feat(projects): automate project infrastructure provisioning

app/services/dma_leakage_estimation.py

@@ -14,7 +14,7 @@ from app.native.wndb.gis.network_views import (
     get_network_link_nodes,
     get_network_node_coords,
 )
-from app.native.wndb.inp.exporter import dump_inp
+from app.services.project_inp import temporary_project_inp
 from app.services.scheme_management import store_analysis_run_with_result
 from app.domain.time import parse_utc_time, utc_now
 
@@ -42,8 +42,6 @@ def run_leakage_identification(
     sensor_nodes: list[str] | None = None,
     scheme_name: str | None = None,
 ) -> dict[str, Any]:
-    inp_path = _prepare_leakage_inp(network)
-
     selected_sensor_nodes = (
         list(dict.fromkeys([node for node in (sensor_nodes or []) if node]))
         if sensor_nodes
@@ -52,7 +50,7 @@ def run_leakage_identification(
     if not selected_sensor_nodes:
         raise ValueError("未提供有效传感器节点，且系统未识别到可用压力传感器。")
 
-    area_map, areas, node_coords = _build_area_map_by_topology(
+    area_map, areas, _ = _build_area_map_by_topology(
         network, selected_sensor_nodes, dma_count
     )
 
@@ -73,26 +71,25 @@ def run_leakage_identification(
         observed_df = observed_pressure_data
 
     q_sum_m3s = DmaLeakageOptimizer._flow_to_m3s(q_sum, q_sum_unit)
-    identifier = DmaLeakageOptimizer(
-        inp_path=inp_path,
-        sensor_nodes=selected_sensor_nodes,
-        area_map=area_map,
-        start_time=start_time,
-        duration=duration,
-        timestep=timestep,
-        q_sum=q_sum_m3s,
-    )
-    result_df = identifier.run_identification(
-        observed_pressure_data=observed_df,
-        pop_size=pop_size,
-        max_gen=max_gen,
-        n_workers=n_workers,
-        output_flow_unit=output_flow_unit,
-        save_result=False,
-    )
+    with temporary_project_inp(network, purpose="dma-leakage") as inp_path:
+        identifier = DmaLeakageOptimizer(
+            inp_path=str(inp_path),
+            sensor_nodes=selected_sensor_nodes,
+            area_map=area_map,
+            start_time=start_time,
+            duration=duration,
+            timestep=timestep,
+            q_sum=q_sum_m3s,
+        )
+        result_df = identifier.run_identification(
+            observed_pressure_data=observed_df,
+            pop_size=pop_size,
+            max_gen=max_gen,
+            n_workers=n_workers,
+            output_flow_unit=output_flow_unit,
+            save_result=False,
+        )
     rows = result_df.to_dict(orient="records")
-    # node_visual_payload = _build_node_visual_payload(area_map, node_coords, rows)
-    # drawing_payload = _build_drawing_payload(node_visual_payload)
     payload = {
         "result_path": result_df.attrs.get("result_path"),
         "sensor_nodes": selected_sensor_nodes,
@@ -100,8 +97,6 @@ def run_leakage_identification(
         "area_count": len(set(area_map.values())),
         "node_area_map": area_map,
         "areas": areas,
-        # "node_visual_payload": node_visual_payload,
-        # "drawing_payload": drawing_payload,
         "rows": rows,
     }
     if scheme_name:
@@ -326,16 +321,3 @@ def _build_observed_pressure_from_scada(
 
 def _to_datetime(value: datetime | str) -> datetime:
     return parse_utc_time(value)
-
-
-def _prepare_leakage_inp(network: str) -> str:
-    project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
-    db_inp_dir = os.path.join(project_root, "db_inp")
-    os.makedirs(db_inp_dir, exist_ok=True)
-    inp_path = os.path.join(db_inp_dir, f"{network}.leakage.inp")
-    if os.path.isfile(inp_path) and os.path.getsize(inp_path) > 0:
-        return inp_path
-    dump_inp(network, inp_path, "2")
-    if not os.path.isfile(inp_path) or os.path.getsize(inp_path) <= 0:
-        raise ValueError(f"漏损识别 INP 文件无效: {inp_path}")
-    return inp_path