暂存文件的引用修复

app/algorithms/api_ex/run_simulation.py

@@ -8,7 +8,7 @@ import json
 import pytz
 import requests
 import time
-import project_info
+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

app/algorithms/api_ex/sensitivity.py

@@ -19,7 +19,7 @@ from spopt.region import Skater
 from shapely.geometry import Point
 import geopandas as gpd
 from sklearn.metrics import pairwise_distances
-import project_info
+import app.services.project_info as project_info
 
 # 2025/03/12
 # Step1: 获取节点坐标

app/algorithms/api_ex/sensor_placement.py

@@ -12,7 +12,7 @@ from wntr.epanet.toolkit import EpanetException
 from numpy.linalg import slogdet
 import random
 from app.services.tjnetwork import *
-import project_info
+import app.services.project_info as project_info
 
 # 2025/03/12
 # Step1: 获取节点坐标

app/algorithms/online_Analysis.py

@@ -1,9 +1,9 @@
 import os
 from app.services.tjnetwork import *
 from app.native.api.project import copy_project
-from run_simulation import run_simulation_ex, from_clock_to_seconds_2
+from app.algorithms.api_ex.run_simulation import run_simulation_ex, from_clock_to_seconds_2
 from math import sqrt, pi
-from epanet.epanet import Output
+from app.services.epanet.epanet import Output
 import json
 from datetime import datetime
 import time
@@ -17,11 +17,11 @@ import app.services.simulation as simulation
 import geopandas as gpd
 from sqlalchemy import create_engine
 import ast
-import sensitivity
 import app.services.project_info as project_info
-import app.algorithms.api_ex.kmeans_sensor
-import app.algorithms.api_ex.Fdataclean
-import app.algorithms.api_ex.Pdataclean
+import app.algorithms.api_ex.kmeans_sensor as kmeans_sensor
+import app.algorithms.api_ex.Fdataclean as Fdataclean
+import app.algorithms.api_ex.Pdataclean as Pdataclean
+import app.algorithms.api_ex.sensitivity as sensitivity
 from app.native.api.postgresql_info import get_pgconn_string
 
 
@@ -1425,7 +1425,7 @@ def pressure_sensor_placement_kmeans(
     # dump_inp
     inp_name = f"./db_inp/{name}.db.inp"
     dump_inp(name, inp_name, "2")
-    sensor_location = api_ex.kmeans_sensor.kmeans_sensor_placement(
+    sensor_location = kmeans_sensor.kmeans_sensor_placement(
         name=name, sensor_num=sensor_number, min_diameter=min_diameter
     )
     try:
@@ -1475,7 +1475,7 @@ def flow_data_clean(input_csv_file: str) -> str:
     if not os.path.exists(input_csv_path):
         raise FileNotFoundError(f"指定的文件不存在: {input_csv_path}")
     # 调用 Fdataclean.clean_flow_data_kf 函数进行数据清洗
-    out_xlsx_path = api_ex.Fdataclean.clean_flow_data_kf(input_csv_path)
+    out_xlsx_path = Fdataclean.clean_flow_data_kf(input_csv_path)
     print("清洗后的数据已保存到:", out_xlsx_path)
 
 
@@ -1502,7 +1502,7 @@ def pressure_data_clean(input_csv_file: str) -> str:
     if not os.path.exists(input_csv_path):
         raise FileNotFoundError(f"指定的文件不存在: {input_csv_path}")
     # 调用 Fdataclean.clean_flow_data_kf 函数进行数据清洗
-    out_xlsx_path = api_ex.Pdataclean.clean_pressure_data_km(input_csv_path)
+    out_xlsx_path = Pdataclean.clean_pressure_data_km(input_csv_path)
     print("清洗后的数据已保存到:", out_xlsx_path)
 
 

app/api/v1/endpoints/data_query.py

@@ -5,7 +5,7 @@ import msgpack
 import datetime
 from app.services.tjnetwork import *
 from app.infra.db.influxdb import api as influxdb_api
-from app.infra.db import redis_client # Assuming redis_client is exposed or needs initialization
+from app.infra.cache.redis_client import redis_client # Assuming redis_client is exposed or needs initialization
 # If redis_client isn't in app.infra.db, we might need to initialize it here or import from main if it was global.
 # Given the instructions, we'll assume it needs to be imported or initialized.
 # For now, let's copy the redis initialization logic if it's not centralized, or better, 

app/api/v1/endpoints/simulation.py

@@ -14,18 +14,19 @@ from app.algorithms.online_Analysis import (
     flushing_analysis,
     contaminant_simulation,
     age_analysis,
-    scheduling_analysis,
+    # scheduling_analysis,
     pressure_regulation,
     project_management,
-    daily_scheduling_analysis,
+    # daily_scheduling_analysis,
     network_update,
-    pump_failure,
+    # pump_failure,
     pressure_sensor_placement_sensitivity,
     pressure_sensor_placement_kmeans,
 )
 
 router = APIRouter()
 
+
 # 必须用这个PlainTextResponse，不然每个key都有引号
 @router.get("/runproject/", response_class=PlainTextResponse)
 async def run_project_endpoint(network: str) -> str:
@@ -78,51 +79,73 @@ async def run_inp_endpoint(network: str) -> str:
 async def dump_output_endpoint(output: str) -> str:
     return dump_output(output)
 
+
 # Analysis Endpoints
 @router.get("/burstanalysis/")
-async def burst_analysis_endpoint(network: str, pipe_id: str, start_time: str, end_time: str, burst_flow: float):
+async def burst_analysis_endpoint(
+    network: str, pipe_id: str, start_time: str, end_time: str, burst_flow: float
+):
     return burst_analysis(network, pipe_id, start_time, end_time, burst_flow)
 
+
 @router.get("/valvecloseanalysis/")
-async def valve_close_analysis_endpoint(network: str, valve_id: str, start_time: str, end_time: str):
+async def valve_close_analysis_endpoint(
+    network: str, valve_id: str, start_time: str, end_time: str
+):
     return valve_close_analysis(network, valve_id, start_time, end_time)
 
+
 @router.get("/flushinganalysis/")
-async def flushing_analysis_endpoint(network: str, pipe_id: str, start_time: str, duration: float, flow: float):
+async def flushing_analysis_endpoint(
+    network: str, pipe_id: str, start_time: str, duration: float, flow: float
+):
     return flushing_analysis(network, pipe_id, start_time, duration, flow)
 
+
 @router.get("/contaminantsimulation/")
-async def contaminant_simulation_endpoint(network: str, node_id: str, start_time: str, duration: float, concentration: float):
+async def contaminant_simulation_endpoint(
+    network: str, node_id: str, start_time: str, duration: float, concentration: float
+):
     return contaminant_simulation(network, node_id, start_time, duration, concentration)
 
+
 @router.get("/ageanalysis/")
 async def age_analysis_endpoint(network: str):
     return age_analysis(network)
 
+
 @router.get("/schedulinganalysis/")
 async def scheduling_analysis_endpoint(network: str):
     return scheduling_analysis(network)
 
+
 @router.get("/pressureregulation/")
-async def pressure_regulation_endpoint(network: str, target_node: str, target_pressure: float):
+async def pressure_regulation_endpoint(
+    network: str, target_node: str, target_pressure: float
+):
     return pressure_regulation(network, target_node, target_pressure)
 
+
 @router.get("/projectmanagement/")
 async def project_management_endpoint(network: str):
     return project_management(network)
 
+
 @router.get("/dailyschedulinganalysis/")
 async def daily_scheduling_analysis_endpoint(network: str):
     return daily_scheduling_analysis(network)
 
+
 @router.get("/networkupdate/")
 async def network_update_endpoint(network: str):
     return network_update(network)
 
+
 @router.get("/pumpfailure/")
 async def pump_failure_endpoint(network: str, pump_id: str, time: str):
     return pump_failure(network, pump_id, time)
 
+
 @router.get("/pressuresensorplacementsensitivity/")
 async def pressure_sensor_placement_sensitivity_endpoint(
     name: str, scheme_name: str, sensor_number: int, min_diameter: int, username: str
@@ -131,6 +154,7 @@ async def pressure_sensor_placement_sensitivity_endpoint(
         name, scheme_name, sensor_number, min_diameter, username
     )
 
+
 @router.get("/pressuresensorplacementkmeans/")
 async def pressure_sensor_placement_kmeans_endpoint(
     name: str, scheme_name: str, sensor_number: int, min_diameter: int, username: str

app/infra/db/postgresql/internal_queries.py

@@ -2,7 +2,7 @@ import time
 from typing import List, Optional
 
 from fastapi.logger import logger
-import postgresql_info
+import app.native.api.postgresql_info as postgresql_info
 import psycopg
 
 

app/infra/db/timescaledb/composite_queries.py

@@ -4,15 +4,15 @@ from datetime import datetime, timedelta
 from psycopg import AsyncConnection
 import pandas as pd
 import numpy as np
-from api_ex.Fdataclean import clean_flow_data_df_kf
-from api_ex.Pdataclean import clean_pressure_data_df_km
-from api_ex.pipeline_health_analyzer import PipelineHealthAnalyzer
+from app.algorithms.api_ex.Fdataclean import clean_flow_data_df_kf
+from app.algorithms.api_ex.Pdataclean import clean_pressure_data_df_km
+from app.algorithms.api_ex.pipeline_health_analyzer import PipelineHealthAnalyzer
 
-from postgresql.internal_queries import InternalQueries
-from postgresql.scada_info import ScadaRepository as PostgreScadaRepository
-from timescaledb.schemas.realtime import RealtimeRepository
-from timescaledb.schemas.scheme import SchemeRepository
-from timescaledb.schemas.scada import ScadaRepository
+from app.infra.db.postgresql.internal_queries import InternalQueries
+from app.infra.db.postgresql.scada_info import ScadaRepository as PostgreScadaRepository
+from app.infra.db.timescaledb.schemas.realtime import RealtimeRepository
+from app.infra.db.timescaledb.schemas.scheme import SchemeRepository
+from app.infra.db.timescaledb.schemas.scada import ScadaRepository
 
 
 class CompositeQueries:

app/infra/db/timescaledb/internal_queries.py

@@ -1,13 +1,13 @@
 from typing import List
 
 from fastapi.logger import logger
-from timescaledb.schemas.scheme import SchemeRepository
-from timescaledb.schemas.realtime import RealtimeRepository
-import timescaledb.timescaledb_info as timescaledb_info
 from datetime import datetime, timedelta
-from timescaledb.schemas.scada import ScadaRepository
 import psycopg
 import time
+from app.infra.db.timescaledb.schemas.scheme import SchemeRepository
+from app.infra.db.timescaledb.schemas.realtime import RealtimeRepository
+import app.infra.db.timescaledb.timescaledb_info as timescaledb_info
+from app.infra.db.timescaledb.schemas.scada import ScadaRepository
 
 
 class InternalStorage:

app/infra/db/timescaledb/router.py

@@ -8,7 +8,7 @@ from .schemas.realtime import RealtimeRepository
 from .schemas.scheme import SchemeRepository
 from .schemas.scada import ScadaRepository
 from .composite_queries import CompositeQueries
-from postgresql.database import get_database_instance as get_postgres_database_instance
+from app.infra.db.postgresql.database import get_database_instance as get_postgres_database_instance
 
 router = APIRouter(prefix="/timescaledb", tags=["TimescaleDB"])
 

app/infra/db/timescaledb/schemas/scheme.py

@@ -2,7 +2,7 @@ from typing import List, Any, Dict
 from datetime import datetime, timedelta, timezone
 from collections import defaultdict
 from psycopg import AsyncConnection, Connection, sql
-import globals
+import app.services.globals as globals
 
 # 定义UTC+8时区
 UTC_8 = timezone(timedelta(hours=8))

app/services/simulation.py

@@ -11,7 +11,7 @@ import pytz
 import requests
 import time
 import shutil
-from epanet.epanet import Output
+from app.services.epanet.epanet import Output
 from typing import Optional, Tuple
 import app.infra.db.influxdb.api as influxdb_api
 import typing

scripts/run_server.py

@@ -1,7 +1,10 @@
 import asyncio
 import sys
+import os
 import uvicorn
 
+# 将项目根目录添加到 python 路径
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 
 if __name__ == "__main__":
     # Windows 设置事件循环策略
@@ -13,6 +16,6 @@ if __name__ == "__main__":
         "app.main:app",
         host="0.0.0.0",
         port=8000,
-        workers=2,  # 这里可以设置多进程
+        # workers=2,  # 这里可以设置多进程
         loop="asyncio",
     )