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Cookiecutter Machine Learning Template

This is a modern Cookiecutter template for initializing Python projects, particularly for machine learning. It provides a comprehensive setup for development, testing, and deployment, incorporating essential tools for effective project management.

Features

This template includes the following features:

You can find an example repository created using this template here.

Quickstart

To get started, follow these steps:

Step 1: Install cookiecutter-ml

First, navigate to the directory where you want to create the project and run:

pip install cookiecutter-ml

Alternatively, you can install cookiecutter and use the GitHub repository URL directly:

pip install cookiecutter
cookiecutter git@github.com:DeepakPant93/cookiecutter-ml.git

Step 2: Create a GitHub Repository

Create a new repository on GitHub, then run the following commands in your terminal, replacing <project-name> with your GitHub repository name and <github_author_handle> with your GitHub username:

cd <project_name>
git init -b main
git add .
git commit -m "Initial commit"
git remote add origin git@github.com:<github_author_handle>/<project_name>.git
git push -u origin main

Step 3: Install the Environment and Pre-commit Hooks

Run the following command to install the environment and pre-commit hooks:

make bake-env

Now you're all set to start development! The CI/CD pipeline will automatically trigger on pull requests, merges to the main branch, and new releases.

For instructions on publishing to PyPI, refer to this guide. To enable automatic documentation with MkDocs, follow the steps in this guide. For code coverage setup, refer to this guide.

Documentation

You can find the documentation for this template here.

Acknowledgements

This project is inspired by Audrey Feldroy's excellent work on the cookiecutter-pypackage template.

Metadata

Release files for cookiecutter-ml 0.0.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for cookiecutter-ml 0.0.3
File Size Uploaded
cookiecutter_ml-0.0.3.tar.gz 110.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for cookiecutter-ml 0.0.3
File Interpreter ABI Platform
cookiecutter_ml-0.0.3-py3-none-any.whl Python 3 none any Details

Total release size: 233.1 kB

Release files / cookiecutter_ml-0.0.3.tar.gz

Download URL cookiecutter_ml-0.0.3.tar.gz
Size 110.1 kB
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6e19f7bb0fdddd4889be1984e7e34fefa011b47ad45300f546daa42f78d6e973
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Uploaded via poetry/1.7.1 CPython/3.12.8 Linux/6.5.0-1025-azure

Release files / cookiecutter_ml-0.0.3-py3-none-any.whl

Download URL cookiecutter_ml-0.0.3-py3-none-any.whl
Size 123.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3994e3fa4fe53e27696dad15d2d1a233e2bac26e4592aa1aeba205bd4434a641
BLAKE2b-256 checksum
How to use checksums
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Uploaded using Trusted Publishing?
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No
Uploaded via poetry/1.7.1 CPython/3.12.8 Linux/6.5.0-1025-azure

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