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Contributing

Thanks for contributing to this project.

The goal of this repository is to keep the codebase production-style, easy to understand, and easy to maintain, so small, clean improvements are preferred over large mixed changes.

Local Setup

  1. Create and activate a virtual environment:

    python3 -m venv .venv
source .venv/bin/activate

  2. Install the project with development dependencies:

    pip install '.[dev]'

  3. Place the M5 source files in data/raw/m5 if you want to run the full real-data workflow.

Common Commands

Run the full pipeline:

retail-forecast run-all

Start the API:

retail-forecast serve-api

Start the dashboard:

streamlit run src/retail_forecasting/dashboard/app.py

Run tests:

pytest

Contribution Guidelines

  • Keep changes focused and easy to review.
  • Prefer separate commits for docs, tooling, and feature work.
  • Update the README when the project behavior or setup changes.
  • Do not commit raw M5 CSV files, local .env files, or generated warehouse artifacts.
  • Before pushing, run pytest and make sure the app still starts locally.

Suggested Commit Style

Examples:

  • docs: clarify local setup and configuration
  • ci: add github actions test workflow
  • feat: improve forecast explorer filtering
  • fix: correct reorder point calculation edge case