What build backend does this skill use?

It primarily recommends and configures Hatchling, a modern, standards-compliant build backend favored by the Scientific Python community for its speed and extensibility.

Does this support modern dependency management?

Yes, it implements PEP 735 dependency groups to manage test, documentation, and development requirements separately and cleanly.

Why does this skill enforce the src/ layout?

The src/ layout is a best practice that prevents accidental imports of uninstalled code from the project root, ensuring that tests run against the actually installed package.

Can I use this for non-scientific Python projects?

While it follows scientific community guidelines, the standards used (PEP 621, Hatchling, src/ layout) are considered best practices for almost any modern Python project.

Scientific Python Packaging

Name: Scientific Python Packaging
Author: uw-ssec

byuw-ssec

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데이터 과학 및 ML

Standardizes the creation of distributable Python packages using modern Scientific Python community best practices and Hatchling build backends.

소개

This skill provides a comprehensive framework for structuring, building, and publishing Python packages tailored specifically for scientific computing and research software engineering. It implements the Scientific Python community guidelines, utilizing pyproject.toml with PEP 621 metadata, the src/ layout for robust import isolation, and the Hatchling build backend. Whether you are preparing a library for PyPI, setting up reproducible research projects, or implementing CLI tools for scientific workflows, this skill ensures your package follows modern standards for dependency management, licensing, and metadata configuration.

주요 기능

Scientific community-aligned dependency management (PEP 735)
Automated pyproject.toml generation with Hatchling build-backend
Implementation of src/ layout for proper package isolation
6 GitHub stars
Standardized metadata for research software and SPDX licensing
Streamlined publishing workflows for PyPI and TestPyPI

사용 사례

Publishing scientific software to PyPI with correct metadata and classifiers
Converting research scripts into professional, installable Python libraries
Standardizing repository structure for collaborative research projects

소개

주요 기능

Scientific community-aligned dependency management (PEP 735)
Automated pyproject.toml generation with Hatchling build-backend
Implementation of src/ layout for proper package isolation
6 GitHub stars
Standardized metadata for research software and SPDX licensing
Streamlined publishing workflows for PyPI and TestPyPI

사용 사례

Publishing scientific software to PyPI with correct metadata and classifiers
Converting research scripts into professional, installable Python libraries
Standardizing repository structure for collaborative research projects