technomancy/leiningen

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Summary Information

Updated 29 minutes ago
Added to GitGenius on September 9th, 2026
Created on November 1st, 2009
Open Issues & Pull Requests: 94 (+0)
GitHub issues: Enabled
Number of forks: 1,569
Total Stargazers: 7,297 (+0)
Total Subscribers: 207 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 15.6 hours
Mean response time: 240.6 days
90th percentile: 358.6 days
Tracked items: 24

Charts & Analytics

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Issue Activity (beta)

Open issues: 3
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 2,332 days
Stale 30+ days: 3
Stale 90+ days: 3

Recent activity

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

Top labels

  • bug (8)
  • upstream (6)
  • Enhancement (3)
  • usability (3)
  • Windows (2)
  • needrepro (2)
  • Newbie (1)
  • investigate (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Leiningen is a build automation and dependency management tool for Clojure projects.

Leiningen addresses the need for a standardized way to manage Clojure project builds, dependencies, and tasks. It provides a declarative project configuration format that specifies dependencies, build settings, and custom tasks, automating compilation, testing, and packaging workflows without requiring developers to write build scripts manually.

Leiningen suits developers working on Clojure applications and libraries who want a batteries-included build tool with sensible defaults. It is particularly valuable for teams that need reproducible builds and straightforward dependency resolution. The tool works well for projects ranging from small scripts to large applications, offering both simplicity for beginners and extensibility for advanced users through custom task definitions.

The project has relocated its primary repository to a community-governed platform while maintaining binary distributions on its original hosting location to reduce infrastructure load. Development discussion occurs through an IRC channel, and the maintainers have explicitly stated they do not consent to the use of the project's code or data for training machine learning models.