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74 lines
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ReStructuredText
74 lines
3.4 KiB
ReStructuredText
.. _tut-whatnow:
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*********
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What Now?
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*********
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Reading this tutorial has probably reinforced your interest in using Python ---
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you should be eager to apply Python to solving your real-world problems. Where
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should you go to learn more?
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This tutorial is part of Python's documentation set. Some other documents in
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the set are:
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* :ref:`library-index`:
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You should browse through this manual, which gives complete (though terse)
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reference material about types, functions, and the modules in the standard
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library. The standard Python distribution includes a *lot* of additional code.
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There are modules to read Unix mailboxes, retrieve documents via HTTP, generate
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random numbers, parse command-line options, write CGI programs, compress data,
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and many other tasks. Skimming through the Library Reference will give you an
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idea of what's available.
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* :ref:`install-index` explains how to install external modules written by other
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Python users.
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* :ref:`reference-index`: A detailed explanation of Python's syntax and
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semantics. It's heavy reading, but is useful as a complete guide to the
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language itself.
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More Python resources:
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* http://www.python.org: The major Python Web site. It contains code,
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documentation, and pointers to Python-related pages around the Web. This Web
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site is mirrored in various places around the world, such as Europe, Japan, and
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Australia; a mirror may be faster than the main site, depending on your
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geographical location.
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* http://docs.python.org: Fast access to Python's documentation.
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* http://pypi.python.org: The Python Package Index, previously also nicknamed
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the Cheese Shop, is an index of user-created Python modules that are available
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for download. Once you begin releasing code, you can register it here so that
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others can find it.
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* http://aspn.activestate.com/ASPN/Python/Cookbook/: The Python Cookbook is a
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sizable collection of code examples, larger modules, and useful scripts.
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Particularly notable contributions are collected in a book also titled Python
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Cookbook (O'Reilly & Associates, ISBN 0-596-00797-3.)
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* http://scipy.org: The Scientific Python project includes modules for fast
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array computations and manipulations plus a host of packages for such
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things as linear algebra, Fourier transforms, non-linear solvers,
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random number distributions, statistical analysis and the like.
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For Python-related questions and problem reports, you can post to the newsgroup
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:newsgroup:`comp.lang.python`, or send them to the mailing list at
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python-list@python.org. The newsgroup and mailing list are gatewayed, so
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messages posted to one will automatically be forwarded to the other. There are
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around 120 postings a day (with peaks up to several hundred), asking (and
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answering) questions, suggesting new features, and announcing new modules.
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Before posting, be sure to check the list of `Frequently Asked Questions
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<http://www.python.org/doc/faq/>`_ (also called the FAQ), or look for it in the
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:file:`Misc/` directory of the Python source distribution. Mailing list
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archives are available at http://mail.python.org/pipermail/. The FAQ answers
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many of the questions that come up again and again, and may already contain the
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solution for your problem.
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.. Postings figure based on average of last six months activity as
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reported by www.egroups.com; Jan. 2000 - June 2000: 21272 msgs / 182
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days = 116.9 msgs / day and steadily increasing. (XXX up to date figures?)
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