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feat(home): swap in the higher-fidelity hero artwork
Same 16:9 frame, but not a drop-in replacement — the composition, palette and
copy area all moved, and each one drives a change here.

COPY AREA

The old artwork was a flat #FDF9F3 down its whole left side. This one runs
peach #FEE8D2 at the top to cream #FDF3E7 around 43% height, and below ~48%
the left edge is foliage rather than cream at all. --hero-ground is resampled
to #FEF2E1, the middle of the pale run where the headline and search actually
sit; the scrim covers the foliage further down.

Measured on rendered pixels with the text hidden, sampling the real glyph runs
(via Range, not the element boxes) plus a 120px growth margin:

           title      body      byline
  light    13.61:1    5.74:1    6.66:1
  dark      9.49:1    5.45:1    8.35:1

Body drops from 6.52:1 to 5.74:1 as the foliage comes closer, still clear.

BAND CROP

The schoolhouse moved to ~82% across the frame, leaving only ~140px of artwork
to its right, so the band crop is anchored to the right edge and takes 1344px
back — putting the school at 73%, which the build script now derives and
prints rather than leaving it to drift from the CSS.

The crop is also 3.2:1 rather than matching the phone. The band is not one
ratio: it runs 2.4:1 on a phone to about 3.8:1 under the one-column
breakpoint. Cropping at the narrow end means the wide end throws away height,
which cut the flag off the roof and the base off the building. Sitting above
the middle costs a little width on phones — where the crop's left is hillside —
and keeps the building whole where it matters.

BAND HEIGHTS

Raised to 13rem (861–860px) and 10rem (≤640px). The band was widest-per-height
at exactly 640px, where an 8.5rem band measured 4.2:1 — worse than any wider
viewport, because the height steps down at that breakpoint while the width does
not. Ratios across the range are now 2.0 / 2.6 / 3.6 / 3.1 / 3.8 rather than
spiking. The search still lands at 442px on a 667px viewport.

WEIGHT

Source is 3.1MB; a browser fetches one file — 29–59kB on desktop, 10–14kB on a
phone. Widths re-cut for the larger master: 2000/1400/1000 wide, 1344/900/600
band.

Verified: 0 AA failures across both themes at 1440 / 860 / 390, every srcset
entry present on disk with no orphans, tsc clean, 159/159, build green.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-15 09:22:37 +01:00
2026-01-06 19:05:22 +00:00
2026-04-07 16:17:56 +01:00
2026-01-07 16:20:49 +00:00
2026-01-07 16:20:49 +00:00
2026-04-01 15:05:21 +01:00

Primary School Compass 🧒📚

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.

Python FastAPI License

Features

  • 📊 Interactive Charts - Visualize KS2 performance trends over time
  • 🔍 Smart Search - Find primary schools by name in Wandsworth & Merton
  • ⚖️ Side-by-Side Comparison - Compare up to 5 schools simultaneously
  • 🏆 Rankings - View top-performing primary schools by various KS2 metrics
  • 📱 Responsive Design - Works beautifully on desktop and mobile

Key Metrics (KS2)

The application tracks these Key Stage 2 performance indicators:

Metric Description
Reading Progress Progress in reading from KS1 to KS2
Writing Progress Progress in writing from KS1 to KS2
Maths Progress Progress in maths from KS1 to KS2
Reading Expected % Percentage meeting expected standard in reading
Writing Expected % Percentage meeting expected standard in writing
Maths Expected % Percentage meeting expected standard in maths
Reading, Writing & Maths Combined % Percentage meeting expected standard in all three subjects

Quick Start

1. Clone and Setup

cd school_results

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2. Run the Application

# Start the server
python -m uvicorn backend.app:app --reload --port 8000

Then open http://localhost:8000 in your browser.

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.

3. (Optional) Use Real Data

To use real UK school performance data:

  1. Visit Compare School Performance - Download Data

  2. Download Key Stage 2 data for the years you want (2019-2024)

    • Select "Key Stage 2" as the data type
  3. Place the CSV files in the data/ folder

  4. Restart the server - it will automatically load and filter to Wandsworth & Merton schools

Note: The app only displays schools in Wandsworth and Merton. Data from other areas will be filtered out.

See the helper script for more details:

python scripts/download_data.py

Project Structure

school_results/
├── backend/
│   └── app.py           # FastAPI application with all API endpoints
├── frontend/
│   ├── index.html       # Main HTML page
│   ├── styles.css       # Styling (warm, editorial design)
│   └── app.js           # Frontend JavaScript
├── data/
│   └── .gitkeep         # Place CSV data files here
├── scripts/
│   └── download_data.py # Helper for downloading/processing data
├── requirements.txt     # Python dependencies
└── README.md

API Endpoints

Endpoint Description
GET /api/schools List schools with optional search/filter
GET /api/schools/{urn} Get detailed data for a specific school
GET /api/compare?urns=... Compare multiple schools
GET /api/rankings Get school rankings by metric
GET /api/filters Get available filter options
GET /api/metrics Get available performance metrics

Example API Usage

# Search for schools
curl "http://localhost:8000/api/schools?search=academy"

# Get school details
curl "http://localhost:8000/api/schools/100001"

# Compare schools
curl "http://localhost:8000/api/compare?urns=100001,100002,100003"

# Get rankings
curl "http://localhost:8000/api/rankings?metric=rwm_expected_pct&year=2024"

Data Format

If using your own CSV data, ensure it includes these columns (or similar):

Column Type Description
URN Integer Unique Reference Number
SCHNAME String School name
LA String Local Authority (must be Wandsworth or Merton)
READPROG Float Reading progress score
WRITPROG Float Writing progress score
MATPROG Float Maths progress score
PTRWM_EXP Float % meeting expected standard in reading, writing & maths
PTREAD_EXP Float % meeting expected standard in reading
PTWRIT_EXP Float % meeting expected standard in writing
PTMAT_EXP Float % meeting expected standard in maths

The application normalizes column names automatically and filters to only show Wandsworth and Merton schools.

Technology Stack

  • Backend: FastAPI (Python) - High-performance async API framework
  • Frontend: Vanilla JavaScript with Chart.js
  • Styling: Custom CSS with CSS variables for theming
  • Data: Pandas for CSV processing

Design Philosophy

The UI features a warm, editorial design inspired by quality publications:

  • Typography: DM Sans for body text, Playfair Display for headings
  • Color Palette: Warm cream background with coral and teal accents
  • Interactions: Smooth animations and hover effects
  • Charts: Clean, readable data visualizations

Development

# Run with auto-reload
python -m uvicorn backend.app:app --reload --port 8000

# Or run directly
python backend/app.py

Coverage

This application is specifically designed for:

  • School Phase: Primary schools only (Key Stage 2)
  • Geographic Area: Wandsworth and Merton (London boroughs)
  • Time Period: Last 5 years of data (2020-2024)

Note: 2021 data shows as unavailable because SATs were cancelled due to COVID-19.

Data Source

Data is sourced from the UK Government's Compare School Performance service, which provides official school performance data for England.

Important: When using real data, please comply with the terms of use and data protection regulations.

Scheduled Jobs

Geocoding Schools (Cron Job)

School postcodes are geocoded by a scheduled job, not on-demand. This improves performance and reduces API calls.

Setup the cron job (runs weekly on Sunday at 2am):

# Edit crontab
crontab -e

# Add this line (adjust paths as needed):
0 2 * * 0 cd /path/to/school_compare && /path/to/venv/bin/python scripts/geocode_schools.py >> /var/log/geocode_schools.log 2>&1

Manual run:

# Geocode only schools missing coordinates
python scripts/geocode_schools.py

# Force re-geocode all schools
python scripts/geocode_schools.py --force

License

MIT License - feel free to use this project for educational purposes.


Built with ❤️ for Wandsworth & Merton families

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