Code of Law

Code of Law scrapes reported Singapore Supreme Court judgments from eLitigation and generates basic analytics/visualizations from the exported dataset.

What this repository does

• Scrapes SG Supreme Court reported judgments by year (elitiscrape.py)
• Exports structured case data to CSV
• Runs analysis and chart generation (analysis.py)
• Saves charts to tables/

Project structure

• elitiscrape.py: scraper CLI
• analysis.py: analysis + plot generation CLI
• sample/elitigation_cases_2020_to_2025.csv: sample dataset for local analysis
• tables/: generated chart outputs

Requirements

• Python 3.10+
• Dependencies from requirements.txt

Install dependencies:

pip install -r requirements.txt

Usage

1. Analyze existing sample data

This runs without scraping and regenerates charts in tables/.

python analysis.py --input sample/elitigation_cases_2020_to_2025.csv --output-dir tables

Generated visuals

Catchword Analysis

Judge Count

Yearly Breakdown

2. Scrape fresh data

Scrape a year range and write a CSV.

python elitiscrape.py --start-year 2020 --end-year 2025 --output sample/elitigation_cases_2020_to_2025.csv

Then analyze that CSV:

python analysis.py --input sample/elitigation_cases_2020_to_2025.csv --output-dir tables

Command options

Scraper (elitiscrape.py)

• --start-year: first year to scrape (default: 2020)
• --end-year: last year to scrape (default: current year)
• --output: output CSV path (default: sample/elitigation_cases_<start>_to_<end>.csv)
• --delay: delay in seconds between list-page requests (default: 0.5)
• --timeout: HTTP timeout in seconds (default: 20)
• --retries: retries per request (default: 3)
• --max-pages: optional page cap per year (for quick checks)
• --max-cases: optional total-case cap (for quick checks)

Analysis (analysis.py)

• --input: input CSV path
• --output-dir: chart output directory (default: tables)
• --top-authors: top N authors in chart (default: 10)
• --top-terms: top N catchword categories in chart (default: 15)

Output schema

The scraper outputs these CSV columns:

• CaseIdentifier
• Catchwords
• Year
• URL
• WordCount
• ParagraphCount
• Author
• LegalParties

Validation

Quick validation run (small scrape + analysis):

python elitiscrape.py --start-year 2025 --end-year 2025 --max-pages 1 --max-cases 10 --output sample/validation_sample.csv
python analysis.py --input sample/validation_sample.csv --output-dir tables

Notes

• Scraping depends on eLitigation page structure and availability.
• Some case fields may be missing if source pages omit them.
• Charts are generated with a non-interactive matplotlib backend so they work in terminal/headless environments.

License

MIT License (see LICENSE).