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fix: analysis 500s, caching, alert page perf

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P0: Fix KeyError in 3 analysis endpoints. geojson.py stores 1d risk
as "risk_value" but analysis.py accessed "risk_1d" — always crashed.

Backend: Add lru_cache to GeoJSON/CSV/Parquet loaders, date helpers,
and district loader. Add try/except and FileNotFoundError guards.

Frontend: Debounce riskRange, merge counts into useMemo, stabilize
handleGridClick with ref, memoize nearest-grid scan, wrap AlertMap
in React.memo, switch useLodGrid from fetch to cachedGet.
This commit is contained in:
Akiba So
2026-06-05 02:27:10 +08:00
parent fc468464b2
commit e64ca3b4f5
9 changed files with 154 additions and 114 deletions
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30
backend/routers/grid.py
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@@ -1,5 +1,6 @@
from fastapi import APIRouter, HTTPException, Query
from datetime import datetime, timedelta
from functools import lru_cache
from pathlib import Path
from typing import Optional
import logging
@@ -22,6 +23,12 @@ from models import (
router = APIRouter(prefix="/api", tags=["grid"])
@lru_cache(maxsize=1)
def _load_parquet(path: Path) -> "pd.DataFrame":
import pandas as pd
return pd.read_parquet(path)
@router.get("/history/aggregated", response_model=HistoricalAggregationResponse)
async def get_historical_aggregated(
start_date: str = Query(..., description="Start date (YYYY-MM-DD)"),
@@ -45,7 +52,13 @@ async def get_historical_aggregated(
import pandas as pd
cases_df = pd.read_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
try:
cases_df = _load_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
except FileNotFoundError:
return HistoricalAggregationResponse(
aggregations=[], total_records=0,
date_range=(start_date, end_date), timestamp=datetime.now().isoformat(),
)
cases_df['date'] = pd.to_datetime(cases_df['date'])
filtered_cases = cases_df[
@@ -78,7 +91,10 @@ async def get_historical_aggregated(
grouped = filtered_cases.copy()
grouped['date'] = grouped['date'].dt.strftime('%Y-%m-%d')
weather_df = pd.read_parquet(PROJECT_ROOT / "processed" / "weather" / "station_daily_2022.parquet")
try:
weather_df = _load_parquet(PROJECT_ROOT / "processed" / "weather" / "station_daily_2022.parquet")
except FileNotFoundError:
weather_df = pd.DataFrame(columns=['date', 'AQI', 'PM25', 'PM10'])
weather_df['date'] = pd.to_datetime(weather_df['date']).dt.strftime('%Y-%m-%d')
# Weather data doesn't have district - aggregate by date only
@@ -124,12 +140,12 @@ async def get_grids_geojson(
import pandas as pd
try:
grid_df = pd.read_parquet(PROJECT_ROOT / "processed" / "grid_100m_index.parquet")
grid_df = _load_parquet(PROJECT_ROOT / "processed" / "grid_100m_index.parquet")
except FileNotFoundError:
return GridGeoJSONResponse(type="FeatureCollection", features=[], timestamp=datetime.now().isoformat())
try:
district_map = pd.read_parquet(PROJECT_ROOT / "processed" / "grid_district_mapping.parquet")
district_map = _load_parquet(PROJECT_ROOT / "processed" / "grid_district_mapping.parquet")
except FileNotFoundError:
return GridGeoJSONResponse(type="FeatureCollection", features=[], timestamp=datetime.now().isoformat())
@@ -139,7 +155,7 @@ async def get_grids_geojson(
merged = merged[merged['district_name'].str.contains(district.replace('区', ''), na=False, regex=False)]
try:
cases_df = pd.read_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
cases_df = _load_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
except FileNotFoundError:
return GridGeoJSONResponse(type="FeatureCollection", features=[], timestamp=datetime.now().isoformat())
cases_df['date'] = pd.to_datetime(cases_df['date']).dt.strftime('%Y-%m-%d')
@@ -313,7 +329,7 @@ async def get_grid_history(
"""
import pandas as pd
district_map = pd.read_parquet(PROJECT_ROOT / "processed" / "grid_district_mapping.parquet")
district_map = _load_parquet(PROJECT_ROOT / "processed" / "grid_district_mapping.parquet")
grid_info = district_map[district_map['grid_id'] == grid_id]
if len(grid_info) == 0:
@@ -321,7 +337,7 @@ async def get_grid_history(
district = grid_info.iloc[0]['district_name']
cases_df = pd.read_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
cases_df = _load_parquet(PROJECT_ROOT / "processed" / "cases_by_district_daily.parquet")
cases_df['date'] = pd.to_datetime(cases_df['date'])
end_date = datetime.now()