A .pyx or .py file is compiled by Cython to a .c file, containing the code of a Python extension module. The .c file is compiled by a C compiler to a .so file (or .pyd on Windows) which can be import-ed directly into a Python session. setuptools takes care of this part. Although Cython can call them for you in certain cases. Write a setuptools setup.py. This is the normal and recommended way. Run
This version of the documentation is for the latest and greatest in-development branch of Cython. For the last release version, see here. Cython - an overview¶ [Cython] is a programming language that makes writing C extensions for the Python language as easy as Python itself. It aims to become a superset of the [Python] language which gives it high-level, object-oriented, functional, and dynamic p
If you use the pure Python syntax we strongly recommend you use a recent Cython 3 release, since significant improvements have been made here compared to the 0.29.x releases. Dynamic memory allocation is mostly a non-issue in Python. Everything is an object, and the reference counting system and garbage collector automatically return memory to the system when it is no longer being used. When it co
If you use the pure Python syntax we strongly recommend you use a recent Cython 3 release, since significant improvements have been made here compared to the 0.29.x releases. Cython supports native parallelism through the cython.parallel module. To use this kind of parallelism, the GIL must be released (see Releasing the GIL). It currently supports OpenMP, but later on more backends might be suppo
This version of the documentation is for the latest and greatest in-development branch of Cython. For the last release version, see here. Installing Cython¶ Many scientific Python distributions, such as Anaconda [Anaconda], Enthought Canopy [Canopy], and Sage [Sage], bundle Cython and no setup is needed. Note however that if your distribution ships a version of Cython which is too old you can stil
This version of the documentation is for the latest and greatest in-development branch of Cython. For the last release version, see here. Using C++ in Cython¶ Overview¶ Cython has native support for most of the C++ language. Specifically: C++ objects can be dynamically allocated with new and del keywords. C++ objects can be stack-allocated. C++ classes can be declared with the new keyword cppclass
This version of the documentation is for the latest and greatest in-development branch of Cython. For the last release version, see here.
Note Cython 0.16 introduced typed memoryviews as a successor to the NumPy integration described here. They are easier to use than the buffer syntax below, have less overhead, and can be passed around without requiring the GIL. They should be preferred to the syntax presented in this page. See Cython for NumPy users. Note There is currently no way to usefully specify Numpy arrays using Python-style
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