
What Now?
*********

Reading this tutorial has probably reinforced your interest in using
Python --- you should be eager to apply Python to solving your real-
world problems. Where should you go to learn more?

This tutorial is part of Python's documentation set.   Some other
documents in the set are:

* *The Python Standard Library*:

  You should browse through this manual, which gives complete (though
  terse) reference material about types, functions, and the modules in
  the standard library.  The standard Python distribution includes a
  *lot* of additional code. There are modules to read Unix mailboxes,
  retrieve documents via HTTP, generate random numbers, parse command-
  line options, write CGI programs, compress data, and many other
  tasks. Skimming through the Library Reference will give you an idea
  of what's available.

* *Installing Python Modules* explains how to install additional
  modules written by other Python users.

* *The Python Language Reference*: A detailed explanation of
  Python's syntax and semantics.  It's heavy reading, but is useful as
  a complete guide to the language itself.

More Python resources:

* http://www.python.org:  The major Python Web site.  It contains
  code, documentation, and pointers to Python-related pages around the
  Web.  This Web site is mirrored in various places around the world,
  such as Europe, Japan, and Australia; a mirror may be faster than
  the main site, depending on your geographical location.

* http://docs.python.org:  Fast access to Python's  documentation.

* http://pypi.python.org: The Python Package Index, previously also
  nicknamed the Cheese Shop, is an index of user-created Python
  modules that are available for download.  Once you begin releasing
  code, you can register it here so that others can find it.

* http://aspn.activestate.com/ASPN/Python/Cookbook/: The Python
  Cookbook is a sizable collection of code examples, larger modules,
  and useful scripts. Particularly notable contributions are collected
  in a book also titled Python Cookbook (O'Reilly & Associates, ISBN
  0-596-00797-3.)

* http://scipy.org: The Scientific Python project includes modules
  for fast array computations and manipulations plus a host of
  packages for such things as linear algebra, Fourier transforms, non-
  linear solvers, random number distributions, statistical analysis
  and the like.

For Python-related questions and problem reports, you can post to the
newsgroup *comp.lang.python*, or send them to the mailing list at
python-list@python.org.  The newsgroup and mailing list are gatewayed,
so messages posted to one will automatically be forwarded to the
other.  There are around 120 postings a day (with peaks up to several
hundred), asking (and answering) questions, suggesting new features,
and announcing new modules. Before posting, be sure to check the list
of *Frequently Asked Questions* (also called the FAQ). Mailing list
archives are available at http://mail.python.org/pipermail/. The FAQ
answers many of the questions that come up again and again, and may
already contain the solution for your problem.
