exaloop/codon

A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support

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Summary Information

Updated 54 minutes ago
Added to GitGenius on September 3rd, 2026
Created on September 27th, 2021
Open Issues & Pull Requests: 117 (+0)
GitHub issues: Enabled
Number of forks: 603
Total Stargazers: 16,840 (+1)
Total Subscribers: 139 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 47.8 hours
Mean response time: 48.8 days
90th percentile: 98.7 days
Tracked items: 291

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 88% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 6% of issues opened in the past year have been closed. Three people close 92% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 81
New in 7 days: 0
Closed in 7 days: 3
Avg open age: 441 days
Stale 30+ days: 76
Stale 90+ days: 71

Recent activity

Opened in 7 days: 0
Closed in 7 days: 3
Comments in 7 days: 1
Events in 7 days: 1

Top labels

  • bug (38)
  • enhancement (30)
  • stdlib (13)
  • question (6)
  • help wanted (5)
  • documentation (3)
  • installation (3)
  • typecheck (2)

Detailed Description

Codon is a high-performance Python compiler that compiles to native machine code without runtime overhead.

Codon addresses the performance gap between Python and compiled languages by implementing static, ahead-of-time compilation to native code. It achieves typical speedups of 10-100x or more over standard Python on a single thread, with performance comparable to C and C++. The compiler is built from the ground up to support native multithreading without the Global Interpreter Lock, enabling additional speedups through parallelism. It includes built-in NumPy support and a comprehensive optimization framework targeting high-level Python constructs.

Codon suits performance-critical applications where Python's syntax and ecosystem are desired but execution speed is essential. It maintains close compatibility with CPython syntax and semantics to minimize the learning curve, though it is not a drop-in replacement—some dynamic Python features unsuitable for static compilation are not supported. The tool provides multiple integration paths for larger Python codebases through a JIT decorator, Python extension backend, and Python interoperability layer that allows calling any Python module. For developers choosing between Codon and alternatives, the README emphasizes that it avoids introducing new syntax or language constructs, keeping the experience as familiar as possible while enabling compilation to executables, LLVM IR generation, and both debug and optimized release builds.

Development activity shows consistent engagement with the project through active continuous integration workflows and maintained documentation including a roadmap and FAQ. The team maintains a public Discord community for user support and discussion.