Pythran 0.7.4 is out!

The pythran team (a great total of 2 active developers) is delighted to announce the release of Pythran 0.7.4, available on the traditional channels:

• pypi: https://pypi.python.org/pypi/pythran
• conda: https://anaconda.org/serge-sans-paille/pythran
• github: https://github.com/serge-sans-paille/pythran

As usual, here is a (new) code sample, once again adapted from a stackoverflow question [0] that showcases pythran capability:

#pythran export check_mask(bool[][], bool[])
#  ^~~~~~~ non intrusive top-level annotation

import numpy as np
#      ^~~~~~ numpy support (partial)
def check_mask(db, out, mask=[1, 0, 1]):
    for idx, line in enumerate(db):
        target, vector = line[0], line[1:]
        # ^~~~~ type destructuring, array view
        if (mask == np.bitwise_and(mask, vector)).all():
        # ^~~~~~~ optimization of high level construct
            if target == 1:
                out[idx] = 1
    return out

Compiled with:

% pythran check_mask.py

And benchmarked with:

% python -m timeit -s 'n=10e3 ; import numpy as np;db  = np.array(np.random.randint(2, size=(n, 4)), dtype=bool); out = np.zeros(int(n),dtype=bool); from eq import check_mask' 'check_mask(db, out)'

On average, the CPython version runs in 137 msec while the pythran version run in 450us on my laptop :-)

Here is an extract of the changelog:

2016-01-05 Serge Guelton <serge.guelton@telecom-bretagne.eu>

    * IPython's magic for pythran now supports extra compile flags

    * Pythran's C++ output is compatible with Python3 and pythran3 can compile it!

    * More syntax checks (and less template traceback)

    * Improved UI (multiline pythran exports, better setup.py...)

    * Pythonic leaning / bugfixing (this tends to be a permanent item)

    * More generic support for numpy's dtype

    * Simpler install (no more boost.python deps, nor nt2 configuration)

    * Faster compilation (no more boost.python deps, smarter pass manager)

    * Better testing (gcc + clang)

Again, thanks a lot to Pierrick for his continuous top-quality work, and to the OpenDreamKit [1] project that funded (most of) the recent developments!

Special thanks to @hainm, @nbecker, @pkoch, @fsteinmetz, @Suor for their feedbacks. You give us the motivation to go on!