README.md

metadata

title: 'Court Case Scheduling Dashboard: Code4Change'
sdk: docker
pinned: true

Code4Change: Intelligent Court Scheduling System

Purpose-built for hackathon evaluation. This repository runs out of the box using the Streamlit dashboard and the uv tool. It can be run locally, in Docker, or on Hugging Face Spaces (Docker runtime).

Requirements

• Python 3.11+
• uv (required)
  • macOS/Linux: curl -LsSf https://astral.sh/uv/install.sh | sh
  • Windows (PowerShell): irm https://astral.sh/uv/install.ps1 | iex

Quick Start (Dashboard)

1. Install uv (see above) and ensure Python 3.11+ is available.
2. Clone this repository.
3. Navigate to the repo root and activate uv:

cd path/to/repo
uv activate

4. Install dependencies:

uv install

5. Launch the dashboard:

uv run streamlit run app.py

Then open http://localhost:8501 in your browser.

The dashboard provides:

• Run EDA pipeline (process raw data and extract parameters)
• Explore data and parameters
• Generate cases and run simulations
• Review cause lists and judge overrides
• Compare performance and export reports

Command Line (optional)

All operations are available via CLI as well:

uv run court-scheduler --help

# End-to-end workflow
uv run court-scheduler workflow --cases 10000 --days 384

For a detailed walkthrough tailored for judges, see docs/HACKATHON_SUBMISSION.md.

Run with Docker (recommended for judges)

If you prefer not to install Python or uv locally, use the provided Docker image.

1. Build the image (run in repo root):

docker build -t code4change-analysis .

2. Show CLI help (Windows PowerShell example with volume mounts):

docker run --rm `
  -v ${PWD}\Data:/app/Data `
  -v ${PWD}\outputs:/app/outputs `
  code4change-analysis court-scheduler --help

3. Example CLI workflow:

docker run --rm `
  -v ${PWD}\Data:/app/Data `
  -v ${PWD}\outputs:/app/outputs `
  code4change-analysis court-scheduler workflow --cases 10000 --days 384

4. Run the Streamlit dashboard:

docker run --rm -p 7860:7860 `
  -v ${PWD}\Data:/app/Data `
  -v ${PWD}\outputs:/app/outputs `
  code4change-analysis

Then open http://localhost:7860.

Notes for Windows CMD: use ^ for line continuation and replace ${PWD} with the full path.

Deploy on Hugging Face Spaces (Docker)

This repository is ready for Hugging Face Spaces using the Docker runtime.

View the live demo at: https://royaalekh-hackathon-code4change.hf.space/

Data (Parquet format)

This repository uses a parquet data format for efficient loading and processing. Provided excel and csv files have been pre-converted to parquet and stored in the Data/ folder.

No manual pre-processing is required; launch the dashboard and click “Run EDA Pipeline.”

Project Structure

Key paths updated to reflect recent refactor:

• app.py — Streamlit entrypoint at the repository root (replaces previous nested path)
• src/ — all scheduler, simulation, dashboard, and core modules (migrated from scheduler/)
• pages/ and src/dashboard/pages/ — Streamlit multipage content
• Data/ — input data in Parquet/CSV
• outputs/ — generated artifacts (cause lists, reports)
• docs/ — documentation and hackathon submission details
• Dockerfile — Docker image definition for local and Hugging Face deployment