Akiba So
e95e2f1338
Ship a new app version with broader analytics, restructured dashboards, and a server-rendered risk map. Frontend: - Add Overview, Demographic, Disease, and Environmental Health analysis pages - Add AnomalyMarkers, CalendarHeatmap, and MetricHeatmapTable components - Rebuild Alerts map onto server-rendered raster risk tiles; expand Monitoring, Trend, and District Comparison views - Extend API client, stores, and TypeScript types Backend: - Add environment router (pollutants, lag correlations) - Add risk_raster util serving XYZ 100m risk tiles - Expand cases endpoints (demographics, seasonality, diagnoses) and insights; harden auth and file-based loaders Data & tooling: - Add processed outpatient/inpatient/combined case parquet (LFS) - Add nested CLAUDE.md guides, pyrightconfig, and test updates
48 lines
1.7 KiB
Markdown
48 lines
1.7 KiB
Markdown
# Routers — API Endpoints
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## Pattern
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Each router file defines one `APIRouter(prefix=..., tags=[...])` with typed endpoints.
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```python
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from fastapi import APIRouter
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from models import SomeResponse
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router = APIRouter(prefix="/api/domain", tags=["domain"])
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@router.get("/endpoint", response_model=SomeResponse)
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async def get_something(...):
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...
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```
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## Conventions
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- Return Pydantic models (`response_model=`), never raw dicts
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- Use `Annotated[Type, Query(...)]` / `Path(...)` for request params
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- Spatial queries use `scipy.spatial.KDTree` for nearest-neighbor lookups
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- GeoJSON parsing is delegated to `utils/geojson.py`
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- Risk level mapping is in `utils/risk.py` — use `risk_value_to_level()` not inline thresholds
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- Large repeated queries use `@lru_cache` (from `functools`)
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- Date helpers from `utils/date_helpers.py` — always `get_latest_date()`, never guess
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## File Map
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| File | Domain |
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|------|--------|
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| `risk.py` | Risk maps, grid detail, history (largest router, ~42 file reads) |
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| `alerts.py` | Alert feed, stats |
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| `cases.py` | Medical case queries (age, disease, district filters) |
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| `analysis.py` | Trend analysis, statistics |
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| `grid.py` | Grid metadata, elevation, population |
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| `reports.py` | Report generation, export |
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| `insights.py` | AI-generated insights |
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| `chat.py` | Chatbot endpoint |
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| `geocoded.py` | Geocoded case data |
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## Anti-Patterns
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- Don't use sync I/O in `async def` — use `async with db.get_connection()` for DB
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- Don't catch bare `Exception` — use specific HTTPException or let it propagate to middleware
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- Don't return raw GeoJSON dicts without Pydantic validation
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- Don't inline risk thresholds — use `utils/risk.risk_value_to_level()`
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