[Python-announce] Pythran release - 0.10.0 - palig
Hi Folks, Pythran, a compiler for scientific kernels written in Python, got a new release. It contains a few changes detailed in the changelog[0] but I'd like to highlight the work[1] of Xingyu Liu during her GSoC on improving pythran <-> scipy integration. It's also a release that recieved a lot of external contributions, and that's always a pleasure. Thanks to you all! $ git log 0.9.9..0.10.0 | grep Author | sort -u | wc -l 21 As usual, Pythran is available since today on PyPI and github, and this will propagate to conda, Fedora etc thanks to our beloved packagers! [0] https://github.com/serge-sans-paille/pythran/blob/0.10.0/Changelog [1] https://serge-sans-paille.github.io/pythran-stories/gsoc21-improve-performance-through-the-use-of-pythran.html ___ Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Member address: arch...@mail-archive.com
pythran 0.9.12 - heskenn
Hi folks, I just shipped a new release of Pythran—a compiler for scientific kernels written in python. It means it is available on PyPI and github, but not yet on conda, fedora, gentoo etc. This one fixes a bunch of issues for Scipy (again), restores compatibility with Cython, but the biggest change is definitively the new dependency tree. Indeed, Pythran no longer depends on networkx, six nor decorator. The dependency on gast and beniget received a version bump for compatibility with python 3.10 changes. Big thanks to the contributors, every commit counts! $ git shortlog -s 0.9.11..0.9.12 1 Ashwin Vishnu 1 Christian Clauss 1 Jochen Schröder 1 Miro Hrončok 2 Ralf Gommers 35 serge-sans-paille 1 刘星雨 A summarized changelog $ git diff 0.9.11..0.9.12 -- Changelog | cut -c 2- (...) 2021-07-06 Serge Guelton * Remove six, networkx and decorator dependency * Bump gast and Beniget requirements to support python 3.10 * Bump xsimd to 7.5.0 * Minimal default support for non-linux, non-osx, now-windows platform * Numpy improvements for np.bincount, np.transpose, np.searchsorted * Restore (and test) cython compatibility * Expose pythran.get_include for toolchain integration * Improve error message on invalid spec * Handle static dispatching based on keyword signature * Raise Memory Error upon (too) large numpy alloc * Support scalar case of scipy.special.binom * Trim the number of warnings in pythonic codebase (...) ___ Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Member address: arch...@mail-archive.com
pythran 0.9.10 - troer-biñsoù
Hi pythraners, /pythran is an ahead of time compiler for high-level scientific kernels written in Python./ I did a quick release of the pythran compiler today. It's only a few months since the previous release, but this one fixes an important memory leak with transposed arguments, so here it comes. Changelog: https://github.com/serge-sans-paille/pythran/blob/0.9.10/Changelog On Github: https://github.com/serge-sans-paille/pythran/tree/0.9.10 On Pypi: https://pypi.org/project/pythran/ Release on conda-forge and on fedora-rawhide should come soon. We recieved a lot more third party contributions than usual for this release, so let me thank Angus Gibson David Brochart Konrad Kleine ocaisa Pierre Augier Ralf Gommers Stefan van der Walt Sylvain Corlay ___ Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Member address: arch...@mail-archive.com
Pythran 0.9.8 - memes tra
Hi Folks, New Pythran release, tagged on github, available on PyPI and conda, and described here: http://serge-sans-paille.github.io/pythran-stories/pythran-097-memes-tra.html Enjoy! ___ Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Member address: arch...@mail-archive.com
Pythran 0.9.6 - talar tro
Hi folks, and sorry for the double posting if any, It's my pleasure to share with you the 0.9.6 release of Pythran, code-named talar-tro [0]. Pythran is a compiler for numerical kernels written in Python. It doesn't require much type information and its inputs are 100% compatible with the Python interpreter (but the other way around is not true!) More than 6 months have passed since last revision, so the changelog is a bit dense [1], but basically, that's the first release that only supports Python3 [2], I made quite a lot of changes in the expression engine and it comes with more supported numpy stuff, hopefully less bugs etc. As usual, it's available on Pypi, conda-forge and github :-) [0] https://br.wikipedia.org/wiki/Talar-tro [1] https://pythran.readthedocs.io/en/latest/Changelog.html [2] Is that even a feature? ___ Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Member address: arch...@mail-archive.com
Re: [pythran] Pythran 0.9.4 - Hollsent
On Thu, Oct 31, 2019 at 07:32:25AM +0100, Serge Guelton wrote: > Hi folks, > > It's always a pleasure to announce a Pythran release, and here we go for a > version bump! > [...] For those of you who are interested in technical details, http://serge-sans-paille.github.io/pythran-stories/pythran-094-hollsent.html may be an interesting read! ++ Serge -- Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.9.4 - Hollsent
Hi folks, It's always a pleasure to announce a Pythran release, and here we go for a version bump! Short reminder: Pythran is an ahead-of-time compiler for scientific Python, with a focus on high-level numerical kernels, parallelism and vectorisation. Here is a simple kernel example, with a pythran annotation. Note that this kernel is still Python-compatible (from https://stackoverflow.com/questions/50658884): #pythran export euclidean_distance_square(float64[1,:], float64[:,:]) import numpy as np def euclidean_distance_square(x1, x2): return -2*np.dot(x1, x2.T) + np.sum(np.square(x1), axis=1)[:, np.newaxis] + np.sum(np.square(x2), axis=1) The Pythran package is available on PyPI, Github and Conda https://pypi.org/project/pythran/ https://anaconda.org/conda-forge/pythran https://github.com/serge-sans-paille/pythran Packages exist for archlinux and Fedora, they'll probably be updated soon :-) The interested reader can have a look to the changelog for details https://pythran.readthedocs.io/en/latest/Changelog.html Most notably, this release provides support for Python 3.7 and Python 3.8, as well as the ability to use clang-cl as a (better) backend compiler for Windows. Huge thanks to all contributors: paugier Anubhab Haldar Jean Laroche polo and bug reporters: paugier nbecker gdementen mgirardis MordicusEtCubitus Dapid piotrbartman m-romanov slayoo martibosch jeanlaroche -- Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.9.3 - Hañv
Hi folks, I just released version 0.9.3 of the Pythran package, Short reminder: Pythran is an ahead-of-time compiler for scientific Python, with a focus on high-level numerical kernels, parallelism and vectorisation. Here is a simple kernel example, with a pythran annotation. Note that that kernel is still Python-compatible (from https://stackoverflow.com/questions/57199248/) : import numpy as np #pythran export col_sum(int[:,:] or float[:,:], int[:]) def col_sum(data, idx): return data.T[idx].sum(0) The Pythran package is available on PyPI, Github and Conda https://pypi.org/project/pythran/ https://anaconda.org/conda-forge/pythran https://github.com/serge-sans-paille/pythran The interested reader can have a look to the changelog for details https://pythran.readthedocs.io/en/latest/Changelog.html Long story short: bug fixes and better 32bit arch support. Plus (Thanks to Miro Hrončok), pythran is now available on Fedora \o/ Huge thanks to all contributors and bug reporters: Jean Laroche Yann Diorcet DWesl Miro Hrončok Piotr Bartmann Jochen Schröder Sylwester Arabas Marti Bosch rorroiga Pierre Augier Anubhab Haldar nbecker -- Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.9.2 - koailh
Hi folks, and sorry for the double posting if any. It's my great pleasure to announce the release of Pythran 0.9.2, codenamed koailh. Pythran is an ahead of time compiler for scientific kernels written in Python. It is backward-compatible with Python (no language extension) and can take advantage of OpenMP annotations and automatic SIMD instruction generation. It's been more than four months since last release, so there's quite a lot of changes. The detailed changelog is available online: https://pythran.readthedocs.io/en/latest/ Notable Changes === In addition to bugfixes and new function support, the most significant changes are the support of a special notation to describe optional argument in Pythran annotations: #pythran export foo(int, int?) This notation is equivalent to: #pythran export foo(int) #pythran export foo(int, int) This release also introduces a new dependency on the beniget package that provides use-def chains construction for Python code: https://github.com/serge-sans-paille/beniget A significant memory leak when converting extended slice from pythran to python has been spoted and fixed. In total, a great deal of 43 issues have been closed! https://github.com/serge-sans-paille/pythran/issues?utf8=%E2%9C%93=is%3Aissue+is%3Aclosed+closed%3A%3E2019-01-20+ Sample Code === As usual, I like to demonstrate Pythran through a small benchmark that used to be unsupported and now provides a nice x6 speedup (without xsimd) up to (with xsimd, non-strided version) over Python reference: import numpy as np #pythran export f_dist(float64[:,:], float64[:,:]) #pythran export f_dist(float64[::,::], float64[::,::]) def f_dist(X1, X2): return np.sum(np.abs(X1[:, None, :] - X2), axis=-1) (from https://stackoverflow.com/questions/55854611/efficient-way-of-vectorizing-distance-calculation/) Download You can retrieve the package through PyPI: https://pypi.org/project/pythran/ Download the source on GitHub: https://github.com/serge-sans-paille/pythran Or using the conda package, now available for Windows in addition to Linux and OSX through conda-forge https://anaconda.org/conda-forge/pythran Thanks == The following people have contributed to this version, through bug reports or commits, in no particular order: - Yann Diorcet - Neal Becker - Ashwin Vishnu - David Menéndez Hurtado - Jean Laroche - Anubhab Haldar - Thierry Dumont - "keke ge-smile" - "garanews" - Said Hadjout - Rodrigo Iga - Pierrick Brunet - Franck Cornevaux-Juignet Special thoughts to these last two, they reported bugs in 2013 and 2014, and the associated fixes only happened in 2019 ^^! Contribute == If you've been brave enough to read this whole mail, the next step is to support Pythran! You can donate your time through bug reports and fixes, give a small motivation boost through a gentle email, or just use it and share the joy. If you need important development in Pythran, you can drive the roadmap! Send an email to the mailing list (or to my personnal email if you're too shy). ++ Serge -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran - 0.8.7
Hi there, Pythran just released its 0.8.7 version. A quick reminder: Pythran is a compiler for scientific Python, it can be used to turn Python kernels as: #pythran export laplacien(float64[][][3]) import numpy as np def laplacien(image): out_image = np.abs(4*image[1:-1,1:-1] - image[0:-2,1:-1] - image[2:,1:-1] - image[1:-1,0:-2] - image[1:-1,2:]) valmax = np.max(out_image) valmax = max(1.,valmax)+1.E-9 out_image /= valmax return out_image In a native library that runs much faster. Note the ``#pythran export`` line that specifies that the native version only accepts 3D arrays with last dimension set to 3. It's available on pypi: https://pypi.org/project/pythran/ on conda-forge (linux and osx): https://anaconda.org/conda-forge/pythran and on github: https://github.com/serge-sans-paille/pythran Special Thanks for this release to: - Yann Diorcet for all his work on the Windows compatibility - Jean Laroche for the bug reports on OSX - Marteen for his « red dragon » gift - h-vetinari, vgroff, DerWeh, ucyo, Chronum94, paugier, gouarin and Dapid for their bug reports. - alexbw for setting up the conda-forge build This release closes the following issues: https://github.com/serge-sans-paille/pythran/issues?utf8=%E2%9C%93=is%3Aissue+is%3Aclosed+updated%3A%3E2018-06-01+ A more detailed changelog is available at https://pythran.readthedocs.io/en/latest/Changelog.html Enjoy, and if not, submit bug report :-) Serge -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran - 0.8.6
Hi there, Pythran just released its 0.8.6 version. A quick reminder: Pythran is a compiler for scientific Python, it can be used to turn Python kernels as: #pythran export _brief_loop(float64[:,:], uint8[:,:], intp[:,:], int[:,:], int[:,:]) def _brief_loop(image, descriptors, keypoints, pos0, pos1): for k in range(len(keypoints)): kr, kc = keypoints[k] for p in range(len(pos0)): pr0, pc0 = pos0[p] pr1, pc1 = pos1[p] descriptors[k,p] = image[kr + pr0, kc + pc0] < image[kr + pr1, kc + pc1] In a native library that runs much faster. It's available on pypi: https://pypi.org/project/pythran/ on conda-forge (linux and osx): https://anaconda.org/conda-forge/pythran and on github: https://github.com/serge-sans-paille/pythran As a fun fact, Pythran is now used as a mean to turn Python code into pure native library used in C++ code base, without Python involved. Some people even use SWIG to turn this code into native libraries called from... Java through JNI :-) Enjoy, Serge -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.8.5
(sorry for the double posting if any) It is my pleasure to announce a new version of the Pythran compiler. Pythran is an Ahead of Time compiler for a subset of the Python language, with a focus on scientific kernels. It can turn code like the one below: #pythran export weights(uint8[:,:]) import numpy as np def weights(input_data, threshold=0.3): n_seq, length = input_data.shape weights = np.zeros(n_seq, dtype=np.float32) for i in range(n_seq): vector = input_data[i, None, :] count_matches = np.sum(vector == input_data, axis=1) over_threshold = count_matches > (threshold * length) total = np.sum(over_threshold) weights[i] = 1 / total return weights into a native module that runs roughly 10 times faster than when interpreted by cpython. It's available on PyPi, Conda and GitHub under BSD license. For the curious reader, the Changelog is reproduced below. It's a megablast! 2018-04-23 Serge Guelton <serge.guel...@telecom-bretagne.eu> - numpy.fft support (thanks to Jean Laroche) - Faster generalized expression - Faster numpy.transpose, numpy.argmax, numpy reduction - Sphinx-compatible generated docstring (thanks to Pierre Augier) - Python output through -P (thanks to Pierre Augier) - Many bugfixes and numpy improvements (thanks to Yann Diorecet and Jean Laroche) -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
[ANN] Pythran 0.7.5 is out
(sorry for the double posting, if any) Dear pythraners and pythonists, The Pythran team (still 2 active developers) is delighted to announce the release of Pythran 0.7.5, 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 What is it? === Pythran is a static compiler for numerical kernels written in Python + Numpy. It basically turns Python-compatible modules into native ones, eventually vectorized and parallelized. Example === Following the tradition, each release comes with a code sample. This one comes from http://jakevdp.github.io/blog/2012/08/24/numba-vs-cython/ #pythran export pythran_pairwise(float64 [][]) import numpy as np def pythran_pairwise(X): return np.sqrt(((X[:, None, :] - X) ** 2).sum(-1)) This kernel relies a lot on Numpy's broadcasting, but Pythran can now compile it efficiently, which is a really nice improvement! It can rip (without vectorization and parallelization turned on) more than a x5 speedup over the Numpy version \o/ More Infos == We have published some technical details about Pythran internal on the blog: http://serge-sans-paille.github.io/pythran-stories/ It is open to third-party contribution! Changelog = * Better Jupyter Note book integration * Numpy Broadcasting support * Improved value binding analysis * Simple inlining optimization * Type engine improvement * Less fat in the generated modules * More and better support for various Numpy functions * Various performance improvement * Global variable handling, as constants only though Acknowledgments === Thanks a lot to Pierrick Brunet for his dedicated work, and to all the bug reporters and patch providers that helped a lot for this release: nils-werner, ronbarak, fred oble, geekou, hainm, nbecker and xantares. -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.7.4 is out!
(sorry for the double posting, if any) Dear pythraners and pythonists, 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.guel...@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! [0] http://stackoverflow.com/questions/34500913/numba-slower-for-numpy-bitwise-and-on-boolean-arrays [1] http://opendreamkit.org/ signature.asc Description: PGP signature -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.7.2 is out!
(sorry for the double posting, if any) Dear pythraners and pythonistae (the latin plural for pythonista?) It is my pleasure to announce the release of Pythran 0.7.2, now available on - pypy: https://pypi.python.org/pypi/pythran - conda: https://anaconda.org/serge-sans-paille/pythran - github: https://github.com/serge-sans-paille/pythran Pythran is an ahead-of-time Python compiler with a focus on high-level scientific computing. It relies on a few non-intrusive annotations to provide (potentially) vectorized, parallel version of high level Python code, like the following, borrowed from stackoverflow [0]; #pythran export GrayScott(int, float, float, float, float) # ^ see the non intrusive, backward compatible annotation ^ import numpy as np def GrayScott(counts, Du, Dv, F, k): n = 300 U = np.zeros((n+2,n+2), dtype=np.float32) V = np.zeros((n+2,n+2), dtype=np.float32) u, v = U[1:-1,1:-1], V[1:-1,1:-1] r = 20 u[:] = 1.0 U[n/2-r:n/2+r,n/2-r:n/2+r] = 0.50 V[n/2-r:n/2+r,n/2-r:n/2+r] = 0.25 u += 0.15*np.random.random((n,n)) v += 0.15*np.random.random((n,n)) for i in range(counts): Lu = ( U[0:-2,1:-1] + U[1:-1,0:-2] - 4*U[1:-1,1:-1] + U[1:-1,2:] + U[2: ,1:-1] ) Lv = ( V[0:-2,1:-1] + V[1:-1,0:-2] - 4*V[1:-1,1:-1] + V[1:-1,2:] + V[2: ,1:-1] ) uvv = u*v*v u += Du*Lu - uvv + F*(1 - u) v += Dv*Lv + uvv - (F + k)*v return V This minor yet amazing version brings in more numpy function support [1], easier install, a conda build, tentative windows support, faster compilation time and generates generally faster native modules. Kudos to Pierrick for the hardwork and to all the bug reporters. You all help a lot to bring the motivation high. Special thanks to the OpenDreamKit[2] project for the financial support. Most of the new features have been implemented thanks to this funding! Changelog extract: 2015-10-13 Serge Guelton <serge.guel...@telecom-bretagne.eu> * Significantly decrease compilation time * Faster execution of numpy generalized slicing * Tentative conda support * Tentative Windows support (using Win Python) * Preserve original docstrings * Add __pythran__ global variable to pythran generated modules * Faster implementation of various itertools functions * Rely on distutils for module code compilation * Support most of numpy.random * Remove git and make dependency to install nt2 * Proper pip support instead of distuils * Remove dependency to boost.python * Remove dependency to tcmalloc * Pythonic library cleaning (less dependencies / header / splitting / mrpropering) * More lazy computations * More numpy function support (including dot on matrices, linalg.norm, mean) * Lot of code cleaning / refactoring (both in Python and C++) * Many bugfixes, thanks to all the bug reporters! [0] http://stackoverflow.com/questions/26823312/numba-or-cython-acceleration-in-reaction-diffusion-algorithm [1] https://pythonhosted.org/pythran/SUPPORT.html [2] http://opendreamkit.org/ -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Pythran 0.7 is out
(sorry for the double posting if any) It is my pleasure to announce a new version of the Pythran compiler. Pythran is a Python compiler for scientific computing, more details on the PyData Paris talk: http://serge-sans-paille.github.io/talks/pydata-2015-04-03.html#/ A huge achievement of this version is being able to efficiently compile the following kernel: https://github.com/serge-sans-paille/pythran/blob/master/pythran/tests/cases/grayscott.py Kudos to Valerio De Carolis, Leopold Haimberger, xantares, T.J. Ragan, Joël Falcou and Neal Becker for their ultra-motivating feedbacks! And thanks *a lot* to Pierrick Brunet for his impressive development work and code reviewing effort! homepage: http://pythonhosted.org/pythran/ github: https://github.com/serge-sans-paille/pythran pypi: https://pypi.python.org/pypi/pythran freenode: #pythran mliste: pyth...@freelists.org More details on this version (from the changelog): * Various numpy.* function implementation improvement (incl. concatenate, str.join, itertools.combinations) * Better error detection during install step * 32 bit compatibility * Complete rewrite of the expression engine * Improved support of numpy extended expression * Better user feedback on invalid pythran spec * More efficient support of string litterals * Faster exponentiation when index is an integer * NT2 revision bump * No-copy list as numpy expression parameters * Accept C and fortran layout for input arrays * Range value analysis and boundcheck removal * Newaxis style indexing * Better array-of-complex support * Glimpses of python3 support * Support for importing user defined modules * Archlinux support * Accept strided array as exported function input -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Re: Call for speakers for the first PyCon Belarus. Python-announce
On Fri, Dec 12, 2014 at 04:32:26PM +0300, Alina Dolgikh wrote: Hello, dear community! I represent Belarusian Python community. We have regular monthly meet-ups for 70-100 persons and we are going to develop further. We are planning to make the first Belarusian PyCon on the 31st of January and looking for speakers. We will be glad to meet at our event speakers, which are experienced in public talks (links for videos of public talks or for the other conferences web-pages are preferable) and can speak at - CI, pypy, C-extensions, python performance I there, I am the core developer of the Pythran[0] compiler, a Python to C++ compiler that focuses on the numpy package optimization, and tries hard to turn high-level Numpy code into low-level, vectorized, parallel C++ code. I presented an early version at Scipy 2013[1], this should give you a decent idea of my yet to improve speaker skills :-/ Any way, I would be happy to speak about it at PyCon Belarusian! If you're intereseted/curious, I can provide a more detailed description ;-) See ya, Serge [0] http://pythonhosted.org/pythran/ [1] https://www.youtube.com/watch?v=KT5-uGEpnGw -- https://mail.python.org/mailman/listinfo/python-list
Pythran 0.6 - C++ for snakes
=== Pythran 0.6 === The Pythran team is glad to announce Pythran 0.6. It contains many performance improvements, better Numpy support and the usual code cleaning and bug fixes. You can download the release from the cheese shop: https://pypi.python.org/pypi/pythran From my custom Debian repo: http://serge.liyun.free.fr/serge/debian.html Or keep playing with the git repo: https://github.com/serge-sans-paille/pythran Bug reports are welcome, on github, #pythran on FreeNode or pyth...@freelists.org! From the Changelog == * Full SIMD support! Almost all numpy expressions are vectorized * Better memory management at the Python/C++ layer, esp. when sharing * Support named parameters * Better complex numbers support * A lot of internal code cleaning * Better code generation for regular loops * MacOS install guide ArchLinux packages * Travis run the test suite, w and w/ SIMD, w and w/ OpenMP * Many performance improvements at the numpy expression level * Faster array copies, including slices * Much better constant folding * Distutils support through a PythranExtension * Improve implementation of many numpy functions * Improve forward substitution * Use most recent nt2 version * Make dependency on libgomp optional What's next? * better numpy support * better/faster OpenMP support * code cleaning and refactoring. Always. -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Re: Pyston 0.2 released
On Thu, Sep 11, 2014 at 12:52:15PM -0700, Kevin Modzelewski wrote: Hi all, we're excited to announce the existence of Pyston 0.2, a much-improved version of our new Python JIT. The new version features greatly improved language support, basic native C API support, and an experimental GIL-free mode. Pyston is now in alpha, and is still not ready for general use, but we have hit a significant milestone of being able to run a number of existing benchmarks and standard libraries. Hi Kevin, Great work! I wonder if (in an undetermined future) the following scenario could stand to optimize calls to native libraries, like numpy: - compile numpy into LLVM bytecode - when meeting a function with a bunch of numpy call, instead of using the CAPI, directly call functions from the numpy bytecode and optimize evertyhing as a whole? Keep up the good work! -- https://mail.python.org/mailman/listinfo/python-list
Python Obfuscation Challenge
Hi all, The QuarksLab[0] company just released a Capture The Flag challenge with an emphasise on Python and CPython: http://blog.quarkslab.com/you-like-python-security-challenge-and-traveling-win-a-free-ticket-to-hitb-kul.html There are a few free tickets to the HITB conference[1] to win, so unleash the hacker in you! enjoy, [0] I am indeed an employee of QuarksLab :-/ [1] https://conference.hitb.org/hitbsecconf2014kul -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
