ComPyle is itself pure Python but depends on numpy and requires either Cython or PyOpenCL or PyCUDA along with the respective backends of a C/C++ compiler, OpenCL and CUDA. If you are only going to execute code on a CPU then all you need is Cython. The full list of requirements is shown in the requirements.txt file on the repository.

You should be able to install ComPyle by doing:

$ pip install compyle

Note that when executing code on a CPU, you will need to have a C/C++ compiler that is compatible with your Python installation. In addition, if you need to use OpenMP you will need to make sure your compiler is compatible with that. Some additional information on this is included below.

Setting up on GNU/Linux

This is usually very simple, just installing the standard gcc/g++ packages ought to work. OpenMP is typically available but if it is not, it can be installed with (on apt-compatible systems):

$ sudo apt-get install libgomp1

Setting up on MacOS

Ensure that you have gcc or clang installed by installing XCode. See this if you installed XCode but can’t find clang or gcc.

If you are getting strange errors of the form:

lang: warning: libstdc++ is deprecated; move to libc++ with a minimum deployment target of OS X 10.9 [-Wdeprecated]
ld: library not found for -lstdc++
clang: error: linker command failed with exit code 1 (use -v to see invocation)

Then try this (on a bash shell):


And run your command again (replace the above with a suitable line on other shells). This is necessary because your Python was compiled with an older deployment target and the current version of XCode that you have installed is not compatible with that. By setting the environment variable you allow compyle to use a newer version. If this works, it is a good idea to set this in your default environment (.bashrc for bash shells) so you do not have to do this every time.

OpenMP on MacOS

The default clang compiler available on MacOS uses an LLVM backend and does not support OpenMP. There are two ways to support OpenMP. The first involves installing the OpenMP support for clang. This can be done with brew using:

$ brew install libomp

Once that is done, it should “just work”. If you get strange errors, try setting the MACOSX_DEPLOYMENT_TARGET as shown above.

Another option is to install GCC for MacOS available on brew using

$ brew install gcc

Once this is done, you need to use this as your default compiler. The gcc formula on brew currently ships with gcc version 9. Therefore, you can tell Python to use the GCC installed by brew by setting:

$ export CC=gcc-9
$ export CXX=g++-9

Note that you still do need to have the command-line-tools for XCode installed, otherwise the important header files are not available. See how-to-install-xcode-command-line-tools for more details. You may also want to set these environment variables in your .bashrc so you don’t have to do this every time.

Once you do this, compyle will automatically use this version of GCC and will also work with OpenMP. Note that on some preliminary benchmarks, GCC’s OpenMP implementation seems about 10% or so faster than the LLVM version. Your mileage may vary.

Setting up on Windows

Windows will work but you need to make sure you have the right compiler installed. See this page for the details of what you need installed.

OpenMP will work if you have this installed. For recent Python versions (>=3.5), install the Microsoft Build Tools for Visual Studio 2019

Setting up OpenCL/CUDA

This is too involved a topic to discuss here, instead look at the appropriate documentation for PyOpenCL and PyCUDA. Once those packages work correctly, you should be all set. Note that if you are only using OpenCL/CUDA you do not need to have Cython or a C/C++ compiler. Some features on CUDA require the use of the CuPy library.