapi_get_pattern_properties(
+@router.get("/patterns/properties", summary="获取模式属性", description="获取指定模式的属性信息")
+def fastapi_get_pattern_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pattern: str = Query(..., description="模式ID")
 ) -> dict[str, Any]:
@@ -61,22 +61,22 @@ async def fastapi_get_pattern_properties(
     """
     return get_pattern(network, pattern)
 
-@router.post("/setpatternproperties/", response_model=None, summary="设置模式属性", description="更新指定模式的属性")
-async def fastapi_set_pattern_properties(
+@router.patch("/patterns/properties", response_model=None, summary="设置模式属性", description="更新指定模式的属性")
+def fastapi_set_pattern_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pattern: str = Query(..., description="模式ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置模式属性。
     
     更新指定模式的属性值。
     """
-    props = await req.json()
+    props = payload
     ps = {"id": pattern} | props
     return set_pattern(network, ChangeSet(ps))
 
-@router.get("/ispattern/", summary="检查模式存在性", description="检查指定的模式是否存在")
-async def fastapi_is_pattern(
+@router.get("/patterns/existence", summary="检查模式存在性", description="检查指定的模式是否存在")
+def fastapi_is_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pattern: str = Query(..., description="模式ID")
 ) -> bool:
@@ -86,8 +86,8 @@ async def fastapi_is_pattern(
     """
     return is_pattern(network, pattern)
 
-@router.get("/getpatterns/", summary="获取所有模式", description="获取网络中的所有模式列表")
-async def fastapi_get_patterns(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
+@router.get("/patterns", summary="获取所有模式", description="获取网络中的所有模式列表")
+def fastapi_get_patterns(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
     """获取所有模式。
     
     返回指定网络中的所有模式ID列表。

app/api/v1/endpoints/components/quality.py

@@ -1,11 +1,10 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_mixing,
     add_source,
-    api,
     delete_mixing,
     delete_source,
     get_emitter,
@@ -23,6 +22,7 @@ from app.services.tjnetwork import (
     get_tank_reaction,
     get_tank_reaction_schema,
     set_emitter,
+    set_mixing,
     set_pipe_reaction,
     set_quality,
     set_reaction,
@@ -32,16 +32,16 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getqualityschema/", summary="获取水质架构", description="获取网络中水质对象的架构定义")
-async def fastapi_get_quality_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/quality", summary="获取水质架构", description="获取网络中水质对象的架构定义")
+def fastapi_get_quality_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取水质架构。
     
     返回指定网络中水质对象的属性架构定义。
     """
     return get_quality_schema(network)
 
-@router.get("/getqualityproperties/", summary="获取水质属性", description="获取指定节点的水质属性信息")
-async def fastapi_get_quality_properties(
+@router.get("/quality-configurations/properties", summary="获取水质属性", description="获取指定节点的水质属性信息")
+def fastapi_get_quality_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> dict[str, Any]:
@@ -51,28 +51,28 @@ async def fastapi_get_quality_properties(
     """
     return get_quality(network, node)
 
-@router.post("/setqualityproperties/", response_model=None, summary="设置水质属性", description="更新指定节点的水质属性")
-async def fastapi_set_quality_properties(
+@router.patch("/quality-configurations/properties", response_model=None, summary="设置水质属性", description="更新指定节点的水质属性")
+def fastapi_set_quality_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置水质属性。
     
     更新指定节点的水质属性值。
     """
-    props = await req.json()
+    props = payload
     return set_quality(network, ChangeSet(props))
 
-@router.get("/getemitterschema", summary="获取发射器架构", description="获取网络中发射器对象的架构定义")
-async def fastapi_get_emitter_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/emitter", summary="获取发射器架构", description="获取网络中发射器对象的架构定义")
+def fastapi_get_emitter_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取发射器架构。
     
     返回指定网络中发射器对象的属性架构定义。
     """
     return get_emitter_schema(network)
 
-@router.get("/getemitterproperties/", summary="获取发射器属性", description="获取指定连接点的发射器属性信息")
-async def fastapi_get_emitter_properties(
+@router.get("/emitters/properties", summary="获取发射器属性", description="获取指定连接点的发射器属性信息")
+def fastapi_get_emitter_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="连接点ID")
 ) -> dict[str, Any]:
@@ -82,30 +82,30 @@ async def fastapi_get_emitter_properties(
     """
     return get_emitter(network, junction)
 
-@router.post("/setemitterproperties/", response_model=None, summary="设置发射器属性", description="更新指定连接点的发射器属性")
-async def fastapi_set_emitter_properties(
+@router.patch("/emitters/properties", response_model=None, summary="设置发射器属性", description="更新指定连接点的发射器属性")
+def fastapi_set_emitter_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="连接点ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置发射器属性。
     
     更新指定连接点的发射器属性值。
     """
-    props = await req.json()
+    props = payload
     ps = {"junction": junction} | props
     return set_emitter(network, ChangeSet(ps))
 
-@router.get("/getsourcechema/", summary="获取水源架构", description="获取网络中水源对象的架构定义")
-async def fastapi_get_source_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/source", summary="获取水源架构", description="获取网络中水源对象的架构定义")
+def fastapi_get_source_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取水源架构。
     
     返回指定网络中水源对象的属性架构定义。
     """
     return get_source_schema(network)
 
-@router.get("/getsource/", summary="获取水源属性", description="获取指定节点的水源属性信息")
-async def fastapi_get_source(
+@router.get("/sources/detail", summary="获取水源属性", description="获取指定节点的水源属性信息")
+def fastapi_get_source(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> dict[str, Any]:
@@ -115,32 +115,32 @@ async def fastapi_get_source(
     """
     return get_source(network, node)
 
-@router.post("/setsource/", response_model=None, summary="设置水源属性", description="更新指定节点的水源属性")
-async def fastapi_set_source(
+@router.patch("/sources", response_model=None, summary="设置水源属性", description="更新指定节点的水源属性")
+def fastapi_set_source(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置水源属性。
     
     更新指定节点的水源属性值。
     """
-    props = await req.json()
+    props = payload
     return set_source(network, ChangeSet(props))
 
-@router.post("/addsource/", response_model=None, summary="添加水源", description="在网络中添加一个新的水源")
-async def fastapi_add_source(
+@router.post("/sources", response_model=None, summary="添加水源", description="在网络中添加一个新的水源")
+def fastapi_add_source(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加水源。
     
     在指定网络中创建一个新的水源，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     return add_source(network, ChangeSet(props))
 
-@router.post("/deletesource/", response_model=None, summary="删除水源", description="从网络中删除指定节点的水源")
-async def fastapi_delete_source(
+@router.delete("/sources", response_model=None, summary="删除水源", description="从网络中删除指定节点的水源")
+def fastapi_delete_source(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> ChangeSet:
@@ -151,44 +151,44 @@ async def fastapi_delete_source(
     props = {"node": node}
     return delete_source(network, ChangeSet(props))
 
-@router.get("/getreactionschema/", summary="获取反应架构", description="获取网络中反应对象的架构定义")
-async def fastapi_get_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/reaction", summary="获取反应架构", description="获取网络中反应对象的架构定义")
+def fastapi_get_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取反应架构。
     
     返回指定网络中反应对象的属性架构定义。
     """
     return get_reaction_schema(network)
 
-@router.get("/getreaction/", summary="获取反应属性", description="获取指定网络中的反应属性信息")
-async def fastapi_get_reaction(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/reactions/detail", summary="获取反应属性", description="获取指定网络中的反应属性信息")
+def fastapi_get_reaction(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取反应属性。
     
     返回指定网络中的反应属性信息。
     """
     return get_reaction(network)
 
-@router.post("/setreaction/", response_model=None, summary="设置反应属性", description="更新指定网络中的反应属性")
-async def fastapi_set_reaction(
+@router.patch("/reactions", response_model=None, summary="设置反应属性", description="更新指定网络中的反应属性")
+def fastapi_set_reaction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置反应属性。
     
     更新指定网络中的反应属性值。
     """
-    props = await req.json()
+    props = payload
     return set_reaction(network, ChangeSet(props))
 
-@router.get("/getpipereactionschema/", summary="获取管道反应架构", description="获取网络中管道反应对象的架构定义")
-async def fastapi_get_pipe_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/pipe-reaction", summary="获取管道反应架构", description="获取网络中管道反应对象的架构定义")
+def fastapi_get_pipe_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取管道反应架构。
     
     返回指定网络中管道反应对象的属性架构定义。
     """
     return get_pipe_reaction_schema(network)
 
-@router.get("/getpipereaction/", summary="获取管道反应属性", description="获取指定管道的反应属性信息")
-async def fastapi_get_pipe_reaction(
+@router.get("/pipe-reactions/detail", summary="获取管道反应属性", description="获取指定管道的反应属性信息")
+def fastapi_get_pipe_reaction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> dict[str, Any]:
@@ -198,28 +198,28 @@ async def fastapi_get_pipe_reaction(
     """
     return get_pipe_reaction(network, pipe)
 
-@router.post("/setpipereaction/", response_model=None, summary="设置管道反应属性", description="更新指定管道的反应属性")
-async def fastapi_set_pipe_reaction(
+@router.patch("/pipe-reactions", response_model=None, summary="设置管道反应属性", description="更新指定管道的反应属性")
+def fastapi_set_pipe_reaction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置管道反应属性。
     
     更新指定管道的反应属性值。
     """
-    props = await req.json()
+    props = payload
     return set_pipe_reaction(network, ChangeSet(props))
 
-@router.get("/gettankreactionschema/", summary="获取水池反应架构", description="获取网络中水池反应对象的架构定义")
-async def fastapi_get_tank_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/tank-reaction", summary="获取水池反应架构", description="获取网络中水池反应对象的架构定义")
+def fastapi_get_tank_reaction_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取水池反应架构。
     
     返回指定网络中水池反应对象的属性架构定义。
     """
     return get_tank_reaction_schema(network)
 
-@router.get("/gettankreaction/", summary="获取水池反应属性", description="获取指定水池的反应属性信息")
-async def fastapi_get_tank_reaction(
+@router.get("/tank-reactions/detail", summary="获取水池反应属性", description="获取指定水池的反应属性信息")
+def fastapi_get_tank_reaction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水池ID")
 ) -> dict[str, Any]:
@@ -229,28 +229,28 @@ async def fastapi_get_tank_reaction(
     """
     return get_tank_reaction(network, tank)
 
-@router.post("/settankreaction/", response_model=None, summary="设置水池反应属性", description="更新指定水池的反应属性")
-async def fastapi_set_tank_reaction(
+@router.patch("/tank-reactions", response_model=None, summary="设置水池反应属性", description="更新指定水池的反应属性")
+def fastapi_set_tank_reaction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置水池反应属性。
     
     更新指定水池的反应属性值。
     """
-    props = await req.json()
+    props = payload
     return set_tank_reaction(network, ChangeSet(props))
 
-@router.get("/getmixingschema/", summary="获取混合架构", description="获取网络中混合对象的架构定义")
-async def fastapi_get_mixing_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/mixing", summary="获取混合架构", description="获取网络中混合对象的架构定义")
+def fastapi_get_mixing_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取混合架构。
     
     返回指定网络中混合对象的属性架构定义。
     """
     return get_mixing_schema(network)
 
-@router.get("/getmixing/", summary="获取混合属性", description="获取指定水池的混合属性信息")
-async def fastapi_get_mixing(
+@router.get("/mixing-configurations/detail", summary="获取混合属性", description="获取指定水池的混合属性信息")
+def fastapi_get_mixing(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水池ID")
 ) -> dict[str, Any]:
@@ -260,38 +260,38 @@ async def fastapi_get_mixing(
     """
     return get_mixing(network, tank)
 
-@router.post("/setmixing/", response_model=None, summary="设置混合属性", description="更新指定水池的混合属性")
-async def fastapi_set_mixing(
+@router.patch("/mixing-configurations", response_model=None, summary="设置混合属性", description="更新指定水池的混合属性")
+def fastapi_set_mixing(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置混合属性。
     
     更新指定水池的混合属性值。
     """
-    props = await req.json()
-    return api.set_mixing(network, ChangeSet(props))
+    props = payload
+    return set_mixing(network, ChangeSet(props))
 
-@router.post("/addmixing/", response_model=None, summary="添加混合", description="在网络中添加一个新的混合")
-async def fastapi_add_mixing(
+@router.post("/mixing-configurations", response_model=None, summary="添加混合", description="在网络中添加一个新的混合")
+def fastapi_add_mixing(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加混合。
     
     在指定网络中创建一个新的混合，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     return add_mixing(network, ChangeSet(props))
 
-@router.post("/deletemixing/", response_model=None, summary="删除混合", description="从网络中删除指定的混合")
-async def fastapi_delete_mixing(
+@router.delete("/mixing-configurations", response_model=None, summary="删除混合", description="从网络中删除指定的混合")
+def fastapi_delete_mixing(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """删除混合。
     
     从指定网络中删除指定的混合及其相关数据。
     """
-    props = await req.json()
+    props = payload
     return delete_mixing(network, ChangeSet(props))

app/api/v1/endpoints/components/visuals.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body, Response
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_label,
     add_vertex,
@@ -24,16 +24,16 @@ import json
 
 router = APIRouter()
 
-@router.get("/getvertexschema/", summary="获取图形元素架构", description="获取网络中图形元素对象的架构定义")
-async def fastapi_get_vertex_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/vertex", summary="获取图形元素架构", description="获取网络中图形元素对象的架构定义")
+def fastapi_get_vertex_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取图形元素架构。
     
     返回指定网络中图形元素对象的属性架构定义。
     """
     return get_vertex_schema(network)
 
-@router.get("/getvertexproperties/", summary="获取图形元素属性", description="获取指定图形元素的属性信息")
-async def fastapi_get_vertex_properties(
+@router.get("/visual-elements/properties", summary="获取图形元素属性", description="获取指定图形元素的属性信息")
+def fastapi_get_vertex_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="图形元素链接")
 ) -> dict[str, Any]:
@@ -43,68 +43,68 @@ async def fastapi_get_vertex_properties(
     """
     return get_vertex(network, link)
 
-@router.post("/setvertexproperties/", response_model=None, summary="设置图形元素属性", description="更新指定图形元素的属性")
-async def fastapi_set_vertex_properties(
+@router.patch("/visual-elements/properties", response_model=None, summary="设置图形元素属性", description="更新指定图形元素的属性")
+def fastapi_set_vertex_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置图形元素属性。
     
     更新指定图形元素的属性值。
     """
-    props = await req.json()
+    props = payload
     return set_vertex(network, ChangeSet(props))
 
-@router.post("/addvertex/", response_model=None, summary="添加图形元素", description="在网络中添加一个新的图形元素")
-async def fastapi_add_vertex(
+@router.post("/visual-elements", response_model=None, summary="添加图形元素", description="在网络中添加一个新的图形元素")
+def fastapi_add_vertex(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加图形元素。
     
     在指定网络中创建一个新的图形元素，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     return add_vertex(network, ChangeSet(props))
 
-@router.post("/deletevertex/", response_model=None, summary="删除图形元素", description="从网络中删除指定的图形元素")
-async def fastapi_delete_vertex(
+@router.delete("/visual-elements", response_model=None, summary="删除图形元素", description="从网络中删除指定的图形元素")
+def fastapi_delete_vertex(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """删除图形元素。
     
     从指定网络中删除指定的图形元素及其相关数据。
     """
-    props = await req.json()
+    props = payload
     return delete_vertex(network, ChangeSet(props))
 
-@router.get("/getallvertexlinks/", response_class=PlainTextResponse, summary="获取所有图形元素链接", description="获取网络中的所有图形元素链接列表")
-async def fastapi_get_all_vertex_links(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
+@router.get("/visual-elements/links", response_class=PlainTextResponse, summary="获取所有图形元素链接", description="获取网络中的所有图形元素链接列表")
+def fastapi_get_all_vertex_links(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
     """获取所有图形元素链接。
     
     返回指定网络中的所有图形元素链接列表。
     """
     return json.dumps(get_all_vertex_links(network))
 
-@router.get("/getallvertices/", response_class=PlainTextResponse, summary="获取所有图形元素", description="获取网络中的所有图形元素详细信息")
-async def fastapi_get_all_vertices(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[str, Any]]:
+@router.get("/all-vertices", response_class=PlainTextResponse, summary="获取所有图形元素", description="获取网络中的所有图形元素详细信息")
+def fastapi_get_all_vertices(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[str, Any]]:
     """获取所有图形元素。
     
     返回指定网络中的所有图形元素详细信息。
     """
     return json.dumps(get_all_vertices(network))
 
-@router.get("/getlabelschema/", summary="获取标签架构", description="获取网络中标签对象的架构定义")
-async def fastapi_get_label_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/label", summary="获取标签架构", description="获取网络中标签对象的架构定义")
+def fastapi_get_label_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取标签架构。
     
     返回指定网络中标签对象的属性架构定义。
     """
     return get_label_schema(network)
 
-@router.get("/getlabelproperties/", summary="获取标签属性", description="获取指定坐标处的标签属性信息")
-async def fastapi_get_label_properties(
+@router.get("/labels/properties", summary="获取标签属性", description="获取指定坐标处的标签属性信息")
+def fastapi_get_label_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     x: float = Query(..., description="X坐标"),
     y: float = Query(..., description="Y坐标")
@@ -115,66 +115,66 @@ async def fastapi_get_label_properties(
     """
     return get_label(network, x, y)
 
-@router.post("/setlabelproperties/", response_model=None, summary="设置标签属性", description="更新指定标签的属性")
-async def fastapi_set_label_properties(
+@router.patch("/labels/properties", response_model=None, summary="设置标签属性", description="更新指定标签的属性")
+def fastapi_set_label_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置标签属性。
     
     更新指定标签的属性值。
     """
-    props = await req.json()
+    props = payload
     return set_label(network, ChangeSet(props))
 
-@router.post("/addlabel/", response_model=None, summary="添加标签", description="在网络中添加一个新的标签")
-async def fastapi_add_label(
+@router.post("/labels", response_model=None, summary="添加标签", description="在网络中添加一个新的标签")
+def fastapi_add_label(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """添加标签。
     
     在指定网络中创建一个新的标签，并设置其初始属性。
     """
-    props = await req.json()
+    props = payload
     return add_label(network, ChangeSet(props))
 
-@router.post("/deletelabel/", response_model=None, summary="删除标签", description="从网络中删除指定的标签")
-async def fastapi_delete_label(
+@router.delete("/labels", response_model=None, summary="删除标签", description="从网络中删除指定的标签")
+def fastapi_delete_label(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """删除标签。
     
     从指定网络中删除指定的标签及其相关数据。
     """
-    props = await req.json()
+    props = payload
     return delete_label(network, ChangeSet(props))
 
-@router.get("/getbackdropschema/", summary="获取背景架构", description="获取网络中背景对象的架构定义")
-async def fastapi_get_backdrop_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/backdrop", summary="获取背景架构", description="获取网络中背景对象的架构定义")
+def fastapi_get_backdrop_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """获取背景架构。
     
     返回指定网络中背景对象的属性架构定义。
     """
     return get_backdrop_schema(network)
 
-@router.get("/getbackdropproperties/", summary="获取背景属性", description="获取指定网络的背景属性信息")
-async def fastapi_get_backdrop_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+@router.get("/backdrops/properties", summary="获取背景属性", description="获取指定网络的背景属性信息")
+def fastapi_get_backdrop_properties(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取背景属性。
     
     返回指定网络的背景属性信息。
     """
     return get_backdrop(network)
 
-@router.post("/setbackdropproperties/", response_model=None, summary="设置背景属性", description="更新指定网络的背景属性")
-async def fastapi_set_backdrop_properties(
+@router.patch("/backdrops/properties", response_model=None, summary="设置背景属性", description="更新指定网络的背景属性")
+def fastapi_set_backdrop_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置背景属性。
     
     更新指定网络的背景属性值。
     """
-    props = await req.json()
+    props = payload
     return set_backdrop(network, ChangeSet(props))

app/api/v1/endpoints/data_query.py

@@ -1,388 +0,0 @@
-from typing import Any, List, Dict, Optional
-import logging
-from datetime import datetime, timedelta, timezone, time as dt_time
-import msgpack
-from fastapi import APIRouter
-from pydantic import BaseModel
-from py_linq import Enumerable
-
-import app.infra.db.influxdb.api as influxdb_api
-import app.services.time_api as time_api
-from app.infra.cache.redis_client import redis_client, encode_datetime, decode_datetime
-
-router = APIRouter()
-logger = logging.getLogger(__name__)
-
-# Basic Node/Link Latest Record Queries
-
-@router.get("/querynodelatestrecordbyid/")
-async def fastapi_query_node_latest_record_by_id(id: str) -> Any:
-    return influxdb_api.query_latest_record_by_ID(id, type="node")
-
-@router.get("/querylinklatestrecordbyid/")
-async def fastapi_query_link_latest_record_by_id(id: str) -> Any:
-    return influxdb_api.query_latest_record_by_ID(id, type="link")
-
-@router.get("/queryscadalatestrecordbyid/")
-async def fastapi_query_scada_latest_record_by_id(id: str) -> Any:
-    return influxdb_api.query_latest_record_by_ID(id, type="scada")
-
-# Time-based Queries
-
-@router.get("/queryallrecordsbytime/")
-async def fastapi_query_all_records_by_time(querytime: str) -> dict[str, list]:
-    results: tuple = influxdb_api.query_all_records_by_time(query_time=querytime)
-    return {"nodes": results[0], "links": results[1]}
-
-@router.get("/queryallrecordsbytimeproperty/")
-async def fastapi_query_all_record_by_time_property(
-    querytime: str, type: str, property: str, bucket: str = "realtime_simulation_result"
-) -> dict[str, list]:
-    results: tuple = influxdb_api.query_all_record_by_time_property(
-        query_time=querytime, type=type, property=property, bucket=bucket
-    )
-    return {"results": results}
-
-@router.get("/queryallschemerecordsbytimeproperty/")
-async def fastapi_query_all_scheme_record_by_time_property(
-    querytime: str,
-    type: str,
-    property: str,
-    schemename: str,
-    bucket: str = "scheme_simulation_result",
-) -> dict[str, list]:
-    """
-    查询指定方案某一时刻的所有记录,查询 'node' 或 'link' 的某一属性值
-    """
-    results: list = influxdb_api.query_all_scheme_record_by_time_property(
-        query_time=querytime,
-        type=type,
-        property=property,
-        scheme_name=schemename,
-        bucket=bucket,
-    )
-    return {"results": results}
-
-@router.get("/querysimulationrecordsbyidtime/")
-async def fastapi_query_simulation_record_by_ids_time(
-    id: str, querytime: str, type: str, bucket: str = "realtime_simulation_result"
-) -> dict[str, list]:
-    results: tuple = influxdb_api.query_simulation_result_by_ID_time(
-        ID=id, type=type, query_time=querytime, bucket=bucket
-    )
-    return {"results": results}
-
-@router.get("/queryschemesimulationrecordsbyidtime/")
-async def fastapi_query_scheme_simulation_record_by_ids_time(
-    scheme_name: str,
-    id: str,
-    querytime: str,
-    type: str,
-    bucket: str = "scheme_simulation_result",
-) -> dict[str, list]:
-    results: tuple = influxdb_api.query_scheme_simulation_result_by_ID_time(
-        scheme_name=scheme_name, ID=id, type=type, query_time=querytime, bucket=bucket
-    )
-    return {"results": results}
-
-# Date-based Queries with Caching
-
-@router.get("/queryallrecordsbydate/")
-async def fastapi_query_all_records_by_date(querydate: str) -> dict:
-    is_today_or_future = time_api.is_today_or_future(querydate)
-    logger.info(f"isToday or future: {is_today_or_future}")
-
-    cache_key = f"queryallrecordsbydate_{querydate}"
-    
-    if not is_today_or_future:
-        data = redis_client.get(cache_key)
-        if data:
-            results = msgpack.unpackb(data, object_hook=decode_datetime)
-            logger.info("return from cache redis")
-            return results
-
-    logger.info("query from influxdb")
-    nodes_links: tuple = influxdb_api.query_all_records_by_date(query_date=querydate)
-    results = {"nodes": nodes_links[0], "links": nodes_links[1]}
-
-    if not is_today_or_future:
-        logger.info("save to cache redis")
-        redis_client.set(cache_key, msgpack.packb(results, default=encode_datetime))
-
-    logger.info("return results")
-    return results
-
-@router.get("/queryallrecordsbytimerange/")
-async def fastapi_query_all_records_by_time_range(
-    starttime: str, endtime: str
-) -> dict[str, list]:
-    cache_key = f"queryallrecordsbytimerange_{starttime}_{endtime}"
-    
-    if not time_api.is_today_or_future(starttime):
-        data = redis_client.get(cache_key)
-        if data:
-            loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-            return loaded_dict
-
-    nodes_links: tuple = influxdb_api.query_all_records_by_time_range(
-        starttime=starttime, endtime=endtime
-    )
-    results = {"nodes": nodes_links[0], "links": nodes_links[1]}
-
-    if not time_api.is_today_or_future(starttime):
-        redis_client.set(cache_key, msgpack.packb(results, default=encode_datetime))
-
-    return results
-
-@router.get("/queryallrecordsbydatewithtype/")
-async def fastapi_query_all_records_by_date_with_type(
-    querydate: str, querytype: str
-) -> list:
-    cache_key = f"queryallrecordsbydatewithtype_{querydate}_{querytype}"
-    data = redis_client.get(cache_key)
-    if data:
-        loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-        return loaded_dict
-
-    results = influxdb_api.query_all_records_by_date_with_type(
-        query_date=querydate, query_type=querytype
-    )
-
-    packed = msgpack.packb(results, default=encode_datetime)
-    redis_client.set(cache_key, packed)
-
-    return results
-
-@router.get("/queryallrecordsbyidsdatetype/")
-async def fastapi_query_all_records_by_ids_date_type(
-    ids: str, querydate: str, querytype: str
-) -> list:
-    cache_key = f"queryallrecordsbydatewithtype_{querydate}_{querytype}"
-    data = redis_client.get(cache_key)
-    
-    results = []
-    if data:
-        results = msgpack.unpackb(data, object_hook=decode_datetime)
-    else:
-        results = influxdb_api.query_all_records_by_date_with_type(
-            query_date=querydate, query_type=querytype
-        )
-        packed = msgpack.packb(results, default=encode_datetime)
-        redis_client.set(cache_key, packed)
-
-    query_ids = ids.split(",")
-    # Using Enumerable from py_linq as in original code
-    e_results = Enumerable(results)
-    lst_results = e_results.where(lambda x: x["ID"] in query_ids).to_list()
-
-    return lst_results
-
-@router.get("/queryallrecordsbydateproperty/")
-async def fastapi_query_all_records_by_date_property(
-    querydate: str, querytype: str, property: str
-) -> list[dict]:
-    cache_key = f"queryallrecordsbydateproperty_{querydate}_{querytype}_{property}"
-    data = redis_client.get(cache_key)
-    if data:
-        loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-        return loaded_dict
-
-    result_dict = influxdb_api.query_all_record_by_date_property(
-        query_date=querydate, type=querytype, property=property
-    )
-    packed = msgpack.packb(result_dict, default=encode_datetime)
-    redis_client.set(cache_key, packed)
-
-    return result_dict
-
-# Curve Queries
-
-@router.get("/querynodecurvebyidpropertydaterange/")
-async def fastapi_query_node_curve_by_id_property_daterange(
-    id: str, prop: str, startdate: str, enddate: str
-):
-    return influxdb_api.query_curve_by_ID_property_daterange(
-        id, type="node", property=prop, start_date=startdate, end_date=enddate
-    )
-
-@router.get("/querylinkcurvebyidpropertydaterange/")
-async def fastapi_query_link_curve_by_id_property_daterange(
-    id: str, prop: str, startdate: str, enddate: str
-):
-    return influxdb_api.query_curve_by_ID_property_daterange(
-        id, type="link", property=prop, start_date=startdate, end_date=enddate
-    )
-
-# SCADA Data Queries
-
-@router.get("/queryscadadatabydeviceidandtime/")
-async def fastapi_query_scada_data_by_device_id_and_time(ids: str, querytime: str):
-    query_ids = ids.split(",")
-    logger.info(querytime)
-    return influxdb_api.query_SCADA_data_by_device_ID_and_time(
-        query_ids_list=query_ids, query_time=querytime
-    )
-
-@router.get("/queryscadadatabydeviceidandtimerange/")
-async def fastapi_query_scada_data_by_device_id_and_time_range(
-    ids: str, starttime: str, endtime: str
-):
-    print(f"query_ids: {ids}, starttime: {starttime}, endtime: {endtime}")
-    query_ids = ids.split(",")
-    return influxdb_api.query_SCADA_data_by_device_ID_and_timerange(
-        query_ids_list=query_ids, start_time=starttime, end_time=endtime
-    )
-
-@router.get("/queryfillingscadadatabydeviceidandtimerange/")
-async def fastapi_query_filling_scada_data_by_device_id_and_time_range(
-    ids: str, starttime: str, endtime: str
-):
-    print(f"query_ids: {ids}, starttime: {starttime}, endtime: {endtime}")
-    query_ids = ids.split(",")
-    return influxdb_api.query_filling_SCADA_data_by_device_ID_and_timerange(
-        query_ids_list=query_ids, start_time=starttime, end_time=endtime
-    )
-
-@router.get("/querycleaningscadadatabydeviceidandtimerange/")
-async def fastapi_query_cleaning_scada_data_by_device_id_and_time_range(
-    ids: str, starttime: str, endtime: str
-):
-    print(f"query_ids: {ids}, starttime: {starttime}, endtime: {endtime}")
-    query_ids = ids.split(",")
-    return influxdb_api.query_cleaning_SCADA_data_by_device_ID_and_timerange(
-        query_ids_list=query_ids, start_time=starttime, end_time=endtime
-    )
-
-@router.get("/querysimulationscadadatabydeviceidandtimerange/")
-async def fastapi_query_simulation_scada_data_by_device_id_and_time_range(
-    ids: str, starttime: str, endtime: str
-):
-    print(f"query_ids: {ids}, starttime: {starttime}, endtime: {endtime}")
-    query_ids = ids.split(",")
-    return influxdb_api.query_simulation_SCADA_data_by_device_ID_and_timerange(
-        query_ids_list=query_ids, start_time=starttime, end_time=endtime
-    )
-
-@router.get("/querycleanedscadadatabydeviceidandtimerange/")
-async def fastapi_query_cleaned_scada_data_by_device_id_and_time_range(
-    ids: str, starttime: str, endtime: str
-):
-    print(f"query_ids: {ids}, starttime: {starttime}, endtime: {endtime}")
-    query_ids = ids.split(",")
-    return influxdb_api.query_cleaned_SCADA_data_by_device_ID_and_timerange(
-        query_ids_list=query_ids, start_time=starttime, end_time=endtime
-    )
-
-@router.get("/queryscadadatabydeviceidanddate/")
-async def fastapi_query_scada_data_by_device_id_and_date(ids: str, querydate: str):
-    query_ids = ids.split(",")
-    return influxdb_api.query_SCADA_data_by_device_ID_and_date(
-        query_ids_list=query_ids, query_date=querydate
-    )
-
-@router.get("/queryallscadarecordsbydate/")
-async def fastapi_query_all_scada_records_by_date(querydate: str):
-    is_today_or_future = time_api.is_today_or_future(querydate)
-    logger.info(f"isToday or future: {is_today_or_future}")
-
-    cache_key = f"queryallscadarecordsbydate_{querydate}"
-    
-    if not is_today_or_future:
-        data = redis_client.get(cache_key)
-        if data:
-            loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-            logger.info("return from cache redis")
-            return loaded_dict
-
-    logger.info("query from influxdb")
-    result_dict = influxdb_api.query_all_SCADA_records_by_date(query_date=querydate)
-
-    if not is_today_or_future:
-        logger.info("save to cache redis")
-        packed = msgpack.packb(result_dict, default=encode_datetime)
-        redis_client.set(cache_key, packed)
-
-    logger.info("return results")
-    return result_dict
-
-@router.get("/queryallschemeallrecords/")
-async def fastapi_query_all_scheme_all_records(
-    schemetype: str, schemename: str, querydate: str
-) -> tuple:
-    cache_key = f"queryallschemeallrecords_{schemetype}_{schemename}_{querydate}"
-    data = redis_client.get(cache_key)
-    if data:
-        loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-        return loaded_dict
-
-    results = influxdb_api.query_scheme_all_record(
-        scheme_type=schemetype, scheme_name=schemename, query_date=querydate
-    )
-    packed = msgpack.packb(results, default=encode_datetime)
-    redis_client.set(cache_key, packed)
-
-    return results
-
-@router.get("/queryschemeallrecordsproperty/")
-async def fastapi_query_all_scheme_all_records_property(
-    schemetype: str, schemename: str, querydate: str, querytype: str, queryproperty: str
-) -> Optional[List]:
-    cache_key = f"queryallschemeallrecords_{schemetype}_{schemename}_{querydate}"
-    data = redis_client.get(cache_key)
-    all_results = None
-    if data:
-        all_results = msgpack.unpackb(data, object_hook=decode_datetime)
-    else:
-        all_results = influxdb_api.query_scheme_all_record(
-            scheme_type=schemetype, scheme_name=schemename, query_date=querydate
-        )
-        packed = msgpack.packb(all_results, default=encode_datetime)
-        redis_client.set(cache_key, packed)
-
-    results = None
-    if querytype == "node":
-        results = all_results[0]
-    elif querytype == "link":
-        results = all_results[1]
-
-    return results
-
-@router.get("/queryinfluxdbbuckets/")
-async def fastapi_query_influxdb_buckets():
-    return influxdb_api.query_buckets()
-
-@router.get("/queryinfluxdbbucketmeasurements/")
-async def fastapi_query_influxdb_bucket_measurements(bucket: str):
-    return influxdb_api.query_measurements(bucket=bucket)
-
-############################################################
-# download history data
-############################################################
-
-class Download_History_Data_Manually(BaseModel):
-    """
-    download_date：样式如 datetime(2025, 5, 4)
-    """
-
-    download_date: datetime
-
-
-@router.post("/download_history_data_manually/")
-async def fastapi_download_history_data_manually(
-    data: Download_History_Data_Manually,
-) -> None:
-    item = data.dict()
-    tz = timezone(timedelta(hours=8))
-    begin_dt = datetime.combine(item.get("download_date").date(), dt_time.min).replace(
-        tzinfo=tz
-    )
-    end_dt = datetime.combine(item.get("download_date").date(), dt_time(23, 59, 59)).replace(
-        tzinfo=tz
-    )
-
-    begin_time = begin_dt.isoformat()
-    end_time = end_dt.isoformat()
-
-    influxdb_api.download_history_data_manually(
-        begin_time=begin_time, end_time=end_time
-    )

app/api/v1/endpoints/extension.py

@@ -1,104 +0,0 @@
-from typing import List, Any
-from fastapi import APIRouter, Request, HTTPException, Query, Body
-from app.services.tjnetwork import (
-    ChangeSet,
-    get_all_extension_data_keys,
-    get_all_extension_data,
-    get_extension_data,
-    set_extension_data
-)
-
-router = APIRouter()
-
-@router.get(
-    "/getallextensiondatakeys/",
-    summary="获取所有扩展数据键",
-    description="获取指定网络的所有扩展数据的键列表"
-)
-async def get_all_extension_data_keys_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[str]:
-    """
-    获取所有扩展数据键。
-    
-    返回指定网络中所有可用的扩展数据键。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        扩展数据键列表
-    """
-    return get_all_extension_data_keys(network)
-
-@router.get(
-    "/getallextensiondata/",
-    summary="获取所有扩展数据",
-    description="获取指定网络的所有扩展数据"
-)
-async def get_all_extension_data_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, Any]:
-    """
-    获取所有扩展数据。
-    
-    返回指定网络的所有扩展数据及其值。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        扩展数据字典
-    """
-    return get_all_extension_data(network)
-
-@router.get(
-    "/getextensiondata/",
-    summary="获取指定扩展数据",
-    description="获取指定网络中指定键的扩展数据值"
-)
-async def get_extension_data_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    key: str = Query(..., description="扩展数据键")
-) -> str | None:
-    """
-    获取指定扩展数据。
-    
-    返回指定网络中指定键对应的扩展数据值。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        key: 扩展数据键
-        
-    Returns:
-        扩展数据值，如果不存在返回None
-    """
-    return get_extension_data(network, key)
-
-@router.post(
-    "/setextensiondata/",
-    response_model=None,
-    summary="设置扩展数据",
-    description="设置指定网络中的扩展数据"
-)
-async def set_extension_data_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    设置扩展数据。
-    
-    在指定网络中设置扩展数据，并返回变更集信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 包含扩展数据的请求体
-        
-    Returns:
-        变更集信息
-    """
-    props = await req.json()
-    print(props)
-    cs = set_extension_data(network, ChangeSet(props))
-    print(cs.operations[0])
-    return cs

app/api/v1/endpoints/geocoding.py

@@ -0,0 +1,29 @@
+from typing import Any
+
+from fastapi import APIRouter, HTTPException, status
+
+from app.services.geocoding import (
+    TiandituGeocodeRequest,
+    TiandituGeocodingAPIError,
+    TiandituGeocodingConfigError,
+    geocode_tianditu,
+)
+
+router = APIRouter()
+
+
+@router.post(
+    "/geocoding-requests",
+    summary="Tianditu Geocoding",
+    description="调用天地图地理编码服务，将结构化地址转换为经纬度",
+)
+async def tianditu_geocode(request: TiandituGeocodeRequest) -> dict[str, Any]:
+    try:
+        return await geocode_tianditu(request)
+    except TiandituGeocodingConfigError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=str(exc),
+        ) from exc
+    except TiandituGeocodingAPIError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.detail) from exc

app/api/v1/endpoints/leakage.py

@@ -2,37 +2,50 @@ import os
 from typing import Any
 from datetime import datetime
 
-from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
-from pydantic import BaseModel, Field
+from fastapi import APIRouter, Depends, HTTPException, Body
+from pydantic import BaseModel, ConfigDict, Field
+from starlette.concurrency import run_in_threadpool
 
 from app.auth.keycloak_dependencies import get_current_keycloak_username
-from app.services.leakage_identifier import (
-    get_leakage_identify_scheme_detail,
-    list_leakage_identify_schemes,
+from app.services.dma_leakage_estimation import (
     run_leakage_identification,
 )
 
 router = APIRouter()
 DEFAULT_N_WORKERS = max(1, min((os.cpu_count() or 1) - 1, 4))
+MAX_POPULATION_SIZE = 1_000
+MAX_GENERATIONS = 1_000
+MAX_DURATION_HOURS = 168
 
 
 class LeakageIdentifyRequest(BaseModel):
     """漏损识别请求模型"""
+
+    model_config = ConfigDict(extra="forbid")
+
     network: str = Field(..., description="管网名称（或数据库名称）")
-    observed_pressure_data: str | dict[str, list[Any]] | list[dict[str, Any]] | None = Field(
-        None, description="观测的压力数据"
+    observed_pressure_data: dict[str, list[Any]] | list[dict[str, Any]] | None = (
+        Field(None, description="观测的压力数据；文件路径不属于公共 API 输入")
     )
-    start_time: float = Field(0, description="起始时间（小时）")
-    duration: float = Field(24, description="持续时间（小时）")
-    timestep: float = Field(5, description="时间步长（分钟）")
-    q_sum: float = Field(0.2, description="总流量（m3/s）")
+    start_time: float = Field(0, ge=0, description="起始时间（小时）")
+    duration: float = Field(
+        24, gt=0, le=MAX_DURATION_HOURS, description="持续时间（小时）"
+    )
+    timestep: float = Field(5, gt=0, le=1440, description="时间步长（分钟）")
+    q_sum: float = Field(0.2, ge=0, description="总流量（m3/s）")
     q_sum_unit: str = Field("m3/s", description="流量单位")
-    output_dir: str = Field("db_inp", description="输出目录")
-    pop_size: int = Field(50, description="种群大小")
-    max_gen: int = Field(100, description="最大代数")
-    n_workers: int = Field(DEFAULT_N_WORKERS, description="工作线程数")
+    pop_size: int = Field(
+        50, ge=2, le=MAX_POPULATION_SIZE, description="种群大小"
+    )
+    max_gen: int = Field(100, ge=1, le=MAX_GENERATIONS, description="最大代数")
+    n_workers: int = Field(
+        DEFAULT_N_WORKERS,
+        ge=1,
+        le=DEFAULT_N_WORKERS,
+        description="工作进程数",
+    )
     output_flow_unit: str = Field("m3/s", description="输出流量单位")
-    dma_count: int | None = Field(None, description="DMA区域数量")
+    dma_count: int | None = Field(None, ge=1, description="DMA区域数量")
     scada_start: datetime | None = Field(None, description="SCADA数据起始时间")
     scada_end: datetime | None = Field(None, description="SCADA数据结束时间")
     sensor_nodes: list[str] | None = Field(None, description="传感器节点列表")
@@ -40,7 +53,7 @@ class LeakageIdentifyRequest(BaseModel):
 
 
 @router.post(
-    "/identify/",
+    "/leakage-identifications",
     summary="执行漏损识别",
     description="基于压力观测数据和遗传算法识别管网中的漏损位置和大小"
 )
@@ -65,69 +78,10 @@ async def identify_leakage(
         HTTPException: 当处理过程中发生错误时
     """
     try:
-        return run_leakage_identification(**data.model_dump(), username=username)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/",
-    summary="查询漏损识别方案列表",
-    description="获取指定网络的所有漏损识别方案"
-)
-async def query_leakage_schemes(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    query_date: datetime | None = Query(None, description="查询日期（可选）")
-) -> list[dict[str, Any]]:
-    """
-    获取漏损识别方案列表。
-    
-    查询指定网络的所有已配置的漏损识别方案，
-    可按日期进行筛选。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        query_date: 查询日期（可选）
-        
-    Returns:
-        漏损识别方案列表
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return list_leakage_identify_schemes(network=network, query_date=query_date)
-    except Exception as exc:
-        raise HTTPException(status_code=400, detail=str(exc))
-
-
-@router.get(
-    "/schemes/{scheme_name}",
-    summary="获取漏损识别方案详情",
-    description="获取指定漏损识别方案的详细信息"
-)
-async def query_leakage_scheme_detail(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    scheme_name: str = Path(..., description="漏损识别方案名称")
-) -> dict[str, Any]:
-    """
-    获取漏损识别方案详情。
-    
-    查询指定漏损识别方案的完整配置和参数信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        scheme_name: 漏损识别方案名称
-        
-    Returns:
-        包含方案详情的字典
-        
-    Raises:
-        HTTPException: 当查询失败时
-    """
-    try:
-        return get_leakage_identify_scheme_detail(
-            network=network, scheme_name=scheme_name
+        return await run_in_threadpool(
+            run_leakage_identification,
+            **data.model_dump(),
+            username=username,
         )
     except Exception as exc:
         raise HTTPException(status_code=400, detail=str(exc))

app/api/v1/endpoints/meta.py

@@ -1,21 +1,18 @@
 import logging
 from fastapi import APIRouter, Depends, HTTPException, status, Query, Path
+import psycopg
 from psycopg import AsyncConnection
-from sqlalchemy import text
-from sqlalchemy.exc import SQLAlchemyError
-from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.auth.project_dependencies import (
     ProjectContext,
     get_project_context,
-    get_project_pg_session,
+    get_project_pg_connection,
     get_project_timescale_connection,
     get_metadata_repository,
 )
 from app.auth.metadata_dependencies import get_current_metadata_user
 from app.core.config import settings
 from app.domain.schemas.metadata import (
-    GeoServerConfigResponse,
     ProjectMetaResponse,
     ProjectSummaryResponse,
 )
@@ -25,7 +22,7 @@ router = APIRouter()
 logger = logging.getLogger(__name__)
 
 
-@router.get("/meta/project", summary="获取项目元数据", description="获取当前项目的元数据和配置信息", response_model=ProjectMetaResponse)
+@router.get("/projects/current/metadata", summary="获取项目元数据", description="获取当前项目的元数据和配置信息", response_model=ProjectMetaResponse)
 async def get_project_metadata(
     ctx: ProjectContext = Depends(get_project_context),
     metadata_repo: MetadataRepository = Depends(get_metadata_repository),
@@ -33,38 +30,26 @@ async def get_project_metadata(
     """
     获取项目元数据
     
-    返回当前项目的完整元数据，包括项目基本信息和GeoServer配置
+    返回当前项目的完整元数据，包括项目基本信息和项目权限
     """
     project = await metadata_repo.get_project_by_id(ctx.project_id)
     if not project:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Project not found"
         )
-    geoserver = await metadata_repo.get_geoserver_config(ctx.project_id)
-    geoserver_payload = (
-        GeoServerConfigResponse(
-            gs_base_url=geoserver.gs_base_url,
-            gs_admin_user=geoserver.gs_admin_user,
-            gs_datastore_name=geoserver.gs_datastore_name,
-            default_extent=geoserver.default_extent,
-            srid=geoserver.srid,
-        )
-        if geoserver
-        else None
-    )
     return ProjectMetaResponse(
         project_id=project.id,
         name=project.name,
         code=project.code,
         description=project.description,
         gs_workspace=project.gs_workspace,
+        map_extent=project.map_extent,
         status=project.status,
         project_role=ctx.project_role,
-        geoserver=geoserver_payload,
     )
 
 
-@router.get("/meta/projects", summary="列出用户项目", description="获取当前用户有权限的所有项目列表", response_model=list[ProjectSummaryResponse])
+@router.get("/projects", summary="列出用户项目", description="获取当前用户有权限的所有项目列表", response_model=list[ProjectSummaryResponse])
 async def list_user_projects(
     current_user=Depends(get_current_metadata_user),
     metadata_repo: MetadataRepository = Depends(get_metadata_repository),
@@ -100,9 +85,9 @@ async def list_user_projects(
     ]
 
 
-@router.get("/meta/db/health", summary="检查数据库健康状态", description="检查项目数据库连接的健康状况")
+@router.get("/projects/current/database-health", summary="检查数据库健康状态", description="检查项目数据库连接的健康状况")
 async def project_db_health(
-    pg_session: AsyncSession = Depends(get_project_pg_session),
+    pg_conn: AsyncConnection = Depends(get_project_pg_connection),
     ts_conn: AsyncConnection = Depends(get_project_timescale_connection),
 ):
     """
@@ -110,7 +95,25 @@ async def project_db_health(
     
     检查PostgreSQL和TimescaleDB数据库的连接状态
     """
-    await pg_session.execute(text("SELECT 1"))
-    async with ts_conn.cursor() as cur:
-        await cur.execute("SELECT 1")
+    try:
+        async with pg_conn.cursor() as cur:
+            await cur.execute("SELECT 1")
+            await cur.fetchone()
+    except psycopg.Error as exc:
+        logger.error("Project PostgreSQL health check failed", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Project PostgreSQL health check failed: {exc}",
+        ) from exc
+
+    try:
+        async with ts_conn.cursor() as cur:
+            await cur.execute("SELECT 1")
+    except psycopg.Error as exc:
+        logger.error("Project TimescaleDB health check failed", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=f"Project TimescaleDB health check failed: {exc}",
+        ) from exc
+
     return {"postgres": "ok", "timescale": "ok"}

app/api/v1/endpoints/misc.py

@@ -1,86 +0,0 @@
-from typing import Any
-import random
-from fastapi import APIRouter, Query
-from fastapi.responses import JSONResponse
-from fastapi import status
-from pydantic import BaseModel
-from app.services.tjnetwork import (
-    get_all_sensor_placements,
-    get_all_burst_locate_results,
-)
-
-router = APIRouter()
-
-
-@router.get("/getjson/", summary="获取JSON示例", description="获取JSON格式响应示例")
-async def fastapi_get_json():
-    """
-    获取JSON示例
-    
-    返回示例JSON格式的响应
-    """
-    return JSONResponse(
-        status_code=status.HTTP_400_BAD_REQUEST,
-        content={
-            "code": 400,
-            "message": "this is message",
-            "data": 123,
-        },
-    )
-
-
-@router.get("/getallsensorplacements/", summary="获取所有传感器位置", description="获取网络中所有传感器的放置位置信息")
-async def fastapi_get_all_sensor_placements(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[Any, Any]]:
-    """
-    获取所有传感器位置
-    
-    返回网络中所有传感器的放置位置及其配置信息
-    """
-    return get_all_sensor_placements(network)
-
-
-@router.get("/getallburstlocateresults/", summary="获取所有爆管定位结果", description="获取网络中所有爆管定位的分析结果")
-async def fastapi_get_all_burst_locate_results(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[Any, Any]]:
-    """
-    获取所有爆管定位结果
-    
-    返回网络中所有的爆管定位分析结果
-    """
-    return get_all_burst_locate_results(network)
-
-
-class Item(BaseModel):
-    """测试数据模型"""
-    str_info: str
-
-
-@router.post("/test_dict/", summary="测试字典处理", description="测试处理字典类型数据")
-async def fastapi_test_dict(data: Item) -> dict[str, str]:
-    """
-    测试字典处理
-    
-    接收Item模型，返回其字典格式
-    """
-    item = data.dict()
-    return item
-
-@router.get("/getrealtimedata/", summary="获取实时数据", description="获取实时监测数据")
-async def fastapi_get_realtimedata():
-    """
-    获取实时数据
-    
-    返回随机生成的实时监测数据示例
-    """
-    data = [random.randint(0, 100) for _ in range(100)]
-    return data
-
-
-@router.get("/getsimulationresult/", summary="获取模拟结果", description="获取仿真计算结果")
-async def fastapi_get_simulationresult():
-    """
-    获取仿真结果
-    
-    返回随机生成的仿真计算结果示例
-    """
-    data = [random.randint(0, 100) for _ in range(100)]
-    return data

app/api/v1/endpoints/model_import.py

@@ -0,0 +1,391 @@
+import json
+from pathlib import Path
+from tempfile import NamedTemporaryFile
+from uuid import UUID, uuid4
+
+from fastapi import (
+    APIRouter,
+    Depends,
+    File,
+    Form,
+    HTTPException,
+    Path as ApiPath,
+    Request,
+    UploadFile,
+    status,
+)
+from sqlalchemy.exc import IntegrityError
+from starlette.concurrency import run_in_threadpool
+
+from app.auth.metadata_dependencies import (
+    get_current_metadata_admin,
+    get_metadata_repository,
+)
+from app.auth.project_dependencies import (
+    ProjectContext,
+    resolve_project_business_routing,
+)
+from app.core.audit import AuditAction, log_audit_event
+from app.core.encryption import is_database_encryption_configured
+from app.domain.schemas.admin_metadata import (
+    AdminProjectResponse,
+    ProjectProvisionResponse,
+)
+from app.infra.db.metadb.repositories.metadata_repository import MetadataRepository
+from app.infra.db.project_routing import activate_project_routing
+from app.native.wndb.core.database import MaterializedViewRefreshAfterCommitError
+from app.services.network_import import network_update
+from app.services.project_provisioning import (
+    ProjectProvisioningError,
+    ProvisionedProjectInfrastructure,
+    provision_project_infrastructure,
+    validate_project_code,
+)
+from app.services.tjnetwork import run_inp
+
+router = APIRouter()
+
+MAX_INP_FILE_BYTES = 50 * 1024 * 1024
+INP_SECTIONS = ("[TITLE]", "[JUNCTIONS]", "[RESERVOIRS]", "[TANKS]", "[PIPES]")
+
+
+async def _get_active_project(project_id: UUID, metadata_repo: MetadataRepository):
+    project = await metadata_repo.get_project_by_id(project_id)
+    if project is None:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Project not found",
+        )
+    if project.status != "active":
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Project is not active",
+        )
+    return project
+
+
+def _validate_inp_bytes(content: bytes, filename: str) -> str:
+    if Path(filename).suffix.lower() != ".inp":
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Only .inp model files are accepted",
+        )
+    if not content:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="INP file is empty",
+        )
+    if len(content) > MAX_INP_FILE_BYTES:
+        raise HTTPException(
+            status_code=status.HTTP_413_REQUEST_ENTITY_TOO_LARGE,
+            detail="INP file exceeds the 50 MiB limit",
+        )
+    for encoding in ("utf-8-sig", "gb18030"):
+        try:
+            text = content.decode(encoding)
+            break
+        except UnicodeDecodeError:
+            continue
+    else:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="INP file encoding is not supported",
+        )
+    upper_text = text.upper()
+    if not any(section in upper_text for section in INP_SECTIONS):
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="Invalid INP file structure",
+        )
+    return text
+
+
+async def _read_upload(file: UploadFile) -> tuple[bytes, str]:
+    filename = Path(file.filename or "").name
+    content = await file.read(MAX_INP_FILE_BYTES + 1)
+    normalized = _validate_inp_bytes(content, filename).encode("utf-8")
+    return normalized, filename
+
+
+async def _audit_model_change(
+    *,
+    request: Request,
+    current_user,
+    metadata_repo: MetadataRepository,
+    project_id: UUID,
+    action: str,
+) -> None:
+    await log_audit_event(
+        action=AuditAction.UPDATE,
+        user_id=current_user.id,
+        project_id=project_id,
+        resource_type="hydraulic_model",
+        resource_id=action,
+        request_data={"operation": action},
+        ip_address=request.client.host if request.client else None,
+        request_method=request.method,
+        request_path=request.url.path,
+        response_status=status.HTTP_200_OK,
+        session=metadata_repo.session,
+    )
+
+
+def _run_uploaded_inp_sync(content: bytes) -> str:
+    target_dir = Path("inp")
+    target_dir.mkdir(parents=True, exist_ok=True)
+    model_name = f"admin_model_{uuid4().hex}"
+    target_path = target_dir / f"{model_name}.inp"
+    target_path.write_bytes(content)
+    return run_inp(model_name)
+
+
+async def _run_uploaded_inp(content: bytes) -> str:
+    return await run_in_threadpool(_run_uploaded_inp_sync, content)
+
+
+def _update_from_inp_sync(content: bytes, project_code: str) -> None:
+    temp_path: Path | None = None
+    try:
+        with NamedTemporaryFile(suffix=".inp", delete=False) as temp_file:
+            temp_file.write(content)
+            temp_path = Path(temp_file.name)
+        network_update(str(temp_path), project_code)
+    finally:
+        if temp_path is not None:
+            temp_path.unlink(missing_ok=True)
+
+
+async def _update_from_inp(content: bytes, project_code: str) -> None:
+    await run_in_threadpool(_update_from_inp_sync, content, project_code)
+
+
+async def _apply_model_update(content: bytes, project_code: str) -> None:
+    try:
+        await _update_from_inp(content, project_code)
+    except MaterializedViewRefreshAfterCommitError:
+        raise
+    except Exception as exc:
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"数据库操作失败: {exc}",
+        ) from exc
+
+
+def _provision_from_inp_sync(
+    content: bytes,
+    *,
+    code: str,
+    workspace: str,
+) -> ProvisionedProjectInfrastructure:
+    temp_path: Path | None = None
+    try:
+        with NamedTemporaryFile(suffix=".inp", delete=False) as temp_file:
+            temp_file.write(content)
+            temp_path = Path(temp_file.name)
+        return provision_project_infrastructure(
+            code=code,
+            workspace=workspace,
+            inp_path=temp_path,
+        )
+    finally:
+        if temp_path is not None:
+            temp_path.unlink(missing_ok=True)
+
+
+@router.post(
+    "/admin/project-provisions",
+    response_model=ProjectProvisionResponse,
+    status_code=status.HTTP_201_CREATED,
+    summary="创建完整供水项目",
+)
+async def provision_project(
+    request: Request,
+    name: str = Form(..., min_length=1, max_length=100),
+    code: str = Form(..., min_length=1, max_length=50),
+    description: str | None = Form(default=None),
+    gs_workspace: str | None = Form(default=None, max_length=100),
+    map_zoom: int = Form(default=14, ge=1, le=22),
+    file: UploadFile = File(..., description="EPANET INP 模型文件"),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> ProjectProvisionResponse:
+    try:
+        normalized_code = validate_project_code(code)
+    except ValueError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail=str(exc),
+        ) from exc
+    workspace = gs_workspace or normalized_code
+    if await metadata_repo.get_project_by_code(normalized_code) is not None:
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail="Project code already exists",
+        )
+    if not is_database_encryption_configured():
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="DATABASE_ENCRYPTION_KEY is not configured",
+        )
+
+    content, filename = await _read_upload(file)
+    validation_result = await _run_uploaded_inp(content)
+    try:
+        validation_payload = json.loads(validation_result)
+    except (TypeError, json.JSONDecodeError) as exc:
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="EPANET validation returned an invalid response",
+        ) from exc
+    if validation_payload.get("simulation_result") != "successful":
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="EPANET model validation failed",
+        )
+    try:
+        infrastructure = await run_in_threadpool(
+            _provision_from_inp_sync,
+            content,
+            code=normalized_code,
+            workspace=workspace,
+        )
+    except ProjectProvisioningError as exc:
+        if isinstance(exc.cause, ValueError):
+            response_status = status.HTTP_409_CONFLICT
+        elif exc.stage == "preflight":
+            response_status = status.HTTP_503_SERVICE_UNAVAILABLE
+        else:
+            response_status = status.HTTP_500_INTERNAL_SERVER_ERROR
+        raise HTTPException(
+            status_code=response_status,
+            detail={
+                "stage": exc.stage,
+                "message": str(exc.cause),
+                "cleanup_errors": exc.cleanup_errors,
+            },
+        ) from exc
+
+    map_extent = {"bbox": list(infrastructure.map_bbox), "zoom": map_zoom}
+    try:
+        project = await metadata_repo.create_provisioned_project(
+            name=name,
+            code=normalized_code,
+            description=description,
+            gs_workspace=workspace,
+            map_extent=map_extent,
+            creator_user_id=current_user.id,
+            business_dsn=infrastructure.business_dsn,
+            timescale_dsn=infrastructure.timescale_dsn,
+            pool_min_size=1,
+            pool_max_size=4,
+        )
+    except Exception as exc:
+        await metadata_repo.session.rollback()
+        cleanup_errors = await run_in_threadpool(infrastructure.cleanup)
+        if isinstance(exc, IntegrityError):
+            response_status = status.HTTP_409_CONFLICT
+            detail = "Project code or workspace conflicts with an existing project"
+        else:
+            response_status = status.HTTP_503_SERVICE_UNAVAILABLE
+            detail = f"Metadata database error: {exc}"
+        if cleanup_errors:
+            detail = f"{detail}; cleanup failures: {', '.join(cleanup_errors)}"
+        raise HTTPException(status_code=response_status, detail=detail) from exc
+
+    await log_audit_event(
+        action=AuditAction.CREATE,
+        user_id=current_user.id,
+        project_id=project.id,
+        resource_type="project_provision",
+        resource_id=str(project.id),
+        request_data={
+            "name": name,
+            "code": normalized_code,
+            "filename": filename,
+            "gs_workspace": workspace,
+            "layers": list(infrastructure.layers),
+        },
+        ip_address=request.client.host if request.client else None,
+        request_method=request.method,
+        request_path=request.url.path,
+        response_status=status.HTTP_201_CREATED,
+        session=metadata_repo.session,
+    )
+    return ProjectProvisionResponse(
+        project=AdminProjectResponse(
+            project_id=project.id,
+            name=project.name,
+            code=project.code,
+            description=project.description,
+            gs_workspace=project.gs_workspace,
+            map_extent=project.map_extent,
+            status=project.status,
+            created_at=project.created_at,
+            updated_at=project.updated_at,
+        ),
+        business_database=normalized_code,
+        model_template_database=infrastructure.model_template,
+        timescale_database=normalized_code,
+        geoserver_workspace=workspace,
+        geoserver_layers=list(infrastructure.layers),
+    )
+
+
+@router.post(
+    "/admin/projects/{project_id}/model-imports",
+    summary="导入桌面端水力模型",
+)
+async def import_project_model(
+    request: Request,
+    project_id: UUID = ApiPath(...),
+    file: UploadFile = File(..., description="桌面端导出的 INP 模型文件"),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> dict:
+    project = await _get_active_project(project_id, metadata_repo)
+    content, filename = await _read_upload(file)
+    result = await _run_uploaded_inp(content)
+    await _audit_model_change(
+        request=request,
+        current_user=current_user,
+        metadata_repo=metadata_repo,
+        project_id=project.id,
+        action="import",
+    )
+    return {"project_id": str(project.id), "filename": filename, "result": result}
+
+
+@router.patch(
+    "/admin/projects/{project_id}/model-imports",
+    summary="更新桌面端水力模型",
+)
+async def update_project_model(
+    request: Request,
+    project_id: UUID = ApiPath(...),
+    file: UploadFile = File(..., description="桌面端导出的 INP 模型文件"),
+    current_user=Depends(get_current_metadata_admin),
+    metadata_repo: MetadataRepository = Depends(get_metadata_repository),
+) -> dict:
+    project = await _get_active_project(project_id, metadata_repo)
+    content, filename = await _read_upload(file)
+    routing = await resolve_project_business_routing(
+        ProjectContext(
+            project_id=project.id,
+            project_code=project.code,
+            user_id=current_user.id,
+            project_role="owner",
+            system_role=current_user.role,
+            is_superuser=current_user.is_superuser,
+        ),
+        metadata_repo,
+    )
+    with activate_project_routing(routing):
+        await _apply_model_update(content, project.code)
+    await _audit_model_change(
+        request=request,
+        current_user=current_user,
+        metadata_repo=metadata_repo,
+        project_id=project.id,
+        action="update",
+    )
+    return {"project_id": str(project.id), "filename": filename, "updated": True}

app/api/v1/endpoints/network/demands.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     calculate_demand_to_network,
     calculate_demand_to_nodes,
@@ -18,11 +18,11 @@ router = APIRouter()
 ############################################################
 
 @router.get(
-    "/getdemandschema",
+    "/network-schemas/demand",
     summary="获取需水量属性架构",
     description="获取指定水网中需水量(Demand)的属性架构定义"
 )
-async def fastapi_get_demand_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+def fastapi_get_demand_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """
     获取需水量属性架构。
     
@@ -32,11 +32,11 @@ async def fastapi_get_demand_schema(network: str = Query(..., description="管
 
 
 @router.get(
-    "/getdemandproperties/",
+    "/demands/properties",
     summary="获取需水量属性",
     description="获取指定水网中节点的需水量属性信息"
 )
-async def fastapi_get_demand_properties(
+def fastapi_get_demand_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点ID")
 ) -> dict[str, Any]:
@@ -49,37 +49,37 @@ async def fastapi_get_demand_properties(
 
 
 # example: set_demand(p, ChangeSet({'junction': 'j1', 'demands': [{'demand': 10.0, 'pattern': None, 'category': 'x'}, {'demand': 20.0, 'pattern': None, 'category': None}]}))
-@router.post(
-    "/setdemandproperties/",
+@router.patch(
+    "/demands/properties",
     response_model=None,
     summary="设置需水量属性",
     description="设置指定水网中节点的需水量属性信息"
 )
-async def fastapi_set_demand_properties(
+def fastapi_set_demand_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     设置节点的需水量属性。
     
     修改指定节点的需水量信息。请求体应包含需水量值、水压等级等属性。
     """
-    props = await req.json()
+    props = payload
     ps = {"junction": junction} | props
     return set_demand(network, ChangeSet(ps))
 
 ############################################################
 # water distribution 36.[Water Distribution]
 ############################################################
-@router.get(
-    "/calculatedemandtonodes/",
+@router.post(
+    "/demands/to-nodes",
     summary="计算需水量到节点分配",
     description="将总需水量按指定方式分配到多个节点"
 )
-async def fastapi_calculate_demand_to_nodes(
+def fastapi_calculate_demand_to_nodes(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> dict[str, float]:
     """
     计算需水量到节点分配。
@@ -92,19 +92,19 @@ async def fastapi_calculate_demand_to_nodes(
         "nodes": 节点ID列表(list[str])
     }
     """
-    props = await req.json()
+    props = payload
     demand = props["demand"]
     nodes = props["nodes"]
     return calculate_demand_to_nodes(network, demand, nodes)
 
-@router.get(
-    "/calculatedemandtoregion/",
+@router.post(
+    "/demands/to-region",
     summary="计算需水量到区域分配",
     description="将总需水量按区域特征分配到该区域内的节点"
 )
-async def fastapi_calculate_demand_to_region(
+def fastapi_calculate_demand_to_region(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> dict[str, float]:
     """
     计算需水量到区域分配。
@@ -117,17 +117,17 @@ async def fastapi_calculate_demand_to_region(
         "region": 区域ID(str)
     }
     """
-    props = await req.json()
+    props = payload
     demand = props["demand"]
     region = props["region"]
     return calculate_demand_to_region(network, demand, region)
 
-@router.get(
-    "/calculatedemandtonetwork/",
+@router.post(
+    "/demands/to-network",
     summary="计算需水量到整网分配",
     description="将需水量均匀分配到整个水网的所有需水节点"
 )
-async def fastapi_calculate_demand_to_network(
+def fastapi_calculate_demand_to_network(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     demand: float = Query(..., description="总需水量(m³/h)", gt=0)
 ) -> dict[str, float]:

app/api/v1/endpoints/network/general.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     delete_junction,
     delete_pipe,
@@ -45,11 +45,11 @@ router = APIRouter()
 ############################################################
 
 @router.get(
-    "/isnode/",
+    "/nodes/existence",
     summary="检查节点有效性",
     description="检查指定ID是否为水网中的有效节点"
 )
-async def fastapi_is_node(
+def fastapi_is_node(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> bool:
@@ -57,11 +57,11 @@ async def fastapi_is_node(
     return is_node(network, node)
 
 @router.get(
-    "/isjunction/",
+    "/junctions/existence",
     summary="检查是否为接点",
     description="检查指定ID是否为水网中的接点(需求点)"
 )
-async def fastapi_is_junction(
+def fastapi_is_junction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> bool:
@@ -69,11 +69,11 @@ async def fastapi_is_junction(
     return is_junction(network, node)
 
 @router.get(
-    "/isreservoir/",
+    "/reservoirs/existence",
     summary="检查是否为水源",
     description="检查指定ID是否为水网中的水源(水库/河流)"
 )
-async def fastapi_is_reservoir(
+def fastapi_is_reservoir(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> bool:
@@ -81,11 +81,11 @@ async def fastapi_is_reservoir(
     return is_reservoir(network, node)
 
 @router.get(
-    "/istank/",
+    "/tanks/existence",
     summary="检查是否为蓄水池",
     description="检查指定ID是否为水网中的蓄水池"
 )
-async def fastapi_is_tank(
+def fastapi_is_tank(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> bool:
@@ -93,11 +93,11 @@ async def fastapi_is_tank(
     return is_tank(network, node)
 
 @router.get(
-    "/islink/",
+    "/links/existence",
     summary="检查管线有效性",
     description="检查指定ID是否为水网中的有效管线"
 )
-async def fastapi_is_link(
+def fastapi_is_link(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> bool:
@@ -105,11 +105,11 @@ async def fastapi_is_link(
     return is_link(network, link)
 
 @router.get(
-    "/ispipe/",
+    "/pipes/existence",
     summary="检查是否为管道",
     description="检查指定ID是否为水网中的管道"
 )
-async def fastapi_is_pipe(
+def fastapi_is_pipe(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> bool:
@@ -117,11 +117,11 @@ async def fastapi_is_pipe(
     return is_pipe(network, link)
 
 @router.get(
-    "/ispump/",
+    "/pumps/existence",
     summary="检查是否为泵",
     description="检查指定ID是否为水网中的泵"
 )
-async def fastapi_is_pump(
+def fastapi_is_pump(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> bool:
@@ -129,11 +129,11 @@ async def fastapi_is_pump(
     return is_pump(network, link)
 
 @router.get(
-    "/isvalve/",
+    "/valves/existence",
     summary="检查是否为阀门",
     description="检查指定ID是否为水网中的阀门"
 )
-async def fastapi_is_valve(
+def fastapi_is_valve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> bool:
@@ -141,11 +141,11 @@ async def fastapi_is_valve(
     return is_valve(network, link)
 
 @router.get(
-    "/getnodetype/",
+    "/node-types",
     summary="获取节点类型",
     description="获取指定节点的类型(接点/水源/蓄水池)"
 )
-async def fastapi_get_node_type(
+def fastapi_get_node_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> str:
@@ -153,11 +153,11 @@ async def fastapi_get_node_type(
     return get_node_type(network, node)
 
 @router.get(
-    "/getlinktype/",
+    "/link-types",
     summary="获取管线类型",
     description="获取指定管线的类型(管道/泵/阀门)"
 )
-async def fastapi_get_link_type(
+def fastapi_get_link_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> str:
@@ -165,11 +165,11 @@ async def fastapi_get_link_type(
     return get_link_type(network, link)
 
 @router.get(
-    "/getelementtype/",
+    "/element-types",
     summary="获取元素类型",
     description="获取指定元素的类型(节点或管线)"
 )
-async def fastapi_get_element_type(
+def fastapi_get_element_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     element: str = Query(..., description="元素ID")
 ) -> str:
@@ -177,11 +177,11 @@ async def fastapi_get_element_type(
     return get_element_type(network, element)
 
 @router.get(
-    "/getelementtypevalue/",
+    "/element-type-values",
     summary="获取元素类型值",
     description="获取指定元素的类型数值标识"
 )
-async def fastapi_get_element_type_value(
+def fastapi_get_element_type_value(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     element: str = Query(..., description="元素ID")
 ) -> int:
@@ -189,25 +189,25 @@ async def fastapi_get_element_type_value(
     return get_element_type_value(network, element)
 
 @router.get(
-    "/getnodes/",
+    "/nodes",
     summary="获取所有节点",
     description="获取指定水网中的所有节点ID列表"
 )
-async def fastapi_get_nodes(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
+def fastapi_get_nodes(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
     """获取水网中所有节点的ID列表。"""
     return get_nodes(network)
 
 @router.get(
-    "/getlinks/",
+    "/links",
     summary="获取所有管线",
     description="获取指定水网中的所有管线ID列表"
 )
-async def fastapi_get_links(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
+def fastapi_get_links(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[str]:
     """获取水网中所有管线的ID列表。"""
     return get_links(network)
 
 @router.get(
-    "/getnodelinks/",
+    "/node-links",
     summary="获取节点的关联管线",
     description="获取指定节点连接的所有管线ID列表"
 )
@@ -223,11 +223,11 @@ def get_node_links_endpoint(
 ############################################################
 
 @router.get(
-    "/getnodeproperties/",
+    "/node-properties",
     summary="获取节点属性",
     description="获取指定节点的所有属性信息"
 )
-async def fast_get_node_properties(
+def fast_get_node_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> dict[str, Any]:
@@ -235,11 +235,11 @@ async def fast_get_node_properties(
     return get_node_properties(network, node)
 
 @router.get(
-    "/getlinkproperties/",
+    "/link-properties",
     summary="获取管线属性",
     description="获取指定管线的所有属性信息"
 )
-async def fast_get_link_properties(
+def fast_get_link_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> dict[str, Any]:
@@ -247,11 +247,11 @@ async def fast_get_link_properties(
     return get_link_properties(network, link)
 
 @router.get(
-    "/getscadaproperties/",
+    "/scada-properties",
     summary="获取SCADA点属性",
     description="获取指定SCADA点的属性信息"
 )
-async def fast_get_scada_properties(
+def fast_get_scada_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     scada: str = Query(..., description="SCADA点ID")
 ) -> dict[str, Any]:
@@ -259,22 +259,22 @@ async def fast_get_scada_properties(
     return get_scada_info(network, scada)
 
 @router.get(
-    "/getallscadaproperties/",
+    "/all-scada-properties",
     summary="获取所有SCADA点属性",
     description="获取指定水网中所有SCADA点的属性信息"
 )
-async def fast_get_all_scada_properties(
+def fast_get_all_scada_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """获取水网中所有SCADA点的属性列表。"""
     return get_all_scada_info(network)
 
 @router.get(
-    "/getelementpropertieswithtype/",
+    "/element-properties-with-types",
     summary="获取指定类型元素属性",
     description="获取指定类型的元素属性信息"
 )
-async def fast_get_element_properties_with_type(
+def fast_get_element_properties_with_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     elementtype: str = Query(..., description="元素类型"),
     element: str = Query(..., description="元素ID")
@@ -283,11 +283,11 @@ async def fast_get_element_properties_with_type(
     return get_element_properties_with_type(network, elementtype, element)
 
 @router.get(
-    "/getelementproperties/",
+    "/element-properties",
     summary="获取元素属性",
     description="获取指定元素的属性信息"
 )
-async def fast_get_element_properties(
+def fast_get_element_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     element: str = Query(..., description="元素ID")
 ) -> dict[str, Any]:
@@ -299,37 +299,37 @@ async def fast_get_element_properties(
 ############################################################
 
 @router.get(
-    "/gettitleschema/",
+    "/title-schemas",
     summary="获取标题属性架构",
     description="获取指定水网的标题(标题)属性架构定义"
 )
-async def fast_get_title_schema(
+def fast_get_title_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """获取水网标题的属性架构。"""
     return get_title_schema(network)
 
 @router.get(
-    "/gettitle/",
+    "/titles",
     summary="获取水网标题属性",
     description="获取指定水网的标题(Title)信息"
 )
-async def fast_get_title(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
+def fast_get_title(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, Any]:
     """获取水网的标题属性。"""
     return get_title(network)
 
-@router.get(
-    "/settitle/",
+@router.patch(
+    "/titles",
     response_model=None,
     summary="设置水网标题属性",
     description="设置指定水网的标题(Title)信息"
 )
-async def fastapi_set_title(
+def fastapi_set_title(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置水网的标题属性。"""
-    props = await req.json()
+    props = payload
     return set_title(network, ChangeSet(props))
 
 ############################################################
@@ -337,41 +337,41 @@ async def fastapi_set_title(
 ############################################################
 
 @router.get(
-    "/getstatusschema",
+    "/status-schemas",
     summary="获取状态属性架构",
     description="获取指定水网的状态(Status)属性架构定义"
 )
-async def fastapi_get_status_schema(
+def fastapi_get_status_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """获取水网状态的属性架构。"""
     return get_status_schema(network)
 
 @router.get(
-    "/getstatus/",
+    "/status",
     summary="获取管线状态",
     description="获取指定管线的状态信息"
 )
-async def fastapi_get_status(
+def fastapi_get_status(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> dict[str, Any]:
     """获取管线的状态属性。"""
     return get_status(network, link)
 
-@router.post(
-    "/setstatus/",
+@router.patch(
+    "/status-properties",
     response_model=None,
     summary="设置管线状态",
     description="设置指定管线的状态信息"
 )
-async def fastapi_set_status_properties(
+def fastapi_set_status_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置管线的状态属性。"""
-    props = await req.json()
+    props = payload
     ps = {"link": link} | props
     return set_status(network, ChangeSet(ps))
 
@@ -379,13 +379,13 @@ async def fastapi_set_status_properties(
 # General Deletion
 ############################################################
 
-@router.post(
-    "/deletenode/",
+@router.delete(
+    "/nodes",
     response_model=None,
     summary="删除节点",
     description="删除指定的节点(接点/水源/蓄水池)"
 )
-async def fastapi_delete_node(
+def fastapi_delete_node(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> ChangeSet:
@@ -399,13 +399,13 @@ async def fastapi_delete_node(
         return delete_tank(network, ChangeSet(ps))
     return ChangeSet() # Should probably raise error or return empty
 
-@router.post(
-    "/deletelink/",
+@router.delete(
+    "/links",
     response_model=None,
     summary="删除管线",
     description="删除指定的管线(管道/泵/阀门)"
 )
-async def fastapi_delete_link(
+def fastapi_delete_link(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     link: str = Query(..., description="管线ID")
 ) -> ChangeSet:

app/api/v1/endpoints/network/geometry.py

@@ -1,18 +1,14 @@
-from fastapi import APIRouter, Request, Depends, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Query
+
 from app.services.tjnetwork import (
-    Any,
-    get_all_scada_info,
     get_major_node_coords,
     get_major_pipe_nodes,
     get_network_in_extent,
     get_network_link_nodes,
-    get_network_node_coords,
     get_node_coord,
 )
-from app.auth.dependencies import get_current_user as verify_token
-from app.infra.cache.redis_client import redis_client, encode_datetime, decode_datetime
-import msgpack
 
 router = APIRouter()
 
@@ -31,15 +27,15 @@ router = APIRouter()
 # # example: set_coord(p, ChangeSet({'node': 'j1', 'x': 1.0, 'y': 2.0}))
 # @router.post("/setcoord/", response_model=None)
 # async def fastapi_set_coord(network: str, req: Request) -> ChangeSet:
-#     props = await req.json()
+#     props = payload
 #     return set_coord(network, ChangeSet(props))
 
 @router.get(
-    "/getnodecoord/",
+    "/node-coords",
     summary="获取节点坐标",
     description="获取指定节点的地理坐标(X, Y)"
 )
-async def fastapi_get_node_coord(
+def fastapi_get_node_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     node: str = Query(..., description="节点ID")
 ) -> dict[str, float] | None:
@@ -48,11 +44,11 @@ async def fastapi_get_node_coord(
 
 # Additional geometry queries found in main.py logic (implicit or explicit)
 @router.get(
-    "/getnetworkinextent/",
+    "/network-in-extents",
     summary="获取范围内的网络元素",
     description="获取指定地理范围内的网络节点和管线"
 )
-async def fastapi_get_network_in_extent(
+def fastapi_get_network_in_extent(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     x1: float = Query(..., description="范围左下角X坐标", alias="x1"),
     y1: float = Query(..., description="范围左下角Y坐标", alias="y1"),
@@ -63,38 +59,11 @@ async def fastapi_get_network_in_extent(
     return get_network_in_extent(network, x1, y1, x2, y2)
 
 @router.get(
-    "/getnetworkgeometries/",
-    dependencies=[Depends(verify_token)],
-    summary="获取完整网络几何信息",
-    description="获取整个水网的所有节点、管线和SCADA点的几何信息(需要身份验证)"
-)
-async def fastapi_get_network_geometries(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, Any] | None:
-    """获取完整的网络几何信息，包括所有节点、管线和SCADA点。结果从缓存返回。"""
-    cache_key = f"getnetworkgeometries_{network}"
-    data = redis_client.get(cache_key)
-    if data:
-        loaded_dict = msgpack.unpackb(data, object_hook=decode_datetime)
-        return loaded_dict
-
-    coords = get_network_node_coords(network)
-    nodes = []
-    for node_id, coord in coords.items():
-        nodes.append(f"{node_id}:{coord['type']}:{coord['x']}:{coord['y']}")
-    links = get_network_link_nodes(network)
-    scadas = get_all_scada_info(network)
-
-    results = {"nodes": nodes, "links": links, "scadas": scadas}
-    redis_client.set(cache_key, msgpack.packb(results, default=encode_datetime))
-    return results
-
-@router.get(
-    "/getmajornodecoords/",
+    "/majornode-coords",
     summary="获取主要节点坐标",
     description="获取直径大于等于指定值的节点坐标"
 )
-async def fastapi_get_majornode_coords(
+def fastapi_get_majornode_coords(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     diameter: int = Query(..., description="最小直径(mm)", gt=0)
 ) -> dict[str, dict[str, float]]:
@@ -102,11 +71,11 @@ async def fastapi_get_majornode_coords(
     return get_major_node_coords(network, diameter)
 
 @router.get(
-    "/getmajorpipenodes/",
+    "/major-pipe-nodes",
     summary="获取主要管道节点",
     description="获取直径大于等于指定值的管道的节点ID"
 )
-async def fastapi_get_major_pipe_nodes(
+def fastapi_get_major_pipe_nodes(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     diameter: int = Query(..., description="最小直径(mm)", gt=0)
 ) -> list[str] | None:
@@ -114,11 +83,11 @@ async def fastapi_get_major_pipe_nodes(
     return get_major_pipe_nodes(network, diameter)
 
 @router.get(
-    "/getnetworklinknodes/",
+    "/network-link-nodes",
     summary="获取网络管线节点",
     description="获取指定水网所有管线的起点和终点节点"
 )
-async def fastapi_get_network_link_nodes(
+def fastapi_get_network_link_nodes(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[str] | None:
     """获取网络中所有管线的连接节点。"""

app/api/v1/endpoints/network/junctions.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_junction,
     delete_junction,
@@ -13,8 +13,8 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getjunctionschema", summary="获取节点架构", description="获取指定项目的节点属性架构和数据类型定义。")
-async def fast_get_junction_schema(
+@router.get("/network-schemas/junction", summary="获取节点架构", description="获取指定项目的节点属性架构和数据类型定义。")
+def fast_get_junction_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """
@@ -27,8 +27,8 @@ async def fast_get_junction_schema(
     """
     return get_junction_schema(network)
 
-@router.post("/addjunction/", response_model=None, summary="添加节点", description="在供水网络中添加新的节点，指定节点ID和空间坐标。")
-async def fastapi_add_junction(
+@router.post("/junctions", response_model=None, summary="添加节点", description="在供水网络中添加新的节点，指定节点ID和空间坐标。")
+def fastapi_add_junction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     x: float = Query(..., description="X 坐标"),
@@ -51,8 +51,8 @@ async def fastapi_add_junction(
     ps = {"id": junction, "x": x, "y": y, "elevation": z}
     return add_junction(network, ChangeSet(ps))
 
-@router.post("/deletejunction/", response_model=None, summary="删除节点", description="从供水网络中删除指定的节点。")
-async def fastapi_delete_junction(
+@router.delete("/junctions", response_model=None, summary="删除节点", description="从供水网络中删除指定的节点。")
+def fastapi_delete_junction(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> ChangeSet:
@@ -69,8 +69,8 @@ async def fastapi_delete_junction(
     ps = {"id": junction}
     return delete_junction(network, ChangeSet(ps))
 
-@router.get("/getjunctionelevation/", summary="获取节点标高", description="获取指定节点的标高（海拔高度）。")
-async def fastapi_get_junction_elevation(
+@router.get("/junctions/elevation", summary="获取节点标高", description="获取指定节点的标高（海拔高度）。")
+def fastapi_get_junction_elevation(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> float:
@@ -87,8 +87,8 @@ async def fastapi_get_junction_elevation(
     ps = get_junction(network, junction)
     return ps["elevation"]
 
-@router.get("/getjunctionx/", summary="获取节点 X 坐标", description="获取指定节点的 X 坐标值。")
-async def fastapi_get_junction_x(
+@router.get("/junctions/x", summary="获取节点 X 坐标", description="获取指定节点的 X 坐标值。")
+def fastapi_get_junction_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> float:
@@ -105,8 +105,8 @@ async def fastapi_get_junction_x(
     ps = get_junction(network, junction)
     return ps["x"]
 
-@router.get("/getjunctiony/", summary="获取节点 Y 坐标", description="获取指定节点的 Y 坐标值。")
-async def fastapi_get_junction_y(
+@router.get("/junctions/y", summary="获取节点 Y 坐标", description="获取指定节点的 Y 坐标值。")
+def fastapi_get_junction_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> float:
@@ -123,8 +123,8 @@ async def fastapi_get_junction_y(
     ps = get_junction(network, junction)
     return ps["y"]
 
-@router.get("/getjunctioncoord/", summary="获取节点坐标", description="获取指定节点的 X 和 Y 坐标。")
-async def fastapi_get_junction_coord(
+@router.get("/junctions/coord", summary="获取节点坐标", description="获取指定节点的 X 和 Y 坐标。")
+def fastapi_get_junction_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> dict[str, float]:
@@ -142,8 +142,8 @@ async def fastapi_get_junction_coord(
     coord = {"x": ps["x"], "y": ps["y"]}
     return coord
 
-@router.get("/getjunctiondemand/", summary="获取节点需水量", description="获取指定节点的需水量。")
-async def fastapi_get_junction_demand(
+@router.get("/junctions/demand", summary="获取节点需水量", description="获取指定节点的需水量。")
+def fastapi_get_junction_demand(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> float:
@@ -160,8 +160,8 @@ async def fastapi_get_junction_demand(
     ps = get_junction(network, junction)
     return ps["demand"]
 
-@router.get("/getjunctionpattern/", summary="获取节点需水模式", description="获取指定节点的需水模式标识。")
-async def fastapi_get_junction_pattern(
+@router.get("/junctions/pattern", summary="获取节点需水模式", description="获取指定节点的需水模式标识。")
+def fastapi_get_junction_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> str:
@@ -178,8 +178,8 @@ async def fastapi_get_junction_pattern(
     ps = get_junction(network, junction)
     return ps["pattern"]
 
-@router.post("/setjunctionelevation/", response_model=None, summary="设置节点标高", description="设置指定节点的标高值。")
-async def fastapi_set_junction_elevation(
+@router.patch("/junctions/elevation", response_model=None, summary="设置节点标高", description="设置指定节点的标高值。")
+def fastapi_set_junction_elevation(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     elevation: float = Query(..., description="标高（海拔高度）")
@@ -198,8 +198,8 @@ async def fastapi_set_junction_elevation(
     ps = {"id": junction, "elevation": elevation}
     return set_junction(network, ChangeSet(ps))
 
-@router.post("/setjunctionx/", response_model=None, summary="设置节点 X 坐标", description="设置指定节点的 X 坐标值。")
-async def fastapi_set_junction_x(
+@router.patch("/junctions/x", response_model=None, summary="设置节点 X 坐标", description="设置指定节点的 X 坐标值。")
+def fastapi_set_junction_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     x: float = Query(..., description="X 坐标值")
@@ -218,8 +218,8 @@ async def fastapi_set_junction_x(
     ps = {"id": junction, "x": x}
     return set_junction(network, ChangeSet(ps))
 
-@router.post("/setjunctiony/", response_model=None, summary="设置节点 Y 坐标", description="设置指定节点的 Y 坐标值。")
-async def fastapi_set_junction_y(
+@router.patch("/junctions/y", response_model=None, summary="设置节点 Y 坐标", description="设置指定节点的 Y 坐标值。")
+def fastapi_set_junction_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     y: float = Query(..., description="Y 坐标值")
@@ -238,8 +238,8 @@ async def fastapi_set_junction_y(
     ps = {"id": junction, "y": y}
     return set_junction(network, ChangeSet(ps))
 
-@router.post("/setjunctioncoord/", response_model=None, summary="设置节点坐标", description="设置指定节点的 X 和 Y 坐标。")
-async def fastapi_set_junction_coord(
+@router.patch("/junctions/coord", response_model=None, summary="设置节点坐标", description="设置指定节点的 X 和 Y 坐标。")
+def fastapi_set_junction_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     x: float = Query(..., description="X 坐标值"),
@@ -260,8 +260,8 @@ async def fastapi_set_junction_coord(
     ps = {"id": junction, "x": x, "y": y}
     return set_junction(network, ChangeSet(ps))
 
-@router.post("/setjunctiondemand/", response_model=None, summary="设置节点需水量", description="设置指定节点的需水量。")
-async def fastapi_set_junction_demand(
+@router.patch("/junctions/demand", response_model=None, summary="设置节点需水量", description="设置指定节点的需水量。")
+def fastapi_set_junction_demand(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     demand: float = Query(..., description="需水量值")
@@ -280,8 +280,8 @@ async def fastapi_set_junction_demand(
     ps = {"id": junction, "demand": demand}
     return set_junction(network, ChangeSet(ps))
 
-@router.post("/setjunctionpattern/", response_model=None, summary="设置节点需水模式", description="设置指定节点的需水模式标识。")
-async def fastapi_set_junction_pattern(
+@router.patch("/junctions/pattern", response_model=None, summary="设置节点需水模式", description="设置指定节点的需水模式标识。")
+def fastapi_set_junction_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
     pattern: str = Query(..., description="需水模式标识")
@@ -300,8 +300,8 @@ async def fastapi_set_junction_pattern(
     ps = {"id": junction, "pattern": pattern}
     return set_junction(network, ChangeSet(ps))
 
-@router.get("/getjunctionproperties/", summary="获取节点属性", description="获取指定节点的所有属性信息。")
-async def fastapi_get_junction_properties(
+@router.get("/junctions/properties", summary="获取节点属性", description="获取指定节点的所有属性信息。")
+def fastapi_get_junction_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID")
 ) -> dict[str, Any]:
@@ -317,8 +317,8 @@ async def fastapi_get_junction_properties(
     """
     return get_junction(network, junction)
 
-@router.get("/getalljunctionproperties/", summary="获取所有节点属性", description="获取指定项目中所有节点的属性信息。")
-async def fastapi_get_all_junction_properties(
+@router.get("/junctions", summary="获取所有节点属性", description="获取指定项目中所有节点的属性信息。")
+def fastapi_get_all_junction_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -333,15 +333,14 @@ async def fastapi_get_all_junction_properties(
         list: 包含所有节点属性的列表
     """
     # 缓存查询结果提高性能
-    # global redis_client # Redis logic removed for clean split, can be re-added if needed or imported
     results = get_all_junctions(network)
     return results
 
-@router.post("/setjunctionproperties/", response_model=None, summary="批量设置节点属性", description="批量设置指定节点的多个属性。")
-async def fastapi_set_junction_properties(
+@router.patch("/junctions/properties", response_model=None, summary="批量设置节点属性", description="批量设置指定节点的多个属性。")
+def fastapi_set_junction_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     junction: str = Query(..., description="节点 ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     批量设置节点属性。
@@ -356,6 +355,6 @@ async def fastapi_set_junction_properties(
     Returns:
         ChangeSet: 包含变更信息的结果
     """
-    props = await req.json()
+    props = payload
     ps = {"id": junction} | props
     return set_junction(network, ChangeSet(ps))

app/api/v1/endpoints/network/pipes.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     PIPE_STATUS_OPEN,
     add_pipe,
@@ -14,8 +14,8 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getpipeschema", summary="获取管道模式", description="获取管道对象的模式定义，包含所有可用字段及其类型")
-async def fastapi_get_pipe_schema(
+@router.get("/network-schemas/pipe", summary="获取管道模式", description="获取管道对象的模式定义，包含所有可用字段及其类型")
+def fastapi_get_pipe_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """
@@ -29,8 +29,8 @@ async def fastapi_get_pipe_schema(
     """
     return get_pipe_schema(network)
 
-@router.post("/addpipe/", response_model=None, summary="添加管道", description="向网络中添加新的管道，需要提供管道的基本参数如长度、管径、粗糙度等")
-async def fastapi_add_pipe(
+@router.post("/pipes", response_model=None, summary="添加管道", description="向网络中添加新的管道，需要提供管道的基本参数如长度、管径、粗糙度等")
+def fastapi_add_pipe(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道标识符"),
     node1: str = Query(..., description="管道起始节点ID"),
@@ -70,8 +70,8 @@ async def fastapi_add_pipe(
     }
     return add_pipe(network, ChangeSet(ps))
 
-@router.post("/deletepipe/", response_model=None, summary="删除管道", description="从网络中删除指定的管道")
-async def fastapi_delete_pipe(
+@router.delete("/pipes", response_model=None, summary="删除管道", description="从网络中删除指定的管道")
+def fastapi_delete_pipe(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="要删除的管道ID")
 ) -> ChangeSet:
@@ -88,8 +88,8 @@ async def fastapi_delete_pipe(
     ps = {"id": pipe}
     return delete_pipe(network, ChangeSet(ps))
 
-@router.get("/getpipenode1/", summary="获取管道起始节点", description="获取指定管道的起始节点ID")
-async def fastapi_get_pipe_node1(
+@router.get("/pipes/node1", summary="获取管道起始节点", description="获取指定管道的起始节点ID")
+def fastapi_get_pipe_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> str | None:
@@ -106,8 +106,8 @@ async def fastapi_get_pipe_node1(
     ps = get_pipe(network, pipe)
     return ps["node1"]
 
-@router.get("/getpipenode2/", summary="获取管道终止节点", description="获取指定管道的终止节点ID")
-async def fastapi_get_pipe_node2(
+@router.get("/pipes/node2", summary="获取管道终止节点", description="获取指定管道的终止节点ID")
+def fastapi_get_pipe_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> str | None:
@@ -124,8 +124,8 @@ async def fastapi_get_pipe_node2(
     ps = get_pipe(network, pipe)
     return ps["node2"]
 
-@router.get("/getpipelength/", summary="获取管道长度", description="获取指定管道的长度")
-async def fastapi_get_pipe_length(
+@router.get("/pipes/length", summary="获取管道长度", description="获取指定管道的长度")
+def fastapi_get_pipe_length(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> float | None:
@@ -142,8 +142,8 @@ async def fastapi_get_pipe_length(
     ps = get_pipe(network, pipe)
     return ps["length"]
 
-@router.get("/getpipediameter/", summary="获取管道管径", description="获取指定管道的管径")
-async def fastapi_get_pipe_diameter(
+@router.get("/pipes/diameter", summary="获取管道管径", description="获取指定管道的管径")
+def fastapi_get_pipe_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> float | None:
@@ -160,8 +160,8 @@ async def fastapi_get_pipe_diameter(
     ps = get_pipe(network, pipe)
     return ps["diameter"]
 
-@router.get("/getpiperoughness/", summary="获取管道粗糙度", description="获取指定管道的粗糙度")
-async def fastapi_get_pipe_roughness(
+@router.get("/pipes/roughness", summary="获取管道粗糙度", description="获取指定管道的粗糙度")
+def fastapi_get_pipe_roughness(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> float | None:
@@ -178,8 +178,8 @@ async def fastapi_get_pipe_roughness(
     ps = get_pipe(network, pipe)
     return ps["roughness"]
 
-@router.get("/getpipeminorloss/", summary="获取管道局部阻力系数", description="获取指定管道的局部阻力系数")
-async def fastapi_get_pipe_minor_loss(
+@router.get("/pipes/minor-loss", summary="获取管道局部阻力系数", description="获取指定管道的局部阻力系数")
+def fastapi_get_pipe_minor_loss(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> float | None:
@@ -196,8 +196,8 @@ async def fastapi_get_pipe_minor_loss(
     ps = get_pipe(network, pipe)
     return ps["minor_loss"]
 
-@router.get("/getpipestatus/", summary="获取管道状态", description="获取指定管道的状态（开启或关闭）")
-async def fastapi_get_pipe_status(
+@router.get("/pipes/status", summary="获取管道状态", description="获取指定管道的状态（开启或关闭）")
+def fastapi_get_pipe_status(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> str | None:
@@ -214,8 +214,8 @@ async def fastapi_get_pipe_status(
     ps = get_pipe(network, pipe)
     return ps["status"]
 
-@router.post("/setpipenode1/", response_model=None, summary="设置管道起始节点", description="设置指定管道的起始节点")
-async def fastapi_set_pipe_node1(
+@router.patch("/pipes/node1", response_model=None, summary="设置管道起始节点", description="设置指定管道的起始节点")
+def fastapi_set_pipe_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     node1: str = Query(..., description="新的起始节点ID")
@@ -234,8 +234,8 @@ async def fastapi_set_pipe_node1(
     ps = {"id": pipe, "node1": node1}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpipenode2/", response_model=None, summary="设置管道终止节点", description="设置指定管道的终止节点")
-async def fastapi_set_pipe_node2(
+@router.patch("/pipes/node2", response_model=None, summary="设置管道终止节点", description="设置指定管道的终止节点")
+def fastapi_set_pipe_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     node2: str = Query(..., description="新的终止节点ID")
@@ -254,8 +254,8 @@ async def fastapi_set_pipe_node2(
     ps = {"id": pipe, "node2": node2}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpipelength/", response_model=None, summary="设置管道长度", description="设置指定管道的长度")
-async def fastapi_set_pipe_length(
+@router.patch("/pipes/length", response_model=None, summary="设置管道长度", description="设置指定管道的长度")
+def fastapi_set_pipe_length(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     length: float = Query(..., description="新的管道长度（单位：米）")
@@ -274,8 +274,8 @@ async def fastapi_set_pipe_length(
     ps = {"id": pipe, "length": length}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpipediameter/", response_model=None, summary="设置管道管径", description="设置指定管道的管径")
-async def fastapi_set_pipe_diameter(
+@router.patch("/pipes/diameter", response_model=None, summary="设置管道管径", description="设置指定管道的管径")
+def fastapi_set_pipe_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     diameter: float = Query(..., description="新的管道管径（单位：毫米）")
@@ -294,8 +294,8 @@ async def fastapi_set_pipe_diameter(
     ps = {"id": pipe, "diameter": diameter}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpiperoughness/", response_model=None, summary="设置管道粗糙度", description="设置指定管道的粗糙度")
-async def fastapi_set_pipe_roughness(
+@router.patch("/pipes/roughness", response_model=None, summary="设置管道粗糙度", description="设置指定管道的粗糙度")
+def fastapi_set_pipe_roughness(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     roughness: float = Query(..., description="新的管道粗糙度值")
@@ -314,8 +314,8 @@ async def fastapi_set_pipe_roughness(
     ps = {"id": pipe, "roughness": roughness}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpipeminorloss/", response_model=None, summary="设置管道局部阻力系数", description="设置指定管道的局部阻力系数")
-async def fastapi_set_pipe_minor_loss(
+@router.patch("/pipes/minor-loss", response_model=None, summary="设置管道局部阻力系数", description="设置指定管道的局部阻力系数")
+def fastapi_set_pipe_minor_loss(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     minor_loss: float = Query(..., description="新的局部阻力系数值")
@@ -334,8 +334,8 @@ async def fastapi_set_pipe_minor_loss(
     ps = {"id": pipe, "minor_loss": minor_loss}
     return set_pipe(network, ChangeSet(ps))
 
-@router.post("/setpipestatus/", response_model=None, summary="设置管道状态", description="设置指定管道的状态（开启或关闭）")
-async def fastapi_set_pipe_status(
+@router.patch("/pipes/status", response_model=None, summary="设置管道状态", description="设置指定管道的状态（开启或关闭）")
+def fastapi_set_pipe_status(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
     status: str = Query(..., description="新的管道状态（开启/关闭）")
@@ -354,8 +354,8 @@ async def fastapi_set_pipe_status(
     ps = {"id": pipe, "status": status}
     return set_pipe(network, ChangeSet(ps))
 
-@router.get("/getpipeproperties/", summary="获取管道属性", description="获取指定管道的所有属性信息")
-async def fastapi_get_pipe_properties(
+@router.get("/pipes/properties", summary="获取管道属性", description="获取指定管道的所有属性信息")
+def fastapi_get_pipe_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID")
 ) -> dict[str, Any]:
@@ -371,8 +371,8 @@ async def fastapi_get_pipe_properties(
     """
     return get_pipe(network, pipe)
 
-@router.get("/getallpipeproperties/", summary="获取所有管道属性", description="获取网络中所有管道的属性信息列表")
-async def fastapi_get_all_pipe_properties(
+@router.get("/pipes", summary="获取所有管道属性", description="获取网络中所有管道的属性信息列表")
+def fastapi_get_all_pipe_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -385,15 +385,14 @@ async def fastapi_get_all_pipe_properties(
         包含所有管道属性的字典列表
     """
     # 缓存查询结果提高性能
-    # global redis_client
     results = get_all_pipes(network)
     return results
 
-@router.post("/setpipeproperties/", response_model=None, summary="设置管道属性", description="批量设置指定管道的多个属性")
-async def fastapi_set_pipe_properties(
+@router.patch("/pipes/properties", response_model=None, summary="设置管道属性", description="批量设置指定管道的多个属性")
+def fastapi_set_pipe_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pipe: str = Query(..., description="管道ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     批量设置管道属性。
@@ -406,6 +405,6 @@ async def fastapi_set_pipe_properties(
     Returns:
         ChangeSet对象，包含本次修改的变更信息
     """
-    props = await req.json()
+    props = payload
     ps = {"id": pipe} | props
     return set_pipe(network, ChangeSet(ps))

app/api/v1/endpoints/network/pumps.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_pump,
     delete_pump,
@@ -13,8 +13,8 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/getpumpschema", summary="获取水泵模式", description="获取水泵对象的模式定义，包含所有可用字段及其类型")
-async def fastapi_get_pump_schema(
+@router.get("/network-schemas/pump", summary="获取水泵模式", description="获取水泵对象的模式定义，包含所有可用字段及其类型")
+def fastapi_get_pump_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """
@@ -28,8 +28,8 @@ async def fastapi_get_pump_schema(
     """
     return get_pump_schema(network)
 
-@router.post("/addpump/", response_model=None, summary="添加水泵", description="向网络中添加新的水泵，需要提供水泵的基本参数如功率等")
-async def fastapi_add_pump(
+@router.post("/pumps", response_model=None, summary="添加水泵", description="向网络中添加新的水泵，需要提供水泵的基本参数如功率等")
+def fastapi_add_pump(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵标识符"),
     node1: str = Query(..., description="水泵起始节点ID"),
@@ -52,8 +52,8 @@ async def fastapi_add_pump(
     ps = {"id": pump, "node1": node1, "node2": node2, "power": power}
     return add_pump(network, ChangeSet(ps))
 
-@router.post("/deletepump/", response_model=None, summary="删除水泵", description="从网络中删除指定的水泵")
-async def fastapi_delete_pump(
+@router.delete("/pumps", response_model=None, summary="删除水泵", description="从网络中删除指定的水泵")
+def fastapi_delete_pump(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="要删除的水泵ID")
 ) -> ChangeSet:
@@ -70,8 +70,8 @@ async def fastapi_delete_pump(
     ps = {"id": pump}
     return delete_pump(network, ChangeSet(ps))
 
-@router.get("/getpumpnode1/", summary="获取水泵起始节点", description="获取指定水泵的起始节点ID")
-async def fastapi_get_pump_node1(
+@router.get("/pumps/node1", summary="获取水泵起始节点", description="获取指定水泵的起始节点ID")
+def fastapi_get_pump_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID")
 ) -> str | None:
@@ -88,8 +88,8 @@ async def fastapi_get_pump_node1(
     ps = get_pump(network, pump)
     return ps["node1"]
 
-@router.get("/getpumpnode2/", summary="获取水泵终止节点", description="获取指定水泵的终止节点ID")
-async def fastapi_get_pump_node2(
+@router.get("/pumps/node2", summary="获取水泵终止节点", description="获取指定水泵的终止节点ID")
+def fastapi_get_pump_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID")
 ) -> str | None:
@@ -106,8 +106,8 @@ async def fastapi_get_pump_node2(
     ps = get_pump(network, pump)
     return ps["node2"]
 
-@router.post("/setpumpnode1/", response_model=None, summary="设置水泵起始节点", description="设置指定水泵的起始节点")
-async def fastapi_set_pump_node1(
+@router.patch("/pumps/node1", response_model=None, summary="设置水泵起始节点", description="设置指定水泵的起始节点")
+def fastapi_set_pump_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID"),
     node1: str = Query(..., description="新的起始节点ID")
@@ -126,8 +126,8 @@ async def fastapi_set_pump_node1(
     ps = {"id": pump, "node1": node1}
     return set_pump(network, ChangeSet(ps))
 
-@router.post("/setpumpnode2/", response_model=None, summary="设置水泵终止节点", description="设置指定水泵的终止节点")
-async def fastapi_set_pump_node2(
+@router.patch("/pumps/node2", response_model=None, summary="设置水泵终止节点", description="设置指定水泵的终止节点")
+def fastapi_set_pump_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID"),
     node2: str = Query(..., description="新的终止节点ID")
@@ -146,8 +146,8 @@ async def fastapi_set_pump_node2(
     ps = {"id": pump, "node2": node2}
     return set_pump(network, ChangeSet(ps))
 
-@router.get("/getpumpproperties/", summary="获取水泵属性", description="获取指定水泵的所有属性信息")
-async def fastapi_get_pump_properties(
+@router.get("/pumps/properties", summary="获取水泵属性", description="获取指定水泵的所有属性信息")
+def fastapi_get_pump_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID")
 ) -> dict[str, Any]:
@@ -163,8 +163,8 @@ async def fastapi_get_pump_properties(
     """
     return get_pump(network, pump)
 
-@router.get("/getallpumpproperties/", summary="获取所有水泵属性", description="获取网络中所有水泵的属性信息列表")
-async def fastapi_get_all_pump_properties(
+@router.get("/pumps", summary="获取所有水泵属性", description="获取网络中所有水泵的属性信息列表")
+def fastapi_get_all_pump_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -177,15 +177,14 @@ async def fastapi_get_all_pump_properties(
         包含所有水泵属性的字典列表
     """
     # 缓存查询结果提高性能
-    # global redis_client
     results = get_all_pumps(network)
     return results
 
-@router.post("/setpumpproperties/", response_model=None, summary="设置水泵属性", description="批量设置指定水泵的多个属性")
-async def fastapi_set_pump_properties(
+@router.patch("/pumps/properties", response_model=None, summary="设置水泵属性", description="批量设置指定水泵的多个属性")
+def fastapi_set_pump_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     pump: str = Query(..., description="水泵ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     批量设置水泵属性。
@@ -198,6 +197,6 @@ async def fastapi_set_pump_properties(
     Returns:
         ChangeSet对象，包含本次修改的变更信息
     """
-    props = await req.json()
+    props = payload
     ps = {"id": pump} | props
     return set_pump(network, ChangeSet(ps))

app/api/v1/endpoints/network/regions.py

@@ -1,602 +1,72 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
+
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
-    add_district_metering_area,
     add_region,
-    add_service_area,
-    add_virtual_district,
-    # calculate_district_metering_area,
-    calculate_district_metering_area_for_network,
-    calculate_district_metering_area_for_nodes,
-    calculate_district_metering_area_for_region,
-    # calculate_region,
-    calculate_service_area,
-    calculate_virtual_district,
-    delete_district_metering_area,
     delete_region,
-    delete_service_area,
-    delete_virtual_district,
-    generate_district_metering_area,
-    # generate_region,
-    generate_service_area,
-    generate_sub_district_metering_area,
-    generate_virtual_district,
-    get_all_district_metering_area_ids,
-    get_all_district_metering_areas,
-    # get_all_regions,
-    get_all_service_areas,
-    get_all_virtual_districts,
-    get_district_metering_area,
-    get_district_metering_area_schema,
+    get_nodes_in_region,
     get_region,
     get_region_schema,
-    get_service_area,
-    get_service_area_schema,
-    get_virtual_district,
-    get_virtual_district_schema,
-    set_district_metering_area,
+    get_regions,
     set_region,
-    set_service_area,
-    set_virtual_district,
 )
 
+
 router = APIRouter()
 
-############################################################
-# region 32
-############################################################
 
-@router.get(
-    "/calculateregion/",
-    summary="计算区域",
-    description="计算指定水网在指定时间步长的区域分区"
-)
-async def fastapi_calculate_region(
+@router.get("/network-schemas/region", summary="获取区域属性架构")
+def get_region_schema_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    time_index: int = Query(..., description="时间步长索引", ge=0)
-) -> dict[str, Any]:
-    """计算区域分区。"""
-    return calculate_region(network, time_index)
-
-@router.get(
-    "/getregionschema/",
-    summary="获取区域属性架构",
-    description="获取指定水网的区域属性架构定义"
-)
-async def fastapi_get_region_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
-    """获取区域的属性架构。"""
     return get_region_schema(network)
 
-@router.get(
-    "/getregion/",
-    summary="获取区域信息",
-    description="获取指定ID的区域详细信息"
-)
-async def fastapi_get_region(
+
+@router.get("/regions", summary="获取区域列表")
+def get_regions_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="区域ID")
+) -> list[dict[str, Any]]:
+    return [get_region(network, region_id) for region_id in get_regions(network)]
+
+
+@router.get("/regions/detail", summary="获取区域信息")
+def get_region_endpoint(
+    network: str = Query(..., description="管网名称（或数据库名称）"),
+    id: str = Query(..., description="区域 ID"),
 ) -> dict[str, Any]:
-    """获取区域的详细信息。"""
     return get_region(network, id)
 
-@router.post(
-    "/setregion/",
-    response_model=None,
-    summary="设置区域属性",
-    description="修改指定区域的属性信息"
-)
-async def fastapi_set_region(
+
+@router.get("/regions/nodes", summary="获取区域节点")
+def get_region_nodes_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """设置区域属性。"""
-    props = await req.json()
-    return set_region(network, ChangeSet(props))
-
-@router.post(
-    "/addregion/",
-    response_model=None,
-    summary="添加新区域",
-    description="向水网添加一个新的区域"
-)
-async def fastapi_add_region(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """添加新的区域。"""
-    props = await req.json()
-    return add_region(network, ChangeSet(props))
-
-@router.post(
-    "/deleteregion/",
-    response_model=None,
-    summary="删除区域",
-    description="删除指定的区域"
-)
-async def fastapi_delete_region(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """删除区域。"""
-    props = await req.json()
-    return delete_region(network, ChangeSet(props))
-
-@router.get(
-    "/getallregions/",
-    summary="获取所有区域",
-    description="获取指定水网中的所有区域信息"
-)
-async def fastapi_get_all_regions(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """获取所有区域的信息列表。"""
-    return get_all_regions(network)
-
-@router.post(
-    "/generateregion/",
-    response_model=None,
-    summary="生成区域分区",
-    description="根据参数自动生成水网的区域分区"
-)
-async def fastapi_generate_region(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inflate_delta: float = Query(..., description="膨胀参数")
-) -> ChangeSet:
-    """生成区域分区。"""
-    return generate_region(network, inflate_delta)
-
-
-############################################################
-# district_metering_area 33
-############################################################
-
-@router.get(
-    "/calculatedistrictmeteringarea/",
-    summary="计算DMA分区",
-    description="计算指定节点集的区域计量(DMA)分区方案"
-)
-async def fastapi_calculate_district_metering_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> list[list[str]]:
-    """
-    计算DMA分区。
-    
-    请求体格式:
-    {
-        "nodes": 节点ID列表(list[str]),
-        "part_count": 分区数量(int),
-        "part_type": 分区类型(int)
-    }
-    """
-    props = await req.json()
-    nodes = props["nodes"]
-    part_count = props["part_count"]
-    part_type = props["part_type"]
-    return calculate_district_metering_area(
-        network, nodes, part_count, part_type
-    )
-
-@router.get(
-    "/calculatedistrictmeteringareaforregion/",
-    summary="计算区域内DMA分区",
-    description="为指定区域计算区域计量(DMA)分区方案"
-)
-async def fastapi_calculate_district_metering_area_for_region(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> list[list[str]]:
-    """
-    计算区域内DMA分区。
-    
-    请求体格式:
-    {
-        "region": 区域ID(str),
-        "part_count": 分区数量(int),
-        "part_type": 分区类型(int)
-    }
-    """
-    props = await req.json()
-    region = props["region"]
-    part_count = props["part_count"]
-    part_type = props["part_type"]
-    return calculate_district_metering_area_for_region(
-        network, region, part_count, part_type
-    )
-
-@router.get(
-    "/calculatedistrictmeteringareafornetwork/",
-    summary="计算整网DMA分区",
-    description="为整个水网计算区域计量(DMA)分区方案"
-)
-async def fastapi_calculate_district_metering_area_for_network(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> list[list[str]]:
-    """
-    计算整网DMA分区。
-    
-    请求体格式:
-    {
-        "part_count": 分区数量(int),
-        "part_type": 分区类型(int)
-    }
-    """
-    props = await req.json()
-    part_count = props["part_count"]
-    part_type = props["part_type"]
-    return calculate_district_metering_area_for_network(network, part_count, part_type)
-
-@router.get(
-    "/getdistrictmeteringareaschema/",
-    summary="获取DMA属性架构",
-    description="获取指定水网的区域计量(DMA)属性架构定义"
-)
-async def fastapi_get_district_metering_area_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-) -> dict[str, dict[str, Any]]:
-    """获取DMA的属性架构。"""
-    return get_district_metering_area_schema(network)
-
-@router.get(
-    "/getdistrictmeteringarea/",
-    summary="获取DMA信息",
-    description="获取指定ID的区域计量(DMA)详细信息"
-)
-async def fastapi_get_district_metering_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="DMA ID")
-) -> dict[str, Any]:
-    """获取DMA的详细信息。"""
-    return get_district_metering_area(network, id)
-
-@router.post(
-    "/setdistrictmeteringarea/",
-    response_model=None,
-    summary="设置DMA属性",
-    description="修改指定DMA的属性信息"
-)
-async def fastapi_set_district_metering_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """设置DMA属性。"""
-    props = await req.json()
-    return set_district_metering_area(network, ChangeSet(props))
-
-@router.post(
-    "/adddistrictmeteringarea/",
-    response_model=None,
-    summary="添加新DMA",
-    description="向水网添加一个新的区域计量(DMA)"
-)
-async def fastapi_add_district_metering_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """添加新的DMA。"""
-    props = await req.json()
-    # boundary should be [(x,y), (x,y)]
-    boundary = props.get("boundary", [])
-    newBoundary = []
-    for pt in boundary:
-        if len(pt) >= 2:
-            newBoundary.append((pt[0], pt[1]))
-    props["boundary"] = newBoundary
-    return add_district_metering_area(network, ChangeSet(props))
-
-@router.post(
-    "/deletedistrictmeteringarea/",
-    response_model=None,
-    summary="删除DMA",
-    description="删除指定的区域计量(DMA)"
-)
-async def fastapi_delete_district_metering_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """删除DMA。"""
-    props = await req.json()
-    return delete_district_metering_area(network, ChangeSet(props))
-
-@router.get(
-    "/getalldistrictmeteringareaids/",
-    summary="获取所有DMA ID",
-    description="获取指定水网中所有DMA的ID列表"
-)
-async def fastapi_get_all_district_metering_area_ids(
-    network: str = Query(..., description="管网名称（或数据库名称）")
+    id: str = Query(..., description="区域 ID"),
 ) -> list[str]:
-    """获取所有DMA的ID列表。"""
-    return get_all_district_metering_area_ids(network)
+    return get_nodes_in_region(network, id)
 
-@router.get(
-    "/getalldistrictmeteringareas/",
-    summary="获取所有DMA",
-    description="获取指定水网中所有DMA的详细信息"
-)
-async def getalldistrictmeteringareas(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """获取所有DMA的详细信息列表。"""
-    return get_all_district_metering_areas(network)
 
-@router.post(
-    "/generatedistrictmeteringarea/",
-    response_model=None,
-    summary="生成DMA分区",
-    description="根据参数自动生成水网的DMA分区方案"
-)
-async def fastapi_generate_district_metering_area(
+@router.patch("/regions", summary="修改区域", response_model=None)
+def set_region_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    part_count: int = Query(..., description="分区数量", gt=0),
-    part_type: int = Query(..., description="分区类型"),
-    inflate_delta: float = Query(..., description="膨胀参数")
+    payload: dict[str, Any] = Body(...),
 ) -> ChangeSet:
-    """生成DMA分区。"""
-    return generate_district_metering_area(
-        network, part_count, part_type, inflate_delta
-    )
+    return set_region(network, ChangeSet(payload))
 
-@router.post(
-    "/generatesubdistrictmeteringarea/",
-    response_model=None,
-    summary="生成DMA子分区",
-    description="为指定DMA生成子DMA分区"
-)
-async def fastapi_generate_sub_district_metering_area(
+
+@router.post("/regions", summary="添加区域", response_model=None)
+def add_region_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    dma: str = Query(..., description="DMA ID"),
-    part_count: int = Query(..., description="分区数量", gt=0),
-    part_type: int = Query(..., description="分区类型"),
-    inflate_delta: float = Query(..., description="膨胀参数")
+    payload: dict[str, Any] = Body(...),
 ) -> ChangeSet:
-    """生成DMA子分区。"""
-    return generate_sub_district_metering_area(
-        network, dma, part_count, part_type, inflate_delta
-    )
+    payload["boundary"] = [tuple(point[:2]) for point in payload.get("boundary", [])]
+    return add_region(network, ChangeSet(payload))
 
 
-############################################################
-# service_area 34
-############################################################
-
-@router.get(
-    "/calculateservicearea/",
-    summary="计算服务区",
-    description="计算指定水网在指定时间步长的服务区分区"
-)
-async def fastapi_calculate_service_area(
+@router.delete("/regions", summary="删除区域", response_model=None)
+def delete_region_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    time_index: int = Query(..., description="时间步长索引", ge=0)
-) -> dict[str, Any]:
-    """计算服务区分区。"""
-    return calculate_service_area(network, time_index)
-
-@router.get(
-    "/getserviceareaschema/",
-    summary="获取服务区属性架构",
-    description="获取指定水网的服务区属性架构定义"
-)
-async def fastapi_get_service_area_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, dict[str, Any]]:
-    """获取服务区的属性架构。"""
-    return get_service_area_schema(network)
-
-@router.get(
-    "/getservicearea/",
-    summary="获取服务区信息",
-    description="获取指定ID的服务区详细信息"
-)
-async def fastapi_get_service_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="服务区ID")
-) -> dict[str, Any]:
-    """获取服务区的详细信息。"""
-    return get_service_area(network, id)
-
-@router.post(
-    "/setservicearea/",
-    response_model=None,
-    summary="设置服务区属性",
-    description="修改指定服务区的属性信息"
-)
-async def fastapi_set_service_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...),
 ) -> ChangeSet:
-    """设置服务区属性。"""
-    props = await req.json()
-    return set_service_area(network, ChangeSet(props))
-
-@router.post(
-    "/addservicearea/",
-    response_model=None,
-    summary="添加新服务区",
-    description="向水网添加一个新的服务区"
-)
-async def fastapi_add_service_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """添加新的服务区。"""
-    props = await req.json()
-    return add_service_area(network, ChangeSet(props))
-
-@router.post(
-    "/deleteservicearea/",
-    response_model=None,
-    summary="删除服务区",
-    description="删除指定的服务区"
-)
-async def fastapi_delete_service_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """删除服务区。"""
-    props = await req.json()
-    return delete_service_area(network, ChangeSet(props))
-
-@router.get(
-    "/getallserviceareas/",
-    summary="获取所有服务区",
-    description="获取指定水网中的所有服务区信息"
-)
-async def fastapi_get_all_service_areas(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """获取所有服务区的信息列表。"""
-    return get_all_service_areas(network)
-
-@router.post(
-    "/generateservicearea/",
-    response_model=None,
-    summary="生成服务区分区",
-    description="根据参数自动生成水网的服务区分区"
-)
-async def fastapi_generate_service_area(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inflate_delta: float = Query(..., description="膨胀参数")
-) -> ChangeSet:
-    """生成服务区分区。"""
-    return generate_service_area(network, inflate_delta)
-
-
-############################################################
-# virtual_district 35
-############################################################
-
-@router.get(
-    "/calculatevirtualdistrict/",
-    summary="计算虚拟分区",
-    description="根据指定的中心节点计算虚拟分区方案"
-)
-async def fastapi_calculate_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    centers: list[str] = Query(..., description="中心节点ID列表")
-) -> dict[str, list[Any]]:
-    """计算虚拟分区。"""
-    return calculate_virtual_district(network, centers)
-
-@router.get(
-    "/getvirtualdistrictschema/",
-    summary="获取虚拟分区属性架构",
-    description="获取指定水网的虚拟分区属性架构定义"
-)
-async def fastapi_get_virtual_district_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-) -> dict[str, dict[str, Any]]:
-    """获取虚拟分区的属性架构。"""
-    return get_virtual_district_schema(network)
-
-@router.get(
-    "/getvirtualdistrict/",
-    summary="获取虚拟分区信息",
-    description="获取指定ID的虚拟分区详细信息"
-)
-async def fastapi_get_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="虚拟分区ID")
-) -> dict[str, Any]:
-    """获取虚拟分区的详细信息。"""
-    return get_virtual_district(network, id)
-
-@router.post(
-    "/setvirtualdistrict/",
-    response_model=None,
-    summary="设置虚拟分区属性",
-    description="修改指定虚拟分区的属性信息"
-)
-async def fastapi_set_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """设置虚拟分区属性。"""
-    props = await req.json()
-    return set_virtual_district(network, ChangeSet(props))
-
-@router.post(
-    "/addvirtualdistrict/",
-    response_model=None,
-    summary="添加新虚拟分区",
-    description="向水网添加一个新的虚拟分区"
-)
-async def fastapi_add_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """添加新的虚拟分区。"""
-    props = await req.json()
-    return add_virtual_district(network, ChangeSet(props))
-
-@router.post(
-    "/deletevirtualdistrict/",
-    response_model=None,
-    summary="删除虚拟分区",
-    description="删除指定的虚拟分区"
-)
-async def fastapi_delete_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """删除虚拟分区。"""
-    props = await req.json()
-    return delete_virtual_district(network, ChangeSet(props))
-
-@router.get(
-    "/getallvirtualdistrict/",
-    summary="获取所有虚拟分区",
-    description="获取指定水网中的所有虚拟分区信息"
-)
-async def fastapi_get_all_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """获取所有虚拟分区的信息列表。"""
-    return get_all_virtual_districts(network)
-
-@router.post(
-    "/generatevirtualdistrict/",
-    response_model=None,
-    summary="生成虚拟分区",
-    description="根据参数自动生成虚拟分区方案"
-)
-async def fastapi_generate_virtual_district(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inflate_delta: float = Query(..., description="膨胀参数"),
-    req: Request = None
-) -> ChangeSet:
-    """生成虚拟分区。"""
-    props = await req.json()
-    return generate_virtual_district(network, props["centers"], inflate_delta)
-
-@router.get(
-    "/calculatedistrictmeteringareafornodes/",
-    summary="计算节点DMA分区",
-    description="为指定节点集计算区域计量(DMA)分区方案"
-)
-async def fastapi_calculate_district_metering_area_for_nodes(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> list[list[str]]:
-    """
-    计算节点DMA分区。
-    
-    请求体格式:
-    {
-        "nodes": 节点ID列表(list[str]),
-        "part_count": 分区数量(int),
-        "part_type": 分区类型(int)
-    }
-    """
-    props = await req.json()
-    nodes = props["nodes"]
-    part_count = props["part_count"]
-    part_type = props["part_type"]
-    return calculate_district_metering_area_for_nodes(
-        network, nodes, part_count, part_type
-    )
+    return delete_region(network, ChangeSet(payload))

app/api/v1/endpoints/network/reservoirs.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_reservoir,
     delete_reservoir,
@@ -14,11 +14,11 @@ from app.services.tjnetwork import (
 router = APIRouter()
 
 @router.get(
-    "/getreservoirschema",
+    "/network-schemas/reservoir",
     summary="获取水库模式",
     description="获取指定供水网络中所有水库的模式/属性字段定义"
 )
-async def fast_get_reservoir_schema(
+def fast_get_reservoir_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """
@@ -35,12 +35,12 @@ async def fast_get_reservoir_schema(
     return get_reservoir_schema(network)
 
 @router.post(
-    "/addreservoir/",
+    "/reservoirs",
     response_model=None,
     summary="添加水库",
     description="在指定供水网络中添加新的水库/水源节点"
 )
-async def fastapi_add_reservoir(
+def fastapi_add_reservoir(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     x: float = Query(..., description="水库的X坐标"),
@@ -65,13 +65,13 @@ async def fastapi_add_reservoir(
     ps = {"id": reservoir, "x": x, "y": y, "head": head}
     return add_reservoir(network, ChangeSet(ps))
 
-@router.post(
-    "/deletereservoir/",
+@router.delete(
+    "/reservoirs",
     response_model=None,
     summary="删除水库",
     description="从指定供水网络中删除指定的水库/水源节点"
 )
-async def fastapi_delete_reservoir(
+def fastapi_delete_reservoir(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="要删除的水库的唯一标识符")
 ) -> ChangeSet:
@@ -91,11 +91,11 @@ async def fastapi_delete_reservoir(
     return delete_reservoir(network, ChangeSet(ps))
 
 @router.get(
-    "/getreservoirhead/",
+    "/reservoirs/head",
     summary="获取水库水头",
     description="获取指定水库的供水水头/总水头值"
 )
-async def fastapi_get_reservoir_head(
+def fastapi_get_reservoir_head(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> float | None:
@@ -115,11 +115,11 @@ async def fastapi_get_reservoir_head(
     return ps["head"]
 
 @router.get(
-    "/getreservoirpattern/",
+    "/reservoirs/pattern",
     summary="获取水库模式",
     description="获取指定水库的运行模式/供水模式"
 )
-async def fastapi_get_reservoir_pattern(
+def fastapi_get_reservoir_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> str | None:
@@ -139,11 +139,11 @@ async def fastapi_get_reservoir_pattern(
     return ps["pattern"]
 
 @router.get(
-    "/getreservoirx/",
+    "/reservoirs/x",
     summary="获取水库X坐标",
     description="获取指定水库的X坐标位置"
 )
-async def fastapi_get_reservoir_x(
+def fastapi_get_reservoir_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> dict[str, float] | None:
@@ -163,11 +163,11 @@ async def fastapi_get_reservoir_x(
     return ps["x"]
 
 @router.get(
-    "/getreservoiry/",
+    "/reservoirs/y",
     summary="获取水库Y坐标",
     description="获取指定水库的Y坐标位置"
 )
-async def fastapi_get_reservoir_y(
+def fastapi_get_reservoir_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> dict[str, float] | None:
@@ -187,11 +187,11 @@ async def fastapi_get_reservoir_y(
     return ps["y"]
 
 @router.get(
-    "/getreservoircoord/",
+    "/reservoirs/coord",
     summary="获取水库坐标",
     description="获取指定水库的平面坐标（X和Y坐标）"
 )
-async def fastapi_get_reservoir_coord(
+def fastapi_get_reservoir_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> dict[str, float] | None:
@@ -211,13 +211,13 @@ async def fastapi_get_reservoir_coord(
     coord = {"id": reservoir, "x": ps["x"], "y": ps["y"]}
     return coord
 
-@router.post(
-    "/setreservoirhead/",
+@router.patch(
+    "/reservoirs/head",
     response_model=None,
     summary="设置水库水头",
     description="更新指定水库的供水水头/总水头值"
 )
-async def fastapi_set_reservoir_head(
+def fastapi_set_reservoir_head(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     head: float = Query(..., description="新的水头值（米）")
@@ -238,13 +238,13 @@ async def fastapi_set_reservoir_head(
     ps = {"id": reservoir, "head": head}
     return set_reservoir(network, ChangeSet(ps))
 
-@router.post(
-    "/setreservoirpattern/",
+@router.patch(
+    "/reservoirs/pattern",
     response_model=None,
     summary="设置水库模式",
     description="更新指定水库的运行模式/供水模式"
 )
-async def fastapi_set_reservoir_pattern(
+def fastapi_set_reservoir_pattern(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     pattern: str = Query(..., description="新的运行模式")
@@ -265,13 +265,13 @@ async def fastapi_set_reservoir_pattern(
     ps = {"id": reservoir, "pattern": pattern}
     return set_reservoir(network, ChangeSet(ps))
 
-@router.post(
-    "/setreservoirx/",
+@router.patch(
+    "/reservoirs/x",
     response_model=None,
     summary="设置水库X坐标",
     description="更新指定水库的X坐标位置"
 )
-async def fastapi_set_reservoir_x(
+def fastapi_set_reservoir_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     x: float = Query(..., description="新的X坐标值")
@@ -292,13 +292,13 @@ async def fastapi_set_reservoir_x(
     ps = {"id": reservoir, "x": x}
     return set_reservoir(network, ChangeSet(ps))
 
-@router.post(
-    "/setreservoiry/",
+@router.patch(
+    "/reservoirs/y",
     response_model=None,
     summary="设置水库Y坐标",
     description="更新指定水库的Y坐标位置"
 )
-async def fastapi_set_reservoir_y(
+def fastapi_set_reservoir_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     y: float = Query(..., description="新的Y坐标值")
@@ -319,13 +319,13 @@ async def fastapi_set_reservoir_y(
     ps = {"id": reservoir, "y": y}
     return set_reservoir(network, ChangeSet(ps))
 
-@router.post(
-    "/setreservoircoord/",
+@router.patch(
+    "/reservoirs/coord",
     response_model=None,
     summary="设置水库坐标",
     description="更新指定水库的平面坐标（X和Y坐标）"
 )
-async def fastapi_set_reservoir_coord(
+def fastapi_set_reservoir_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
     x: float = Query(..., description="新的X坐标值"),
@@ -349,11 +349,11 @@ async def fastapi_set_reservoir_coord(
     return set_reservoir(network, ChangeSet(ps))
 
 @router.get(
-    "/getreservoirproperties/",
+    "/reservoirs/properties",
     summary="获取水库属性",
     description="获取指定水库的所有属性"
 )
-async def fastapi_get_reservoir_properties(
+def fastapi_get_reservoir_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符")
 ) -> dict[str, Any]:
@@ -372,11 +372,11 @@ async def fastapi_get_reservoir_properties(
     return get_reservoir(network, reservoir)
 
 @router.get(
-    "/getallreservoirproperties/",
+    "/reservoirs",
     summary="获取所有水库属性",
     description="获取指定供水网络中所有水库的属性"
 )
-async def fastapi_get_all_reservoir_properties(
+def fastapi_get_all_reservoir_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -393,16 +393,16 @@ async def fastapi_get_all_reservoir_properties(
     results = get_all_reservoirs(network)
     return results
 
-@router.post(
-    "/setreservoirproperties/",
+@router.patch(
+    "/reservoirs/properties",
     response_model=None,
     summary="设置水库属性",
     description="批量更新指定水库的多个属性"
 )
-async def fastapi_set_reservoir_properties(
+def fastapi_set_reservoir_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     reservoir: str = Query(..., description="水库的唯一标识符"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     设置水库的多个属性。
@@ -417,6 +417,6 @@ async def fastapi_set_reservoir_properties(
     Returns:
         包含操作变更集的ChangeSet对象
     """
-    props = await req.json()
+    props = payload
     ps = {"id": reservoir} | props
     return set_reservoir(network, ChangeSet(ps))

app/api/v1/endpoints/network/tags.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     get_tag,
     get_tag_schema,
@@ -16,22 +16,22 @@ router = APIRouter()
 ############################################################
 
 @router.get(
-    "/gettagschema/",
+    "/network-schemas/tag",
     summary="获取标签属性架构",
     description="获取指定水网的标签(Tag)属性架构定义"
 )
-async def fastapi_get_tag_schema(
+def fastapi_get_tag_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """获取标签的属性架构。"""
     return get_tag_schema(network)
 
 @router.get(
-    "/gettag/",
+    "/tags/detail",
     summary="获取标签信息",
     description="获取指定类型和ID的标签信息"
 )
-async def fastapi_get_tag(
+def fastapi_get_tag(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     t_type: str = Query(..., description="标签类型"),
     id: str = Query(..., description="元素ID")
@@ -40,27 +40,27 @@ async def fastapi_get_tag(
     return get_tag(network, t_type, id)
 
 @router.get(
-    "/gettags/",
+    "/tags",
     summary="获取所有标签",
     description="获取指定水网中的所有标签信息"
 )
-async def fastapi_get_tags(
+def fastapi_get_tags(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """获取水网中所有标签的列表。"""
     tags = get_tags(network)
     return tags
 
-@router.post(
-    "/settag/",
+@router.patch(
+    "/tags",
     response_model=None,
     summary="设置标签",
     description="为指定元素设置或修改标签信息"
 )
-async def fastapi_set_tag(
+def fastapi_set_tag(
     network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """设置标签信息。"""
-    props = await req.json()
+    props = payload
     return set_tag(network, ChangeSet(props))

app/api/v1/endpoints/network/tanks.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     add_tank,
     delete_tank,
@@ -13,8 +13,8 @@ from app.services.tjnetwork import (
 
 router = APIRouter()
 
-@router.get("/gettankschema", summary="获取水箱模式", description="获取指定网络的水箱数据结构模式定义")
-async def fast_get_tank_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
+@router.get("/network-schemas/tank", summary="获取水箱模式", description="获取指定网络的水箱数据结构模式定义")
+def fast_get_tank_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[str, Any]]:
     """
     获取水箱的数据结构模式。
     
@@ -26,8 +26,8 @@ async def fast_get_tank_schema(network: str = Query(..., description="管网名
     """
     return get_tank_schema(network)
 
-@router.post("/addtank/", summary="新增水箱", description="向指定网络中新增一个水箱", response_model=None)
-async def fastapi_add_tank(
+@router.post("/tanks", summary="新增水箱", description="向指定网络中新增一个水箱", response_model=None)
+def fastapi_add_tank(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     x: float = Query(..., description="X坐标"),
@@ -70,8 +70,8 @@ async def fastapi_add_tank(
     }
     return add_tank(network, ChangeSet(ps))
 
-@router.post("/deletetank/", summary="删除水箱", description="删除指定网络中的水箱", response_model=None)
-async def fastapi_delete_tank(
+@router.delete("/tanks", summary="删除水箱", description="删除指定网络中的水箱", response_model=None)
+def fastapi_delete_tank(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> ChangeSet:
@@ -88,8 +88,8 @@ async def fastapi_delete_tank(
     ps = {"id": tank}
     return delete_tank(network, ChangeSet(ps))
 
-@router.get("/gettankelevation/", summary="获取水箱标高", description="获取指定水箱的标高值")
-async def fastapi_get_tank_elevation(
+@router.get("/tanks/elevation", summary="获取水箱标高", description="获取指定水箱的标高值")
+def fastapi_get_tank_elevation(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -106,8 +106,8 @@ async def fastapi_get_tank_elevation(
     ps = get_tank(network, tank)
     return ps["elevation"]
 
-@router.get("/gettankinitlevel/", summary="获取水箱初始水位", description="获取指定水箱的初始水位值")
-async def fastapi_get_tank_init_level(
+@router.get("/tanks/init-level", summary="获取水箱初始水位", description="获取指定水箱的初始水位值")
+def fastapi_get_tank_init_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -124,8 +124,8 @@ async def fastapi_get_tank_init_level(
     ps = get_tank(network, tank)
     return ps["init_level"]
 
-@router.get("/gettankminlevel/", summary="获取水箱最小水位", description="获取指定水箱的最小水位值")
-async def fastapi_get_tank_min_level(
+@router.get("/tanks/min-level", summary="获取水箱最小水位", description="获取指定水箱的最小水位值")
+def fastapi_get_tank_min_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -142,8 +142,8 @@ async def fastapi_get_tank_min_level(
     ps = get_tank(network, tank)
     return ps["min_level"]
 
-@router.get("/gettankmaxlevel/", summary="获取水箱最大水位", description="获取指定水箱的最大水位值")
-async def fastapi_get_tank_max_level(
+@router.get("/tanks/max-level", summary="获取水箱最大水位", description="获取指定水箱的最大水位值")
+def fastapi_get_tank_max_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -160,8 +160,8 @@ async def fastapi_get_tank_max_level(
     ps = get_tank(network, tank)
     return ps["max_level"]
 
-@router.get("/gettankdiameter/", summary="获取水箱直径", description="获取指定水箱的直径值")
-async def fastapi_get_tank_diameter(
+@router.get("/tanks/diameter", summary="获取水箱直径", description="获取指定水箱的直径值")
+def fastapi_get_tank_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -178,8 +178,8 @@ async def fastapi_get_tank_diameter(
     ps = get_tank(network, tank)
     return ps["diameter"]
 
-@router.get("/gettankminvol/", summary="获取水箱最小体积", description="获取指定水箱的最小体积值")
-async def fastapi_get_tank_min_vol(
+@router.get("/tanks/min-vol", summary="获取水箱最小体积", description="获取指定水箱的最小体积值")
+def fastapi_get_tank_min_vol(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float | None:
@@ -196,8 +196,8 @@ async def fastapi_get_tank_min_vol(
     ps = get_tank(network, tank)
     return ps["min_vol"]
 
-@router.get("/gettankvolcurve/", summary="获取水箱容积曲线", description="获取指定水箱的容积曲线标识")
-async def fastapi_get_tank_vol_curve(
+@router.get("/tanks/vol-curve", summary="获取水箱容积曲线", description="获取指定水箱的容积曲线标识")
+def fastapi_get_tank_vol_curve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> str | None:
@@ -214,8 +214,8 @@ async def fastapi_get_tank_vol_curve(
     ps = get_tank(network, tank)
     return ps["vol_curve"]
 
-@router.get("/gettankoverflow/", summary="获取水箱溢流口", description="获取指定水箱的溢流口配置")
-async def fastapi_get_tank_overflow(
+@router.get("/tanks/overflow", summary="获取水箱溢流口", description="获取指定水箱的溢流口配置")
+def fastapi_get_tank_overflow(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> str | None:
@@ -232,8 +232,8 @@ async def fastapi_get_tank_overflow(
     ps = get_tank(network, tank)
     return ps["overflow"]
 
-@router.get("/gettankx/", summary="获取水箱X坐标", description="获取指定水箱的X坐标值")
-async def fastapi_get_tank_x(
+@router.get("/tanks/x", summary="获取水箱X坐标", description="获取指定水箱的X坐标值")
+def fastapi_get_tank_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float:
@@ -250,8 +250,8 @@ async def fastapi_get_tank_x(
     ps = get_tank(network, tank)
     return ps["x"]
 
-@router.get("/gettanky/", summary="获取水箱Y坐标", description="获取指定水箱的Y坐标值")
-async def fastapi_get_tank_y(
+@router.get("/tanks/y", summary="获取水箱Y坐标", description="获取指定水箱的Y坐标值")
+def fastapi_get_tank_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> float:
@@ -268,8 +268,8 @@ async def fastapi_get_tank_y(
     ps = get_tank(network, tank)
     return ps["y"]
 
-@router.get("/gettankcoord/", summary="获取水箱坐标", description="获取指定水箱的X和Y坐标")
-async def fastapi_get_tank_coord(
+@router.get("/tanks/coord", summary="获取水箱坐标", description="获取指定水箱的X和Y坐标")
+def fastapi_get_tank_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> dict[str, float]:
@@ -287,8 +287,8 @@ async def fastapi_get_tank_coord(
     coord = {"x": ps["x"], "y": ps["y"]}
     return coord
 
-@router.post("/settankelevation/", summary="设置水箱标高", description="设置指定水箱的标高值", response_model=None)
-async def fastapi_set_tank_elevation(
+@router.patch("/tanks/elevation", summary="设置水箱标高", description="设置指定水箱的标高值", response_model=None)
+def fastapi_set_tank_elevation(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     elevation: float = Query(..., description="新的标高值")
@@ -307,8 +307,8 @@ async def fastapi_set_tank_elevation(
     ps = {"id": tank, "elevation": elevation}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankinitlevel/", summary="设置水箱初始水位", description="设置指定水箱的初始水位值", response_model=None)
-async def fastapi_set_tank_init_level(
+@router.patch("/tanks/init-level", summary="设置水箱初始水位", description="设置指定水箱的初始水位值", response_model=None)
+def fastapi_set_tank_init_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     init_level: float = Query(..., description="新的初始水位值")
@@ -327,8 +327,8 @@ async def fastapi_set_tank_init_level(
     ps = {"id": tank, "init_level": init_level}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankminlevel/", summary="设置水箱最小水位", description="设置指定水箱的最小水位值", response_model=None)
-async def fastapi_set_tank_min_level(
+@router.patch("/tanks/min-level", summary="设置水箱最小水位", description="设置指定水箱的最小水位值", response_model=None)
+def fastapi_set_tank_min_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     min_level: float = Query(..., description="新的最小水位值")
@@ -347,8 +347,8 @@ async def fastapi_set_tank_min_level(
     ps = {"id": tank, "min_level": min_level}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankmaxlevel/", summary="设置水箱最大水位", description="设置指定水箱的最大水位值", response_model=None)
-async def fastapi_set_tank_max_level(
+@router.patch("/tanks/max-level", summary="设置水箱最大水位", description="设置指定水箱的最大水位值", response_model=None)
+def fastapi_set_tank_max_level(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     max_level: float = Query(..., description="新的最大水位值")
@@ -367,8 +367,8 @@ async def fastapi_set_tank_max_level(
     ps = {"id": tank, "max_level": max_level}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankdiameter/", summary="设置水箱直径", description="设置指定水箱的直径值", response_model=None)
-async def fastapi_set_tank_diameter(
+@router.patch("/tanks/diameter", summary="设置水箱直径", description="设置指定水箱的直径值", response_model=None)
+def fastapi_set_tank_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     diameter: float = Query(..., description="新的直径值")
@@ -387,8 +387,8 @@ async def fastapi_set_tank_diameter(
     ps = {"id": tank, "diameter": diameter}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankminvol/", summary="设置水箱最小体积", description="设置指定水箱的最小体积值", response_model=None)
-async def fastapi_set_tank_min_vol(
+@router.patch("/tanks/min-vol", summary="设置水箱最小体积", description="设置指定水箱的最小体积值", response_model=None)
+def fastapi_set_tank_min_vol(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     min_vol: float = Query(..., description="新的最小体积值")
@@ -407,8 +407,8 @@ async def fastapi_set_tank_min_vol(
     ps = {"id": tank, "min_vol": min_vol}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankvolcurve/", summary="设置水箱容积曲线", description="设置指定水箱的容积曲线标识", response_model=None)
-async def fastapi_set_tank_vol_curve(
+@router.patch("/tanks/vol-curve", summary="设置水箱容积曲线", description="设置指定水箱的容积曲线标识", response_model=None)
+def fastapi_set_tank_vol_curve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     vol_curve: str = Query(..., description="新的容积曲线标识")
@@ -427,8 +427,8 @@ async def fastapi_set_tank_vol_curve(
     ps = {"id": tank, "vol_curve": vol_curve}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankoverflow/", summary="设置水箱溢流口", description="设置指定水箱的溢流口配置", response_model=None)
-async def fastapi_set_tank_overflow(
+@router.patch("/tanks/overflow", summary="设置水箱溢流口", description="设置指定水箱的溢流口配置", response_model=None)
+def fastapi_set_tank_overflow(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     overflow: str = Query(..., description="新的溢流口配置")
@@ -447,8 +447,8 @@ async def fastapi_set_tank_overflow(
     ps = {"id": tank, "overflow": overflow}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankx/", summary="设置水箱X坐标", description="设置指定水箱的X坐标值", response_model=None)
-async def fastapi_set_tank_x(
+@router.patch("/tanks/x", summary="设置水箱X坐标", description="设置指定水箱的X坐标值", response_model=None)
+def fastapi_set_tank_x(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     x: float = Query(..., description="新的X坐标值")
@@ -467,8 +467,8 @@ async def fastapi_set_tank_x(
     ps = {"id": tank, "x": x}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settanky/", summary="设置水箱Y坐标", description="设置指定水箱的Y坐标值", response_model=None)
-async def fastapi_set_tank_y(
+@router.patch("/tanks/y", summary="设置水箱Y坐标", description="设置指定水箱的Y坐标值", response_model=None)
+def fastapi_set_tank_y(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     y: float = Query(..., description="新的Y坐标值")
@@ -487,8 +487,8 @@ async def fastapi_set_tank_y(
     ps = {"id": tank, "y": y}
     return set_tank(network, ChangeSet(ps))
 
-@router.post("/settankcoord/", summary="设置水箱坐标", description="设置指定水箱的X和Y坐标", response_model=None)
-async def fastapi_set_tank_coord(
+@router.patch("/tanks/coord", summary="设置水箱坐标", description="设置指定水箱的X和Y坐标", response_model=None)
+def fastapi_set_tank_coord(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
     x: float = Query(..., description="新的X坐标值"),
@@ -509,8 +509,8 @@ async def fastapi_set_tank_coord(
     ps = {"id": tank, "x": x, "y": y}
     return set_tank(network, ChangeSet(ps))
 
-@router.get("/gettankproperties/", summary="获取水箱属性", description="获取指定水箱的所有属性")
-async def fastapi_get_tank_properties(
+@router.get("/tanks/properties", summary="获取水箱属性", description="获取指定水箱的所有属性")
+def fastapi_get_tank_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID")
 ) -> dict[str, Any]:
@@ -526,8 +526,8 @@ async def fastapi_get_tank_properties(
     """
     return get_tank(network, tank)
 
-@router.get("/getalltankproperties/", summary="获取所有水箱属性", description="获取指定网络中所有水箱的属性")
-async def fastapi_get_all_tank_properties(
+@router.get("/tanks", summary="获取所有水箱属性", description="获取指定网络中所有水箱的属性")
+def fastapi_get_all_tank_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -540,15 +540,14 @@ async def fastapi_get_all_tank_properties(
         包含所有水箱属性的字典列表
     """
     # 缓存查询结果提高性能
-    # global redis_client
     results = get_all_tanks(network)
     return results
 
-@router.post("/settankproperties/", summary="设置水箱属性", description="批量设置指定水箱的多个属性", response_model=None)
-async def fastapi_set_tank_properties(
+@router.patch("/tanks/properties", summary="设置水箱属性", description="批量设置指定水箱的多个属性", response_model=None)
+def fastapi_set_tank_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     tank: str = Query(..., description="水箱ID"),
-    req: Request = None
+    payload: dict[str, Any] = Body(...)
 ) -> ChangeSet:
     """
     批量设置水箱的属性。
@@ -561,6 +560,6 @@ async def fastapi_set_tank_properties(
     Returns:
         包含变更信息的ChangeSet对象
     """
-    props = await req.json()
+    props = payload
     ps = {"id": tank} | props
     return set_tank(network, ChangeSet(ps))

app/api/v1/endpoints/network/valves.py

@@ -1,7 +1,7 @@
-from fastapi import APIRouter, Request, Query, Path, Body
-from typing import Any, List, Dict, Union
+from typing import Any
+
+from fastapi import APIRouter, Body, Query
 from app.services.tjnetwork import (
-    Any,
     ChangeSet,
     VALVES_TYPE_PRV,
     add_valve,
@@ -15,11 +15,11 @@ from app.services.tjnetwork import (
 router = APIRouter()
 
 @router.get(
-    "/getvalveschema",
+    "/network-schemas/valve",
     summary="获取阀门架构",
     description="获取指定水网中所有阀门的架构和字段定义",
 )
-async def fastapi_get_valve_schema(
+def fastapi_get_valve_schema(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> dict[str, dict[str, Any]]:
     """
@@ -30,12 +30,12 @@ async def fastapi_get_valve_schema(
     return get_valve_schema(network)
 
 @router.post(
-    "/addvalve/",
+    "/valves",
     response_model=None,
     summary="添加阀门",
     description="在指定的水网中添加新的阀门",
 )
-async def fastapi_add_valve(
+def fastapi_add_valve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     node1: str = Query(..., description="起点节点ID"),
@@ -62,13 +62,13 @@ async def fastapi_add_valve(
 
     return add_valve(network, ChangeSet(ps))
 
-@router.post(
-    "/deletevalve/",
+@router.delete(
+    "/valves",
     response_model=None,
     summary="删除阀门",
     description="从指定的水网中删除指定的阀门",
 )
-async def fastapi_delete_valve(
+def fastapi_delete_valve(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> ChangeSet:
@@ -81,11 +81,11 @@ async def fastapi_delete_valve(
     return delete_valve(network, ChangeSet(ps))
 
 @router.get(
-    "/getvalvenode1/",
+    "/valves/node1",
     summary="获取阀门起点节点",
     description="获取指定阀门连接的起点节点ID",
 )
-async def fastapi_get_valve_node1(
+def fastapi_get_valve_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> str | None:
@@ -98,11 +98,11 @@ async def fastapi_get_valve_node1(
     return ps["node1"]
 
 @router.get(
-    "/getvalvenode2/",
+    "/valves/node2",
     summary="获取阀门终点节点",
     description="获取指定阀门连接的终点节点ID",
 )
-async def fastapi_get_valve_node2(
+def fastapi_get_valve_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> str | None:
@@ -115,11 +115,11 @@ async def fastapi_get_valve_node2(
     return ps["node2"]
 
 @router.get(
-    "/getvalvediameter/",
+    "/valves/diameter",
     summary="获取阀门直径",
     description="获取指定阀门的直径",
 )
-async def fastapi_get_valve_diameter(
+def fastapi_get_valve_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> float | None:
@@ -132,11 +132,11 @@ async def fastapi_get_valve_diameter(
     return ps["diameter"]
 
 @router.get(
-    "/getvalvetype/",
+    "/valves/type",
     summary="获取阀门类型",
     description="获取指定阀门的类型",
 )
-async def fastapi_get_valve_type(
+def fastapi_get_valve_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> str | None:
@@ -149,11 +149,11 @@ async def fastapi_get_valve_type(
     return ps["type"]
 
 @router.get(
-    "/getvalvesetting/",
+    "/valves/setting",
     summary="获取阀门开度",
     description="获取指定阀门的开度/设置值",
 )
-async def fastapi_get_valve_setting(
+def fastapi_get_valve_setting(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> float | None:
@@ -166,11 +166,11 @@ async def fastapi_get_valve_setting(
     return ps["setting"]
 
 @router.get(
-    "/getvalveminorloss/",
+    "/valves/minor-loss",
     summary="获取阀门损失系数",
     description="获取指定阀门的损失系数",
 )
-async def fastapi_get_valve_minor_loss(
+def fastapi_get_valve_minor_loss(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> float | None:
@@ -182,13 +182,13 @@ async def fastapi_get_valve_minor_loss(
     ps = get_valve(network, valve)
     return ps["minor_loss"]
 
-@router.post(
-    "/setvalvenode1/",
+@router.patch(
+    "/valves/node1",
     response_model=None,
     summary="设置阀门起点节点",
     description="设置指定阀门的起点节点",
 )
-async def fastapi_set_valve_node1(
+def fastapi_set_valve_node1(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     node1: str = Query(..., description="新的起点节点ID"),
@@ -201,13 +201,13 @@ async def fastapi_set_valve_node1(
     ps = {"id": valve, "node1": node1}
     return set_valve(network, ChangeSet(ps))
 
-@router.post(
-    "/setvalvenode2/",
+@router.patch(
+    "/valves/node2",
     response_model=None,
     summary="设置阀门终点节点",
     description="设置指定阀门的终点节点",
 )
-async def fastapi_set_valve_node2(
+def fastapi_set_valve_node2(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     node2: str = Query(..., description="新的终点节点ID"),
@@ -220,13 +220,13 @@ async def fastapi_set_valve_node2(
     ps = {"id": valve, "node2": node2}
     return set_valve(network, ChangeSet(ps))
 
-@router.post(
-    "/setvalvenodediameter/",
+@router.patch(
+    "/valves/diameter",
     response_model=None,
     summary="设置阀门直径",
     description="设置指定阀门的直径",
 )
-async def fastapi_set_valve_diameter(
+def fastapi_set_valve_diameter(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     diameter: float = Query(..., description="新的直径值（mm）"),
@@ -239,13 +239,13 @@ async def fastapi_set_valve_diameter(
     ps = {"id": valve, "diameter": diameter}
     return set_valve(network, ChangeSet(ps))
 
-@router.post(
-    "/setvalvetype/",
+@router.patch(
+    "/valves/type",
     response_model=None,
     summary="设置阀门类型",
     description="设置指定阀门的类型",
 )
-async def fastapi_set_valve_type(
+def fastapi_set_valve_type(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     type: str = Query(..., description="新的阀门类型"),
@@ -258,13 +258,13 @@ async def fastapi_set_valve_type(
     ps = {"id": valve, "type": type}
     return set_valve(network, ChangeSet(ps))
 
-@router.post(
-    "/setvalvesetting/",
+@router.patch(
+    "/valves/setting",
     response_model=None,
     summary="设置阀门开度",
     description="设置指定阀门的开度/设置值",
 )
-async def fastapi_set_valve_setting(
+def fastapi_set_valve_setting(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
     setting: float = Query(..., description="新的开度值"),
@@ -278,11 +278,11 @@ async def fastapi_set_valve_setting(
     return set_valve(network, ChangeSet(ps))
 
 @router.get(
-    "/getvalveproperties/",
+    "/valves/properties",
     summary="获取阀门所有属性",
     description="获取指定阀门的所有属性",
 )
-async def fastapi_get_valve_properties(
+def fastapi_get_valve_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
 ) -> dict[str, Any]:
@@ -294,11 +294,11 @@ async def fastapi_get_valve_properties(
     return get_valve(network, valve)
 
 @router.get(
-    "/getallvalveproperties/",
+    "/valves",
     summary="获取所有阀门属性",
     description="获取指定水网中所有阀门的属性",
 )
-async def fastapi_get_all_valve_properties(
+def fastapi_get_all_valve_properties(
     network: str = Query(..., description="管网名称（或数据库名称）")
 ) -> list[dict[str, Any]]:
     """
@@ -307,26 +307,25 @@ async def fastapi_get_all_valve_properties(
     返回指定水网中所有阀门的完整属性列表。
     """
     # 缓存查询结果提高性能
-    # global redis_client
     results = get_all_valves(network)
     return results
 
-@router.post(
-    "/setvalveproperties/",
+@router.patch(
+    "/valves/properties",
     response_model=None,
     summary="批量设置阀门属性",
     description="批量设置指定阀门的多个属性",
 )
-async def fastapi_set_valve_properties(
+def fastapi_set_valve_properties(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     valve: str = Query(..., description="阀门ID"),
-    req: Request = None,
+    payload: dict[str, Any] = Body(...),
 ) -> ChangeSet:
     """
     批量设置阀门的属性。
     
     更新指定阀门的一个或多个属性，通过JSON请求体传递要更新的属性。
     """
-    props = await req.json()
+    props = payload
     ps = {"id": valve} | props
     return set_valve(network, ChangeSet(ps))

app/api/v1/endpoints/project.py

@@ -1,48 +1,20 @@
 import json
-from fastapi import APIRouter, Request, HTTPException, Query, Path, Body, Depends
-from fastapi.responses import PlainTextResponse
-from typing import Any, Dict, List
+from fastapi import APIRouter, HTTPException, Query, Depends
 from app.infra.db.metadb.repositories.metadata_repository import MetadataRepository
-from app.auth.project_dependencies import get_metadata_repository
-from app.domain.schemas.metadata import ProjectMetaResponse, GeoServerConfigResponse
-import app.services.project_info as project_info
-from app.infra.db.postgresql.database import get_database_instance as get_pg_db
-from app.infra.db.timescaledb.database import get_database_instance as get_ts_db
+from app.auth.project_dependencies import (
+    get_metadata_repository,
+)
+from app.domain.schemas.metadata import ProjectMetaResponse
 from app.services.tjnetwork import (
     ChangeSet,
-    list_project,
-    have_project,
-    create_project,
-    delete_project,
-    is_project_open,
-    open_project,
-    close_project,
-    copy_project,
-    import_inp,
     export_inp,
-    read_inp,
-    dump_inp,
     get_all_vertices,
-    get_all_scada_elements,
-    get_all_district_metering_areas,
-    get_all_service_areas,
-    get_all_virtual_districts,
-    get_extension_data,
-    convert_inp_v3_to_v2,
+    get_all_scada_info,
 )
 
-# For inp file upload/download
-import os
-from fastapi import Response, status
-from fastapi.responses import FileResponse
-inpDir = "data/" # Assuming data directory exists or is defined somewhere. 
-# In main.py it was likely global. For safety, let's use a relative path or get from config. 
-# But let's stick to what main.py probably used or a default.
-
 router = APIRouter()
-lockedPrjs: Dict[str, str] = {}
 
-@router.get("/project_info/", summary="获取项目信息", description="从数据库获取项目的详细信息，包括地图范围等。", response_model=ProjectMetaResponse)
+@router.get("/projects/current", summary="获取项目信息", description="从数据库获取项目的详细信息，包括地图范围等。", response_model=ProjectMetaResponse)
 async def get_project_info_endpoint(
     network: str = Query(..., description="管网名称（或项目代码）"),
     metadata_repo: MetadataRepository = Depends(get_metadata_repository),
@@ -55,17 +27,6 @@ async def get_project_info_endpoint(
     project_detail = await metadata_repo.get_project_detail_by_code(network)
     if not project_detail:
         raise HTTPException(status_code=404, detail=f"Project {network} not found")
-        
-    geoserver_payload = None
-    if project_detail.geoserver:
-         geoserver_payload = GeoServerConfigResponse(
-            gs_base_url=project_detail.geoserver.gs_base_url,
-            gs_admin_user=project_detail.geoserver.gs_admin_user,
-            gs_datastore_name=project_detail.geoserver.gs_datastore_name,
-            default_extent=project_detail.geoserver.default_extent,
-            srid=project_detail.geoserver.srid,
-        )
-
     return ProjectMetaResponse(
         project_id=project_detail.project_id,
         name=project_detail.name,
@@ -75,144 +36,10 @@ async def get_project_info_endpoint(
         map_extent=project_detail.map_extent,
         status=project_detail.status,
         project_role="viewer", # Default role for public access
-        geoserver=geoserver_payload
     )
 
-@router.get("/listprojects/", summary="获取项目列表", description="获取服务器上所有可用的供水管网项目名称列表。")
-async def list_projects_endpoint() -> list[str]:
-    """
-    获取项目列表
-
-    返回所有已创建项目的名称列表。
-    """
-    return list_project()
-
-@router.get("/haveproject/", summary="检查项目是否存在", description="检查指定名称的项目是否存在。")
-async def have_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    检查项目是否存在
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    return have_project(network)
-
-@router.post("/createproject/", summary="创建新项目", description="创建一个新的供水管网项目。如果项目已存在，可能会覆盖或报错（取决于底层实现）。")
-async def create_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    创建新项目
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    create_project(network)
-    return network
-
-@router.post("/deleteproject/", summary="删除项目", description="永久删除指定的供水管网项目。此操作不可恢复。")
-async def delete_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    删除项目
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    delete_project(network)
-    return True
-
-@router.get("/isprojectopen/", summary="检查项目是否已打开", description="检查指定项目是否已被加载到内存中。")
-async def is_project_open_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    检查项目是否已打开
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    return is_project_open(network)
-
-@router.post("/openproject/", summary="打开项目", description="将指定项目加载到内存中，并初始化数据库连接池。")
-async def open_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    打开项目
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    open_project(network)
-    
-    # 尝试连接指定数据库
-    try:
-        # 初始化 PostgreSQL 连接池
-        pg_instance = await get_pg_db(network)
-        async with pg_instance.get_connection() as conn:
-            async with conn.cursor() as cur:
-                await cur.execute("SELECT 1")
-        
-        # 初始化 TimescaleDB 连接池
-        ts_instance = await get_ts_db(network)
-        async with ts_instance.get_connection() as conn:
-            async with conn.cursor() as cur:
-                await cur.execute("SELECT 1")
-                
-    except Exception as e:
-        # 记录错误但不阻断项目打开，或者根据需求决定是否阻断
-        # 这里选择打印错误，因为 open_project 原本只负责原生部分
-        print(f"Failed to connect to databases for {network}: {str(e)}")
-        # 如果数据库连接是必须的，可以抛出异常:
-        # raise HTTPException(status_code=500, detail=f"Database connection failed: {str(e)}")
-
-    return network
-
-@router.post("/closeproject/", summary="关闭项目", description="将指定项目从内存中卸载，释放资源。")
-async def close_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    关闭项目
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    close_project(network)
-    return True
-
-@router.post("/copyproject/", summary="复制项目", description="将现有项目复制为新项目。")
-async def copy_project_endpoint(
-    source: str = Query(..., description="管网名称（或数据库名称）"),
-    target: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    复制项目
-
-    - **source**: 管网名称（或数据库名称）
-    - **target**: 管网名称（或数据库名称）
-    """
-    copy_project(source, target)
-    return True
-
-@router.post("/importinp/", summary="导入 INP 文件内容", description="将 INP 格式的文本内容导入到指定项目中。")
-async def import_inp_endpoint(
-    req: Request,
-    network: str = Query(..., description="管网名称（或数据库名称）")
-):
-    """
-    导入 INP 文件内容
-
-    - **network**: 管网名称（或数据库名称）
-    - **req**: 请求体，需包含 `{"inp": "..."}` 结构
-    """
-    jo_root = await req.json()
-    inp_text = jo_root["inp"]
-    ps = {"inp": inp_text}
-    ret = import_inp(network, ChangeSet(ps))
-    print(ret)
-    return ret
-
-@router.get("/exportinp/", response_model=None, summary="导出项目为 ChangeSet", description="导出项目的变更集 (ChangeSet)，包含顶点、SCADA 元素、DMA、SA、VD 等信息。")
-async def export_inp_endpoint(
+@router.get("/projects/current/exports/change-set", response_model=None, summary="导出项目为 ChangeSet", description="导出项目的变更集 (ChangeSet)，包含顶点、SCADA 元素、DMA、SA、VD 等信息。")
+def export_inp_endpoint(
     network: str = Query(..., description="管网名称（或数据库名称）"),
     version: str = Query(..., description="版本号 (通常用于增量更新)")
 ) -> ChangeSet:
@@ -224,364 +51,7 @@ async def export_inp_endpoint(
     """
     cs = export_inp(network, version)
     op = cs.operations[0]
-    open_project(network)
     op["vertex"] = json.dumps(get_all_vertices(network))
-    op["scada"] = json.dumps(get_all_scada_elements(network))
-    op["dma"] = json.dumps(get_all_district_metering_areas(network))
-    op["sa"] = json.dumps(get_all_service_areas(network))
-    op["vd"] = json.dumps(get_all_virtual_districts(network))
-    op["legend"] = get_extension_data(network, "legend")
-
-    db = get_extension_data(network, "scada_db")
-    print(db)
-    scada_db = ""
-    if db:
-        scada_db = db
-    print(scada_db)
-    op["scada_db"] = scada_db
-
-    close_project(network)
-
-    return cs
-
-@router.post("/readinp/", summary="读取 INP 文件到项目", description="从服务器文件系统中读取指定的 INP 文件并加载到项目中。")
-async def read_inp_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inp: str = Query(..., description="INP 文件名 (不包含路径)")
-) -> bool:
-    """
-    读取 INP 文件到项目
-
-    - **network**: 管网名称（或数据库名称）
-    - **inp**: INP 文件名
-    """
-    read_inp(network, inp)
-    return True
-
-@router.get("/dumpinp/", summary="导出项目到 INP 文件", description="将项目当前状态保存为 INP 文件到服务器文件系统。")
-async def dump_inp_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inp: str = Query(..., description="目标文件名")
-) -> bool:
-    """
-    导出项目到 INP 文件
-
-    - **network**: 管网名称（或数据库名称）
-    - **inp**: 目标文件名
-    """
-    dump_inp(network, inp)
-    return True
-
-@router.get("/isprojectlocked/", summary="检查项目是否被锁定", description="检查指定项目是否处于锁定状态。")
-async def is_project_locked_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    检查项目是否被锁定
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    return network in lockedPrjs.keys()
-
-@router.get("/isprojectlockedbyme/", summary="检查项目是否被当前用户锁定", description="检查指定项目是否被当前客户端 (IP) 锁定。")
-async def is_project_locked_by_me_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    检查项目是否被当前用户锁定
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    client_host = req.client.host
-    return lockedPrjs.get(network) == client_host
-
-# 0 successfully locked
-# 1 already locked by you
-# 2 locked by others
-@router.post("/lockproject/", summary="锁定项目", description="锁定指定项目以防止并发修改。")
-async def lock_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    锁定项目
-
-    返回值:
-    - **0**: 锁定成功
-    - **1**: 已被当前用户锁定
-    - **2**: 已被其他用户锁定
-    """
-    client_host = req.client.host
-    if not network in lockedPrjs.keys():
-        lockedPrjs[network] = client_host
-        return 0
-    else:
-        if lockedPrjs.get(network) == client_host:
-            return 1
-        else:
-            return 2
-
-@router.post("/unlockproject/", summary="解锁项目", description="释放对项目的锁定。")
-def unlock_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    解锁项目
-
-    只有锁定者才能解锁。
-    """
-    client_host = req.client.host
-    if lockedPrjs.get(network) == client_host:
-        print("delete key")
-        del lockedPrjs[network]
-        return True
-
-    return False
-
-# inp file operations
-@router.post("/uploadinp/", status_code=status.HTTP_200_OK, summary="上传 INP 文件", description="上传 INP 文件到服务器数据目录。")
-async def fastapi_upload_inp(
-    afile: bytes = Body(..., description="文件二进制内容"),
-    name: str = Query(..., description="保存的文件名")
-):
-    """
-    上传 INP 文件
-
-    - **afile**: 文件内容
-    - **name**: 文件名
-    """
-    if not os.path.exists(inpDir):
-        os.makedirs(inpDir, exist_ok=True)
-        
-    filePath = inpDir + str(name)
-    with open(filePath, "wb") as f:
-        f.write(afile)
-    return True
-
-@router.get("/downloadinp/", status_code=status.HTTP_200_OK, summary="下载 INP 文件", description="从服务器数据目录下载指定的 INP 文件。")
-async def fastapi_download_inp(
-    name: str = Query(..., description="文件名"),
-    response: Response = None
-):
-    """
-    下载 INP 文件
-
-    - **name**: 文件名
-    """
-    filePath = inpDir + name
-    if os.path.exists(filePath):
-        return FileResponse(
-            filePath, media_type="application/octet-stream", filename="inp.inp"
-        )
-    else:
-        response.status_code = status.HTTP_400_BAD_REQUEST
-        return True
-
-# DingZQ, 2024-12-28, convert v3 to v2
-@router.get("/convertv3tov2/", response_model=None, summary="转换 INP V3 为 V2", description="将 EPANET 3.0 格式的 INP 内容转换为 2.x 格式。")
-async def fastapi_convert_v3_to_v2(
-    req: Request
-) -> ChangeSet:
-    """
-    转换 INP V3 为 V2
-
-    - **req**: 请求体，需包含 `{"inp": "..."}` 结构
-    """
-    network = "v3Tov2"
-    jo_root = await req.json()
-    inp = jo_root["inp"]
-    cs = convert_inp_v3_to_v2(inp)
-    op = cs.operations[0]
-    open_project(network)
-    op["vertex"] = json.dumps(get_all_vertices(network))
-    op["scada"] = json.dumps(get_all_scada_elements(network))
-    op["dma"] = json.dumps(get_all_district_metering_areas(network))
-    op["sa"] = json.dumps(get_all_service_areas(network))
-    op["vd"] = json.dumps(get_all_virtual_districts(network))
-    op["legend"] = get_extension_data(network, "legend")
-
-    db = get_extension_data(network, "scada_db")
-    print(db)
-    scada_db = ""
-    if db:
-        scada_db = db
-    print(scada_db)
-    op["scada_db"] = scada_db
-
-    close_project(network)
-
-    return cs
-
-@router.post("/readinp/", summary="读取 INP 文件到项目", description="从服务器文件系统中读取指定的 INP 文件并加载到项目中。")
-async def read_inp_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inp: str = Query(..., description="INP 文件名 (不包含路径)")
-) -> bool:
-    """
-    读取 INP 文件到项目
-
-    - **network**: 管网名称（或数据库名称）
-    - **inp**: INP 文件名
-    """
-    read_inp(network, inp)
-    return True
-
-@router.get("/dumpinp/", summary="导出项目到 INP 文件", description="将项目当前状态保存为 INP 文件到服务器文件系统。")
-async def dump_inp_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    inp: str = Query(..., description="目标文件名")
-) -> bool:
-    """
-    导出项目到 INP 文件
-
-    - **network**: 管网名称（或数据库名称）
-    - **inp**: 目标文件名
-    """
-    dump_inp(network, inp)
-    return True
-
-@router.get("/isprojectlocked/", summary="检查项目是否被锁定", description="检查指定项目是否处于锁定状态。")
-async def is_project_locked_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    检查项目是否被锁定
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    return network in lockedPrjs.keys()
-
-@router.get("/isprojectlockedbyme/", summary="检查项目是否被当前用户锁定", description="检查指定项目是否被当前客户端 (IP) 锁定。")
-async def is_project_locked_by_me_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    检查项目是否被当前用户锁定
-
-    - **network**: 管网名称（或数据库名称）
-    """
-    client_host = req.client.host
-    return lockedPrjs.get(network) == client_host
-
-# 0 successfully locked
-# 1 already locked by you
-# 2 locked by others
-@router.post("/lockproject/", summary="锁定项目", description="锁定指定项目以防止并发修改。")
-async def lock_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    锁定项目
-
-    返回值:
-    - **0**: 锁定成功
-    - **1**: 已被当前用户锁定
-    - **2**: 已被其他用户锁定
-    """
-    client_host = req.client.host
-    if not network in lockedPrjs.keys():
-        lockedPrjs[network] = client_host
-        return 0
-    else:
-        if lockedPrjs.get(network) == client_host:
-            return 1
-        else:
-            return 2
-
-@router.post("/unlockproject/", summary="解锁项目", description="释放对项目的锁定。")
-def unlock_project_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-):
-    """
-    解锁项目
-
-    只有锁定者才能解锁。
-    """
-    client_host = req.client.host
-    if lockedPrjs.get(network) == client_host:
-        print("delete key")
-        del lockedPrjs[network]
-        return True
-
-    return False
-
-# inp file operations
-@router.post("/uploadinp/", status_code=status.HTTP_200_OK, summary="上传 INP 文件", description="上传 INP 文件到服务器数据目录。")
-async def fastapi_upload_inp(
-    afile: bytes = Body(..., description="文件二进制内容"),
-    name: str = Query(..., description="保存的文件名")
-):
-    """
-    上传 INP 文件
-
-    - **afile**: 文件内容
-    - **name**: 文件名
-    """
-    if not os.path.exists(inpDir):
-        os.makedirs(inpDir, exist_ok=True)
-        
-    filePath = inpDir + str(name)
-    with open(filePath, "wb") as f:
-        f.write(afile)
-    return True
-
-@router.get("/downloadinp/", status_code=status.HTTP_200_OK, summary="下载 INP 文件", description="从服务器数据目录下载指定的 INP 文件。")
-async def fastapi_download_inp(
-    name: str = Query(..., description="文件名"),
-    response: Response = None
-):
-    """
-    下载 INP 文件
-
-    - **name**: 文件名
-    """
-    filePath = inpDir + name
-    if os.path.exists(filePath):
-        return FileResponse(
-            filePath, media_type="application/octet-stream", filename="inp.inp"
-        )
-    else:
-        response.status_code = status.HTTP_400_BAD_REQUEST
-        return True
-
-# DingZQ, 2024-12-28, convert v3 to v2
-@router.get("/convertv3tov2/", response_model=None, summary="转换 INP V3 为 V2", description="将 EPANET 3.0 格式的 INP 内容转换为 2.x 格式。")
-async def fastapi_convert_v3_to_v2(
-    req: Request
-) -> ChangeSet:
-    """
-    转换 INP V3 为 V2
-
-    - **req**: 请求体，需包含 `{"inp": "..."}` 结构
-    """
-    network = "v3Tov2"
-    jo_root = await req.json()
-    inp = jo_root["inp"]
-    cs = convert_inp_v3_to_v2(inp)
-    op = cs.operations[0]
-    open_project(network)
-    op["vertex"] = json.dumps(get_all_vertices(network))
-    op["scada"] = json.dumps(get_all_scada_elements(network))
-    op["dma"] = json.dumps(get_all_district_metering_areas(network))
-    op["sa"] = json.dumps(get_all_service_areas(network))
-    op["vd"] = json.dumps(get_all_virtual_districts(network))
-    op["legend"] = get_extension_data(network, "legend")
-
-    db = get_extension_data(network, "scada_db")
-    print(db)
-    scada_db = ""
-    if db:
-        scada_db = db
-    print(scada_db)
-    op["scada_db"] = scada_db
-
-    close_project(network)
+    op["scada"] = json.dumps(get_all_scada_info(network))
 
     return cs

app/api/v1/endpoints/project_data.py

@@ -1,10 +1,10 @@
-from fastapi import APIRouter, Depends, HTTPException, Path, Query
+from uuid import UUID
+
+from fastapi import APIRouter, Depends, HTTPException, Query
 from psycopg import AsyncConnection
 
-import app.native.wndb as wndb
-from app.infra.db.postgresql.scheme import SchemeRepository
+from app.infra.db.postgresql.analysis import AnalysisRepository
 from app.auth.project_dependencies import get_project_pg_connection
-from app.services import project_info
 
 router = APIRouter()
 
@@ -16,28 +16,8 @@ async def get_database_connection(
     yield conn
 
 
-@router.get("/scada-info", summary="获取SCADA信息", description="使用连接池查询所有SCADA信息")
-async def get_scada_info_with_connection(
-    conn: AsyncConnection = Depends(get_database_connection),
-):
-    """
-    获取所有SCADA信息
-    
-    返回项目中所有的SCADA设备信息
-    """
-    try:
-        _ = conn
-        network_name = project_info.name
-        scada_data = wndb.get_all_scada_info(network_name) if network_name else []
-        return {"success": True, "data": scada_data, "count": len(scada_data)}
-    except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"查询SCADA信息时发生错误: {str(e)}"
-        )
-
-
-@router.get("/scheme-list", summary="获取方案列表", description="使用连接池查询所有方案信息")
-async def get_scheme_list_with_connection(
+@router.get("/analysis/runs", summary="获取分析运行列表")
+async def get_analysis_runs(
     conn: AsyncConnection = Depends(get_database_connection),
 ):
     """
@@ -46,14 +26,15 @@ async def get_scheme_list_with_connection(
     返回项目中所有方案的详细信息
     """
     try:
-        scheme_data = await SchemeRepository.get_schemes(conn)
-        return {"success": True, "data": scheme_data, "count": len(scheme_data)}
+        runs = await AnalysisRepository.list_runs(conn)
+        return {"success": True, "data": runs, "count": len(runs)}
     except Exception as e:
-        raise HTTPException(status_code=500, detail=f"查询方案信息时发生错误: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"查询分析运行时发生错误: {str(e)}")
 
 
-@router.get("/burst-locate-result", summary="获取爆管定位结果", description="使用连接池查询所有爆管定位结果")
-async def get_burst_locate_result_with_connection(
+@router.get("/analysis/runs/{run_id}", summary="获取分析运行")
+async def get_analysis_run(
+    run_id: UUID,
     conn: AsyncConnection = Depends(get_database_connection),
 ):
     """
@@ -62,17 +43,22 @@ async def get_burst_locate_result_with_connection(
     返回项目中所有的爆管定位分析结果
     """
     try:
-        burst_data = await SchemeRepository.get_burst_locate_results(conn)
-        return {"success": True, "data": burst_data, "count": len(burst_data)}
+        run = await AnalysisRepository.get_run(conn, run_id)
+        if run is None:
+            raise HTTPException(status_code=404, detail="分析运行不存在")
+        return run
+    except HTTPException:
+        raise
     except Exception as e:
         raise HTTPException(
-            status_code=500, detail=f"查询爆管定位结果时发生错误: {str(e)}"
+            status_code=500, detail=f"查询分析运行时发生错误: {str(e)}"
         )
 
 
-@router.get("/burst-locate-result/{burst_incident}", summary="按事件查询爆管定位结果", description="根据爆管事件ID查询对应的爆管定位结果")
-async def get_burst_locate_result_by_incident(
-    burst_incident: str = Path(..., description="爆管事件ID"),
+@router.get("/analysis/runs/{run_id}/results", summary="获取分析结果")
+async def get_analysis_results(
+    run_id: UUID,
+    result_type: str | None = Query(default=None, description="结果类型"),
     conn: AsyncConnection = Depends(get_database_connection),
 ):
     """
@@ -82,11 +68,9 @@ async def get_burst_locate_result_by_incident(
         burst_incident: 爆管事件的唯一标识符
     """
     try:
-        return await SchemeRepository.get_burst_locate_result_by_incident(
-            conn, burst_incident
-        )
+        return await AnalysisRepository.list_results(conn, run_id, result_type)
     except Exception as e:
         raise HTTPException(
             status_code=500,
-            detail=f"根据 burst_incident 查询爆管定位结果时发生错误: {str(e)}",
+            detail=f"查询分析结果时发生错误: {str(e)}",
         )

app/api/v1/endpoints/risk.py

@@ -1,127 +0,0 @@
-from typing import Any, List, Dict
-from fastapi import APIRouter, Query, Path
-from app.services.tjnetwork import (
-    get_pipe_risk_probability_now,
-    get_pipe_risk_probability,
-    get_pipes_risk_probability,
-    get_network_pipe_risk_probability_now,
-    get_pipe_risk_probability_geometries,
-)
-
-router = APIRouter()
-
-@router.get(
-    "/getpiperiskprobabilitynow/",
-    summary="获取管道当前风险概率",
-    description="获取指定管道当前时刻的风险概率值"
-)
-async def fastapi_get_pipe_risk_probability_now(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    pipe_id: str = Query(..., description="管道ID")
-) -> dict[str, Any]:
-    """
-    获取管道当前风险概率。
-    
-    查询指定管道在当前时刻的风险概率值。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        pipe_id: 管道ID
-        
-    Returns:
-        包含风险概率信息的字典
-    """
-    return get_pipe_risk_probability_now(network, pipe_id)
-
-
-@router.get(
-    "/getpiperiskprobability/",
-    summary="获取管道风险概率历史",
-    description="获取指定管道的风险概率历史数据"
-)
-async def fastapi_get_pipe_risk_probability(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    pipe_id: str = Query(..., description="管道ID")
-) -> dict[str, Any]:
-    """
-    获取管道风险概率历史。
-    
-    查询指定管道的历史风险概率数据。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        pipe_id: 管道ID
-        
-    Returns:
-        包含风险概率历史的字典
-    """
-    return get_pipe_risk_probability(network, pipe_id)
-
-
-@router.get(
-    "/getpipesriskprobability/",
-    summary="批量获取多条管道风险概率",
-    description="批量获取多条管道的风险概率值"
-)
-async def fastapi_get_pipes_risk_probability(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    pipe_ids: str = Query(..., description="逗号分隔的管道ID列表")
-) -> list[dict[str, Any]]:
-    """
-    批量获取多条管道风险概率。
-    
-    查询多条指定管道的风险概率值。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        pipe_ids: 逗号分隔的管道ID列表（例如：pipe1,pipe2,pipe3）
-        
-    Returns:
-        包含多条管道风险概率的列表
-    """
-    pipeids = pipe_ids.split(",")
-    return get_pipes_risk_probability(network, pipeids)
-
-
-@router.get(
-    "/getnetworkpiperiskprobabilitynow/",
-    summary="获取整个网络的管道风险概率",
-    description="获取指定网络中所有管道的当前风险概率值"
-)
-async def fastapi_get_network_pipe_risk_probability_now(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-) -> list[dict[str, Any]]:
-    """
-    获取整个网络的管道风险概率。
-    
-    查询指定网络中所有管道在当前时刻的风险概率值。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        包含网络内所有管道风险概率的列表
-    """
-    return get_network_pipe_risk_probability_now(network)
-
-
-@router.get(
-    "/getpiperiskprobabilitygeometries/",
-    summary="获取管道风险几何信息",
-    description="获取指定网络中管道的风险相关几何数据"
-)
-async def fastapi_get_pipe_risk_probability_geometries(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, Any]:
-    """
-    获取管道风险几何信息。
-    
-    查询指定网络中管道的地理和风险相关的几何数据。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        包含几何信息和风险数据的字典
-    """
-    return get_pipe_risk_probability_geometries(network)

app/api/v1/endpoints/scada.py

@@ -1,527 +1,42 @@
 from typing import Any
-from fastapi import APIRouter, Request, Query
-from app.services.tjnetwork import (
-    ChangeSet,
-    get_scada_info,
-    get_all_scada_info,
-    get_scada_device_schema,
-    get_scada_device,
-    set_scada_device,
-    add_scada_device,
-    delete_scada_device,
-    clean_scada_device,
-    get_all_scada_device_ids,
-    get_all_scada_devices,
-    get_scada_device_data_schema,
-    get_scada_device_data,
-    set_scada_device_data,
-    add_scada_device_data,
-    delete_scada_device_data,
-    clean_scada_device_data,
-    get_scada_element_schema,
-    get_scada_element,
-    set_scada_element,
-    add_scada_element,
-    delete_scada_element,
-    clean_scada_element,
-    get_all_scada_elements,
-    get_scada_element_schema,
-    get_scada_info_schema,
-)
+
+from fastapi import APIRouter, Depends, HTTPException
+from psycopg import AsyncConnection
+
+from app.auth.project_dependencies import get_project_pg_connection
+from app.domain.schemas.scada import ScadaDeviceResponse
+from app.infra.db.postgresql.scada import ScadaInfoRepository, get_scada_info_schema
+
 
 router = APIRouter()
 
-@router.get("/getscadaproperties/", summary="获取SCADA属性", tags=["SCADA基础"])
-async def fast_get_scada_properties(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    scada: str = Query(..., description="SCADA设备ID")
-) -> dict[str, Any]:
-    """
-    获取单个SCADA设备的属性信息
-    
-    根据管网名称和SCADA设备ID获取该设备的完整属性。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        scada: SCADA设备ID
-        
-    Returns:
-        SCADA设备的属性字典
-    """
-    return get_scada_info(network, scada)
 
-@router.get("/getallscadaproperties/", summary="获取所有SCADA属性", tags=["SCADA基础"])
-async def fast_get_all_scada_properties(
-    network: str = Query(..., description="管网名称（或数据库名称）")
+@router.get("/network-schemas/scada-device", summary="获取 SCADA 设备结构")
+def get_scada_device_schema() -> dict[str, dict[str, Any]]:
+    return get_scada_info_schema("")
+
+
+@router.get(
+    "/scada-devices",
+    summary="获取 SCADA 设备列表",
+    response_model=list[ScadaDeviceResponse],
+)
+async def get_scada_devices(
+    conn: AsyncConnection = Depends(get_project_pg_connection),
 ) -> list[dict[str, Any]]:
-    """
-    获取指定管网所有SCADA设备的属性信息
-    
-    查询该管网下所有已配置的SCADA设备的属性列表。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA设备属性列表
-    """
-    return get_all_scada_info(network)
+    return await ScadaInfoRepository.get_scadas(conn)
 
 
-############################################################
-# scada_device 设备管理
-############################################################
-
-@router.get("/getscadadeviceschema/", summary="获取SCADA设备架构", tags=["SCADA设备"])
-async def fastapi_get_scada_device_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, dict[str, Any]]:
-    """
-    获取SCADA设备的数据架构
-    
-    返回SCADA设备表的字段定义和类型信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA设备的字段架构信息
-    """
-    return get_scada_device_schema(network)
-
-@router.get("/getscadadevice/", summary="获取SCADA设备", tags=["SCADA设备"])
-async def fastapi_get_scada_device(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="SCADA设备ID")
+@router.get(
+    "/scada-devices/{device_id}",
+    summary="获取 SCADA 设备",
+    response_model=ScadaDeviceResponse,
+)
+async def get_scada_device(
+    device_id: str,
+    conn: AsyncConnection = Depends(get_project_pg_connection),
 ) -> dict[str, Any]:
-    """
-    获取单个SCADA设备的信息
-    
-    根据设备ID查询该设备的详细信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        id: SCADA设备ID
-        
-    Returns:
-        SCADA设备信息
-    """
-    return get_scada_device(network, id)
-
-@router.post("/setscadadevice/", response_model=None, summary="更新SCADA设备", tags=["SCADA设备"])
-async def fastapi_set_scada_device(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    更新SCADA设备信息
-    
-    修改指定SCADA设备的属性。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要更新的设备属性
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return set_scada_device(network, ChangeSet(props))
-
-@router.post("/addscadadevice/", response_model=None, summary="添加SCADA设备", tags=["SCADA设备"])
-async def fastapi_add_scada_device(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    添加新的SCADA设备
-    
-    在指定管网中添加一个新的SCADA设备。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含新设备的属性
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return add_scada_device(network, ChangeSet(props))
-
-@router.post("/deletescadadevice/", response_model=None, summary="删除SCADA设备", tags=["SCADA设备"])
-async def fastapi_delete_scada_device(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    删除SCADA设备
-    
-    从指定管网中删除一个SCADA设备。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要删除的设备ID
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return delete_scada_device(network, ChangeSet(props))
-
-@router.post("/cleanscadadevice/", response_model=None, summary="清空SCADA设备表", tags=["SCADA设备"])
-async def fastapi_clean_scada_device(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> ChangeSet:
-    """
-    清空SCADA设备表
-    
-    删除指定管网中所有的SCADA设备。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        变更集合信息
-    """
-    return clean_scada_device(network)
-
-@router.get("/getallscadadeviceids/", summary="获取所有SCADA设备ID", tags=["SCADA设备"])
-async def fastapi_get_all_scada_device_ids(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[str]:
-    """
-    获取指定管网所有SCADA设备的ID列表
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA设备ID列表
-    """
-    return get_all_scada_device_ids(network)
-
-@router.get("/getallscadadevices/", summary="获取所有SCADA设备", tags=["SCADA设备"])
-async def fastapi_get_all_scada_devices(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """
-    获取指定管网所有SCADA设备的完整信息
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA设备信息列表
-    """
-    return get_all_scada_devices(network)
-
-
-############################################################
-# scada_device_data 设备数据管理
-############################################################
-
-@router.get("/getscadadevicedataschema/", summary="获取SCADA设备数据架构", tags=["SCADA设备数据"])
-async def fastapi_get_scada_device_data_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-) -> dict[str, dict[str, Any]]:
-    """
-    获取SCADA设备数据的表结构
-    
-    返回SCADA设备数据表的字段定义和类型信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA设备数据的字段架构信息
-    """
-    return get_scada_device_data_schema(network)
-
-@router.get("/getscadadevicedata/", summary="获取SCADA设备数据", tags=["SCADA设备数据"])
-async def fastapi_get_scada_device_data(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    device_id: str = Query(..., description="SCADA设备ID")
-) -> dict[str, Any]:
-    """
-    获取单个SCADA设备的数据
-    
-    查询指定设备的监测数据或配置数据。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        device_id: SCADA设备ID
-        
-    Returns:
-        SCADA设备数据
-    """
-    return get_scada_device_data(network, device_id)
-
-@router.post("/setscadadevicedata/", response_model=None, summary="更新SCADA设备数据", tags=["SCADA设备数据"])
-async def fastapi_set_scada_device_data(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    更新SCADA设备数据
-    
-    修改指定SCADA设备的数据。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要更新的数据
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return set_scada_device_data(network, ChangeSet(props))
-
-@router.post("/addscadadevicedata/", response_model=None, summary="添加SCADA设备数据", tags=["SCADA设备数据"])
-async def fastapi_add_scada_device_data(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    添加新的SCADA设备数据
-    
-    为指定SCADA设备添加新的数据记录。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含新数据的内容
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return add_scada_device_data(network, ChangeSet(props))
-
-@router.post("/deletescadadevicedata/", response_model=None, summary="删除SCADA设备数据", tags=["SCADA设备数据"])
-async def fastapi_delete_scada_device_data(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    删除SCADA设备数据
-    
-    删除指定SCADA设备的数据记录。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要删除的数据ID
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return delete_scada_device_data(network, ChangeSet(props))
-
-@router.post("/cleanscadadevicedata/", response_model=None, summary="清空SCADA设备数据表", tags=["SCADA设备数据"])
-async def fastapi_clean_scada_device_data(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> ChangeSet:
-    """
-    清空SCADA设备数据表
-    
-    删除指定管网中所有SCADA设备的数据。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        变更集合信息
-    """
-    return clean_scada_device_data(network)
-
-
-############################################################
-# scada_element SCADA元素映射
-############################################################
-
-@router.get("/getscadaelementschema/", summary="获取SCADA元素架构", tags=["SCADA元素映射"])
-async def fastapi_get_scada_element_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-) -> dict[str, dict[str, Any]]:
-    """
-    获取SCADA元素映射的表结构
-    
-    返回SCADA元素映射表的字段定义和类型信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA元素映射的字段架构信息
-    """
-    return get_scada_element_schema(network)
-
-@router.get("/getscadaelements/", summary="获取所有SCADA元素映射", tags=["SCADA元素映射"])
-async def fastapi_get_scada_elements(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """
-    获取指定管网所有SCADA元素映射
-    
-    查询所有SCADA设备与管网元素（节点/管道）的映射关系。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA元素映射列表
-    """
-    return get_all_scada_elements(network)
-
-@router.get("/getscadaelement/", summary="获取单个SCADA元素映射", tags=["SCADA元素映射"])
-async def fastapi_get_scada_element(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="SCADA元素映射ID")
-) -> dict[str, Any]:
-    """
-    获取单个SCADA元素映射的信息
-    
-    根据ID查询特定的SCADA设备与管网元素的映射关系。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        id: SCADA元素映射ID
-        
-    Returns:
-        SCADA元素映射信息
-    """
-    return get_scada_element(network, id)
-
-@router.post("/setscadaelement/", response_model=None, summary="更新SCADA元素映射", tags=["SCADA元素映射"])
-async def fastapi_set_scada_element(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    更新SCADA元素映射
-    
-    修改SCADA设备与管网元素的映射关系。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要更新的映射信息
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return set_scada_element(network, ChangeSet(props))
-
-@router.post("/addscadaelement/", response_model=None, summary="添加SCADA元素映射", tags=["SCADA元素映射"])
-async def fastapi_add_scada_element(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    添加新的SCADA元素映射
-    
-    创建SCADA设备与管网元素的新映射关系。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含新映射的信息
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return add_scada_element(network, ChangeSet(props))
-
-@router.post("/deletescadaelement/", response_model=None, summary="删除SCADA元素映射", tags=["SCADA元素映射"])
-async def fastapi_delete_scada_element(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    req: Request = None
-) -> ChangeSet:
-    """
-    删除SCADA元素映射
-    
-    移除SCADA设备与管网元素的映射关系。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        req: 请求体，包含要删除的映射ID
-        
-    Returns:
-        变更集合信息
-    """
-    props = await req.json()
-    return delete_scada_element(network, ChangeSet(props))
-
-@router.post("/cleanscadaelement/", response_model=None, summary="清空SCADA元素映射表", tags=["SCADA元素映射"])
-async def fastapi_clean_scada_element(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> ChangeSet:
-    """
-    清空SCADA元素映射表
-    
-    删除指定管网中所有的SCADA元素映射。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        变更集合信息
-    """
-    return clean_scada_element(network)
-
-
-############################################################
-# scada_info SCADA信息
-############################################################
-
-@router.get("/getscadainfoschema/", summary="获取SCADA信息架构", tags=["SCADA信息"])
-async def fastapi_get_scada_info_schema(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> dict[str, dict[str, Any]]:
-    """
-    获取SCADA信息表的结构
-    
-    返回SCADA信息表的字段定义和类型信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA信息的字段架构信息
-    """
-    return get_scada_info_schema(network)
-
-@router.get("/getscadainfo/", summary="获取SCADA信息", tags=["SCADA信息"])
-async def fastapi_get_scada_info(
-    network: str = Query(..., description="管网名称（或数据库名称）"),
-    id: str = Query(..., description="SCADA信息ID")
-) -> dict[str, Any]:
-    """
-    获取单个SCADA信息
-    
-    根据ID查询SCADA的详细配置信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        id: SCADA信息ID
-        
-    Returns:
-        SCADA信息详情
-    """
-    return get_scada_info(network, id)
-
-@router.get("/getallscadainfo/", summary="获取所有SCADA信息", tags=["SCADA信息"])
-async def fastapi_get_all_scada_info(
-    network: str = Query(..., description="管网名称（或数据库名称）")
-) -> list[dict[str, Any]]:
-    """
-    获取指定管网所有SCADA的信息
-    
-    查询该管网下所有已配置的SCADA的完整信息。
-    
-    Args:
-        network: 管网名称（或数据库名称）
-        
-    Returns:
-        SCADA信息列表
-    """
-    return get_all_scada_info(network)
+    device = await ScadaInfoRepository.get_scada(conn, device_id)
+    if device is None:
+        raise HTTPException(status_code=404, detail="SCADA 设备不存在")
+    return device

app/api/v1/endpoints/schemes.py

@@ -1,32 +0,0 @@
-from fastapi import APIRouter, Query
-from typing import Any, List, Dict
-from app.services.tjnetwork import get_scheme_schema, get_scheme, get_all_schemes
-
-router = APIRouter()
-
-@router.get("/getschemeschema/", summary="获取方案模式", description="获取指定网络的方案模式定义")
-async def fastapi_get_scheme_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[Any, Any]]:
-    """
-    获取方案模式定义
-    
-    返回指定网络的方案模式结构定义
-    """
-    return get_scheme_schema(network)
-
-@router.get("/getscheme/", summary="获取单个方案", description="根据名称获取指定的方案信息")
-async def fastapi_get_scheme(network: str = Query(..., description="管网名称（或数据库名称）"), schema_name: str = Query(..., description="方案名称")) -> dict[Any, Any]:
-    """
-    获取单个方案详情
-    
-    返回指定网络中指定名称的方案详细信息
-    """
-    return get_scheme(network, schema_name)
-
-@router.get("/getallschemes/", summary="获取所有方案", description="获取指定网络的所有方案信息")
-async def fastapi_get_all_schemes(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[Any, Any]]:
-    """
-    获取所有方案列表
-    
-    返回指定网络中所有可用的方案
-    """
-    return get_all_schemes(network)

app/api/v1/endpoints/sensor_placement.py

@@ -0,0 +1,286 @@
+import logging
+from typing import Any
+from urllib.parse import quote
+from uuid import UUID
+
+from fastapi import APIRouter, Depends, HTTPException, Path, Query, status
+from fastapi.responses import StreamingResponse
+from starlette.concurrency import run_in_threadpool
+
+from app.auth.metadata_dependencies import get_current_metadata_user
+from app.auth.project_dependencies import (
+    ProjectContext,
+    get_project_context,
+    use_project_business_routing,
+)
+from app.infra.db.project_routing import ActiveProjectRouting
+from app.domain.schemas.sensor_placement import (
+    SensorPointResponse,
+    SensorPlacementExportRequest,
+    SensorPlacementOptimizeRequest,
+    SensorPlacementSchemeResponse,
+    SensorPlacementUpdateRequest,
+)
+from app.services.sensor_placement import (
+    SensorPlacementConflictError,
+    SensorPlacementNotFoundError,
+    SensorPlacementValidationError,
+    build_sensor_placement_workbook,
+    can_edit_sensor_placement,
+    get_sensor_placement_candidate,
+    get_sensor_placement_run,
+    list_sensor_placement_runs,
+    optimize_sensor_placement_by_kmeans,
+    optimize_sensor_placement_by_sensitivity,
+    update_sensor_placement_run,
+)
+
+router = APIRouter()
+logger = logging.getLogger(__name__)
+
+
+def _project_network(network: str, project_context: ProjectContext) -> str:
+    if network != project_context.project_code:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="请求的管网不属于当前项目",
+        )
+    return project_context.project_code
+
+
+def _can_modify_project(project_context: ProjectContext) -> bool:
+    return project_context.project_role == "member"
+
+
+def _require_project_write(
+    project_context: ProjectContext,
+) -> None:
+    if not _can_modify_project(project_context):
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="当前项目角色为只读，不能修改监测点方案",
+        )
+
+
+def _service_http_error(exc: Exception) -> HTTPException:
+    if isinstance(exc, SensorPlacementNotFoundError):
+        return HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=str(exc),
+        )
+    if isinstance(exc, SensorPlacementConflictError):
+        return HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail=str(exc),
+        )
+    return HTTPException(
+        status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
+        detail=str(exc),
+    )
+
+
+def _get_run_response(
+    network: str,
+    run_id: UUID,
+    current_user: Any,
+    project_context: ProjectContext,
+) -> dict[str, Any]:
+    try:
+        run = get_sensor_placement_run(network, run_id)
+        return {
+            **run,
+            "can_edit": (
+                _can_modify_project(project_context)
+                and can_edit_sensor_placement(current_user, run)
+            ),
+        }
+    except (
+        SensorPlacementNotFoundError,
+        SensorPlacementValidationError,
+    ) as exc:
+        raise _service_http_error(exc) from exc
+
+
+@router.get(
+    "/sensor-placement-candidates/{node_id}",
+    response_model=SensorPointResponse,
+    summary="获取监测点候选节点详情",
+)
+async def get_sensor_placement_candidate_detail(
+    node_id: str = Path(..., min_length=1, max_length=32),
+    project_context: ProjectContext = Depends(get_project_context),
+    _routing: ActiveProjectRouting = Depends(use_project_business_routing),
+) -> dict[str, Any]:
+    try:
+        return await run_in_threadpool(
+            get_sensor_placement_candidate,
+            project_context.project_code,
+            node_id,
+        )
+    except SensorPlacementValidationError as exc:
+        raise _service_http_error(exc) from exc
+
+
+@router.post(
+    "/sensor-placement-runs",
+    response_model=SensorPlacementSchemeResponse,
+    summary="创建并返回监测点优化方案",
+)
+async def optimize_sensor_placement_scheme(
+    payload: SensorPlacementOptimizeRequest,
+    project_context: ProjectContext = Depends(get_project_context),
+    current_user=Depends(get_current_metadata_user),
+) -> dict[str, Any]:
+    network = _project_network(payload.network, project_context)
+    _require_project_write(project_context)
+    optimizer = (
+        optimize_sensor_placement_by_sensitivity
+        if payload.method == "sensitivity"
+        else optimize_sensor_placement_by_kmeans
+    )
+    try:
+        created = await run_in_threadpool(
+            optimizer,
+            project_code=network,
+            run_name=payload.run_name,
+            sensor_count=payload.sensor_count,
+            min_diameter=payload.min_diameter,
+            created_by=current_user.username,
+        )
+        run = get_sensor_placement_run(network, created["run_id"])
+        return {**run, "can_edit": True}
+    except (
+        SensorPlacementConflictError,
+        SensorPlacementValidationError,
+        ValueError,
+    ) as exc:
+        raise _service_http_error(exc) from exc
+    except Exception as exc:
+        logger.exception("Sensor placement optimization failed")
+        raise HTTPException(
+            status_code=500,
+            detail="监测点优化失败，请稍后重试",
+        ) from exc
+
+
+@router.get(
+    "/sensor-placement-runs",
+    response_model=list[SensorPlacementSchemeResponse],
+    summary="获取监测点优化运行",
+)
+async def get_sensor_placement_runs(
+    project_context: ProjectContext = Depends(get_project_context),
+    _routing: ActiveProjectRouting = Depends(use_project_business_routing),
+) -> list[dict[str, Any]]:
+    return await run_in_threadpool(
+        list_sensor_placement_runs,
+        project_context.project_code,
+    )
+
+
+@router.get(
+    "/sensor-placement-runs/{run_id}",
+    response_model=SensorPlacementSchemeResponse,
+    summary="获取监测点方案详情",
+)
+def get_sensor_placement_run_detail(
+    run_id: UUID,
+    network: str = Query(..., min_length=1),
+    project_context: ProjectContext = Depends(get_project_context),
+    current_user=Depends(get_current_metadata_user),
+) -> dict[str, Any]:
+    return _get_run_response(
+        _project_network(network, project_context),
+        run_id,
+        current_user,
+        project_context,
+    )
+
+
+@router.put(
+    "/sensor-placement-runs/{run_id}",
+    response_model=SensorPlacementSchemeResponse,
+    summary="覆盖保存监测点方案",
+)
+def overwrite_sensor_placement_run(
+    run_id: UUID,
+    payload: SensorPlacementUpdateRequest,
+    network: str = Query(..., min_length=1),
+    project_context: ProjectContext = Depends(get_project_context),
+    current_user=Depends(get_current_metadata_user),
+) -> dict[str, Any]:
+    network = _project_network(network, project_context)
+    _require_project_write(project_context)
+    run = _get_run_response(
+        network,
+        run_id,
+        current_user,
+        project_context,
+    )
+    if not run["can_edit"]:
+        raise HTTPException(status_code=403, detail="无权修改该监测点优化运行")
+
+    try:
+        updated = update_sensor_placement_run(
+            network,
+            run_id,
+            expected_sensor_locations=payload.expected_sensor_locations,
+            sensor_locations=payload.sensor_locations,
+        )
+        return {**updated, "can_edit": True}
+    except (
+        SensorPlacementConflictError,
+        SensorPlacementNotFoundError,
+        SensorPlacementValidationError,
+    ) as exc:
+        raise _service_http_error(exc) from exc
+
+
+@router.post(
+    "/sensor-placement-runs/{run_id}/exports/excel",
+    summary="导出监测点工程清单",
+)
+async def export_sensor_placement_excel(
+    run_id: UUID,
+    payload: SensorPlacementExportRequest,
+    network: str = Query(..., min_length=1),
+    project_context: ProjectContext = Depends(get_project_context),
+    current_user=Depends(get_current_metadata_user),
+) -> StreamingResponse:
+    network = _project_network(network, project_context)
+    run = _get_run_response(
+        network,
+        run_id,
+        current_user,
+        project_context,
+    )
+    if (
+        payload.sensor_locations != run["sensor_locations"]
+        and not run["can_edit"]
+    ):
+        raise HTTPException(status_code=403, detail="无权导出该方案的未保存草稿")
+
+    try:
+        workbook = await run_in_threadpool(
+            build_sensor_placement_workbook,
+            network=network,
+            scheme=run,
+            sensor_location=payload.sensor_locations,
+            adjustment_status=payload.adjustment_status,
+        )
+    except SensorPlacementValidationError as exc:
+        raise _service_http_error(exc) from exc
+
+    filename = f"{run['name']}_监测点清单.xlsx"
+    encoded_filename = quote(filename)
+    return StreamingResponse(
+        workbook,
+        media_type=(
+            "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        ),
+        headers={
+            "Content-Disposition": (
+                f"attachment; filename*=UTF-8''{encoded_filename}"
+            )
+        },
+    )

app/api/v1/endpoints/snapshots.py

@@ -1,204 +0,0 @@
-from fastapi import APIRouter, Request, Query
-from app.services.tjnetwork import (
-    ChangeSet,
-    get_current_operation,
-    execute_undo,
-    execute_redo,
-    list_snapshot,
-    have_snapshot,
-    have_snapshot_for_operation,
-    have_snapshot_for_current_operation,
-    take_snapshot_for_operation,
-    take_snapshot_for_current_operation,
-    take_snapshot,
-    pick_snapshot,
-    pick_operation,
-    sync_with_server,
-    execute_batch_commands,
-    execute_batch_command,
-    get_restore_operation,
-    set_restore_operation,
-)
-
-router = APIRouter()
-
-@router.get("/getcurrentoperationid/", summary="获取当前操作ID", description="获取网络当前的操作ID")
-async def get_current_operation_id_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")) -> int:
-    """
-    获取当前操作ID
-    
-    返回网络当前正在执行的操作ID
-    """
-    return get_current_operation(network)
-
-@router.post("/undo/", summary="撤销操作", description="撤销网络上最后的一个操作")
-async def undo_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")):
-    """
-    撤销操作
-    
-    撤销网络上最近执行的一个操作
-    """
-    return execute_undo(network)
-
-@router.post("/redo/", summary="重做操作", description="重做网络上被撤销的操作")
-async def redo_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")):
-    """
-    重做操作
-    
-    重做网络上被撤销的操作
-    """
-    return execute_redo(network)
-
-@router.get("/getsnapshots/", summary="获取快照列表", description="获取网络中的所有快照")
-async def list_snapshot_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[tuple[int, str]]:
-    """
-    获取快照列表
-    
-    返回网络中所有可用的快照及其信息
-    """
-    return list_snapshot(network)
-
-@router.get("/havesnapshot/", summary="检查快照是否存在", description="检查指定标签的快照是否存在")
-async def have_snapshot_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), tag: str = Query(..., description="快照标签")) -> bool:
-    """
-    检查快照是否存在
-    
-    返回指定标签的快照是否存在
-    """
-    return have_snapshot(network, tag)
-
-@router.get("/havesnapshotforoperation/", summary="检查操作快照是否存在", description="检查指定操作ID的快照是否存在")
-async def have_snapshot_for_operation_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), operation: int = Query(..., description="操作ID")) -> bool:
-    """
-    检查操作快照是否存在
-    
-    返回指定操作ID的快照是否存在
-    """
-    return have_snapshot_for_operation(network, operation)
-
-@router.get("/havesnapshotforcurrentoperation/", summary="检查当前操作快照是否存在", description="检查当前操作的快照是否存在")
-async def have_snapshot_for_current_operation_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")) -> bool:
-    """
-    检查当前操作快照是否存在
-    
-    返回当前操作的快照是否存在
-    """
-    return have_snapshot_for_current_operation(network)
-
-@router.post("/takesnapshotforoperation/", summary="为操作创建快照", description="为指定的操作创建快照")
-async def take_snapshot_for_operation_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"), 
-    operation: int = Query(..., description="操作ID"), 
-    tag: str = Query(..., description="快照标签")
-) -> None:
-    """
-    为操作创建快照
-    
-    为指定操作创建一个带标签的快照
-    """
-    return take_snapshot_for_operation(network, operation, tag)
-
-@router.post("/takesnapshotforcurrentoperation", summary="为当前操作创建快照", description="为当前操作创建快照")
-async def take_snapshot_for_current_operation_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), tag: str = Query(..., description="快照标签")) -> None:
-    """
-    为当前操作创建快照
-    
-    为网络当前操作创建一个快照
-    """
-    return take_snapshot_for_current_operation(network, tag)
-
-# 兼容旧拼写: takenapshotforcurrentoperation
-@router.post("/takenapshotforcurrentoperation", summary="为当前操作创建快照（兼容模式）", description="为当前操作创建快照（兼容旧的API路径）")
-async def take_snapshot_for_current_operation_legacy_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), tag: str = Query(..., description="快照标签")) -> None:
-    """
-    为当前操作创建快照（兼容模式）
-    
-    兼容旧的API路径，为网络当前操作创建一个快照
-    """
-    return take_snapshot_for_current_operation(network, tag)
-
-@router.post("/takesnapshot/", summary="创建快照", description="为网络创建一个快照")
-async def take_snapshot_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), tag: str = Query(..., description="快照标签")) -> None:
-    """
-    创建快照
-    
-    为网络创建一个带标签的快照
-    """
-    return take_snapshot(network, tag)
-
-@router.post("/picksnapshot/", summary="选择快照", description="选择并恢复到指定的快照", response_model=None)
-async def pick_snapshot_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), tag: str = Query(..., description="快照标签"), discard: bool = Query(False, description="是否丢弃当前更改")) -> ChangeSet:
-    """
-    选择快照
-    
-    选择并恢复到指定的快照
-    """
-    return pick_snapshot(network, tag, discard)
-
-@router.post("/pickoperation/", summary="选择操作", description="选择并恢复到指定的操作", response_model=None)
-async def pick_operation_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"), 
-    operation: int = Query(..., description="操作ID"), 
-    discard: bool = Query(False, description="是否丢弃当前更改")
-) -> ChangeSet:
-    """
-    选择操作
-    
-    选择并恢复到指定的操作
-    """
-    return pick_operation(network, operation, discard)
-
-@router.get("/syncwithserver/", summary="与服务器同步", description="将网络与服务器同步到指定操作", response_model=None)
-async def sync_with_server_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), operation: int = Query(..., description="目标操作ID")) -> ChangeSet:
-    """
-    与服务器同步
-    
-    将网络与服务器同步到指定的操作
-    """
-    return sync_with_server(network, operation)
-
-@router.post("/batch/", summary="执行批量命令", description="执行多个网络操作命令", response_model=None)
-async def execute_batch_commands_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), req: Request = None) -> ChangeSet:
-    """
-    执行批量命令
-    
-    在网络上执行多个操作命令
-    """
-    jo_root = await req.json()
-    cs: ChangeSet = ChangeSet()
-    cs.operations = jo_root["operations"]
-    rcs = execute_batch_commands(network, cs)
-    return rcs
-
-@router.post("/compressedbatch/", summary="执行压缩批量命令", description="执行压缩的批量命令", response_model=None)
-async def execute_compressed_batch_commands_endpoint(
-    network: str = Query(..., description="管网名称（或数据库名称）"), 
-    req: Request = None
-) -> ChangeSet:
-    """
-    执行压缩批量命令
-    
-    执行压缩格式的批量命令
-    """
-    jo_root = await req.json()
-    cs: ChangeSet = ChangeSet()
-    cs.operations = jo_root["operations"]
-    return execute_batch_command(network, cs)
-
-@router.get("/getrestoreoperation/", summary="获取恢复操作ID", description="获取网络的恢复操作ID")
-async def get_restore_operation_endpoint(network: str = Query(..., description="管网名称（或数据库名称）")) -> int:
-    """
-    获取恢复操作ID
-    
-    返回网络的恢复操作ID
-    """
-    return get_restore_operation(network)
-
-@router.post("/setrestoreoperation/", summary="设置恢复操作ID", description="设置网络的恢复操作ID")
-async def set_restore_operation_endpoint(network: str = Query(..., description="管网名称（或数据库名称）"), operation: int = Query(..., description="操作ID")) -> None:
-    """
-    设置恢复操作ID
-    
-    设置网络的恢复操作ID
-    """
-    return set_restore_operation(network, operation)

app/api/v1/endpoints/timeseries/analysis.py

@@ -0,0 +1,61 @@
+from datetime import datetime
+from uuid import UUID
+
+from fastapi import APIRouter, Depends, HTTPException, Query
+from psycopg import AsyncConnection
+
+from app.infra.db.timescaledb.repositories.analysis import AnalysisResultsRepository
+
+from .dependencies import get_timescale_connection
+
+router = APIRouter()
+
+
+@router.get("/timeseries/analysis/runs/{run_id}/nodes/{node_id}")
+async def get_analysis_node_series(
+    run_id: UUID,
+    node_id: str,
+    start_time: datetime = Query(...),
+    end_time: datetime = Query(...),
+    field: str = Query(...),
+    conn: AsyncConnection = Depends(get_timescale_connection),
+):
+    try:
+        return await AnalysisResultsRepository.get_node_series(
+            conn, run_id, node_id, start_time, end_time, field
+        )
+    except ValueError as exc:
+        raise HTTPException(status_code=400, detail=str(exc)) from exc
+
+
+@router.get("/timeseries/analysis/runs/{run_id}/links/{link_id}")
+async def get_analysis_link_series(
+    run_id: UUID,
+    link_id: str,
+    start_time: datetime = Query(...),
+    end_time: datetime = Query(...),
+    field: str = Query(...),
+    conn: AsyncConnection = Depends(get_timescale_connection),
+):
+    try:
+        return await AnalysisResultsRepository.get_link_series(
+            conn, run_id, link_id, start_time, end_time, field
+        )
+    except ValueError as exc:
+        raise HTTPException(status_code=400, detail=str(exc)) from exc
+
+
+@router.get("/timeseries/analysis/runs/{run_id}/values")
+async def get_analysis_values_at_time(
+    run_id: UUID,
+    result_time: datetime = Query(...),
+    element_type: str = Query(..., pattern="^(node|link)$"),
+    field: str = Query(...),
+    conn: AsyncConnection = Depends(get_timescale_connection),
+):
+    try:
+        return await AnalysisResultsRepository.get_values_at_time(
+            conn, run_id, element_type, result_time, field
+        )
+    except ValueError as exc:
+        raise HTTPException(status_code=400, detail=str(exc)) from exc

app/api/v1/endpoints/timeseries/composite.py

@@ -2,194 +2,36 @@ from fastapi import APIRouter, Depends, HTTPException, Query
 from datetime import datetime
 from psycopg import AsyncConnection
 
-from app.infra.db.timescaledb.composite_queries import CompositeQueries
+from app.services.timeseries_analysis import TimeseriesAnalysisService
+from app.domain.schemas.timeseries_history import (
+    ElementHistoryQuery,
+    ElementHistoryResponse,
+)
+from app.services.timeseries_history import TimeseriesHistoryService
 from .dependencies import get_timescale_connection, get_postgres_connection
 
 router = APIRouter()
 
 
-@router.get("/composite/scada-simulation", summary="获取SCADA关联的模拟数据",
-            tags=["复合查询"])
-async def get_scada_associated_simulation_data(
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    device_ids: str = Query(..., description="SCADA设备ID列表，逗号分隔"),
-    scheme_type: str = Query(None, description="方案类型，若为空则查询实时数据"),
-    scheme_name: str = Query(None, description="方案名称，若为空则查询实时数据"),
+@router.post(
+    "/timeseries/views/element-history/query",
+    summary="批量查询管网元素历史数据",
+    response_model=ElementHistoryResponse,
+)
+async def query_element_history(
+    payload: ElementHistoryQuery,
     timescale_conn: AsyncConnection = Depends(get_timescale_connection),
     postgres_conn: AsyncConnection = Depends(get_postgres_connection),
-):
-    """
-    获取SCADA关联的link/node模拟值
-    
-    根据传入的SCADA device_ids，找到关联的link/node，
-    并根据对应的type，查询对应的模拟数据。支持查询实时或方案数据。
-
-    Args:
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        device_ids: SCADA设备ID列表，用逗号分隔
-        scheme_type: 方案类型，若为空则查询实时数据
-        scheme_name: 方案名称，若为空则查询实时数据
-        timescale_conn: TimescaleDB连接
-        postgres_conn: PostgreSQL连接
-        
-    Returns:
-        SCADA关联的模拟数据
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误，未找到数据时返回404错误
-    """
+) -> ElementHistoryResponse:
     try:
-        device_ids_list = (
-            [id.strip() for id in device_ids.split(",") if id.strip()]
-            if device_ids
-            else []
+        return await TimeseriesHistoryService.query(
+            timescale_conn, postgres_conn, payload
         )
-
-        if scheme_type and scheme_name:
-            result = await CompositeQueries.get_scada_associated_scheme_simulation_data(
-                timescale_conn,
-                postgres_conn,
-                device_ids_list,
-                start_time,
-                end_time,
-                scheme_type,
-                scheme_name,
-            )
-        else:
-            result = (
-                await CompositeQueries.get_scada_associated_realtime_simulation_data(
-                    timescale_conn,
-                    postgres_conn,
-                    device_ids_list,
-                    start_time,
-                    end_time,
-                )
-            )
-        if result is None:
-            raise HTTPException(status_code=404, detail="No simulation data found")
-        return result
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
+    except ValueError as exc:
+        raise HTTPException(status_code=422, detail=str(exc)) from exc
 
 
-@router.get("/composite/element-simulation", summary="获取管网元素的模拟数据",
-            tags=["复合查询"])
-async def get_feature_simulation_data(
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    feature_infos: str = Query(
-        ..., description="特征信息，格式: id1:type1,id2:type2，type为pipe（管道）或junction（节点）"
-    ),
-    scheme_type: str = Query(None, description="方案类型，若为空则查询实时数据"),
-    scheme_name: str = Query(None, description="方案名称，若为空则查询实时数据"),
-    timescale_conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    获取link/node模拟值
-    
-    根据传入的featureInfos，找到关联的link/node，
-    并根据对应的type，查询对应的模拟数据。支持查询实时或方案数据。
-
-    Args:
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        feature_infos: 格式为 "element_id1:type1,element_id2:type2"
-                      例如: "P1:pipe,J1:junction"
-        scheme_type: 方案类型，若为空则查询实时数据
-        scheme_name: 方案名称，若为空则查询实时数据
-        timescale_conn: TimescaleDB连接
-        
-    Returns:
-        管网元素的模拟数据
-        
-    Raises:
-        HTTPException: 当feature_infos为空返回400错误，未找到数据返回404错误，其他错误返回400错误
-    """
-    try:
-        feature_infos_list = []
-        if feature_infos:
-            for item in feature_infos.split(","):
-                item = item.strip()
-                if ":" in item:
-                    element_id, element_type = item.split(":", 1)
-                    feature_infos_list.append(
-                        (element_id.strip(), element_type.strip())
-                    )
-
-        if not feature_infos_list:
-            raise HTTPException(status_code=400, detail="feature_infos cannot be empty")
-
-        if scheme_type and scheme_name:
-            result = await CompositeQueries.get_scheme_simulation_data(
-                timescale_conn,
-                feature_infos_list,
-                start_time,
-                end_time,
-                scheme_type,
-                scheme_name,
-            )
-        else:
-            result = await CompositeQueries.get_realtime_simulation_data(
-                timescale_conn,
-                feature_infos_list,
-                start_time,
-                end_time,
-            )
-
-        if result is None:
-            raise HTTPException(status_code=404, detail="No simulation data found")
-        return result
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.get("/composite/element-scada", summary="获取管网元素关联的SCADA监测数据",
-            tags=["复合查询"])
-async def get_element_associated_scada_data(
-    element_id: str = Query(..., description="管网元素ID（管道或节点）"),
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    use_cleaned: bool = Query(False, description="是否使用清洗后的数据"),
-    timescale_conn: AsyncConnection = Depends(get_timescale_connection),
-    postgres_conn: AsyncConnection = Depends(get_postgres_connection),
-):
-    """
-    获取link/node关联的SCADA监测值
-    
-    根据传入的link/node id，匹配SCADA信息，
-    如果存在关联的SCADA device_id，获取实际的监测数据。
-
-    Args:
-        element_id: 管网元素ID
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        use_cleaned: 是否使用清洗后的数据，默认为False使用原始数据
-        timescale_conn: TimescaleDB连接
-        postgres_conn: PostgreSQL连接
-        
-    Returns:
-        管网元素关联的SCADA监测数据
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误，未找到关联数据返回404错误
-    """
-    try:
-        result = await CompositeQueries.get_element_associated_scada_data(
-            timescale_conn, postgres_conn, element_id, start_time, end_time, use_cleaned
-        )
-        if result is None:
-            raise HTTPException(
-                status_code=404, detail="No associated SCADA data found"
-            )
-        return result
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.post("/composite/clean-scada", summary="清洗SCADA监测数据",
-             tags=["复合查询"])
+@router.post("/timeseries/scada-cleaning-runs", summary="清洗SCADA监测数据")
 async def clean_scada_data(
     device_ids: str = Query(..., description="设备ID列表或 'all' 表示清洗所有设备"),
     start_time: datetime = Query(..., description="清洗数据的开始时间"),
@@ -225,19 +67,18 @@ async def clean_scada_data(
                 if device_ids
                 else []
             )
-        return await CompositeQueries.clean_scada_data(
+        return await TimeseriesAnalysisService.clean_scada_data(
             timescale_conn, postgres_conn, device_ids_list, start_time, end_time
         )
     except ValueError as e:
         raise HTTPException(status_code=400, detail=str(e))
 
 
-@router.get("/composite/pipeline-health-prediction", summary="预测管道健康状况",
-            tags=["复合查询"])
+@router.get("/pipeline-health-predictions", summary="预测管道健康状况")
 async def predict_pipeline_health(
     query_time: datetime = Query(..., description="查询时间"),
-    network_name: str = Query(..., description="管网名称（或数据库名称）"),
     timescale_conn: AsyncConnection = Depends(get_timescale_connection),
+    postgres_conn: AsyncConnection = Depends(get_postgres_connection),
 ):
     """
     预测管道健康状况
@@ -247,7 +88,6 @@ async def predict_pipeline_health(
 
     Args:
         query_time: 查询时间
-        network_name: 管网名称（或数据库名称）
         timescale_conn: TimescaleDB连接
 
     Returns:
@@ -257,8 +97,8 @@ async def predict_pipeline_health(
         HTTPException: 当模型文件不存在返回404错误，其他错误返回400或500错误
     """
     try:
-        return await CompositeQueries.predict_pipeline_health(
-            timescale_conn, network_name, query_time
+        return await TimeseriesAnalysisService.predict_pipeline_health(
+            timescale_conn, postgres_conn, query_time
         )
     except ValueError as e:
         raise HTTPException(status_code=400, detail=str(e))

app/api/v1/endpoints/timeseries/realtime.py

@@ -2,17 +2,43 @@ from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
 from typing import List
 from datetime import datetime
 from psycopg import AsyncConnection
+from pydantic import BaseModel
 
 from app.infra.db.timescaledb.repositories.realtime import RealtimeRepository
 from .dependencies import get_timescale_connection
 
 router = APIRouter()
 
+TIME_WITH_TZ_DESC = "ISO 8601 / RFC 3339 时间，必须显式带时区；可直接传 UTC+8，服务端会先转换为 UTC 再处理。"
+TIME_RANGE_START_DESC = f"时间范围开始时间。{TIME_WITH_TZ_DESC}"
+TIME_RANGE_END_DESC = f"时间范围结束时间。{TIME_WITH_TZ_DESC}"
 
-@router.post("/realtime/links/batch", status_code=201, summary="批量插入实时管道数据", 
-             tags=["时间序列-实时数据"])
+
+class RealtimeLinkBatchItem(BaseModel):
+    time: datetime
+    id: str
+    flow: float | None = None
+    friction: float | None = None
+    headloss: float | None = None
+    quality: float | None = None
+    reaction: float | None = None
+    setting: float | None = None
+    status: float | None = None
+    velocity: float | None = None
+
+
+class RealtimeNodeBatchItem(BaseModel):
+    time: datetime
+    id: str
+    actual_demand: float | None = None
+    total_head: float | None = None
+    pressure: float | None = None
+    quality: float | None = None
+
+
+@router.post("/timeseries/realtime/links/batches", status_code=201, summary="批量插入实时管道数据")
 async def insert_realtime_links(
-    data: List[dict] = Body(..., description="管道数据列表，每项包含管道ID、时间戳等信息"),
+    data: List[RealtimeLinkBatchItem] = Body(..., description="同一时间点的管道快照数据"),
     conn: AsyncConnection = Depends(get_timescale_connection)
 ):
     """
@@ -26,20 +52,27 @@ async def insert_realtime_links(
     Returns:
         插入成功的记录数
     """
-    await RealtimeRepository.insert_links_batch(conn, data)
+    await RealtimeRepository.insert_links_batch(
+        conn, [item.model_dump() for item in data]
+    )
     return {"message": f"Inserted {len(data)} records"}
 
 
-@router.get("/realtime/links", summary="查询实时管道数据", tags=["时间序列-实时数据"])
+@router.get(
+    "/timeseries/realtime/links",
+    summary="查询实时管道数据",
+    description="按时间范围查询实时管道数据。start_time 和 end_time 必须显式带时区；允许传 UTC+8，服务端会先归一化为 UTC 再执行查询。",
+)
 async def get_realtime_links(
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
+    start_time: datetime = Query(..., description=TIME_RANGE_START_DESC),
+    end_time: datetime = Query(..., description=TIME_RANGE_END_DESC),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
     查询指定时间范围内的实时管道数据
     
-    根据时间范围查询所有实时管道的监测值。
+    根据时间范围查询所有实时管道的监测值。传入时间必须显式包含时区，
+    可以直接使用 UTC+8，服务端会先统一转换为 UTC 再参与数据库查询。
     
     Args:
         start_time: 查询开始时间
@@ -51,10 +84,14 @@ async def get_realtime_links(
     return await RealtimeRepository.get_links_by_time_range(conn, start_time, end_time)
 
 
-@router.delete("/realtime/links", summary="删除实时管道数据", tags=["时间序列-实时数据"])
+@router.delete(
+    "/timeseries/realtime/links",
+    summary="删除实时管道数据",
+    description="按时间范围删除实时管道数据。start_time 和 end_time 必须显式带时区；允许传 UTC+8，服务端按请求中的绝对时间删除对应 UTC 数据。",
+)
 async def delete_realtime_links(
-    start_time: datetime = Query(..., description="删除开始时间"),
-    end_time: datetime = Query(..., description="删除结束时间"),
+    start_time: datetime = Query(..., description=TIME_RANGE_START_DESC),
+    end_time: datetime = Query(..., description=TIME_RANGE_END_DESC),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
@@ -73,11 +110,10 @@ async def delete_realtime_links(
     return {"message": "Deleted successfully"}
 
 
-@router.patch("/realtime/links/{link_id}/field", summary="更新实时管道字段", 
-              tags=["时间序列-实时数据"])
+@router.patch("/timeseries/realtime/links/{link_id}/field", summary="更新实时管道字段")
 async def update_realtime_link_field(
     link_id: str = Path(..., description="管道ID"),
-    time: datetime = Query(..., description="更新数据的时间戳"),
+    time: datetime = Query(..., description=f"要更新记录的时间戳。{TIME_WITH_TZ_DESC}"),
     field: str = Query(..., description="要更新的字段名称"),
     value: float = Query(..., description="更新的字段值"),
     conn: AsyncConnection = Depends(get_timescale_connection),
@@ -106,10 +142,9 @@ async def update_realtime_link_field(
         raise HTTPException(status_code=400, detail=str(e))
 
 
-@router.post("/realtime/nodes/batch", status_code=201, summary="批量插入实时节点数据",
-             tags=["时间序列-实时数据"])
+@router.post("/timeseries/realtime/nodes/batches", status_code=201, summary="批量插入实时节点数据")
 async def insert_realtime_nodes(
-    data: List[dict] = Body(..., description="节点数据列表，每项包含节点ID、时间戳等信息"),
+    data: List[RealtimeNodeBatchItem] = Body(..., description="同一时间点的节点快照数据"),
     conn: AsyncConnection = Depends(get_timescale_connection)
 ):
     """
@@ -123,20 +158,27 @@ async def insert_realtime_nodes(
     Returns:
         插入成功的记录数
     """
-    await RealtimeRepository.insert_nodes_batch(conn, data)
+    await RealtimeRepository.insert_nodes_batch(
+        conn, [item.model_dump() for item in data]
+    )
     return {"message": f"Inserted {len(data)} records"}
 
 
-@router.get("/realtime/nodes", summary="查询实时节点数据", tags=["时间序列-实时数据"])
+@router.get(
+    "/timeseries/realtime/nodes",
+    summary="查询实时节点数据",
+    description="按时间范围查询实时节点数据。start_time 和 end_time 必须显式带时区；允许传 UTC+8，服务端会先归一化为 UTC 再执行查询。",
+)
 async def get_realtime_nodes(
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
+    start_time: datetime = Query(..., description=TIME_RANGE_START_DESC),
+    end_time: datetime = Query(..., description=TIME_RANGE_END_DESC),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
     查询指定时间范围内的实时节点数据
     
-    根据时间范围查询所有实时节点的监测值。
+    根据时间范围查询所有实时节点的监测值。传入时间必须显式包含时区，
+    可以直接使用 UTC+8，服务端会先统一转换为 UTC 再参与数据库查询。
     
     Args:
         start_time: 查询开始时间
@@ -148,10 +190,14 @@ async def get_realtime_nodes(
     return await RealtimeRepository.get_nodes_by_time_range(conn, start_time, end_time)
 
 
-@router.delete("/realtime/nodes", summary="删除实时节点数据", tags=["时间序列-实时数据"])
+@router.delete(
+    "/timeseries/realtime/nodes",
+    summary="删除实时节点数据",
+    description="按时间范围删除实时节点数据。start_time 和 end_time 必须显式带时区；允许传 UTC+8，服务端按请求中的绝对时间删除对应 UTC 数据。",
+)
 async def delete_realtime_nodes(
-    start_time: datetime = Query(..., description="删除开始时间"),
-    end_time: datetime = Query(..., description="删除结束时间"),
+    start_time: datetime = Query(..., description=TIME_RANGE_START_DESC),
+    end_time: datetime = Query(..., description=TIME_RANGE_END_DESC),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
@@ -172,12 +218,11 @@ async def delete_realtime_nodes(
 
 
 
-@router.post("/realtime/simulation/store", status_code=201, summary="存储实时模拟结果",
-             tags=["时间序列-实时数据"])
+@router.post("/timeseries/realtime/simulation-results", status_code=201, summary="存储实时模拟结果")
 async def store_realtime_simulation_result(
     node_result_list: List[dict] = Body(..., description="节点模拟结果列表"),
     link_result_list: List[dict] = Body(..., description="管道模拟结果列表"),
-    result_start_time: str = Query(..., description="模拟结果开始时间"),
+    result_start_time: str = Query(..., description=f"模拟结果开始时间。{TIME_WITH_TZ_DESC}"),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
@@ -199,10 +244,13 @@ async def store_realtime_simulation_result(
     return {"message": "Simulation results stored successfully"}
 
 
-@router.get("/realtime/query/by-time-property", summary="按时间和属性查询实时数据",
-            tags=["时间序列-实时数据"])
+@router.get(
+    "/timeseries/realtime/records",
+    summary="按时间和属性查询实时数据",
+    description="查询指定时间点的实时属性值。query_time 必须显式带时区；允许传 UTC+8，服务端会先归一化为 UTC 再执行查询。",
+)
 async def query_realtime_records_by_time_property(
-    query_time: str = Query(..., description="查询时间"),
+    query_time: str = Query(..., description=f"查询时间。{TIME_WITH_TZ_DESC}"),
     type: str = Query(..., description="数据类型，pipe（管道）或 junction（节点）"),
     property: str = Query(..., description="要查询的属性名称"),
     conn: AsyncConnection = Depends(get_timescale_connection),
@@ -232,12 +280,15 @@ async def query_realtime_records_by_time_property(
         raise HTTPException(status_code=400, detail=str(e))
 
 
-@router.get("/realtime/query/by-id-time", summary="按ID和时间查询实时模拟数据",
-            tags=["时间序列-实时数据"])
+@router.get(
+    "/timeseries/realtime/simulation-results",
+    summary="按ID和时间查询实时模拟数据",
+    description="查询指定元素在某一时间点的实时模拟结果。query_time 必须显式带时区；允许传 UTC+8，服务端会先归一化为 UTC 再执行查询。",
+)
 async def query_realtime_simulation_by_id_time(
     id: str = Query(..., description="元素ID（管道ID或节点ID）"),
     type: str = Query(..., description="元素类型，pipe（管道）或 junction（节点）"),
-    query_time: str = Query(..., description="查询时间"),
+    query_time: str = Query(..., description=f"查询时间。{TIME_WITH_TZ_DESC}"),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """

app/api/v1/endpoints/timeseries/scada.py

@@ -2,52 +2,89 @@ from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
 from typing import List
 from datetime import datetime
 from psycopg import AsyncConnection
+from pydantic import BaseModel, Field, field_validator
 
+from app.infra.db.postgresql.scada import ScadaInfoRepository
 from app.infra.db.timescaledb.repositories.scada import ScadaRepository
-from .dependencies import get_timescale_connection
+from .dependencies import get_postgres_connection, get_timescale_connection
 
 router = APIRouter()
+SCADA_BATCH_MAX_ITEMS = 10_000
 
 
-@router.post("/scada/batch", status_code=201, summary="批量插入SCADA监测数据",
-             tags=["时间序列-监测数据"])
+class ScadaReadingBatchItem(BaseModel):
+    time: datetime
+    device_id: str = Field(min_length=1)
+    monitored_value: float | None = None
+    cleaned_value: float | None = None
+
+    @field_validator("device_id")
+    @classmethod
+    def normalize_device_id(cls, value: str) -> str:
+        normalized = value.strip()
+        if not normalized:
+            raise ValueError("device_id must not be blank")
+        return normalized
+
+
+@router.post("/timeseries/scada-readings/batches", status_code=201, summary="批量插入SCADA监测数据")
 async def insert_scada_data(
-    data: List[dict] = Body(..., description="SCADA设备监测数据列表"),
-    conn: AsyncConnection = Depends(get_timescale_connection)
+    data: List[ScadaReadingBatchItem] = Body(
+        ...,
+        min_length=1,
+        max_length=SCADA_BATCH_MAX_ITEMS,
+        description="SCADA设备监测数据列表",
+    ),
+    conn: AsyncConnection = Depends(get_timescale_connection),
+    postgres_conn: AsyncConnection = Depends(get_postgres_connection),
 ):
     """
     批量插入SCADA监测数据
-    
+
     将多个设备的实时监测数据批量插入时间序列数据库。
-    
+
     Args:
         data: SCADA设备监测数据列表，每项包含device_id、时间戳和监测值等信息
-        
+
     Returns:
         插入成功的记录数
     """
-    await ScadaRepository.insert_scada_batch(conn, data)
+    rows = [item.model_dump() for item in data]
+    requested_ids = list(dict.fromkeys(item["device_id"] for item in rows))
+    existing_ids = await ScadaInfoRepository.get_existing_device_ids(
+        postgres_conn, requested_ids
+    )
+    missing_ids = [
+        device_id for device_id in requested_ids if device_id not in existing_ids
+    ]
+    if missing_ids:
+        raise HTTPException(
+            status_code=422,
+            detail=f"SCADA devices do not exist in BizDB: {', '.join(missing_ids)}",
+        )
+    await ScadaRepository.insert_scada_batch(conn, rows)
     return {"message": f"Inserted {len(data)} records"}
 
 
-@router.get("/scada/by-ids-time-range", summary="按设备ID和时间范围查询SCADA数据",
-            tags=["时间序列-监测数据"])
+@router.get("/timeseries/scada-readings", summary="按设备ID和时间范围查询SCADA数据")
 async def get_scada_by_ids_time_range(
     start_time: datetime = Query(..., description="查询开始时间"),
     end_time: datetime = Query(..., description="查询结束时间"),
-    device_ids: str = Query(..., description="设备ID列���，逗号分隔，如 'device1,device2,device3'"),
+    device_ids: str = Query(
+        ..., description="设备ID列表，逗号分隔，如 'device1,device2,device3'"
+    ),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
     按设备ID和时间范围查询SCADA监测数据
-    
+
     查询多个设备在指定时间范围内的所有监测数据。
-    
+
     Args:
         start_time: 查询开始时间
         end_time: 查询结束时间
         device_ids: 设备ID列表，用逗号分隔
-        
+
     Returns:
         SCADA监测数据列表
     """
@@ -59,29 +96,32 @@ async def get_scada_by_ids_time_range(
     )
 
 
-@router.get("/scada/by-ids-field-time-range", summary="按设备ID、字段和时间范围查询SCADA数据",
-            tags=["时间序列-监测数据"])
+@router.get(
+    "/timeseries/scada-readings/fields", summary="按设备ID、字段和时间范围查询SCADA数据"
+)
 async def get_scada_field_by_ids_time_range(
     start_time: datetime = Query(..., description="查询开始时间"),
     end_time: datetime = Query(..., description="查询结束时间"),
     field: str = Query(..., description="要查询的字段名称"),
-    device_ids: str = Query(..., description="设备ID列表，逗号分隔，如 'device1,device2,device3'"),
+    device_ids: str = Query(
+        ..., description="设备ID列表，逗号分隔，如 'device1,device2,device3'"
+    ),
     conn: AsyncConnection = Depends(get_timescale_connection),
 ):
     """
     按设备ID、字段和时间范围查询特定SCADA数据
-    
+
     查询多个设备在指定时间范围内的特定字段监测数据。
-    
+
     Args:
         start_time: 查询开始时间
         end_time: 查询结束时间
         field: 字段名称
         device_ids: 设备ID列表，用逗号分隔
-        
+
     Returns:
         SCADA字段数据列表
-        
+
     Raises:
         HTTPException: 当字段不存在或查询参数无效时返回400错误
     """
@@ -98,8 +138,7 @@ async def get_scada_field_by_ids_time_range(
         raise HTTPException(status_code=400, detail=str(e))
 
 
-@router.patch("/scada/{device_id}/field", summary="更新SCADA设备字段",
-              tags=["时间序列-监测数据"])
+@router.patch("/timeseries/scada-readings/{device_id}/field", summary="更新SCADA设备字段")
 async def update_scada_field(
     device_id: str = Path(..., description="设备ID"),
     time: datetime = Query(..., description="更新数据的时间戳"),
@@ -109,18 +148,18 @@ async def update_scada_field(
 ):
     """
     更新指定设备的字段值
-    
+
     更新SCADA设备在特定时间的某个字段监测数据。
-    
+
     Args:
         device_id: 设备ID
         time: 数据时间戳
         field: 字段名称
         value: 字段新值
-        
+
     Returns:
         更新结果信息
-        
+
     Raises:
         HTTPException: 当字段不存在或更新失败时返回400错误
     """
@@ -131,8 +170,7 @@ async def update_scada_field(
         raise HTTPException(status_code=400, detail=str(e))
 
 
-@router.delete("/scada/by-id-time-range", summary="按设备ID和时间范围删除SCADA数据",
-               tags=["时间序列-监测数据"])
+@router.delete("/timeseries/scada-readings", summary="按设备ID和时间范围删除SCADA数据")
 async def delete_scada_data(
     device_id: str = Query(..., description="设备ID"),
     start_time: datetime = Query(..., description="删除开始时间"),
@@ -141,14 +179,14 @@ async def delete_scada_data(
 ):
     """
     删除指定设备和时间范围内的SCADA数据
-    
+
     删除在指定时间范围内的特定设备监测数据。
-    
+
     Args:
         device_id: 设备ID
         start_time: 删除开始时间
         end_time: 删除结束时间
-        
+
     Returns:
         删除结果信息
     """

app/api/v1/endpoints/timeseries/scheme.py

@@ -1,398 +0,0 @@
-from fastapi import APIRouter, Depends, HTTPException, Query, Path, Body
-from typing import List
-from datetime import datetime
-from psycopg import AsyncConnection
-
-from app.infra.db.timescaledb.repositories.scheme import SchemeRepository
-from .dependencies import get_timescale_connection
-
-router = APIRouter()
-
-
-@router.post("/scheme/links/batch", status_code=201, summary="批量插入方案管道数据",
-             tags=["时间序列-方案数据"])
-async def insert_scheme_links(
-    data: List[dict] = Body(..., description="方案管道数据列表"),
-    conn: AsyncConnection = Depends(get_timescale_connection)
-):
-    """
-    批量插入方案管道数据
-    
-    将特定方案的管道模拟数据批量插入时间序列数据库。
-    
-    Args:
-        data: 方案管道数据列表
-        
-    Returns:
-        插入成功的记录数
-    """
-    await SchemeRepository.insert_links_batch(conn, data)
-    return {"message": f"Inserted {len(data)} records"}
-
-
-@router.get("/scheme/links", summary="查询方案管道数据", tags=["时间序列-方案数据"])
-async def get_scheme_links(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    查询指定方案和时间范围内的管道数据
-    
-    根据方案和时间范围查询管道的模拟值。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        
-    Returns:
-        方案管道数据列表
-    """
-    return await SchemeRepository.get_links_by_scheme_and_time_range(
-        conn, scheme_type, scheme_name, start_time, end_time
-    )
-
-
-@router.get("/scheme/links/{link_id}/field", summary="查询方案管道字段数据",
-            tags=["时间序列-方案数据"])
-async def get_scheme_link_field(
-    link_id: str = Path(..., description="管道ID"),
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    field: str = Query(..., description="要查询的字段名称"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    查询指定方案管道的特定字段数据
-    
-    查询特定方案中指定管道在时间范围内的特定字段值。
-    
-    Args:
-        link_id: 管道ID
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        field: 字段名称
-        
-    Returns:
-        字段数据列表
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误
-    """
-    try:
-        return await SchemeRepository.get_link_field_by_scheme_and_time_range(
-            conn, scheme_type, scheme_name, start_time, end_time, link_id, field
-        )
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.patch("/scheme/links/{link_id}/field", summary="更新方案管道字段",
-              tags=["时间序列-方案数据"])
-async def update_scheme_link_field(
-    link_id: str = Path(..., description="管道ID"),
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    time: datetime = Query(..., description="更新数据的时间戳"),
-    field: str = Query(..., description="要更新的字段名称"),
-    value: float = Query(..., description="更新的字段值"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    更新指定方案管道的字段值
-    
-    更新特定方案中指定管道在某个时间的字段数据。
-    
-    Args:
-        link_id: 管道ID
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        time: 数据时间戳
-        field: 字段名称
-        value: 字段新值
-        
-    Returns:
-        更新结果信息
-        
-    Raises:
-        HTTPException: 当字段不存在或更新失败时返回400错误
-    """
-    try:
-        await SchemeRepository.update_link_field(
-            conn, time, scheme_type, scheme_name, link_id, field, value
-        )
-        return {"message": "Updated successfully"}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.delete("/scheme/links", summary="删除方案管道数据", tags=["时间序列-方案数据"])
-async def delete_scheme_links(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    start_time: datetime = Query(..., description="删除开始时间"),
-    end_time: datetime = Query(..., description="删除结束时间"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    删除指定方案和时间范围内的管道数据
-    
-    删除在指定方案和时间范围内的所有管道模拟数据。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        start_time: 删除开始时间
-        end_time: 删除结束时间
-        
-    Returns:
-        删除结果信息
-    """
-    await SchemeRepository.delete_links_by_scheme_and_time_range(
-        conn, scheme_type, scheme_name, start_time, end_time
-    )
-    return {"message": "Deleted successfully"}
-
-
-@router.post("/scheme/nodes/batch", status_code=201, summary="批量插入方案节点数据",
-             tags=["时间序列-方案数据"])
-async def insert_scheme_nodes(
-    data: List[dict] = Body(..., description="方案节点数据列表"),
-    conn: AsyncConnection = Depends(get_timescale_connection)
-):
-    """
-    批量插入方案节点数据
-    
-    将特定方案的节点模拟数据批量插入时间序列数据库。
-    
-    Args:
-        data: 方案节点数据列表
-        
-    Returns:
-        插入成功的记录数
-    """
-    await SchemeRepository.insert_nodes_batch(conn, data)
-    return {"message": f"Inserted {len(data)} records"}
-
-
-@router.get("/scheme/nodes/{node_id}/field", summary="查询方案节点字段数据",
-            tags=["时间序列-方案数据"])
-async def get_scheme_node_field(
-    node_id: str = Path(..., description="节点ID"),
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    start_time: datetime = Query(..., description="查询开始时间"),
-    end_time: datetime = Query(..., description="查询结束时间"),
-    field: str = Query(..., description="要查询的字段名称"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    查询指定方案节点的特定字段数据
-    
-    查询特定方案中指定节点在时间范围内的特定字段值。
-    
-    Args:
-        node_id: 节点ID
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        start_time: 查询开始时间
-        end_time: 查询结束时间
-        field: 字段名称
-        
-    Returns:
-        字段数据列表
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误
-    """
-    try:
-        return await SchemeRepository.get_node_field_by_scheme_and_time_range(
-            conn, scheme_type, scheme_name, start_time, end_time, node_id, field
-        )
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.patch("/scheme/nodes/{node_id}/field", summary="更新方案节点字段",
-              tags=["时间序列-方案数据"])
-async def update_scheme_node_field(
-    node_id: str = Path(..., description="节点ID"),
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    time: datetime = Query(..., description="更新数据的时间戳"),
-    field: str = Query(..., description="要更新的字段名称"),
-    value: float = Query(..., description="更新的字段值"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    更新指定方案节点的字段值
-    
-    更新特定方案中指定节点在某个时间的字段数据。
-    
-    Args:
-        node_id: 节点ID
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        time: 数据时间戳
-        field: 字段名称
-        value: 字段新值
-        
-    Returns:
-        更新结果信息
-        
-    Raises:
-        HTTPException: 当字段不存在或更新失败时返回400错误
-    """
-    try:
-        await SchemeRepository.update_node_field(
-            conn, time, scheme_type, scheme_name, node_id, field, value
-        )
-        return {"message": "Updated successfully"}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.delete("/scheme/nodes", summary="删除方案节点数据", tags=["时间序列-方案数据"])
-async def delete_scheme_nodes(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    start_time: datetime = Query(..., description="删除开始时间"),
-    end_time: datetime = Query(..., description="删除结束时间"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    删除指定方案和时间范围内的节点数据
-    
-    删除在指定方案和时间范围内的所有节点模拟数据。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        start_time: 删除开始时间
-        end_time: 删除结束时间
-        
-    Returns:
-        删除结果信息
-    """
-    await SchemeRepository.delete_nodes_by_scheme_and_time_range(
-        conn, scheme_type, scheme_name, start_time, end_time
-    )
-    return {"message": "Deleted successfully"}
-
-
-@router.post("/scheme/simulation/store", status_code=201, summary="存储方案模拟结果",
-             tags=["时间序列-方案数据"])
-async def store_scheme_simulation_result(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    node_result_list: List[dict] = Body(..., description="节点模拟结果列表"),
-    link_result_list: List[dict] = Body(..., description="管道模拟结果列表"),
-    result_start_time: str = Query(..., description="模拟结果开始时间"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    存储方案模拟结果到时间序列数据库
-    
-    将特定方案的节点和管道模拟计算结果批量存储到TimescaleDB数据库。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        node_result_list: 节点模拟结果列表
-        link_result_list: 管道模拟结果列表
-        result_start_time: 模拟结果对应的起始时间
-        
-    Returns:
-        存储结果信息
-    """
-    await SchemeRepository.store_scheme_simulation_result(
-        conn,
-        scheme_type,
-        scheme_name,
-        node_result_list,
-        link_result_list,
-        result_start_time,
-    )
-    return {"message": "Scheme simulation results stored successfully"}
-
-
-@router.get("/scheme/query/by-scheme-time-property", summary="按方案、时间和属性查询数据",
-            tags=["时间序列-方案数据"])
-async def query_scheme_records_by_scheme_time_property(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    query_time: str = Query(..., description="查询时间"),
-    type: str = Query(..., description="元素类型，pipe（管道）或 junction（节点）"),
-    property: str = Query(..., description="要查询的属性名称"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    按指定方案、时间和属性查询所有方案数据
-    
-    查询在特定方案和时间点，所有指定类型元素的特定属性值。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        query_time: 查询时间
-        type: 元素类型（pipe或junction）
-        property: 属性名称
-        
-    Returns:
-        查询结果列表
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误
-    """
-    try:
-        results = await SchemeRepository.query_all_record_by_scheme_time_property(
-            conn, scheme_type, scheme_name, query_time, type, property
-        )
-        return {"results": results}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-
-
-@router.get("/scheme/query/by-id-time", summary="按ID和时间查询方案模拟数据",
-            tags=["时间序列-方案数据"])
-async def query_scheme_simulation_by_id_time(
-    scheme_type: str = Query(..., description="方案类型"),
-    scheme_name: str = Query(..., description="方案名称"),
-    id: str = Query(..., description="元素ID（管道ID或节点ID）"),
-    type: str = Query(..., description="元素类型，pipe（管道）或 junction（节点）"),
-    query_time: str = Query(..., description="查询时间"),
-    conn: AsyncConnection = Depends(get_timescale_connection),
-):
-    """
-    按指定ID和时间查询方案模拟结果
-    
-    查询特定方案中的元素在某一时间点的模拟数据。
-    
-    Args:
-        scheme_type: 方案类型
-        scheme_name: 方案名称
-        id: 元素ID
-        type: 元素类型（pipe或junction）
-        query_time: 查询时间
-        
-    Returns:
-        模拟结果数据
-        
-    Raises:
-        HTTPException: 当查询参数无效时返回400错误
-    """
-    try:
-        result = await SchemeRepository.query_scheme_simulation_result_by_id_time(
-            conn, scheme_type, scheme_name, id, type, query_time
-        )
-        return {"result": result}
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))

app/api/v1/endpoints/user_management.py

@@ -1,215 +0,0 @@
-"""
-用户管理 API 接口
-
-演示权限控制的使用
-"""
-
-from typing import List
-from fastapi import APIRouter, Depends, HTTPException, status, Path, Query
-from app.domain.schemas.user import UserResponse, UserUpdate, UserCreate
-from app.domain.models.role import UserRole
-from app.domain.schemas.user import UserInDB
-from app.infra.db.metadb.repositories.user_repository import UserRepository
-from app.auth.dependencies import get_user_repository, get_current_active_user
-from app.auth.permissions import get_current_admin, require_role, check_resource_owner
-
-router = APIRouter()
-
-
-@router.get(
-    "/",
-    summary="列出所有用户",
-    description="获取用户列表（仅管理员）",
-    response_model=List[UserResponse],
-)
-async def list_users(
-    skip: int = Query(0, ge=0, description="跳过的用户数"),
-    limit: int = Query(100, ge=1, le=1000, description="返回的最大用户数"),
-    current_user: UserInDB = Depends(require_role(UserRole.ADMIN)),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> List[UserResponse]:
-    """
-    获取用户列表
-
-    获取系统中所有的用户信息（需要管理员权限）
-    """
-    users = await user_repo.get_all_users(skip=skip, limit=limit)
-    return [UserResponse.model_validate(user) for user in users]
-
-
-@router.get(
-    "/{user_id}",
-    summary="获取用户详情",
-    description="获取指定用户的详细信息",
-    response_model=UserResponse,
-)
-async def get_user(
-    user_id: int = Path(..., gt=0, description="用户ID"),
-    current_user: UserInDB = Depends(get_current_active_user),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> UserResponse:
-    """
-    获取用户详情
-
-    管理员可查看所有用户，普通用户只能查看自己
-    """
-    # 检查权限
-    if not check_resource_owner(user_id, current_user):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="You don't have permission to view this user",
-        )
-
-    user = await user_repo.get_user_by_id(user_id)
-    if not user:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="User not found"
-        )
-
-    return UserResponse.model_validate(user)
-
-
-@router.put(
-    "/{user_id}",
-    summary="更新用户信息",
-    description="更新指定用户的信息",
-    response_model=UserResponse,
-)
-async def update_user(
-    user_id: int = Path(..., gt=0, description="用户ID"),
-    user_update: UserUpdate = None,
-    current_user: UserInDB = Depends(get_current_active_user),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> UserResponse:
-    """
-    更新用户信息
-
-    管理员可更新所有用户，普通用户只能更新自己（且不能修改角色）
-    """
-    # 检查用户是否存在
-    target_user = await user_repo.get_user_by_id(user_id)
-    if not target_user:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="User not found"
-        )
-
-    # 权限检查
-    is_owner = current_user.id == user_id
-    is_admin = UserRole(current_user.role).has_permission(UserRole.ADMIN)
-
-    if not is_owner and not is_admin:
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="You don't have permission to update this user",
-        )
-
-    # 非管理员不能修改角色和激活状态
-    if not is_admin:
-        if user_update.role is not None:
-            raise HTTPException(
-                status_code=status.HTTP_403_FORBIDDEN,
-                detail="Only admins can change user roles",
-            )
-        if user_update.is_active is not None:
-            raise HTTPException(
-                status_code=status.HTTP_403_FORBIDDEN,
-                detail="Only admins can change user active status",
-            )
-
-    # 更新用户
-    updated_user = await user_repo.update_user(user_id, user_update)
-    if not updated_user:
-        raise HTTPException(
-            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="Failed to update user",
-        )
-
-    return UserResponse.model_validate(updated_user)
-
-
-@router.delete("/{user_id}", summary="删除用户", description="删除指定用户（仅管理员）")
-async def delete_user(
-    user_id: int = Path(..., gt=0, description="用户ID"),
-    current_user: UserInDB = Depends(get_current_admin),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> dict:
-    """
-    删除用户
-
-    删除指定用户（需要管理员权限，不能删除自己）
-    """
-    # 不能删除自己
-    if current_user.id == user_id:
-        raise HTTPException(
-            status_code=status.HTTP_400_BAD_REQUEST,
-            detail="You cannot delete your own account",
-        )
-
-    success = await user_repo.delete_user(user_id)
-    if not success:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="User not found"
-        )
-
-    return {"message": "User deleted successfully"}
-
-
-@router.post(
-    "/{user_id}/activate",
-    summary="激活用户",
-    description="激活指定用户账户（仅管理员）",
-    response_model=UserResponse,
-)
-async def activate_user(
-    user_id: int = Path(..., gt=0, description="用户ID"),
-    current_user: UserInDB = Depends(get_current_admin),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> UserResponse:
-    """
-    激活用户
-
-    激活指定用户的账户（需要管理员权限）
-    """
-    user_update = UserUpdate(is_active=True)
-    updated_user = await user_repo.update_user(user_id, user_update)
-
-    if not updated_user:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="User not found"
-        )
-
-    return UserResponse.model_validate(updated_user)
-
-
-@router.post(
-    "/{user_id}/deactivate",
-    summary="停用用户",
-    description="停用指定用户账户（仅管理员）",
-    response_model=UserResponse,
-)
-async def deactivate_user(
-    user_id: int = Path(..., gt=0, description="用户ID"),
-    current_user: UserInDB = Depends(get_current_admin),
-    user_repo: UserRepository = Depends(get_user_repository),
-) -> UserResponse:
-    """
-    停用用户
-
-    停用指定用户的账户（需要管理员权限，不能停用自己）
-    """
-    # 不能停用自己
-    if current_user.id == user_id:
-        raise HTTPException(
-            status_code=status.HTTP_400_BAD_REQUEST,
-            detail="You cannot deactivate your own account",
-        )
-
-    user_update = UserUpdate(is_active=False)
-    updated_user = await user_repo.update_user(user_id, user_update)
-
-    if not updated_user:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="User not found"
-        )
-
-    return UserResponse.model_validate(updated_user)

app/api/v1/endpoints/users.py

@@ -1,36 +0,0 @@
-from fastapi import APIRouter, Request, Query
-from typing import Any, List, Dict, Union
-from app.services.tjnetwork import Any, get_all_users, get_user, get_user_schema
-
-router = APIRouter()
-
-###########################################################
-# user 39
-###########################################################
-
-@router.get("/getuserschema/", summary="获取用户模式", description="获取指定网络的用户模式定义")
-async def fastapi_get_user_schema(network: str = Query(..., description="管网名称（或数据库名称）")) -> dict[str, dict[Any, Any]]:
-    """
-    获取用户模式定义
-    
-    返回指定网络的用户模式结构定义
-    """
-    return get_user_schema(network)
-
-@router.get("/getuser/", summary="获取单个用户", description="获取指定网络中的单个用户信息")
-async def fastapi_get_user(network: str = Query(..., description="管网名称（或数据库名称）"), user_name: str = Query(..., description="用户名")) -> dict[Any, Any]:
-    """
-    获取用户信息
-    
-    返回指定网络中指定用户名的详细信息
-    """
-    return get_user(network, user_name)
-
-@router.get("/getallusers/", summary="获取所有用户", description="获取指定网络的所有用户列表")
-async def fastapi_get_all_users(network: str = Query(..., description="管网名称（或数据库名称）")) -> list[dict[Any, Any]]:
-    """
-    获取所有用户列表
-    
-    返回指定网络中所有用户的信息
-    """
-    return get_all_users(network)

app/api/v1/endpoints/web_search.py

@@ -0,0 +1,29 @@
+from typing import Any
+
+from fastapi import APIRouter, HTTPException, status
+
+from app.services.web_search import (
+    BochaSearchAPIError,
+    BochaSearchConfigError,
+    WebSearchRequest,
+    search_bocha_web,
+)
+
+router = APIRouter()
+
+
+@router.post(
+    "/web-searches",
+    summary="Web Search",
+    description="调用 Bocha Web Search API 获取实时网页搜索结果",
+)
+async def web_search(request: WebSearchRequest) -> dict[str, Any]:
+    try:
+        return await search_bocha_web(request)
+    except BochaSearchConfigError as exc:
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail=str(exc),
+        ) from exc
+    except BochaSearchAPIError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.detail) from exc