Why is the src/ layout recommended for scientific packages?

The src/ layout forces developers to install the package before running tests, preventing accidental imports of local source code and ensuring the software works exactly as it will for end-users.

Which build backend does this skill use?

This skill utilizes Hatchling, which is the recommended build backend for the Scientific Python community due to its speed, standard compliance, and extensibility.

Can I manage dependencies for testing and documentation separately?

Absolutely. This skill uses PEP 735 dependency groups to organize requirements for development, testing, and documentation without cluttering the core runtime dependencies.

Does this skill support pyproject.toml metadata?

Yes, it fully implements PEP 621 standards for project metadata, ensuring your package information is readable by all modern Python build and installation tools.

Scientific Python Packaging

Name: Scientific Python Packaging
Author: uw-ssec

byuw-ssec

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数据科学与机器学习

Streamlines the creation of distributable scientific Python packages using modern pyproject.toml standards and community-best practices.

关于

This skill provides expert guidance for researchers and developers building Python software for scientific computing. It automates the implementation of Scientific Python community standards, focusing on the modern 'src/' layout, PEP 621 metadata, and the Hatchling build backend. By following this skill, users can transform local research scripts into professional, reproducible packages ready for PyPI distribution, complete with optimized dependency management and standardized project structures.

主要功能

Step-by-step distribution workflows for PyPI and TestPyPI
Modern dependency group management following PEP 735
Automated configuration for scientific data files and CLI tools
5 GitHub stars
Implementation of the 'src/' layout for improved package isolation
Standardized pyproject.toml generation using Hatchling and PEP 621

使用场景

Converting research code into an installable and peer-reviewable library
Migrating legacy setup.py projects to modern, standards-compliant packaging
Structuring complex scientific software with integrated datasets and documentation

关于

主要功能

Step-by-step distribution workflows for PyPI and TestPyPI
Modern dependency group management following PEP 735
Automated configuration for scientific data files and CLI tools
5 GitHub stars
Implementation of the 'src/' layout for improved package isolation
Standardized pyproject.toml generation using Hatchling and PEP 621

使用场景

Converting research code into an installable and peer-reviewable library
Migrating legacy setup.py projects to modern, standards-compliant packaging
Structuring complex scientific software with integrated datasets and documentation