python_doc_md/Beginner/tutorial/whatnow.md

# What Now? {#tut-whatnow}

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:

- `library-index`{.interpreted-text role="ref"}:

  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, compress data, and many other tasks. Skimming through the Library Reference will give you an idea of what\'s available.

- `installing-index`{.interpreted-text role="ref"} explains how to install additional modules written by other Python users.

- `reference-index`{.interpreted-text role="ref"}: 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 website. It contains code, documentation, and pointers to Python-related pages around the web.
- <https://docs.python.org>: Fast access to Python\'s documentation.
- <https://pypi.org>: The Python Package Index, previously also nicknamed the Cheese Shop[^1], 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.)
- <https://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 `comp.lang.python`{.interpreted-text role="newsgroup"}, 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 <faq-index>`{.interpreted-text role="ref"} (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.

**Footnotes**

[^1]: \"Cheese Shop\" is a Monty Python sketch: a customer enters a cheese shop, but whatever cheese he asks for, the clerk says it\'s missing.