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A Python package standard and generator for scientific code. Use scikit-package to launch a new project or migrate existing ones to support the latest Python versions and streamline the process of distributing and maintaining your software package.

Project description

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scikit-package offers tools and practices for the scientific community to make better and more reusable Scientific Python packages and applications:

  • We help scientists share scientific code to amplify research impact.

  • We help scientists save time, allowing them to focus on writing scientific code.

  • We offer best practices from the group’s experience in developing scientific software.

Overview

Here is an overview of the 5 levels of sharing code and the key features of scikit-package:

Diagram of 5 levels of sharing code with key features and scikit-package commands

Demo

Here is how you can use the package create public command to create a new Level 5 Python package called diffpy.my-project in just 1–2 minutes:

Demonstration of creating a new Level 5 package with scikit-package

Getting started

Are you interested in using scikit-package? Begin with the Getting Started page in our online documentation at https://scikit-package.github.io/scikit-package!

Installation

The preferred method is to use Miniconda Python and install from the “conda-forge” channel of Conda packages.

To add “conda-forge” to the conda channels, run the following in a terminal.

conda config --add channels conda-forge

We want to install our packages in a suitable conda environment. The following creates and activates a new environment named skpkg_env

conda create -n skpkg_env scikit-package
conda activate skpkg_env

To confirm that the installation was successful, type

python -c "import scikit_package; print(scikit_package.__version__)"

The output should print the latest version displayed on the badges above.

If the above does not work, you can use pip to download and install the latest release from Python Package Index. To install using pip into your skpkg_env environment, type

pip install scikit-package

If you prefer to install from sources, after installing the dependencies, obtain the source archive from GitHub. Once installed, cd into your scikit-package directory and run the following

pip install .

This package also provides command-line utilities. To conform the installation, type

package --version

To view the basic usage and available commands, type

package --h

How to cite scikit-package

If you use scikit-package to standardize your Python software, we would like you to cite scikit-package:

  1. Lee and C. Myers and A. Yang and T. Zhang and S. J. L. Billinge, scikit-package - software packaging standards and roadmap for sharing reproducible scientific software (https://arxiv.org/abs/2507.03328)

Support and Contribute

If you see a bug or want to request a feature, please report it as an issue and/or submit a fix as a PR.

Feel free to fork the project and contribute. To install scikit-package in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory

pip install -e .

To ensure code quality and to prevent accidental commits into the default branch, please set up the use of our pre-commit hooks.

  1. Install pre-commit in your working environment by running conda install pre-commit.

  2. Initialize pre-commit (one time only) pre-commit install.

Thereafter your code will be linted by black and isort and checked against flake8 before you can commit. If it fails by black or isort, just rerun and it should pass (black and isort will modify the files so should pass after they are modified). If the flake8 test fails please see the error messages and fix them manually before trying to commit again.

Improvements and fixes are always appreciated.

Before contributing, please read our Code of Conduct.

Contact

For more information on scikit-package please visit the project web-page or email Simon Billinge at sb2896@columbia.edu}}.

Acknowledgements

This GitHub repository is built and maintained with the help of scikit-package as well.

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