mahmoud/boltons

🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like...

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Summary Information

Updated 41 minutes ago
Added to GitGenius on September 9th, 2026
Created on February 20th, 2013
Open Issues & Pull Requests: 79 (+0)
GitHub issues: Enabled
Number of forks: 432
Total Stargazers: 6,921 (+0)
Total Subscribers: 130 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 9.3 hours
Mean response time: 347.3 days
90th percentile: 1202.3 days
Tracked items: 22

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 9% of issues opened in the past year have been closed. Three people close 89% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 7
New in 7 days: 2
Closed in 7 days: 2
Avg open age: 788 days
Stale 30+ days: 5
Stale 90+ days: 4

Recent activity

Opened in 7 days: 2
Closed in 7 days: 2
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Boltons is a pure-Python utility library that extends the standard library with over 230 additional constructs, recipes, and snippets.

The project addresses the gap between what Python's standard library provides and what developers frequently need in practice. It offers implementations of commonly useful data structures and algorithms—such as an optimized OrderedMultiDict, multiple PriorityQueue variants, atomic file operations, and recursive data structure iteration—without introducing external dependencies. Each module is self-contained and can be used independently or vendored directly into a project if the full library is too large.

Boltons suits developers building general-purpose applications who want reliable, well-tested utilities without adding dependencies. It works best for foundational needs like file handling, iteration patterns, queue operations, and data structure manipulation. The project explicitly acknowledges that specialized third-party libraries exist for advanced use cases and documents these alternatives in its modules, positioning itself as a "good enough" solution for basic requirements rather than a replacement for domain-specific tools.

Development activity shows consistent maintenance with regular updates across multiple Python versions. The project maintains test coverage including doctests and supports a wide range of Python versions from 3.7 through 3.14 as well as PyPy3. The codebase is organized around clear architectural principles documented in the repository, with an explicit design philosophy guiding what functionality belongs in the library. The maintainers actively review feature requests and pull requests, with documentation of the integration process for developers considering vendorization.