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.. _tut-whatnow:
*********
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:
* :ref:`library-index`:
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.
* :ref:`installing-index` explains how to install additional modules written
by other Python users.
* :ref:`reference-index`: 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.
* https://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.
* https://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
: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
:ref:`Frequently Asked Questions <faq-index>` (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.
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