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Numerical Python
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Purpose
Numerical Python adds a fast, compact multidimensional array language facility
to Python.
Availability
The Numerical Python
Project Page has releases, links to the FTP site, a bug tracking system,
and a browser for the source repository plus instructions on how to use
CVS anonymously. Binary releases are at the FTP site as well.
Note that installation of Numerical requires the Distutils
package. Before building Numeric, obtain and install the Distutils.
The Distutils will be distributed with Python beginning with the 1.6 release.
Note on Distutils versions
Distutils is currently undergoing rapid change. Numpy 15.2 expects Distutils-0.1.3. If you are using a more recent version of Distutils, look in the Distutils distribution for a setup file for Numpy to replace the one in the Numpy distribution.
We plan to upgrade to the Distutils that will be a part of
Python 1.6 when it is released.
Documentation
Numerical Python (Adobe Acrobat)
Random Array Additions Lee
A. Barford (1/19/2000)
Related Sites
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Pyfort, the Python / Fortran connection tool.
See Pyfort Home Page
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CXX, the C++ toolkit for writing Python extensions.
See CXX Project Page
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RNG, a random number package from LLNL, is downloadable from the project
FTP site.
See Numpy FTP site
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Frequently asked questions about Python including Numerical Python are at
Python FAQTS
MiniFAQ
No official FAQ is available yet. But here is an informal one.
Why Numerical Python?
If x and y are Numerical Python arrays, then the speed of the operation
x + y is close to the speed of doing it in C if the arrays are big enough.
Thus, Python can be extended with a full scientific array language with
sophisticated indexing and shaping operations and yet be closer to the
speed of a compiled language than to the speed of Python itself.
How do I become a "developer"?
Write to one of the current developers and describe your experience and
interests. The current developers act as a committee of equal peers and
will discuss your request. Paul Dubois (dubois@users.sourceforge.net) serves
as the chairperson of this group and has veto power over requests for enhancements.
There are different communities of users with different goals and aspirations.
To keep Numerical as useful as possible to as many people as possible,
we are taking a conservative approach to growth, applying Bertrand Meyer's
famous hope for Eiffel that it would "grow no faster than the rate of inflation."
Assignment doesn't make a copy?
Right. Doing y=x just creates a new name for the same array object. While
consistent with Python, this is upsetting to users of other array languages.
Likewise, x[i:j] is not a copy. Please read the manual.
"HAL 9000" Graphic by Steven Russell.