collect all Python distributions under 'Resources'

Also add a short section introduction about the purpose of this section.
This commit is contained in:
Valentin Haenel
2013-02-21 22:04:28 +01:00
parent 46d48e8748
commit 15394324a2
+18 -15
View File
@@ -52,6 +52,24 @@ users to Python. Many examples, along with the source code to re-create them,
can be browsed at the `matplotlib gallery
<http://matplotlib.sourceforge.net/gallery.html>`_.
Resources
:::::::::
Installation of scientific Python packages can be troublesome. Many of these
packages are implemented as Python C extensions which need to be compiled.
This section lists various so-called Python distributions which provide precompiled and
easy-to-install collections of scientific Python packages.
Unofficial Windows Binaries for Python Extension Packages
---------------------------------------------------------
Many people who do scientific computing are on Windows. And yet many of the
scientific computing packages are notoriously difficult to build and install.
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/pythonlibs/>`_ however, has
compiled a list of Windows binaries for many useful Python packages. The list
of packages has grown from a mainly scientific python resource to a more
general list. It might be a good idea to check it out if you're on Windows.
Enthought
---------
@@ -62,18 +80,3 @@ Enthought, scientific python has never been easier (one click to install about
variants: a free version `EPD Free <http://enthought.com/products/epd_free.php>`_
and a paid version with various `pricing options.
<http://enthought.com/products/epd_sublevels.php>`_
Resources
:::::::::
Many people who do scientific computing are on Windows. And yet many of the
scientific computing packages are notoriously difficult to build and install.
`Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/pythonlibs/>`_ however, has
compiled a list of Windows binaries for many useful Python packages. The list
of packages has grown from a mainly scientific python resource to a more
general list. It might be a good idea to check it out if you're on Windows.
For a quick introduction to scientific python:
http://scipy-lectures.github.com