[SciPy-user] Pros and Cons of Python verses other array environments
zelakiew at crd.ge.com
Fri Sep 29 07:36:21 CDT 2006
Fernando Perez <fperez.net <at> gmail.com> writes:
> On 9/28/06, R. Padraic Springuel <R.Springuel <at> umit.maine.edu> wrote:
> > For those of you objecting to the "difficulty" in importing several
> > different packages to get all the different capabilities here going at
> > once, there is an easy fix here suggested by Travis's use of Pylab as
> > the title for the grouping. If you look at matplotlib's pylab.py file
> > that it places in your site-packages directory, its just redirects the
> > import statement to find what's needed. Add a few lines to this file
> > and it can pull in numpy, scipy, and IPython at the same time. What
> > might make things easier for the beginner would be to have all of the
> > packages Travis mentioned available in a bundled download that is easily
> > installable (like Enthought Python, but without the extra bells &
> > whistles) and with a modified version of the pylab.py file that contains
> > all the necessary import statements.
> > It might also be nice if this kind of package would automatically
> > configure the interpreter to issue the necessary import statements
> > automatically when it starts. In this way, the beginner need not learn
> > about import statements right away. All the basics are right there for
> > them.
> That's pretty much what
> ipython -pylab
> does already, modulo importing scipy, which it does NOT assume is
> installed. But doing
> ipython -pylab -p scipy
> does that. The next version of ipython will add the latter as a
> shortcut in the Windows start menu upon installation, at Ryan Krauss'
> suggestion. *nix users are perfectly capable of making an alias if
> they so desire.
When it comes to the distribution, I like Enthought's Python package, but it is
only for Windows. What I have done for Linux is set up a gar make system (also
used by konstruct and gargnome) to build everything anyone needs to get a python
system up and running. The download is quite small (1 makefile per package to
be built). The makefile tells the system the name and location of the download.
When make is run it automatically goes to the web, gets the source, builds and
installs it. All the user has to do is type 'make install' and they have a full
scientific python environment waiting for them. Right now I have it set up to
build blas, lapack, numpy, scipy, pygtk, matplotlib, ipython and python2.4 (if
it is not already there). I also add a little script in their path that can be
run to set the correct environment variables, launch ipython and import scipy
Perhaps this is a way to easily get Linux users up and running.
More information about the SciPy-user