GitHub - cython/cython: The most widely used Python to C compiler (original) (raw)

Welcome to Cython!

Cython is an optimising Python compiler that makes writing C extensions for Python as easy as Python itself.

Cython translates Python code to C/C++ code, but additionally supports calling C functions and declaring C types on variables and class attributes. This allows broad to fine-grained manual tuning that lets the compiler generate very efficient C code from Cython code.

This makes Cython the ideal language for wrapping external C libraries, and for fast C modules that speed up the execution of Python code.

• Official website: https://cython.org/
• Documentation: https://docs.cython.org/
• Github repository: https://github.com/cython/cython
• Wiki: https://github.com/cython/cython/wiki

Cython has more than 70 million downloadsper month on PyPI. You can support the Cython project viaGithub Sponsors orTidelift.

Installation:

If you already have a C compiler, just run following command:

pip install Cython

otherwise, see the installation page.

License:

The original Pyrex program, which Cython is based on, was licensed "free of restrictions" (see below). Cython itself is licensed under the permissive Apache License.

See LICENSE.txt.

Contributing:

Want to contribute to the Cython project? Here is some help to get you started.

Differences to other Python compilers

Started as a project in the early 2000s, Cython has outlivedmost other attemptsat producing static compilers for the Python language.

Similar projects that have a relevance today include:

• PyPy, a Python implementation with a JIT compiler.
  • Pros: JIT compilation with runtime optimisations, fully language compliant, good integration with external C/C++ code
  • Cons: non-CPython runtime, relatively large resource usage of the runtime, limited compatibility with CPython extensions, non-obvious performance results
• Numba, a Python extension that features a JIT compiler for a subset of the language, based on the LLVM compiler infrastructure (probably best known for its clang C compiler). It mostly targets numerical code that uses NumPy.
  • Pros: JIT compilation with runtime optimisations
  • Cons: limited language support, relatively large runtime dependency (LLVM), non-obvious performance results
• Pythran, a static Python-to-C++ extension compiler for a subset of the language, mostly targeted at numerical computation. Pythran can be (and is probably best) used as an additionalbackend for NumPy codein Cython.
• mypyc, a static Python-to-C extension compiler, based on the mypy static Python analyser. Like Cython'spure Python mode, mypyc can make use of PEP-484 type annotations to optimise code for static types.
  • Pros: good support for language and PEP-484 typing, good type inference, reasonable performance gains
  • Cons: no support for low-level optimisations and typing, opinionated Python type interpretation, reduced Python compatibility and introspection after compilation
• Nuitka, a static Python-to-C extension compiler.
  • Pros: highly language compliant, reasonable performance gains, support for static application linking (similar tocython_freezebut with the ability to bundle library dependencies into a self-contained executable)
  • Cons: no support for low-level optimisations and typing

In comparison to the above, Cython provides

• fast, efficient and highly compliant support for almost all Python language features, including dynamic features and introspection
• full runtime compatibility with all still-in-use and future versions of CPython
• "generate once, compile everywhere" C code generation that allows for reproducible performance results and testing
• C compile time adaptation to the target platform and Python version
• support for other C-API implementations, including PyPy and Pyston
• seamless integration with C/C++ code
• broad support for manual optimisation and tuning down to the C level
• a large user base with thousands of libraries, packages and tools
• more than two decades of bug fixing and static code optimisations

The following is from Pyrex:

Cython was originally based on Pyrexby Greg Ewing, with the following written in the Pyrex readme document:

This is a development version of Pyrex, a language for writing Python extension modules.

For more info, take a look at:

• Doc/About.html for a description of the language
• INSTALL.txt for installation instructions
• USAGE.txt for usage instructions
• Demos for usage examples

Comments, suggestions, bug reports, etc. are most welcome!

Copyright stuff: Pyrex is free of restrictions. You may use, redistribute, modify and distribute modified versions.

The latest version of Pyrex can be found here.

Greg Ewing, Computer Science Dept

University of Canterbury

Christchurch, New Zealand

A citizen of NewZealandCorp, a wholly-owned subsidiary of USA Inc.