http://pythran.readthedocs.io

Pythran is an ahead of time compiler for a subset of the Python language, with a focus on scientific computing. It takes a Python module annotated with a few interface description and turns it into a native Python module with the same interface, but (hopefully) faster.

It is meant to efficiently compile scientific programs, and takes advantage of multi-cores and SIMD instruction units.

Pythran supports Python 2.7 and also has a decent Python 3 support.

Pythran sources are hosted on https://github.com/serge-sans-paille/pythran.

Pythran releases are hosted on http://pypi.python.org/pypi/pythran.

Pythran is available through Conda on https://anaconda.org/conda-forge/pythran.

1. Gather dependencies:

   Pythran depends on a few Python modules and several C++ libraries. On a debian-like platform, run:

   $> sudo apt-get install libatlas-base-dev
   $> sudo apt-get install python-dev python-ply python-networkx python-numpy
   

2. Use easy_install or pip:

   $> pip install pythran
   

1. Install conda, following the instruction given in http://conda.pydata.org/docs/install/quick.html

2. Run:

   $> conda install -c conda-forge pythran
   

Using brew (http://brew.sh/):

$> easy_install pip

$> pip install pythran

Depending on your setup, you may need to add the following to your \~/.pythranrc`` file:

[compiler]
CXX=g++-4.9
CC=gcc-4.9

Using any working AUR helper, say aurman:

$> aurman -S python-pythran

Windows support is on going and only targets Python 3.5+ with Visual Studio 2017.

% pip install pythran

See MANUAL file.

A simple pythran input could be dprod.py:

"""
Naive dotproduct! Pythran supports numpy.dot
"""
#pythran export dprod(int list, int list)
def dprod(l0,l1):
    """WoW, generator expression, zip and sum."""
    return sum(x * y for x, y in zip(l0, l1))

To turn it into a native module, run:

$> pythran dprod.py

That will generate a native dprod.so that can be imported just like the former module:

$> python -c 'import dprod' # this imports the native module instead

The user documentation is available in the MANUAL file from the doc directory.

The developer documentation is available in the DEVGUIDE file from the doc directory. The also is a TUTORIAL file for those who don't like reading documentation.

A todo list is maintained in the eponymous TODO file.

The CLI documentation is available from the pythran help command:

$> pythran --help

Some extra developer documentation is also available using pydoc. Beware, this is the computer science incarnation for the famous Where's Waldo? game:

$> pydoc pythran
$> pydoc pythran.typing

See the pythran/tests/cases/ directory from the sources.

Praise, flame and cookies:

• [email protected] -- register at http://www.freelists.org/list/pythran first!
• #pythran on FreeNode
• [email protected]

The mailing list archive is available at http://www.freelists.org/archive/pythran/.

If you need to cite a Pythran paper, feel free to use:

@article{guelton2015pythran,
  title={Pythran: Enabling static optimization of scientific python programs},
  author={Guelton, Serge and Brunet, Pierrick and Amini, Mehdi and Merlini,
                  Adrien and Corbillon, Xavier and Raynaud, Alan},
  journal={Computational Science \& Discovery},
  volume={8},
  number={1},
  pages={014001},
  year={2015},
  publisher={IOP Publishing}
}

See AUTHORS file.

See LICENSE file.