========================== Announcing Numexpr 2.0.1 ========================== Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It wears multi-threaded capabilities, as well as support for Intel's VML library, which allows for squeezing the last drop of performance out of your multi-core processors. What's new ========== In this release, better docstrings for `evaluate` and reduction methods (`sum`, `prod`) is in place. Also, compatibility with Python 2.5 has been restored (2.4 is definitely not supported anymore). In case you want to know more in detail what has changed in this version, see: http://code.google.com/p/numexpr/wiki/ReleaseNotes or have a look at RELEASE_NOTES.txt in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ You can get the packages from PyPI as well: http://pypi.python.org/pypi/numexpr Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted
What about python3 support? Thanks Nadav. ________________________________________ From: numpy-discussion-bounces@scipy.org [numpy-discussion-bounces@scipy.org] On Behalf Of Francesc Alted [faltet@gmail.com] Sent: 08 January 2012 12:49 To: Discussion of Numerical Python; numexpr Subject: [Numpy-discussion] ANN: Numexpr 2.0.1 released ========================== Announcing Numexpr 2.0.1 ========================== Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It wears multi-threaded capabilities, as well as support for Intel's VML library, which allows for squeezing the last drop of performance out of your multi-core processors. What's new ========== In this release, better docstrings for `evaluate` and reduction methods (`sum`, `prod`) is in place. Also, compatibility with Python 2.5 has been restored (2.4 is definitely not supported anymore). In case you want to know more in detail what has changed in this version, see: http://code.google.com/p/numexpr/wiki/ReleaseNotes or have a look at RELEASE_NOTES.txt in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ You can get the packages from PyPI as well: http://pypi.python.org/pypi/numexpr Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Python3 is not on my radar yet. Perhaps others might be interested on doing the port. Francesc 2012/1/8 Nadav Horesh <nadavh@visionsense.com>:
What about python3 support?
Thanks
Nadav.
________________________________________ From: numpy-discussion-bounces@scipy.org [numpy-discussion-bounces@scipy.org] On Behalf Of Francesc Alted [faltet@gmail.com] Sent: 08 January 2012 12:49 To: Discussion of Numerical Python; numexpr Subject: [Numpy-discussion] ANN: Numexpr 2.0.1 released
========================== Announcing Numexpr 2.0.1 ==========================
Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python.
It wears multi-threaded capabilities, as well as support for Intel's VML library, which allows for squeezing the last drop of performance out of your multi-core processors.
What's new ==========
In this release, better docstrings for `evaluate` and reduction methods (`sum`, `prod`) is in place. Also, compatibility with Python 2.5 has been restored (2.4 is definitely not supported anymore).
In case you want to know more in detail what has changed in this version, see:
http://code.google.com/p/numexpr/wiki/ReleaseNotes
or have a look at RELEASE_NOTES.txt in the tarball.
Where I can find Numexpr? =========================
The project is hosted at Google code in:
http://code.google.com/p/numexpr/
You can get the packages from PyPI as well:
http://pypi.python.org/pypi/numexpr
Share your experience =====================
Let us know of any bugs, suggestions, gripes, kudos, etc. you may have.
Enjoy!
-- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Francesc Alted
participants (2)
-
Francesc Alted -
Nadav Horesh