backend/requirements.txt

fastapi==0.109.0
uvicorn[standard]==0.27.0
pydantic==2.5.3
pydantic-settings==2.1.0
asyncpg==0.29.0
asyncpg-stubs==0.29.0
geoalchemy2==0.14.3
shapely==2.0.2
python-multipart==0.0.6
python-jose[cryptography]==3.3.0
passlib[bcrypt]==1.7.4
python-dotenv==1.0.0
scipy>=1.11.0
pandas>=2.0.0
numpy>=1.24.0
pyarrow>=14.0.0
openpyxl>=3.1.0
feat: Initial CBPOA commit — 武汉儿童呼吸疾病风险评估系统 Context: Build a spatial risk assessment system correlating air quality data with children's respiratory disease incidence across Wuhan. Approach: FastAPI backend serving PostGIS spatial queries, React frontend with Deck.gl maps, and a PyTorch SpatialTemporalGCN pipeline for multi-day (1d/3d/7d) risk prediction. Changes: - backend/ — FastAPI API with auth (JWT), alerts, risk analysis, geocoded case data, grid statistics, and report endpoints - frontend/ — React dashboard with interactive risk maps, alert monitoring, district comparison charts, and timeline player - models/ — SpatialTemporalGCN model with trained weights and ONNX export for inference - scripts/ — ETL pipeline for weather + medical data, grid generation, feature engineering, training, and daily inference - deploy/ — Docker Compose configs for backend, frontend, and MLflow - docs/ — API docs, deployment guide, user guide, and code review Impact: Enables spatial risk visualization, alert monitoring, and ML-driven health risk forecasting for environmental health teams. 2026-06-05 02:13:49 +08:00			`fastapi==0.109.0`
			`uvicorn[standard]==0.27.0`
			`pydantic==2.5.3`
			`pydantic-settings==2.1.0`
			`asyncpg==0.29.0`
			`asyncpg-stubs==0.29.0`
			`geoalchemy2==0.14.3`
			`shapely==2.0.2`
			`python-multipart==0.0.6`
			`python-jose[cryptography]==3.3.0`
			`passlib[bcrypt]==1.7.4`
			`python-dotenv==1.0.0`
			`scipy>=1.11.0`
			`pandas>=2.0.0`
			`numpy>=1.24.0`
			`pyarrow>=14.0.0`
			`openpyxl>=3.1.0`