claude.md
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# SchoolCompare.co.uk - Project Context
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## Overview
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SchoolCompare is a web application for comparing UK primary school (KS2) performance data. It allows users to:
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- Search and browse schools by name, location (postcode), or local authority
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- Compare multiple schools side-by-side with charts and tables
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- View school rankings by various KS2 metrics
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- See historical performance trends across years
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## Architecture
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### Backend (Python/FastAPI)
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- **Framework**: FastAPI with uvicorn
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- **Database**: PostgreSQL with SQLAlchemy ORM
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- **Data Source**: UK Government "Compare School Performance" CSV downloads
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Key files:
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- `backend/app.py` - Main FastAPI application, API routes
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- `backend/config.py` - Configuration via pydantic-settings (env vars, .env file)
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- `backend/database.py` - SQLAlchemy engine, session management
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- `backend/models.py` - Database models (School, SchoolResult)
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- `backend/data_loader.py` - Data queries, geocoding, legacy DataFrame compatibility
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- `backend/schemas.py` - Column mappings, metric definitions, LA code mappings
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### Frontend (Vanilla JS)
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- Single-page application with hash-based routing
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- Chart.js for data visualization
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- No build step required
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Key files:
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- `frontend/index.html` - Main HTML structure
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- `frontend/app.js` - All application logic, API calls, rendering
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- `frontend/styles.css` - Styling (CSS variables, responsive design)
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### Database Schema
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```
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schools school_results
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├── id (PK) ├── id (PK)
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├── urn (unique, indexed) ├── school_id (FK → schools.id)
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├── school_name ├── year (indexed)
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├── local_authority ├── rwm_expected_pct
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├── school_type ├── reading_expected_pct
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├── postcode ├── ... (all KS2 metrics)
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├── latitude, longitude └── unique(school_id, year)
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└── results → SchoolResult[]
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```
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## Configuration
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Environment variables (or `.env` file):
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- `DATABASE_URL` - PostgreSQL connection string (default: `postgresql://schoolcompare:schoolcompare@localhost:5432/schoolcompare`)
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- `HOST`, `PORT` - Server binding (default: `0.0.0.0:80`)
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- `ALLOWED_ORIGINS` - CORS origins
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## Running Locally
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1. Start PostgreSQL:
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```bash
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docker compose up -d db
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```
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2. Run migration to import CSV data:
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```bash
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python scripts/migrate_csv_to_db.py --drop
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# Add --geocode to geocode postcodes (slower, adds lat/long)
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```
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3. Start the app:
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```bash
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uvicorn backend.app:app --host 0.0.0.0 --port 8000
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```
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## Docker Deployment
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```bash
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docker compose up -d
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```
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This starts:
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- `db` - PostgreSQL 16 with persistent volume
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- `app` - FastAPI application on port 80
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## Data
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- Source: UK Government Compare School Performance downloads
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- Location: `data/` directory with year folders (e.g., `2023-2024/england_ks2final.csv`)
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- The `scripts/download_data.py` can fetch data from the government website
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## Key Features
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- **Location Search**: Enter postcode to find nearby schools (uses postcodes.io API)
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- **Multi-school Comparison**: Select multiple schools, view metrics across years
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- **Rankings**: Top schools by any KS2 metric, filterable by local authority
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- **Variability Analysis**: Shows standard deviation of scores across years
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## API Endpoints
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- `GET /api/schools` - List/search schools (supports pagination, location search)
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- `GET /api/schools/{urn}` - School details with all yearly data
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- `GET /api/compare?urns=123,456` - Compare multiple schools
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- `GET /api/rankings` - School rankings by metric
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- `GET /api/filters` - Available filter options (LAs, types, years)
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- `GET /api/metrics` - Metric definitions (single source of truth)
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- `GET /api/data-info` - Database stats
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## Recent Changes
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- Migrated from CSV file storage to PostgreSQL database
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- Added location-based search using postcode geocoding
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- Added local authority filter to rankings
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- Improved frontend with featured schools, loading states, API caching
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