cython – cython

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 downloads _
per month on PyPI. You can support the Cython project via
Github Sponsors _ or
Tidelift _.

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 outlived
most other attempts _
at 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 additional
backend for NumPy code _
in Cython.

• mypyc _, a static Python-to-C extension

compiler, based on the mypy _ static Python
analyser. Like Cython's
pure 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 to
cython_freeze _
but 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 Pyrex _
by 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.