Data Science Project Template

A simple project structure for data scientists to begin a new project. It provides necessary files. We keep the cookie cutter as simple as possible with focus on production and not development.

How to use

• Go to workflows, run Create Repo workflow by providing the following inputs:
  • Repo name: Name of the repository you want to create
  • Product name: Name of the data science product.
  • Operation team: Name of the team who owns the product, e.g. Data Science, MLOps.

What it does

• Create Repo creates a repository with provided repo name, runs cookiecutter to render files, adds and commits them to the new repository.

📖 Repository structure consist of following files:

├── README.md              <- The top-level README for developers using this project
├── main.py                <- Main script to run model flow (i.e. from raw data to predictions)
├── pre-commit-config.yaml <- Pre-commit hooks
├── .gitignore             <- File with 
├── requirements.txt       <- Requirements for production
├── .flake8                <- Configuration for flake8
├── pytest.ini             <- Pytest settings
└── .github/workflows
    ├── CI.yml             <- CI to run tests and precommit