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May 3, 20260 citationsOpen Access

PoolinGH:Fast, Efficient, and Robust GitHub Repository Mining

MAMaxime; id_orcid 0009-0002-1241-8319 AndréMRMarco RagliantiSSSouhaila Serbout

Key Points

  • The aim is to create a library that improves efficiency and robustness in mining GitHub repositories.
  • Developed a lightweight and open-source library, PoolinGH, for mining GitHub data.
  • Utilized automatic pooling of multiple access tokens and parallelized queries.
  • Implemented error management and recovery techniques to handle API limitations.
  • PoolinGH demonstrated tangible gains, processing tens of thousands of requests successfully.
  • Optimized queuing and regulated network usage improved compliance with GitHub API limits.

Abstract

Researchers in Mining (open-source) Software Repositories (MSR) often create datasets that should survive the single paper and support long-term investigation of specific phenomena. Although popular, these studies recurrently deal with similar technical limitations. For instance, public collaborative development platforms, such as GitHub, impose hourly rate limits on their API requests. Furthermore, depending on network and API conditions, queries can fail and disrupt the process. These unexpected events can slow down or even invalidate the mining. Nevertheless, there are ways to minimize the undesirable effects in a reusable way while still complying with such limitations. However, best practices are often (re-)implemented on an ad hoc basis. Whatever works. We propose PoolinGH, a lightweight, open-source, easy-to-use library, aimed at supporting researchers. It is designed to accelerate and ensure efficient and robust mining on the GitHub REST API while taking full advantage of its capabilities. PoolinGH enables automatic pooling of multiple access tokens and parallelizes queries. It optimizes queues and regulates network and API usage for respecting GitHub’s limits and best practices. Error management and recovery or pruning in case of deadlocks are ensured. Search coverage maximization and progress monitoring are among the most useful features to avoid reinventing the wheel. We also provide solution templates that meet common needs for specific extensions of PoolinGH. A preliminary evaluation of these examples, involving tens of thousands of requests, demonstrates tangible gains.

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Cite This Study

André et al. (2026) studied this question.

synapsesocial.com/papers/69f6e5ac8071d4f1bdfc6555https://doi.org/10.1145/3793302.3793321
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