
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:

* https://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.

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

* https://pypi.python.org/pypi: 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://code.activestate.com/recipes/langs/python/: 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://www.pyvideo.org collects links to Python-related videos
  from conferences and user-group meetings.

* 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 hundreds of postings a day, asking (and answering)
questions, suggesting new features, and announcing new modules.
Mailing list archives are available at
https://mail.python.org/pipermail/.

Before posting, be sure to check the list of Frequently Asked
Questions (also called the FAQ).  The FAQ answers many of the
questions that come up again and again, and may already contain the
solution for your problem.
