codon/docs/intro/faq.md

Technical

What is Codon?

Codon is a high-performance Python compiler that compiles Python code to native machine code without any runtime overhead. Typical speedups over Python are on the order of 10-100x or more, on a single thread. Codon's performance is typically on par with that of C/C++. Unlike Python, Codon supports native multithreading, which can lead to speedups many times higher still. Codon is extensible via a plugin infrastructure, which lets you incorporate new libraries, compiler optimizations and even keywords.

What isn't Codon?

While Codon supports nearly all of Python's syntax, it is not a drop-in replacement, and large codebases might require modifications to be run through the Codon compiler. For example, some of Python's modules are not yet implemented within Codon, and a few of Python's dynamic features are disallowed. The Codon compiler produces detailed error messages to help identify and resolve any incompatibilities. Codon supports seamless Python interoperability to handle cases where specific Python libraries or dynamism are required.

How does Codon compare to...

• CPython? Codon tries to follow CPython's syntax, semantics and APIs as closely as possible, aside from a few cases where Codon differs from CPython for performance reasons (one example being Codon's 64-bit int vs. CPython's arbitrary- width int). Performance-wise, speedups over CPython are usually on the order of 10-100x.

• Numba? While Codon does offer a JIT decorator similar to Numba's, Codon is in general an ahead-of-time compiler that compiles end-to-end programs to native code. It also supports compilation of a much broader set of Python constructs and libraries.

• PyPy? PyPy strives to effectively be a drop-in replacement for CPython, whereas Codon differs in a few places in order to eliminate any dynamic runtime or virtual machine, and thereby attain much better performance.

• C++? Codon often generates the same code as an equivalent C or C++ program. Codon can sometimes generate better code than C/C++ compilers for a variety of reasons, such as better container implementations, the fact that Codon does not use object files and inlines all library code, or Codon-specific compiler optimizations that are not performed with C or C++.

• Julia? Codon's compilation process is actually much closer to C++ than to Julia. Julia is a dynamically-typed language that performs type inference as an optimization, whereas Codon type checks the entire program ahead of time. Codon also tries to circumvent the learning curve of a new language by adopting Python's syntax and semantics.

You can see results from Codon's benchmark suite suite at exaloop.io/benchmarks. More benchmarks can be found in the 2019 paper on bioinformatics-specific use cases (note that the name used in that paper is that of Codon's predecessor, "Seq").

I want to use Codon, but I have a large Python codebase I don't want to port.

You can use Codon on a per-function basis via the @codon.jit decorator, which can be used within Python codebases. This will compile only the annotated functions and automatically handle data conversions to and from Codon. It also allows for the use of any Codon-specific modules or extensions, such as multithreading.

What about interoperability with other languages and frameworks?

Interoperability is and will continue to be a priority for Codon. We don't want using Codon to render you unable to use all the other great frameworks and libraries that exist. Codon supports full interoperability with Python and C/C++.

Does Codon use garbage collection?

Yes, Codon uses the Boehm garbage collector.

Codon doesn't support Python module X or function Y.

While Codon covers a sizeable subset of Python's standard library, it does not yet cover every function from every module. Note that missing functions can still be called through Python via from python import. Many of the functions that lack Codon-native implementations (e.g. I/O or OS related functions) will generally also not see substantial speedups from Codon.

Codon is no faster than Python for my application.

Applications that spend most of their time in C-implemented library code generally do not see substantial performance improvements in Codon. Similarly, applications that are I/O or network-bound will have the same bottlenecks in Codon.

Codon is slower than Python for my application.

Please report any cases where Codon is noticeably slower than Python as bugs on our issue tracker.

Usage

Is Codon free?

Codon is and always will be free for non-production use. That means you can use Codon freely for personal, academic, or other non-commercial applications.

Is Codon open source?

Codon is licensed under the Business Source License (BSL), which means its source code is publicly available and it's free for non-production use. The BSL is technically not an "open source" license, although in many circumstances you can still treat Codon as you would any other open source project. Importantly, as per the BSL, each version of Codon converts to an actual open source license (specifically, Apache) after 3 years.

How can I use Codon for production or commercial use?

Please reach out to info@exaloop.io to inquire about about a production-use license.

Contributing

Does Codon accept outside contributions?

Absolutely, we'd be delighted to accept any contributions in the form of issues, bug reports, feature requests or pull requests.

I want to contribute. Where do I start?

If you have a specific feature or use case in mind, here is a quick breakdown of the codebase to help provide a sense of where to look first:

• codon/: compiler code
  • codon/parser/: parser and type checker code: this is the first step of compilation
  • codon/sir/: Codon IR and optimizations: the second step of compilation
  • codon/sir/llvm/: conversion from Codon IR to LLVM IR and machine code: the last step of compilation
  • codon/runtime/: runtime library: used during execution
• stdlib/: standard library code

You can also take a look at some of the open issues. If you have any question or suggestions, please feel free to ask in the forum.

Is there a Contributor License Agreement (CLA)?

Yes, there is a CLA that is required to be agreed to before any pull requests are merged. Please see exaloop.io/cla.txt for more information. To agree to the CLA, send an email with your GitHub username to info@exaloop.io.