pypy.org
PyPy - Call for donations - PyPy to support Python3!
http://www.pypy.org/py3donate.html
Call for donations - PyPy to support Python3! The release of Python 3 has been a major undertaking for the Python community, both technically and socially. So far the PyPy interpreter implements only version 2 of the Python language and is increasingly used in production systems. It thus contributes to the general risk of a long lasting Python community split where a lot of people continue using Python 2 while others work with Python 3, making it harder for everyone. For donations higher than $1,000, we ...
pypy.org
PyPy - 2nd Call for donations - Transactional Memory in PyPy
http://www.pypy.org/tmdonate2.html
2nd Call for donations - Transactional Memory in PyPy. What is the Global Interpreter Lock? What is Transactional Memory? Hardware vs Software Transactional Memory. Why do TM with PyPy instead of CPython? Platforms other than the x86-64 Linux. Work plan and funding details. Benefits of This Work to the Python Community and the General Public. This is the second call for donations on the topic of Transactional Memory (. The present proposal is about development of the second half: first, fixing the variou...
pypy.org
PyPy - Welcome to PyPy
http://www.pypy.org/index.html
PyPy is a fast. Alternative implementation of the Python. Language (2.7.10 and 3.3.5). It has several advantages and distinct features:. Thanks to its Just-in-Time compiler, Python programs often run faster. On PyPy. (What is a JIT compiler? Ldquo;If you want your code to run faster, you should probably just use PyPy.” — Guido van Rossum (creator of Python). Memory-hungry Python programs (several hundreds of MBs or more) might end up taking less space. Than they do in CPython. PyPy is highly compatible.
pypy.org
PyPy - People of PyPy
http://www.pypy.org/people.html
Maciej is a freelancer working mostly on PyPy for the past several years. He's a core developer since 2006, working on all kinds of parts in the entire codebase including JIT, GC and assembler backends. Maciej has been going to many conferences, advertising PyPy to a broader audience for the past several years, including a keynote at Pycon 2010. He's also the main maintainer of jitviewer. A tool for analyzing performance of your python programs under PyPy. Holger Krekel is a founder of the PyPy project a...
pypy.org
PyPy - Python compatibility
http://www.pypy.org/compat.html
PyPy implements the Python language version 2.7.10. It supports all of the core language, passing Python test suite (with minor modifications that were already accepted in the main python in newer versions). It supports most of the commonly used Python standard library modules. List of installable top 1000 PyPI packages. Support for the CPython C API. However, this feature is not yet complete. We strongly advise use of CFFI. Supported, but written in pure Python:. Pillow (the PIL fork). The main differen...
pypy.org
PyPy - Performance
http://pypy.org/performance.html
Insider's point of view. This document collects strategies, tactics and tricks for making your code run faster under PyPy. Many of these are also useful hints for stock Python and other languages. For contrast, we also describe some CPython (stock Python) optimizations that are not needed in PyPy. As a general rule, when considering performance issues, follow these three points: first. Them (it is counter-productive to fight imaginary performance issues); then. PyPy 2.6 introduced vmprof. Measuring will ...
morepypy.blogspot.com
PyPy Status Blog: PhD Thesis about PyPy's CLI JIT Backend
https://morepypy.blogspot.com/2010/10/phd-thesis-about-pypys-cli-jit-backend.html
Friday, October 22, 2010. PhD Thesis about PyPy's CLI JIT Backend. Few months ago I finished the PhD studies and now my thesis. Is available, just in case someone does not have anything better to do than read it :-). The title of the thesis is High performance implementation of Python for CLI/.NET with JIT compiler generation for dynamic languages. Here is the summary of chapters:. Characterization of the target platform. Tracing JITs in a nutshell. The PyPy JIT compiler generator. The CLI JIT backend.
pypy.org
PyPy - Call for donations - PyPy to support Numpy!
http://www.pypy.org/numpydonate.html
Call for donations - PyPy to support Numpy! We have closed this campaign. We have achieved most of the goals of the orignal work plan while raising most of the funds. Work will continue to make Numpy and the rest of the numeric stack more usable on PyPy. On our blog for updates. There is also an automatically generated. Showing what parts of NumPy are already usable. This is a proposal to provide a fully compatible working NumPy. We already had some success providing a very basic NumPy implementation.
morepypy.blogspot.com
PyPy Status Blog: NumPyPy status - January 2015
https://morepypy.blogspot.com/2015/02/numpypy-status-january-2015.html
Wednesday, February 11, 2015. NumPyPy status - January 2015. Here is what has been done in January thanks to the funding of NumPyPy. I would like to thank all the donors and tell you that you can still donate :. I have focused on implementing the object dtype this month, it is now possible to store objects inside ndarrays using the object dtype. It is also possible to add an object ndarray to any other ndarray (implementing other operators is trivial). The next things I plan on working on next are :.
