python_enhancement_proposals

# Python Enhancement Proposals

## Description
Python Enhancement Proposals, or PEPs, are design documents that generally provide a technical specification and rationale for new features of the Python programming language.
There are been 661 PEPs published.
The majority of PEPs are published in the Public Domain, but 5 were published under the “Open Publication License” and omitted from this dataset.
PEPs are long, highly-polished, and technical in nature and often include code examples paired with their prose.
PEPs are authored in ReStructured Text; we used [pandoc](https://pandoc.org/) to convert them to plain text.

## Dataset Statistics
| Documents | UTF-8 GB |
|-----------|----------|
| 656 | 0.01 |

## License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see [our paper](https://huggingface.co/papers/2506.05209)). If you believe you have found an instance of incorrect licensing in this dataset, please [start a discussion](https://github.com/r-three/common-pile/discussions/new) on this repository.

## Other Versions
This is the "raw" version of the Python Enhancement Proposals dataset.
If you are looking for the filtered version used to train [Comma v0.1](https://huggingface.co/common-pile/comma-v0.1), you can find it [here](https://huggingface.co/datasets/common-pile/python_enhancement_proposals_filtered).

## Citation
If you use this dataset, please cite:
```bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}
```

# Python增强提案（Python Enhancement Proposals，PEPs）

## 描述
Python增强提案（Python Enhancement Proposals，简称PEPs）是一类设计文档，通常为Python编程语言的新功能提供技术规范与理论依据。目前已发布661份PEPs。其中绝大多数PEPs以公共领域（Public Domain）授权发布，但有5份采用“开放出版许可（Open Publication License）”授权，因此未被纳入本数据集。PEPs篇幅较长、打磨精细且具备较强的技术属性，通常会在正文中搭配代码示例。PEPs采用ReStructured Text格式撰写，我们使用[pandoc](https://pandoc.org/)将其转换为纯文本格式。

## 数据集统计
| 文档数量 | UTF-8 格式体积（GB） |
|-----------|---------------------|
| 656 | 0.01 |

## 授权问题
尽管我们致力于提供完全准确的授权信息，但授权洗白与元数据不准确可能导致我们错误地为部分文档分配了错误的授权（如需进一步讨论该局限性，请参阅[我们的论文](https://huggingface.co/papers/2506.05209)）。若您认为本数据集存在授权信息错误的案例，请前往此仓库[发起讨论](https://github.com/r-three/common-pile/discussions/new)。

## 其他版本
本版本为Python增强提案数据集的“原始版”。若您正在寻找用于训练[Comma v0.1](https://huggingface.co/common-pile/comma-v0.1)的过滤版数据集，可在[此处](https://huggingface.co/datasets/common-pile/python_enhancement_proposals_filtered)获取。

## 引用说明
若您使用本数据集，请引用以下文献：
bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}