docs: describe the system that exists, not the one we started with
The README still opened on "Primary School Compass", a KS2 tool for Wandsworth and Merton served by FastAPI and vanilla JavaScript with Chart.js. Every layer of that sentence is now wrong: coverage is England-wide across KS2, KS4, all-through and post-16, Next.js owns the public UI, and school data comes from dbt-built `marts.*` rather than CSVs loaded at startup. The setup instructions walked a reader into a virtualenv and a CSV import that cannot build the current schema, so following the docs produced an empty database and a wrong mental model at the same time. Replace the narrative docs with two reference documents that were checked against the code: docs/ARCHITECTURE.md for request flow, data ownership, the backend/frontend module boundaries and the real publication sequence, and docs/DEVELOPMENT.md for the checks that actually run, including the container and CI version skew that makes "just run pytest" misleading. The env examples drifted the same way. ALLOWED_ORIGINS is a JSON array, not a comma-separated list; the frontend needs FASTAPI_URL, DATABASE_URL and PAYLOAD_SECRET, none of which were documented; and RATE_LIMIT_BURST, DEFAULT_PAGE_SIZE and MAX_PAGE_SIZE were presented as tuning controls the routes do not consult. Each is now stated as it behaves. MIGRATION_SUMMARY.md keeps its content but gains a banner, because it reads like setup instructions and is not. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016y2J6bs8gbuSJbH18w7Tan
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# Primary School Compass 🧒📚
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# SchoolCompare
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A modern web application for comparing **primary school (KS2)** performance data in **Wandsworth and Merton** over the last 5 years. Built with FastAPI and vanilla JavaScript with Chart.js visualizations.
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SchoolCompare compares schools across England: primary (KS2), secondary (KS4),
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all-through and post-16 provision, with coverage depending on the source dataset.
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It provides school search, postcode maps, comparisons, rankings, place pages,
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Ofsted information, admissions and destination measures. Editorial content lives
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in a Payload CMS blog.
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## Start here
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## Features
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- [Architecture and data flow](docs/ARCHITECTURE.md)
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- [Development and validation](docs/DEVELOPMENT.md)
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- [Deployment and promotion](docs/DEPLOY.md)
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- [Legacy and unused-code inventory](docs/LEGACY_CODE.md)
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- [Frontend conventions](nextjs-app/README.md)
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- [CMS publishing](nextjs-app/docs/PUBLISHING.md)
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- 📊 **Interactive Charts** - Visualize KS2 performance trends over time
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- 🔍 **Smart Search** - Find primary schools by name in Wandsworth & Merton
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- ⚖️ **Side-by-Side Comparison** - Compare up to 5 schools simultaneously
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- 🏆 **Rankings** - View top-performing primary schools by various KS2 metrics
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- 📱 **Responsive Design** - Works beautifully on desktop and mobile
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## Repository map
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## Key Metrics (KS2)
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| Path | Responsibility |
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|---|---|
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| `backend/` | FastAPI routes, cached school data, read-only SQLAlchemy mappings, feature flags |
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| `nextjs-app/` | Next.js App Router, React UI, Payload CMS, frontend tests |
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| `pipeline/plugins/extractors/` | Custom Singer taps for GIAS, EES, Ofsted and other datasets |
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| `pipeline/transform/` | dbt staging/intermediate models, marts, seeds and data tests |
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| `pipeline/dags/` | Airflow extraction, transformation and publication workflows |
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| `pipeline/scripts/` | Search indexing, code generation and operational diagnostics |
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| `e2e/` | Playwright journeys against a running environment |
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| `.gitea/workflows/` | PR checks, staging deployment and manual production promotion |
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| `scripts/` | CI review tooling and historical data utilities; see the legacy inventory |
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| `docs/superpowers/`, `mockups/` | Design history and prototypes, not application entry points |
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The application tracks these Key Stage 2 performance indicators:
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## Runtime
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| Metric | Description |
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|--------|-------------|
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| **Reading Progress** | Progress in reading from KS1 to KS2 |
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| **Writing Progress** | Progress in writing from KS1 to KS2 |
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| **Maths Progress** | Progress in maths from KS1 to KS2 |
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| **Reading Expected %** | Percentage meeting expected standard in reading |
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| **Writing Expected %** | Percentage meeting expected standard in writing |
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| **Maths Expected %** | Percentage meeting expected standard in maths |
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| **Reading, Writing & Maths Combined %** | Percentage meeting expected standard in all three subjects |
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The public site is **Next.js**, not the FastAPI root page. Browser `/api/*`
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requests pass through a Next.js route handler to FastAPI. Server-rendered pages
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call FastAPI directly using `FASTAPI_URL`, including its `/api` suffix.
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## Quick Start
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PostgreSQL/PostGIS stores school data. Meltano/Singer extracts source data;
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dbt builds `marts.*`; FastAPI reads those tables. Typesense serves text search
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and autocomplete. Payload runs inside Next.js and owns a separate `payload`
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database schema and uploaded media.
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### 1. Clone and Setup
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There is **no automatic CSV import or sample dataset on startup**. A working
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school-data environment needs populated marts from the pipeline or an approved
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database snapshot. See [development](docs/DEVELOPMENT.md) before choosing a setup.
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```bash
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cd school_results
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## Validation
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# Create virtual environment
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python -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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# Install dependencies
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pip install -r requirements.txt
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```sh
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cd nextjs-app
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npm ci
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npm run typecheck
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npm test -- --runInBand
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```
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### 2. Run the Application
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Backend checks, pipeline validation, runtime versions and E2E requirements are
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listed in [DEVELOPMENT.md](docs/DEVELOPMENT.md). No `npm run lint` script is
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currently defined.
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```bash
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# Start the server
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python -m uvicorn backend.app:app --reload --port 8000
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```
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Then open http://localhost:8000 in your browser.
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The app will run with **sample data** by default, showing **110 primary schools** (66 in Wandsworth, 44 in Merton) with 5 years of KS2 performance data.
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### 3. (Optional) Use Real Data
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To use real UK school performance data:
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1. Visit [Compare School Performance - Download Data](https://www.compare-school-performance.service.gov.uk/download-data)
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2. Download **Key Stage 2** data for the years you want (2019-2024)
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- Select "Key Stage 2" as the data type
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3. Place the CSV files in the `data/` folder
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4. Restart the server - it will automatically load and filter to Wandsworth & Merton schools
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**Note:** The app only displays schools in Wandsworth and Merton. Data from other areas will be filtered out.
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See the helper script for more details:
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```bash
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python scripts/download_data.py
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```
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## Project Structure
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```
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school_results/
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├── backend/
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│ └── app.py # FastAPI application with all API endpoints
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├── frontend/
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│ ├── index.html # Main HTML page
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│ ├── styles.css # Styling (warm, editorial design)
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│ └── app.js # Frontend JavaScript
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├── data/
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│ └── .gitkeep # Place CSV data files here
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├── scripts/
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│ └── download_data.py # Helper for downloading/processing data
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├── requirements.txt # Python dependencies
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└── README.md
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```
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## API Endpoints
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| Endpoint | Description |
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|----------|-------------|
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| `GET /api/schools` | List schools with optional search/filter |
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| `GET /api/schools/{urn}` | Get detailed data for a specific school |
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| `GET /api/compare?urns=...` | Compare multiple schools |
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| `GET /api/rankings` | Get school rankings by metric |
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| `GET /api/filters` | Get available filter options |
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| `GET /api/metrics` | Get available performance metrics |
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### Example API Usage
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```bash
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# Search for schools
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curl "http://localhost:8000/api/schools?search=academy"
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# Get school details
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curl "http://localhost:8000/api/schools/100001"
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# Compare schools
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curl "http://localhost:8000/api/compare?urns=100001,100002,100003"
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# Get rankings
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curl "http://localhost:8000/api/rankings?metric=rwm_expected_pct&year=2024"
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```
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## Data Format
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If using your own CSV data, ensure it includes these columns (or similar):
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| Column | Type | Description |
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|--------|------|-------------|
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| URN | Integer | Unique Reference Number |
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| SCHNAME | String | School name |
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| LA | String | Local Authority (must be Wandsworth or Merton) |
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| READPROG | Float | Reading progress score |
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| WRITPROG | Float | Writing progress score |
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| MATPROG | Float | Maths progress score |
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| PTRWM_EXP | Float | % meeting expected standard in reading, writing & maths |
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| PTREAD_EXP | Float | % meeting expected standard in reading |
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| PTWRIT_EXP | Float | % meeting expected standard in writing |
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| PTMAT_EXP | Float | % meeting expected standard in maths |
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The application normalizes column names automatically and filters to only show Wandsworth and Merton schools.
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## Technology Stack
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- **Backend**: FastAPI (Python) - High-performance async API framework
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- **Frontend**: Vanilla JavaScript with Chart.js
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- **Styling**: Custom CSS with CSS variables for theming
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- **Data**: Pandas for CSV processing
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## Design Philosophy
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The UI features a warm, editorial design inspired by quality publications:
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- **Typography**: DM Sans for body text, Playfair Display for headings
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- **Color Palette**: Warm cream background with coral and teal accents
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- **Interactions**: Smooth animations and hover effects
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- **Charts**: Clean, readable data visualizations
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## Development
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```bash
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# Run with auto-reload
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python -m uvicorn backend.app:app --reload --port 8000
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# Or run directly
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python backend/app.py
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```
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## Coverage
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This application is specifically designed for:
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- **School Phase**: Primary schools only (Key Stage 2)
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- **Geographic Area**: Wandsworth and Merton (London boroughs)
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- **Time Period**: Last 5 years of data (2020-2024)
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Note: 2021 data shows as unavailable because SATs were cancelled due to COVID-19.
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## Data Source
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Data is sourced from the UK Government's [Compare School Performance](https://www.compare-school-performance.service.gov.uk/) service, which provides official school performance data for England.
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**Important**: When using real data, please comply with the [terms of use](https://www.compare-school-performance.service.gov.uk/download-data) and data protection regulations.
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## Scheduled Jobs
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### Geocoding Schools (Cron Job)
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School postcodes are geocoded by a scheduled job, not on-demand. This improves performance and reduces API calls.
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**Setup the cron job** (runs weekly on Sunday at 2am):
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```bash
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# Edit crontab
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crontab -e
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# Add this line (adjust paths as needed):
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0 2 * * 0 cd /path/to/school_compare && /path/to/venv/bin/python scripts/geocode_schools.py >> /var/log/geocode_schools.log 2>&1
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```
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**Manual run:**
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```bash
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# Geocode only schools missing coordinates
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python scripts/geocode_schools.py
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# Force re-geocode all schools
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python scripts/geocode_schools.py --force
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```
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## License
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MIT License - feel free to use this project for educational purposes.
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---
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Built with ❤️ for Wandsworth & Merton families
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## Deployment
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Work on a feature branch and open a PR. Merging to `main` builds images and
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deploys staging. Production promotion is a separate, human-triggered Gitea
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workflow. Use [DEPLOY.md](docs/DEPLOY.md) and the Portainer compose files as the
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operational references. The generic compose examples still reference `:latest`,
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which the current release workflow does not publish.
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