# An Empirical Analysis of the Python Package Index (PyPI)

**Authors:** Ethan Bommarito, Michael Bommarito

arXiv: 1907.11073 · 2019-07-29

## TL;DR

This paper provides a comprehensive empirical analysis of PyPI, detailing its growth, distribution patterns, and contributor dynamics over 15 years, offering insights into the Python ecosystem's development.

## Contribution

It presents the first large-scale empirical summary of PyPI, analyzing package metadata, source code, and trends, serving as a foundation for future Python ecosystem research.

## Key findings

- Robust growth in packages, authors, and import statements over 15 years
- Highly skewed distributions in package contributions and imports
- Most packages are contributed by single individuals

## Abstract

In this research, we provide a comprehensive empirical summary of the Python Package Repository, PyPI, including both package metadata and source code covering 178,592 packages, 1,745,744 releases, 76,997 contributors, and 156,816,750 import statements. We provide counts and trends for packages, releases, dependencies, category classifications, licenses, and package imports, as well as authors, maintainers, and organizations. As one of the largest and oldest software repositories as of publication, PyPI provides insight not just into the Python ecosystem today, but also trends in software development and licensing more broadly over time. Within PyPI, we find that the growth of the repository has been robust under all measures, with a compound annual growth rate of 47% for active packages, 39% for new authors, and 61% for new import statements over the last 15 years. As with many similar social systems, we find a number of highly right-skewed distributions, including the distribution of releases per package, packages and releases per author, imports per package, and size per package and release. However, we also find that most packages are contributed by single individuals, not multiple individuals or organizations. The data, methods, and calculations herein provide an anchor for public discourse on PyPI and serve as a foundation for future research on the Python software ecosystem.

## Full text

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## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/1907.11073/full.md

## References

24 references — full list in the complete paper: https://tomesphere.com/paper/1907.11073/full.md

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Source: https://tomesphere.com/paper/1907.11073