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e22b004f9e26e1a87fe21a311c8e9fd535cdd0dc
CA/frontend/package.json

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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
{
"name": "wuhan-child-risk-frontend",
"private": true,
"version": "1.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "tsc && vite build",
"preview": "vite preview"
},
"dependencies": {
feat: GeoScene frontend POC + Docker deploy for remote host Migrate maps to @geoscene/core, polish monitoring/alerts UX, fix timeline basemap flicker and district alert regions, and ship compose/nginx Docker deploy assets with CBPOA_ROOT data mounts. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-24 03:28:29 +08:00
"@geoscene/core": "4.32.10",
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
"axios": "^1.6.7",
"lucide-react": "^0.330.0",
"react": "^18.2.0",
"react-dom": "^18.2.0",
feat(frontend): Phase 1 UX foundation — react-router v6 + responsive AppShell Atomic foundation for the consensus-approved UX modernization (makes the platform URL-addressable, refresh-safe, and mobile-usable for hospital demos). - Migrate hand-rolled useState page switching → react-router v6 (routes.tsx, thin App.tsx auth gate, NavLink SideNav, lazy+Suspense per route) - Add responsive AppShell: persistent rail (lg:) ⇄ off-canvas drawer + hamburger (<lg); kills hardcoded ml-[200px]; usable at 375px - Add ui primitive kit (Skeleton/LoadingState/EmptyState/Card/Panel/Segmented) - Sweep all raw "加载中..." text loaders → skeleton primitives (G4) - Centralize test ids (utils/testids.ts); rewrite e2e for URL nav (17/17 pass: deep-link, refresh-preserves-page, back, 375px drawer/no-scroll) - Harden DemographicAnalysis against API shape mismatch (defensive normalize) - gitignore playwright-report/ and test-results/ Gates: tsc --noEmit 0 · pnpm build ok · e2e 17/17 · grep 加载中 zero outside ui/ Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-21 20:12:13 +08:00
"react-router-dom": "^6.30.4",
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
"recharts": "^2.12.0",
"zustand": "^4.5.0"
},
"devDependencies": {
"@playwright/test": "^1.59.1",
chore: add test infrastructure and update risk router - Add vitest config and unit tests for components, api, stores - Add Playwright e2e test for user flows - Add backend test files - Update risk.py with LOD grid KDTree optimization
2026-06-09 12:54:55 +08:00
"@testing-library/jest-dom": "^6.9.1",
"@testing-library/react": "^14.3.1",
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
"@types/react": "^18.2.55",
"@types/react-dom": "^18.2.19",
"@vitejs/plugin-react": "^4.2.1",
"autoprefixer": "^10.4.17",
chore: add test infrastructure and update risk router - Add vitest config and unit tests for components, api, stores - Add Playwright e2e test for user flows - Add backend test files - Update risk.py with LOD grid KDTree optimization
2026-06-09 12:54:55 +08:00
"jsdom": "^24.1.3",
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
"postcss": "^8.4.35",
"tailwindcss": "^3.4.1",
"typescript": "^5.3.3",
chore: add test infrastructure and update risk router - Add vitest config and unit tests for components, api, stores - Add Playwright e2e test for user flows - Add backend test files - Update risk.py with LOD grid KDTree optimization
2026-06-09 12:54:55 +08:00
"vite": "^5.1.0",
"vitest": "^1.6.1"
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
}
}
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