jiang
fa188af0b1
Reorganize WNDB by responsibility and remove legacy scheme endpoints.\n\nRoute analysis and time-series access through project pools, preserve transactional realtime replacement, and refresh GIS materialized views after writes.\n\nAdd database architecture documentation, live pooling coverage, API contract updates, and executable container verification.\n\nBREAKING CHANGE: legacy scheme APIs and flat app.native.wndb module imports are removed.
322 lines
13 KiB
Python
322 lines
13 KiB
Python
from typing import List
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from fastapi.logger import logger
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from datetime import datetime, timedelta
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from psycopg import sql
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from psycopg.rows import dict_row
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import time
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from app.infra.db.project_routing import get_project_timescale_pgconn_string
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from app.infra.db.timescaledb.sync_pool import timescale_connection
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from app.infra.db.timescaledb.repositories.analysis import AnalysisResultsRepository
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from app.infra.db.timescaledb.repositories.realtime import RealtimeRepository
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from app.infra.db.timescaledb.repositories.scada import ScadaRepository
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from app.services.time_api import parse_utc_time
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class InternalStorage:
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@staticmethod
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def store_realtime_simulation(
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node_result_list: List[dict],
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link_result_list: List[dict],
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result_start_time: str,
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db_name: str = None,
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max_retries: int = 3,
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):
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"""存储实时模拟结果"""
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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RealtimeRepository.store_realtime_simulation_result_sync(
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conn, node_result_list, link_result_list, result_start_time
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)
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break # 成功
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except Exception as e:
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logger.error(f"存储尝试 {attempt + 1} 失败: {e}")
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if attempt < max_retries - 1:
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time.sleep(1) # 重试前等待
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else:
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raise # 达到最大重试次数后抛出异常
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@staticmethod
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def store_analysis_simulation(
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run_id,
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node_result_list: List[dict],
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link_result_list: List[dict],
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result_start_time: str,
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num_periods: int = 1,
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result_timestep_seconds: int | None = None,
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db_name: str = None,
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max_retries: int = 3,
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):
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"""Store immutable simulation results for one analysis run."""
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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node_rows, link_rows = AnalysisResultsRepository.prepare_simulation_rows(
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node_result_list, link_result_list, result_start_time,
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num_periods, result_timestep_seconds or 3600,
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)
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AnalysisResultsRepository.store_results_sync(
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conn, run_id, node_rows, link_rows
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)
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break # 成功
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except Exception as e:
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logger.error(f"存储尝试 {attempt + 1} 失败: {e}")
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if attempt < max_retries - 1:
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time.sleep(1) # 重试前等待
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else:
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raise # 达到最大重试次数后抛出异常
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class InternalQueries:
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@staticmethod
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def query_scada_by_ids_time(
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device_ids: List[str],
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query_time: str,
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db_name: str = None,
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max_retries: int = 3,
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) -> dict:
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"""查询指定时间点的 SCADA 数据"""
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target_time = parse_utc_time(query_time, field_name="query_time")
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start_time = target_time - timedelta(seconds=1)
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end_time = target_time + timedelta(seconds=1)
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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rows = ScadaRepository.get_scada_by_ids_time_range_sync(
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conn, device_ids, start_time, end_time
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)
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# 处理结果，返回每个 device_id 的第一个值
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result = {}
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for device_id in device_ids:
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device_rows = [
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row for row in rows if row["device_id"] == device_id
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]
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if device_rows:
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result[device_id] = device_rows[0]["monitored_value"]
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else:
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result[device_id] = None
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return result
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except Exception as e:
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logger.error(f"查询尝试 {attempt + 1} 失败: {e}")
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if attempt < max_retries - 1:
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time.sleep(1)
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else:
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raise
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@staticmethod
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def query_scada_by_ids_timerange(
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device_ids: List[str],
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start_time: str | datetime,
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end_time: str | datetime,
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db_name: str = None,
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max_retries: int = 3,
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) -> dict[str, list[dict]]:
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"""查询指定时间窗的 SCADA 数据，返回 {device_id: [{time, value}, ...]}。"""
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start_dt = parse_utc_time(start_time, field_name="start_time")
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end_dt = parse_utc_time(end_time, field_name="end_time")
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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rows = ScadaRepository.get_scada_by_ids_time_range_sync(
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conn, device_ids, start_dt, end_dt
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)
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result: dict[str, list[dict]] = {
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device_id: [] for device_id in device_ids
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}
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for row in rows:
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device_id = row["device_id"]
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value = row.get("cleaned_value")
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if value is None:
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value = row.get("monitored_value")
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result.setdefault(device_id, []).append(
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{"time": row["time"].isoformat(), "value": value}
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)
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for device_id in result:
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result[device_id].sort(key=lambda item: item["time"])
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return result
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except Exception as e:
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logger.error(f"查询尝试 {attempt + 1} 失败: {e}")
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if attempt < max_retries - 1:
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time.sleep(1)
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else:
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raise
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@staticmethod
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def query_latest_scada_time(
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device_ids: List[str],
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before_time: str | datetime | None = None,
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db_name: str = None,
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max_retries: int = 3,
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) -> datetime | None:
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"""Return the latest SCADA timestamp for the selected devices."""
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before_dt = (
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parse_utc_time(before_time, field_name="before_time")
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if before_time is not None
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else None
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)
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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return ScadaRepository.get_latest_scada_time_sync(
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conn,
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device_ids,
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before_dt,
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)
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except Exception:
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if attempt < max_retries - 1:
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time.sleep(1)
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else:
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raise
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@staticmethod
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def query_realtime_simulation_by_ids_timerange(
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element_ids: List[str],
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start_time: str | datetime,
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end_time: str | datetime,
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element_type: str,
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field: str,
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db_name: str = None,
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max_retries: int = 3,
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) -> dict[str, list[dict]]:
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"""查询实时模拟结果，返回 {id: [{time, value}, ...]}。"""
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return InternalQueries._query_simulation_by_ids_timerange(
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schema_name="realtime",
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element_ids=element_ids,
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start_time=start_time,
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end_time=end_time,
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element_type=element_type,
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field=field,
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db_name=db_name,
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max_retries=max_retries,
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)
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@staticmethod
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def query_analysis_simulation_by_ids_timerange(
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element_ids: List[str],
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start_time: str | datetime,
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end_time: str | datetime,
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element_type: str,
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field: str,
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run_id,
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db_name: str = None,
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max_retries: int = 3,
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) -> dict[str, list[dict]]:
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"""Query one analysis run, returning {id: [{time, value}, ...]}."""
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return InternalQueries._query_simulation_by_ids_timerange(
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schema_name="analysis",
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element_ids=element_ids,
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start_time=start_time,
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end_time=end_time,
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element_type=element_type,
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field=field,
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db_name=db_name,
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max_retries=max_retries,
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run_id=run_id,
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)
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@staticmethod
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def _query_simulation_by_ids_timerange(
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*,
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schema_name: str,
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element_ids: List[str],
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start_time: str | datetime,
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end_time: str | datetime,
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element_type: str,
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field: str,
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db_name: str = None,
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max_retries: int = 3,
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run_id=None,
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) -> dict[str, list[dict]]:
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normalized_element_ids = list(
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dict.fromkeys(
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normalized
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for normalized in (str(element_id).strip() for element_id in element_ids)
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if normalized
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)
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)
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if not normalized_element_ids:
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return {}
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start_dt = parse_utc_time(start_time, field_name="start_time")
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end_dt = parse_utc_time(end_time, field_name="end_time")
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table_name, id_column, valid_fields = InternalQueries._resolve_simulation_table(element_type)
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if field not in valid_fields:
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raise ValueError(f"Invalid field for {element_type}: {field}")
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if schema_name not in {"realtime", "analysis"}:
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raise ValueError(f"Unsupported schema_name: {schema_name}")
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if schema_name == "analysis" and run_id is None:
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raise ValueError("analysis query requires run_id")
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for attempt in range(max_retries):
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try:
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with timescale_connection(db_name) as conn:
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with conn.cursor(row_factory=dict_row) as cur:
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if schema_name == "analysis":
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query = sql.SQL(
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"SELECT btrim({}::text) AS id, time, {} FROM {}.{} "
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"WHERE run_id = %s AND time >= %s AND time <= %s "
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"AND btrim({}::text) = ANY(%s)"
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).format(
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sql.Identifier(id_column),
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sql.Identifier(field),
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sql.Identifier(schema_name),
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sql.Identifier(table_name),
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sql.Identifier(id_column),
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)
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cur.execute(
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query,
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(run_id, start_dt, end_dt, normalized_element_ids),
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)
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else:
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query = sql.SQL(
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"SELECT btrim({}::text) AS id, time, {} FROM {}.{} "
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"WHERE time >= %s AND time <= %s AND btrim({}::text) = ANY(%s)"
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).format(
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sql.Identifier(id_column),
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sql.Identifier(field),
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sql.Identifier(schema_name),
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sql.Identifier(table_name),
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sql.Identifier(id_column),
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)
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cur.execute(query, (start_dt, end_dt, normalized_element_ids))
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rows = cur.fetchall()
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result: dict[str, list[dict]] = {
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element_id: [] for element_id in normalized_element_ids
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}
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for row in rows:
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element_id = str(row["id"]).strip()
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result.setdefault(element_id, []).append(
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{"time": row["time"].isoformat(), "value": row[field]}
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)
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for element_id in result:
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result[element_id].sort(key=lambda item: item["time"])
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return result
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except Exception as e:
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logger.error(f"查询尝试 {attempt + 1} 失败: {e}")
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if attempt < max_retries - 1:
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time.sleep(1)
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else:
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raise
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@staticmethod
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def _resolve_simulation_table(element_type: str) -> tuple[str, str, set[str]]:
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normalized_type = element_type.lower()
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if normalized_type == "node":
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return "node_results", "node_id", {"actual_demand", "total_head", "pressure", "quality"}
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if normalized_type == "link":
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return "link_results", "link_id", {
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"flow",
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"friction",
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"headloss",
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"quality",
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"reaction",
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"setting",
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"status",
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"velocity",
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}
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raise ValueError(f"Unsupported element_type: {element_type}")
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