doc/source/ipython.rst

.. IPython documentation master file, created by sphinx-quickstart.py on Mon Mar 24 17:01:34 2008.
   You can adapt this file completely to your liking, but it should at least
   contain the root 'toctree' directive.

Welcome to IPython's documentation!
===================================

Contents:

.. toctree::
   :maxdepth: 2

Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

Overview
========

One of Python's most useful features is its interactive interpreter.
This system allows very fast testing of ideas without the overhead of
creating test files as is typical in most programming languages.
However, the interpreter supplied with the standard Python distribution
is somewhat limited for extended interactive use.

IPython is a free software project (released under the BSD license)
which tries to:

   1. Provide an interactive shell superior to Python's default. IPython
      has many features for object introspection, system shell access,
      and its own special command system for adding functionality when
      working interactively. It tries to be a very efficient environment
      both for Python code development and for exploration of problems
      using Python objects (in situations like data analysis).
   2. Serve as an embeddable, ready to use interpreter for your own
      programs. IPython can be started with a single call from inside
      another program, providing access to the current namespace. This
      can be very useful both for debugging purposes and for situations
      where a blend of batch-processing and interactive exploration are
      needed.
   3. Offer a flexible framework which can be used as the base
      environment for other systems with Python as the underlying
      language. Specifically scientific environments like Mathematica,
      IDL and Matlab inspired its design, but similar ideas can be
      useful in many fields.
   4. Allow interactive testing of threaded graphical toolkits. IPython
      has support for interactive, non-blocking control of GTK, Qt and
      WX applications via special threading flags. The normal Python
      shell can only do this for Tkinter applications.


Main features
-------------

* Dynamic object introspection. One can access docstrings, function
  definition prototypes, source code, source files and other details
  of any object accessible to the interpreter with a single
  keystroke ('?', and using '??' provides additional detail).
* Searching through modules and namespaces with '*' wildcards, both
  when using the '?' system and via the %psearch command.
* Completion in the local namespace, by typing TAB at the prompt.
  This works for keywords, methods, variables and files in the
  current directory. This is supported via the readline library, and
  full access to configuring readline's behavior is provided.
* Numbered input/output prompts with command history (persistent
  across sessions and tied to each profile), full searching in this
  history and caching of all input and output.
* User-extensible 'magic' commands. A set of commands prefixed with
  % is available for controlling IPython itself and provides
  directory control, namespace information and many aliases to
  common system shell commands.
* Alias facility for defining your own system aliases.
* Complete system shell access. Lines starting with ! are passed
  directly to the system shell, and using !! captures shell output
  into python variables for further use.
* Background execution of Python commands in a separate thread.
  IPython has an internal job manager called jobs, and a
  conveninence backgrounding magic function called %bg.
* The ability to expand python variables when calling the system
  shell. In a shell command, any python variable prefixed with $ is
  expanded. A double $$ allows passing a literal $ to the shell (for
  access to shell and environment variables like $PATH).
* Filesystem navigation, via a magic %cd command, along with a
  persistent bookmark system (using %bookmark) for fast access to
  frequently visited directories.
* A lightweight persistence framework via the %store command, which
  allows you to save arbitrary Python variables. These get restored
  automatically when your session restarts.
* Automatic indentation (optional) of code as you type (through the
  readline library).
* Macro system for quickly re-executing multiple lines of previous
  input with a single name. Macros can be stored persistently via
  %store and edited via %edit.
* Session logging (you can then later use these logs as code in your
  programs). Logs can optionally timestamp all input, and also store
  session output (marked as comments, so the log remains valid
  Python source code).
* Session restoring: logs can be replayed to restore a previous
  session to the state where you left it.
* Verbose and colored exception traceback printouts. Easier to parse
  visually, and in verbose mode they produce a lot of useful
  debugging information (basically a terminal version of the cgitb
  module).
* Auto-parentheses: callable objects can be executed without
  parentheses: 'sin 3' is automatically converted to 'sin(3)'.
* Auto-quoting: using ',' or ';' as the first character forces
  auto-quoting of the rest of the line: ',my_function a b' becomes
  automatically 'my_function("a","b")', while ';my_function a b'
  becomes 'my_function("a b")'.
* Extensible input syntax. You can define filters that pre-process
  user input to simplify input in special situations. This allows
  for example pasting multi-line code fragments which start with
  '>>>' or '...' such as those from other python sessions or the
  standard Python documentation.
* Flexible configuration system. It uses a configuration file which
  allows permanent setting of all command-line options, module
  loading, code and file execution. The system allows recursive file
  inclusion, so you can have a base file with defaults and layers
  which load other customizations for particular projects.
* Embeddable. You can call IPython as a python shell inside your own
  python programs. This can be used both for debugging code or for
  providing interactive abilities to your programs with knowledge
  about the local namespaces (very useful in debugging and data
  analysis situations).
* Easy debugger access. You can set IPython to call up an enhanced
  version of the Python debugger (pdb) every time there is an
  uncaught exception. This drops you inside the code which triggered
  the exception with all the data live and it is possible to
  navigate the stack to rapidly isolate the source of a bug. The
  %run magic command -with the -d option- can run any script under
  pdb's control, automatically setting initial breakpoints for you.
  This version of pdb has IPython-specific improvements, including
  tab-completion and traceback coloring support.
* Profiler support. You can run single statements (similar to
  profile.run()) or complete programs under the profiler's control.
  While this is possible with standard cProfile or profile modules,
  IPython wraps this functionality with magic commands (see '%prun'
  and '%run -p') convenient for rapid interactive work.
* Doctest support. The special %doctest_mode command toggles a mode
  that allows you to paste existing doctests (with leading '>>>'
  prompts and whitespace) and uses doctest-compatible prompts and
  output, so you can use IPython sessions as doctest code.


Portability and Python requirements
-----------------------------------

Python requirements: IPython requires with Python version 2.3 or newer.
If you are still using Python 2.2 and can not upgrade, the last version
of IPython which worked with Python 2.2 was 0.6.15, so you will have to
use that.

IPython is developed under Linux, but it should work in any reasonable
Unix-type system (tested OK under Solaris and the BSD family, for which
a port exists thanks to Dryice Liu).

Mac OS X: it works, apparently without any problems (thanks to Jim Boyle
at Lawrence Livermore for the information). Thanks to Andrea Riciputi,
Fink support is available.

CygWin: it works mostly OK, though some users have reported problems
with prompt coloring. No satisfactory solution to this has been found so
far, you may want to disable colors permanently in the ipythonrc
configuration file if you experience problems. If you have proper color
support under cygwin, please post to the IPython mailing list so this
issue can be resolved for all users.

Windows: it works well under Windows XP/2k, and I suspect NT should
behave similarly. Section 2.3 <node2.html#sub:Under-Windows> describes
installation details for Windows, including some additional tools needed
on this platform.

Windows 9x support is present, and has been reported to work fine (at
least on WinME).

Note, that I have very little access to and experience with Windows
development. However, an excellent group of Win32 users (led by Ville
Vainio), consistently contribute bugfixes and platform-specific
enhancements, so they more than make up for my deficiencies on that
front. In fact, Win32 users report using IPython as a system shell (see
Sec. 12 <node12.html#sec:IPython-as-shell> for details), as it offers a
level of control and features which the default cmd.exe doesn't provide.


Location
========

IPython is generously hosted at http://ipython.scipy.org by the
Enthought, Inc and the SciPy project. This site offers downloads,
subversion access, mailing lists and a bug tracking system. I am very
grateful to Enthought (http://www.enthought.com) and all of the SciPy
team for their contribution.

Installation
============

Instant instructions
--------------------

If you are of the impatient kind, under Linux/Unix simply untar/unzip
the download, then install with 'python setup.py install'. Under
Windows, double-click on the provided .exe binary installer.

Then, take a look at Sections 3 <node3.html#sec:good_config> for
configuring things optimally and 4 <node4.html#sec:quick_tips> for quick
tips on efficient use of IPython. You can later refer to the rest of the
manual for all the gory details.

See the notes in sec. 2.4 <#sec:upgrade> for upgrading IPython versions.


    Detailed Unix instructions (Linux, Mac OS X, etc.)

For RPM based systems, simply install the supplied package in the usual
manner. If you download the tar archive, the process is:

   1. Unzip/untar the ipython-XXX.tar.gz file wherever you want (XXX is
      the version number). It will make a directory called ipython-XXX.
      Change into that directory where you will find the files README
      and setup.py. Once you've completed the installation, you can
      safely remove this directory.
   2. If you are installing over a previous installation of version
      0.2.0 or earlier, first remove your $HOME/.ipython directory,
      since the configuration file format has changed somewhat (the '='
      were removed from all option specifications). Or you can call
      ipython with the -upgrade option and it will do this automatically
      for you.
   3. IPython uses distutils, so you can install it by simply typing at
      the system prompt (don't type the $)::
      
      	$ python setup.py install
      	
      Note that this assumes you have root access to your machine. If
      you don't have root access or don't want IPython to go in the
      default python directories, you'll need to use the ``--home`` option
      (or ``--prefix``). For example::
      
      	$ python setup.py install --home $HOME/local
      	
      will install IPython into $HOME/local and its subdirectories
      (creating them if necessary).
      You can type::
      
      	$ python setup.py --help
      	
      for more details.
      
      Note that if you change the default location for ``--home`` at
      installation, IPython may end up installed at a location which is
      not part of your $PYTHONPATH environment variable. In this case,
      you'll need to configure this variable to include the actual
      directory where the IPython/ directory ended (typically the value
      you give to ``--home`` plus /lib/python).


Mac OSX information
-------------------

Under OSX, there is a choice you need to make. Apple ships its own build
of Python, which lives in the core OSX filesystem hierarchy. You can
also manually install a separate Python, either purely by hand
(typically in /usr/local) or by using Fink, which puts everything under
/sw. Which route to follow is a matter of personal preference, as I've
seen users who favor each of the approaches. Here I will simply list the
known installation issues under OSX, along with their solutions.

This page: http://geosci.uchicago.edu/~tobis/pylab.html contains
information on this topic, with additional details on how to make
IPython and matplotlib play nicely under OSX.


GUI problems
------------

The following instructions apply to an install of IPython under OSX from
unpacking the .tar.gz distribution and installing it for the default
Python interpreter shipped by Apple. If you are using a fink install,
fink will take care of these details for you, by installing IPython
against fink's Python.

IPython offers various forms of support for interacting with graphical
applications from the command line, from simple Tk apps (which are in
principle always supported by Python) to interactive control of WX, Qt
and GTK apps. Under OSX, however, this requires that ipython is
installed by calling the special pythonw script at installation time,
which takes care of coordinating things with Apple's graphical environment.

So when installing under OSX, it is best to use the following command:: 

	$ sudo pythonw setup.py install --install-scripts=/usr/local/bin

or

	$ sudo pythonw setup.py install --install-scripts=/usr/bin
	
depending on where you like to keep hand-installed executables.

The resulting script will have an appropriate shebang line (the first
line in the script whic begins with #!...) such that the ipython
interpreter can interact with the OS X GUI. If the installed version
does not work and has a shebang line that points to, for example, just
/usr/bin/python, then you might have a stale, cached version in your
build/scripts-<python-version> directory. Delete that directory and
rerun the setup.py.

It is also a good idea to use the special flag ``--install-scripts`` as
indicated above, to ensure that the ipython scripts end up in a location
which is part of your $PATH. Otherwise Apple's Python will put the
scripts in an internal directory not available by default at the command
line (if you use /usr/local/bin, you need to make sure this is in your
$PATH, which may not be true by default).


Readline problems
-----------------

By default, the Python version shipped by Apple does not include the
readline library, so central to IPython's behavior. If you install
IPython against Apple's Python, you will not have arrow keys, tab
completion, etc. For Mac OSX 10.3 (Panther), you can find a prebuilt
readline library here:
http://pythonmac.org/packages/readline-5.0-py2.3-macosx10.3.zip

If you are using OSX 10.4 (Tiger), after installing this package you
need to either:

   1. move readline.so from /Library/Python/2.3 to
      /Library/Python/2.3/site-packages, or
   2. install http://pythonmac.org/packages/TigerPython23Compat.pkg.zip

Users installing against Fink's Python or a properly hand-built one
should not have this problem.


DarwinPorts
-----------

I report here a message from an OSX user, who suggests an alternative
means of using IPython under this operating system with good results.
Please let me know of any updates that may be useful for this section.
His message is reproduced verbatim below:

    From: Markus Banfi <markus.banfi-AT-mospheira.net> 

    As a MacOS X (10.4.2) user I prefer to install software using
    DawinPorts instead of Fink. I had no problems installing ipython
    with DarwinPorts. It's just: 

    sudo port install py-ipython 

    It automatically resolved all dependencies (python24, readline,
    py-readline). So far I did not encounter any problems with the
    DarwinPorts port of ipython. 



Windows instructions
--------------------

Some of IPython's very useful features are:

    * Integrated readline support (Tab-based file, object and attribute
      completion, input history across sessions, editable command line,
      etc.)
    * Coloring of prompts, code and tracebacks.

These, by default, are only available under Unix-like operating systems.
However, thanks to Gary Bishop's work, Windows XP/2k users can also
benefit from them. His readline library originally implemented both GNU
readline functionality and color support, so that IPython under Windows
XP/2k can be as friendly and powerful as under Unix-like environments.

This library, now named PyReadline, has been absorbed by the IPython
team (Jörgen Stenarson, in particular), and it continues to be developed
with new features, as well as being distributed directly from the
IPython site.

The PyReadline extension requires CTypes and the windows IPython
installer needs PyWin32, so in all you need:

   1. PyWin32 from http://sourceforge.net/projects/pywin32.
   2. PyReadline for Windows from
      http://ipython.scipy.org/moin/PyReadline/Intro. That page contains
      further details on using and configuring the system to your liking.
   3. Finally, only if you are using Python 2.3 or 2.4, you need CTypes
      from http://starship.python.net/crew/theller/ctypes(you must use
      version 0.9.1 or newer). This package is included in Python 2.5,
      so you don't need to manually get it if your Python version is 2.5
      or newer.

Warning about a broken readline-like library: several users have
reported problems stemming from using the pseudo-readline library at
http://newcenturycomputers.net/projects/readline.html. This is a broken
library which, while called readline, only implements an incomplete
subset of the readline API. Since it is still called readline, it fools
IPython's detection mechanisms and causes unpredictable crashes later.
If you wish to use IPython under Windows, you must NOT use this library,
which for all purposes is (at least as of version 1.6) terminally broken.


Installation procedure
----------------------

Once you have the above installed, from the IPython download directory
grab the ipython-XXX.win32.exe file, where XXX represents the version
number. This is a regular windows executable installer, which you can
simply double-click to install. It will add an entry for IPython to your
Start Menu, as well as registering IPython in the Windows list of
applications, so you can later uninstall it from the Control Panel.

IPython tries to install the configuration information in a directory
named .ipython (_ipython under Windows) located in your 'home'
directory. IPython sets this directory by looking for a HOME environment
variable; if such a variable does not exist, it uses HOMEDRIVE\HOMEPATH
(these are always defined by Windows). This typically gives something
like C:\Documents and Settings\YourUserName, but your local details may
vary. In this directory you will find all the files that configure
IPython's defaults, and you can put there your profiles and extensions.
This directory is automatically added by IPython to sys.path, so
anything you place there can be found by import statements.


Upgrading
---------

For an IPython upgrade, you should first uninstall the previous version.
This will ensure that all files and directories (such as the
documentation) which carry embedded version strings in their names are
properly removed.


Manual installation under Win32
-------------------------------

In case the automatic installer does not work for some reason, you can
download the ipython-XXX.tar.gz file, which contains the full IPython
source distribution (the popular WinZip can read .tar.gz files). After
uncompressing the archive, you can install it at a command terminal just
like any other Python module, by using 'python setup.py install'.

After the installation, run the supplied win32_manual_post_install.py
script, which creates the necessary Start Menu shortcuts for you.



Upgrading from a previous version
---------------------------------

If you are upgrading from a previous version of IPython, after doing the
routine installation described above, you should call IPython with the
-upgrade option the first time you run your new copy. This will
automatically update your configuration directory while preserving
copies of your old files. You can then later merge back any personal
customizations you may have made into the new files. It is a good idea
to do this as there may be new options available in the new
configuration files which you will not have.

Under Windows, if you don't know how to call python scripts with
arguments from a command line, simply delete the old config directory
and IPython will make a new one. Win2k and WinXP users will find it in
C:\Documents and Settings\YourUserName\_ipython, and Win 9x users under
C:\Program Files\IPython\_ipython.

Initial configuration of your environment
=========================================

This section will help you set various things in your environment for
your IPython sessions to be as efficient as possible. All of IPython's
configuration information, along with several example files, is stored
in a directory named by default $HOME/.ipython. You can change this by
defining the environment variable IPYTHONDIR, or at runtime with the
command line option -ipythondir.

If all goes well, the first time you run IPython it should automatically
create a user copy of the config directory for you, based on its builtin
defaults. You can look at the files it creates to learn more about
configuring the system. The main file you will modify to configure
IPython's behavior is called ipythonrc (with a .ini extension under
Windows), included for reference in Sec. 7.1
<node7.html#sec:ipytonrc-sample>. This file is very commented and has
many variables you can change to suit your taste, you can find more
details in Sec. 7 <node7.html#sec:customization>. Here we discuss the
basic things you will want to make sure things are working properly from
the beginning.



Access to the Python help system
--------------------------------

This is true for Python in general (not just for IPython): you should
have an environment variable called PYTHONDOCS pointing to the directory
where your HTML Python documentation lives. In my system it's
/usr/share/doc/python-docs-2.3.4/html, check your local details or ask
your systems administrator.

This is the directory which holds the HTML version of the Python
manuals. Unfortunately it seems that different Linux distributions
package these files differently, so you may have to look around a bit.
Below I show the contents of this directory on my system for reference::

    [html]> ls 
    about.dat acks.html dist/ ext/ index.html lib/ modindex.html
    stdabout.dat tut/ about.html api/ doc/ icons/ inst/ mac/ ref/ style.css

You should really make sure this variable is correctly set so that
Python's pydoc-based help system works. It is a powerful and convenient
system with full access to the Python manuals and all modules accessible
to you.

Under Windows it seems that pydoc finds the documentation automatically,
so no extra setup appears necessary.


Editor
------

The %edit command (and its alias %ed) will invoke the editor set in your
environment as EDITOR. If this variable is not set, it will default to
vi under Linux/Unix and to notepad under Windows. You may want to set
this variable properly and to a lightweight editor which doesn't take
too long to start (that is, something other than a new instance of
Emacs). This way you can edit multi-line code quickly and with the power
of a real editor right inside IPython.

If you are a dedicated Emacs user, you should set up the Emacs server so
that new requests are handled by the original process. This means that
almost no time is spent in handling the request (assuming an Emacs
process is already running). For this to work, you need to set your
EDITOR environment variable to 'emacsclient'. The code below, supplied
by Francois Pinard, can then be used in your .emacs file to enable the
server::

    (defvar server-buffer-clients) 
    (when (and (fboundp 'server-start) (string-equal (getenv "TERM") 'xterm)) 
      (server-start) 
      (defun fp-kill-server-with-buffer-routine () 
        (and server-buffer-clients (server-done))) 
      (add-hook 'kill-buffer-hook 'fp-kill-server-with-buffer-routine))

You can also set the value of this editor via the commmand-line option
'-editor' or in your ipythonrc file. This is useful if you wish to use
specifically for IPython an editor different from your typical default
(and for Windows users who tend to use fewer environment variables).


Color
-----

The default IPython configuration has most bells and whistles turned on
(they're pretty safe). But there's one that may cause problems on some
systems: the use of color on screen for displaying information. This is
very useful, since IPython can show prompts and exception tracebacks
with various colors, display syntax-highlighted source code, and in
general make it easier to visually parse information.

The following terminals seem to handle the color sequences fine:

    * Linux main text console, KDE Konsole, Gnome Terminal, E-term,
      rxvt, xterm.
    * CDE terminal (tested under Solaris). This one boldfaces light colors.
    * (X)Emacs buffers. See sec.3.4 <#sec:emacs> for more details on
      using IPython with (X)Emacs.
    * A Windows (XP/2k) command prompt with Gary Bishop's support
      extensions. Gary's extensions are discussed in Sec. 2.3
      <node2.html#sub:Under-Windows>.
    * A Windows (XP/2k) CygWin shell. Although some users have reported
      problems; it is not clear whether there is an issue for everyone
      or only under specific configurations. If you have full color
      support under cygwin, please post to the IPython mailing list so
      this issue can be resolved for all users.

These have shown problems:

    * Windows command prompt in WinXP/2k logged into a Linux machine via
      telnet or ssh.
    * Windows native command prompt in WinXP/2k, without Gary Bishop's
      extensions. Once Gary's readline library is installed, the normal
      WinXP/2k command prompt works perfectly.

Currently the following color schemes are available:

    * NoColor: uses no color escapes at all (all escapes are empty '' ''
      strings). This 'scheme' is thus fully safe to use in any terminal.
    * Linux: works well in Linux console type environments: dark
      background with light fonts. It uses bright colors for
      information, so it is difficult to read if you have a light
      colored background.
    * LightBG: the basic colors are similar to those in the Linux scheme
      but darker. It is easy to read in terminals with light backgrounds.

IPython uses colors for two main groups of things: prompts and
tracebacks which are directly printed to the terminal, and the object
introspection system which passes large sets of data through a pager.


Input/Output prompts and exception tracebacks
---------------------------------------------

You can test whether the colored prompts and tracebacks work on your
system interactively by typing '%colors Linux' at the prompt (use
'%colors LightBG' if your terminal has a light background). If the input
prompt shows garbage like::

    [0;32mIn [[1;32m1[0;32m]: [0;00m
                               
instead of (in color) something like::
    
    In [1]:
        
this means that your terminal doesn't properly handle color escape
sequences. You can go to a 'no color' mode by typing '%colors NoColor'.

You can try using a different terminal emulator program (Emacs users,
see below). To permanently set your color preferences, edit the file
$HOME/.ipython/ipythonrc and set the colors option to the desired value.


Object details (types, docstrings, source code, etc.)
-----------------------------------------------------

IPython has a set of special functions for studying the objects you are
working with, discussed in detail in Sec. 6.4
<node6.html#sec:dyn-object-info>. But this system relies on passing
information which is longer than your screen through a data pager, such
as the common Unix less and more programs. In order to be able to see
this information in color, your pager needs to be properly configured. I
strongly recommend using less instead of more, as it seems that more
simply can not understand colored text correctly.

In order to configure less as your default pager, do the following:

   1. Set the environment PAGER variable to less.
   2. Set the environment LESS variable to -r (plus any other options
      you always want to pass to less by default). This tells less to
      properly interpret control sequences, which is how color
      information is given to your terminal.

For the csh or tcsh shells, add to your ~/.cshrc file the lines::

    setenv PAGER less 
    setenv LESS -r

There is similar syntax for other Unix shells, look at your system
documentation for details.

If you are on a system which lacks proper data pagers (such as Windows),
IPython will use a very limited builtin pager.

(X)Emacs configuration
----------------------

Thanks to the work of Alexander Schmolck and Prabhu Ramachandran,
currently (X)Emacs and IPython get along very well.

Important note: You will need to use a recent enough version of
python-mode.el, along with the file ipython.el. You can check that the
version you have of python-mode.el is new enough by either looking at
the revision number in the file itself, or asking for it in (X)Emacs via
M-x py-version. Versions 4.68 and newer contain the necessary fixes for
proper IPython support.

The file ipython.el is included with the IPython distribution, in the
documentation directory (where this manual resides in PDF and HTML
formats).

Once you put these files in your Emacs path, all you need in your .emacs
file is::

    (require 'ipython) 

This should give you full support for executing code snippets via
IPython, opening IPython as your Python shell via C-c !, etc.

If you happen to get garbage instead of colored prompts as described in
the previous section, you may need to set also in your .emacs file::

    (setq ansi-color-for-comint-mode t) 


Notes:

    * There is one caveat you should be aware of: you must start the
      IPython shell before attempting to execute any code regions via
      ``C-c |``. Simply type C-c ! to start IPython before passing any code
      regions to the interpreter, and you shouldn't experience any
      problems.
      This is due to a bug in Python itself, which has been fixed for
      Python 2.3, but exists as of Python 2.2.2 (reported as SF bug [
      737947 ]).
    * The (X)Emacs support is maintained by Alexander Schmolck, so all
      comments/requests should be directed to him through the IPython
      mailing lists.
    * This code is still somewhat experimental so it's a bit rough
      around the edges (although in practice, it works quite well).
    * Be aware that if you customize py-python-command previously, this
      value will override what ipython.el does (because loading the
      customization variables comes later).

Quick tips
==========

IPython can be used as an improved replacement for the Python prompt,
and for that you don't really need to read any more of this manual. But
in this section we'll try to summarize a few tips on how to make the
most effective use of it for everyday Python development, highlighting
things you might miss in the rest of the manual (which is getting long).
We'll give references to parts in the manual which provide more detail
when appropriate.

The following article by Jeremy Jones provides an introductory tutorial
about IPython:
http://www.onlamp.com/pub/a/python/2005/01/27/ipython.html

    * The TAB key. TAB-completion, especially for attributes, is a
      convenient way to explore the structure of any object you're
      dealing with. Simply type object_name.<TAB> and a list of the
      object's attributes will be printed (see sec. 6.5
      <node6.html#sec:readline> for more). Tab completion also works on
      file and directory names, which combined with IPython's alias
      system allows you to do from within IPython many of the things you
      normally would need the system shell for.
    * Explore your objects. Typing object_name? will print all sorts of
      details about any object, including docstrings, function
      definition lines (for call arguments) and constructor details for
      classes. The magic commands %pdoc, %pdef, %psource and %pfile will
      respectively print the docstring, function definition line, full
      source code and the complete file for any object (when they can be
      found). If automagic is on (it is by default), you don't need to
      type the '%' explicitly. See sec. 6.4
      <node6.html#sec:dyn-object-info> for more.
    * The %run magic command allows you to run any python script and
      load all of its data directly into the interactive namespace.
      Since the file is re-read from disk each time, changes you make to
      it are reflected immediately (in contrast to the behavior of
      import). I rarely use import for code I am testing, relying on
      %run instead. See sec. 6.2 <node6.html#sec:magic> for more on this
      and other magic commands, or type the name of any magic command
      and ? to get details on it. See also sec. 6.9
      <node6.html#sec:dreload> for a recursive reload command.
      %run also has special flags for timing the execution of your
      scripts (-t) and for executing them under the control of either
      Python's pdb debugger (-d) or profiler (-p). With all of these,
      %run can be used as the main tool for efficient interactive
      development of code which you write in your editor of choice.
    * Use the Python debugger, pdb^2 <footnode.html#foot360>. The %pdb
      command allows you to toggle on and off the automatic invocation
      of an IPython-enhanced pdb debugger (with coloring, tab completion
      and more) at any uncaught exception. The advantage of this is that
      pdb starts inside the function where the exception occurred, with
      all data still available. You can print variables, see code,
      execute statements and even walk up and down the call stack to
      track down the true source of the problem (which often is many
      layers in the stack above where the exception gets triggered).
      Running programs with %run and pdb active can be an efficient to
      develop and debug code, in many cases eliminating the need for
      print statements or external debugging tools. I often simply put a
      1/0 in a place where I want to take a look so that pdb gets
      called, quickly view whatever variables I need to or test various
      pieces of code and then remove the 1/0.
      Note also that '%run -d' activates pdb and automatically sets
      initial breakpoints for you to step through your code, watch
      variables, etc. See Sec. 6.12 <node6.html#sec:cache_output> for
      details.
    * Use the output cache. All output results are automatically stored
      in a global dictionary named Out and variables named _1, _2, etc.
      alias them. For example, the result of input line 4 is available
      either as Out[4] or as _4. Additionally, three variables named _,
      __ and ___ are always kept updated with the for the last three
      results. This allows you to recall any previous result and further
      use it for new calculations. See Sec. 6.12
      <node6.html#sec:cache_output> for more.
    * Put a ';' at the end of a line to supress the printing of output.
      This is useful when doing calculations which generate long output
      you are not interested in seeing. The _* variables and the Out[]
      list do get updated with the contents of the output, even if it is
      not printed. You can thus still access the generated results this
      way for further processing.
    * A similar system exists for caching input. All input is stored in
      a global list called In , so you can re-execute lines 22 through
      28 plus line 34 by typing 'exec In[22:29]+In[34]' (using Python
      slicing notation). If you need to execute the same set of lines
      often, you can assign them to a macro with the %macro function.
      See sec. 6.11 <node6.html#sec:cache_input> for more.
    * Use your input history. The %hist command can show you all
      previous input, without line numbers if desired (option -n) so you
      can directly copy and paste code either back in IPython or in a
      text editor. You can also save all your history by turning on
      logging via %logstart; these logs can later be either reloaded as
      IPython sessions or used as code for your programs.
    * Define your own system aliases. Even though IPython gives you
      access to your system shell via the ! prefix, it is convenient to
      have aliases to the system commands you use most often. This
      allows you to work seamlessly from inside IPython with the same
      commands you are used to in your system shell.
      IPython comes with some pre-defined aliases and a complete system
      for changing directories, both via a stack (see %pushd, %popd and
      %dhist) and via direct %cd. The latter keeps a history of visited
      directories and allows you to go to any previously visited one.
    * Use Python to manipulate the results of system commands. The '!!'
      special syntax, and the %sc and %sx magic commands allow you to
      capture system output into Python variables.
    * Expand python variables when calling the shell (either via '!' and
      '!!' or via aliases) by prepending a $ in front of them. You can
      also expand complete python expressions. See sec. 6.7
      <node6.html#sub:System-shell-access> for more.
    * Use profiles to maintain different configurations (modules to
      load, function definitions, option settings) for particular tasks.
      You can then have customized versions of IPython for specific
      purposes. See sec. 7.3 <node7.html#sec:profiles> for more.
    * Embed IPython in your programs. A few lines of code are enough to
      load a complete IPython inside your own programs, giving you the
      ability to work with your data interactively after automatic
      processing has been completed. See sec. 9 <node9.html#sec:embed>
      for more.
    * Use the Python profiler. When dealing with performance issues, the
      %run command with a -p option allows you to run complete programs
      under the control of the Python profiler. The %prun command does a
      similar job for single Python expressions (like function calls).
    * Use the IPython.demo.Demo class to load any Python script as an
      interactive demo. With a minimal amount of simple markup, you can
      control the execution of the script, stopping as needed. See
      sec. 14 <node14.html#sec:interactive-demos> for more.
    * Run your doctests from within IPython for development and
      debugging. The special %doctest_mode command toggles a mode where
      the prompt, output and exceptions display matches as closely as
      possible that of the default Python interpreter. In addition, this
      mode allows you to directly paste in code that contains leading
      '>>>' prompts, even if they have extra leading whitespace (as is
      common in doctest files). This combined with the '%history -tn'
      call to see your translated history (with these extra prompts
      removed and no line numbers) allows for an easy doctest workflow,
      where you can go from doctest to interactive execution to pasting
      into valid Python code as needed.


Source code handling tips
-------------------------

IPython is a line-oriented program, without full control of the
terminal. Therefore, it doesn't support true multiline editing. However,
it has a number of useful tools to help you in dealing effectively with
more complex editing.

The %edit command gives a reasonable approximation of multiline editing,
by invoking your favorite editor on the spot. IPython will execute the
code you type in there as if it were typed interactively. Type %edit?
for the full details on the edit command.

If you have typed various commands during a session, which you'd like to
reuse, IPython provides you with a number of tools. Start by using %hist
to see your input history, so you can see the line numbers of all input.
Let us say that you'd like to reuse lines 10 through 20, plus lines 24
and 28. All the commands below can operate on these with the syntax::

    %command 10-20 24 28 

where the command given can be:

    * %macro <macroname>: this stores the lines into a variable which,
      when called at the prompt, re-executes the input. Macros can be
      edited later using '%edit macroname', and they can be stored
      persistently across sessions with '%store macroname' (the storage
      system is per-profile). The combination of quick macros,
      persistent storage and editing, allows you to easily refine
      quick-and-dirty interactive input into permanent utilities, always
      available both in IPython and as files for general reuse.
    * %edit: this will open a text editor with those lines pre-loaded
      for further modification. It will then execute the resulting
      file's contents as if you had typed it at the prompt.
    * %save <filename>: this saves the lines directly to a named file on
      disk.

While %macro saves input lines into memory for interactive re-execution,
sometimes you'd like to save your input directly to a file. The %save
magic does this: its input sytnax is the same as %macro, but it saves
your input directly to a Python file. Note that the %logstart command
also saves input, but it logs all input to disk (though you can
temporarily suspend it and reactivate it with %logoff/%logon); %save
allows you to select which lines of input you need to save.


Lightweight 'version control'
-----------------------------

When you call %edit with no arguments, IPython opens an empty editor
with a temporary file, and it returns the contents of your editing
session as a string variable. Thanks to IPython's output caching
mechanism, this is automatically stored::

    In [1]: %edit

    IPython will make a temporary file named: /tmp/ipython_edit_yR-HCN.py

    Editing... done. Executing edited code...

    hello - this is a temporary file

    Out[1]: "print 'hello - this is a temporary file'\n"

Now, if you call '%edit -p', IPython tries to open an editor with the
same data as the last time you used %edit. So if you haven't used %edit
in the meantime, this same contents will reopen; however, it will be
done in a new file. This means that if you make changes and you later
want to find an old version, you can always retrieve it by using its
output number, via '%edit _NN', where NN is the number of the output
prompt.

Continuing with the example above, this should illustrate this idea::

    In [2]: edit -p

    IPython will make a temporary file named: /tmp/ipython_edit_nA09Qk.py

    Editing... done. Executing edited code...

    hello - now I made some changes

    Out[2]: "print 'hello - now I made some changes'\n"

    In [3]: edit _1

    IPython will make a temporary file named: /tmp/ipython_edit_gy6-zD.py

    Editing... done. Executing edited code...

    hello - this is a temporary file

    IPython version control at work :)

    Out[3]: "print 'hello - this is a temporary file'\nprint 'IPython version control at work :)'\n"


This section was written after a contribution by Alexander Belchenko on
the IPython user list.


Effective logging
-----------------

A very useful suggestion sent in by Robert Kern follows:

I recently happened on a nifty way to keep tidy per-project log files. I
made a profile for my project (which is called "parkfield").

    include ipythonrc

    # cancel earlier logfile invocation:

    logfile ''

    execute import time

    execute __cmd = '/Users/kern/research/logfiles/parkfield-%s.log rotate'

    execute __IP.magic_logstart(__cmd % time.strftime('%Y-%m-%d'))

I also added a shell alias for convenience:

    alias parkfield="ipython -pylab -profile parkfield" 

Now I have a nice little directory with everything I ever type in,
organized by project and date.

Contribute your own: If you have your own favorite tip on using IPython
efficiently for a certain task (especially things which can't be done in
the normal Python interpreter), don't hesitate to send it!

Command-line use
================

You start IPython with the command::

    $ ipython [options] files

If invoked with no options, it executes all the files listed in sequence
and drops you into the interpreter while still acknowledging any options
you may have set in your ipythonrc file. This behavior is different from
standard Python, which when called as python -i will only execute one
file and ignore your configuration setup.

Please note that some of the configuration options are not available at
the command line, simply because they are not practical here. Look into
your ipythonrc configuration file for details on those. This file
typically installed in the $HOME/.ipython directory. For Windows users,
$HOME resolves to C:\\Documents and Settings\\YourUserName in most
instances. In the rest of this text, we will refer to this directory as
IPYTHONDIR.


Special Threading Options

The following special options are ONLY valid at the beginning of the
command line, and not later. This is because they control the initial-
ization of ipython itself, before the normal option-handling mechanism
is active.

    * [-gthread, -qthread, -q4thread, -wthread, -pylab:] Only one of
      these can be given, and it can only be given as the first option
      passed to IPython (it will have no effect in any other position).
      They provide threading support for the GTK, Qt (versions 3 and 4)
      and WXPython toolkits, and for the matplotlib library.
    * [ ] With any of the first four options, IPython starts running a
      separate thread for the graphical toolkit's operation, so that you
      can open and control graphical elements from within an IPython
      command line, without blocking. All four provide essentially the
      same functionality, respectively for GTK, Qt3, Qt4 and WXWidgets
      (via their Python interfaces).
    * [ ] Note that with -wthread, you can additionally use the
      -wxversion option to request a specific version of wx to be used.
      This requires that you have the wxversion Python module installed,
      which is part of recent wxPython distributions.
    * [ ] If -pylab is given, IPython loads special support for the mat
      plotlib library (http://matplotlib.sourceforge.net), allowing
      interactive usage of any of its backends as defined in the user's
      ~/.matplotlib/matplotlibrc file. It automatically activates GTK,
      Qt or WX threading for IPyhton if the choice of matplotlib backend
      requires it. It also modifies the %run command to correctly
      execute (without blocking) any matplotlib-based script which calls
      show() at the end.
    * [-tk] The -g/q/q4/wthread options, and -pylab (if matplotlib is
      configured to use GTK, Qt3, Qt4 or WX), will normally block Tk
      graphical interfaces. This means that when either GTK, Qt or WX
      threading is active, any attempt to open a Tk GUI will result in a
      dead window, and possibly cause the Python interpreter to crash.
      An extra option, -tk, is available to address this issue. It can
      only be given as a second option after any of the above (-gthread,
      -wthread or -pylab).
    * [ ] If -tk is given, IPython will try to coordinate Tk threading
      with GTK, Qt or WX. This is however potentially unreliable, and
      you will have to test on your platform and Python configuration to
      determine whether it works for you. Debian users have reported
      success, apparently due to the fact that Debian builds all of Tcl,
      Tk, Tkinter and Python with pthreads support. Under other Linux
      environments (such as Fedora Core 2/3), this option has caused
      random crashes and lockups of the Python interpreter. Under other
      operating systems (Mac OSX and Windows), you'll need to try it to
      find out, since currently no user reports are available.
    * [ ] There is unfortunately no way for IPython to determine at run
      time whether -tk will work reliably or not, so you will need to do
      some experiments before relying on it for regular work.



Regular Options
---------------

After the above threading options have been given, regular options can
follow in any order. All options can be abbreviated to their shortest
non-ambiguous form and are case-sensitive. One or two dashes can be
used. Some options have an alternate short form, indicated after a ``|``.

Most options can also be set from your ipythonrc configuration file. See
the provided example for more details on what the options do. Options
given at the command line override the values set in the ipythonrc file.

All options with a [no] prepended can be specified in negated form
(-nooption instead of -option) to turn the feature off.

    * [-help:] print a help message and exit.
    * [-pylab:] this can only be given as the first option passed to
      IPython (it will have no effect in any other position). It adds
      special support for the matplotlib library
      (http://matplotlib.sourceforge.net
      http://matplotlib.sourceforge.net), allowing interactive usage of
      any of its backends as defined in the user's .matplotlibrc file.
      It automatically activates GTK or WX threading for IPyhton if the
      choice of matplotlib backend requires it. It also modifies the
      %run command to correctly execute (without blocking) any
      matplotlib-based script which calls show() at the end. See Sec. 15
      <node15.html#sec:matplotlib-support> for more details.
    * [-autocall] <val>: Make IPython automatically call any callable
      object even if you didn't type explicit parentheses. For example,
      'str 43' becomes 'str(43)' automatically. The value can be '0' to
      disable the feature, '1' for smart autocall, where it is not
      applied if there are no more arguments on the line, and '2' for
      full autocall, where all callable objects are automatically called
      (even if no arguments are present). The default is '1'.
    * [-[no]autoindent:] Turn automatic indentation on/off.
    * [-[no]automagic:] make magic commands automatic (without needing
      their first character to be %). Type %magic at the IPython prompt
      for more information.
    * [-[no]autoedit_syntax:] When a syntax error occurs after editing a
      file, automatically open the file to the trouble causing line for
      convenient fixing.
    * [-[no]banner:] Print the initial information banner (default on).
    * [-c <command>:] execute the given command string, and set sys.argv
      to ['c']. This is similar to the -c option in the normal Python
      interpreter.
    * [-cache_size|cs <n>:] size of the output cache (maximum number of
      entries to hold in memory). The default is 1000, you can change it
      permanently in your config file. Setting it to 0 completely
      disables the caching system, and the minimum value accepted is 20
      (if you provide a value less than 20, it is reset to 0 and a
      warning is issued) This limit is defined because otherwise you'll
      spend more time re-flushing a too small cache than working.
    * [-classic|cl:] Gives IPython a similar feel to the classic Python
      prompt.
    * [-colors <scheme>:] Color scheme for prompts and exception
      reporting. Currently implemented: NoColor, Linux and LightBG.
    * [-[no]color_info:] IPython can display information about objects
      via a set of functions, and optionally can use colors for this,
      syntax highlighting source code and various other elements.
      However, because this information is passed through a pager (like
      'less') and many pagers get confused with color codes, this option
      is off by default. You can test it and turn it on permanently in
      your ipythonrc file if it works for you. As a reference, the
      'less' pager supplied with Mandrake 8.2 works ok, but that in
      RedHat 7.2 doesn't.
    * [ ] Test it and turn it on permanently if it works with your
      system. The magic function %color_info allows you to toggle this
      interactively for testing.
    * [-[no]debug:] Show information about the loading process. Very
      useful to pin down problems with your configuration files or to
      get details about session restores.
    * [-[no]deep_reload:] IPython can use the deep_reload module which
      reloads changes in modules recursively (it replaces the reload()
      function, so you don't need to change anything to use it).
      deep_reload() forces a full reload of modules whose code may have
      changed, which the default reload() function does not.
    * [ ] When deep_reload is off, IPython will use the normal reload(),
      but deep_reload will still be available as dreload(). This feature
      is off by default [which means that you have both normal reload()
      and dreload()].
    * [-editor <name>:] Which editor to use with the %edit command. By
      default, IPython will honor your EDITOR environment variable (if
      not set, vi is the Unix default and notepad the Windows one).
      Since this editor is invoked on the fly by IPython and is meant
      for editing small code snippets, you may want to use a small,
      lightweight editor here (in case your default EDITOR is something
      like Emacs).
    * [-ipythondir <name>:] name of your IPython configuration directory
      IPYTHONDIR. This can also be specified through the environment
      variable IPYTHONDIR.
    * [-log|l:] generate a log file of all input. The file is named
      ipython_log.py in your current directory (which prevents logs from
      multiple IPython sessions from trampling each other). You can use
      this to later restore a session by loading your logfile as a file
      to be executed with option -logplay (see below).
    * [-logfile|lf <name>:] specify the name of your logfile.
    * [-logplay|lp <name>:] you can replay a previous log. For restoring
      a session as close as possible to the state you left it in, use
      this option (don't just run the logfile). With -logplay, IPython
      will try to reconstruct the previous working environment in full,
      not just execute the commands in the logfile.
    * [ ] When a session is restored, logging is automatically turned on
      again with the name of the logfile it was invoked with (it is read
      from the log header). So once you've turned logging on for a
      session, you can quit IPython and reload it as many times as you
      want and it will continue to log its history and restore from the
      beginning every time.
    * [ ] Caveats: there are limitations in this option. The history
      variables _i*,_* and _dh don't get restored properly. In the
      future we will try to implement full session saving by writing and
      retrieving a 'snapshot' of the memory state of IPython. But our
      first attempts failed because of inherent limitations of Python's
      Pickle module, so this may have to wait.
    * [-[no]messages:] Print messages which IPython collects about its
      startup process (default on).
    * [-[no]pdb:] Automatically call the pdb debugger after every
      uncaught exception. If you are used to debugging using pdb, this
      puts you automatically inside of it after any call (either in
      IPython or in code called by it) which triggers an exception which
      goes uncaught.
    * [-[no]pprint:] ipython can optionally use the pprint (pretty
      printer) module for displaying results. pprint tends to give a
      nicer display of nested data structures. If you like it, you can
      turn it on permanently in your config file (default off).
    * [-profile|p] <name>: assume that your config file is
      ipythonrc-<name> (looks in current dir first, then in IPYTHONDIR).
      This is a quick way to keep and load multiple config files for
      different tasks, especially if you use the include option of
      config files. You can keep a basic IPYTHONDIR/ipythonrc file and
      then have other 'profiles' which include this one and load extra
      things for particular tasks. For example:
    * [ ] 1. $HOME/.ipython/ipythonrc : load basic things you always want.
    * [ ] 2. $HOME/.ipython/ipythonrc-math : load (1) and basic
      math-related modules.
    * [ ] 3. $HOME/.ipython/ipythonrc-numeric : load (1) and Numeric and
      plotting modules.
    * [ ] Since it is possible to create an endless loop by having
      circular file inclusions, IPython will stop if it reaches 15
      recursive inclusions.
    * [-prompt_in1|pi1 <string>:] Specify the string used for input
      prompts. Note that if you are using numbered prompts, the number
      is represented with a '\#' in the string. Don't forget to quote
      strings with spaces embedded in them. Default: 'In [\#]:'.
      Sec. 7.2 <node7.html#sec:prompts> discusses in detail all the
      available escapes to customize your prompts.
    * [-prompt_in2|pi2 <string>:] Similar to the previous option, but
      used for the continuation prompts. The special sequence '\D' is
      similar to '\#', but with all digits replaced dots (so you can
      have your continuation prompt aligned with your input prompt).
      Default: '   .\D.:' (note three spaces at the start for alignment
      with 'In [\#]').
    * [-prompt_out|po <string>:] String used for output prompts, also
      uses numbers like prompt_in1. Default: 'Out[\#]:'
    * [-quick:] start in bare bones mode (no config file loaded).
    * [-rcfile <name>:] name of your IPython resource configuration
      file. Normally IPython loads ipythonrc (from current directory) or
      IPYTHONDIR/ipythonrc.
    * [ ] If the loading of your config file fails, IPython starts with
      a bare bones configuration (no modules loaded at all).
    * [-[no]readline:] use the readline library, which is needed to
      support name completion and command history, among other things.
      It is enabled by default, but may cause problems for users of
      X/Emacs in Python comint or shell buffers.
    * [ ] Note that X/Emacs 'eterm' buffers (opened with M-x term)
      support IPython's readline and syntax coloring fine, only 'emacs'
      (M-x shell and C-c !) buffers do not.
    * [-screen_length|sl <n>:] number of lines of your screen. This is
      used to control printing of very long strings. Strings longer than
      this number of lines will be sent through a pager instead of
      directly printed.
    * [ ] The default value for this is 0, which means IPython will
      auto-detect your screen size every time it needs to print certain
      potentially long strings (this doesn't change the behavior of the
      'print' keyword, it's only triggered internally). If for some
      reason this isn't working well (it needs curses support), specify
      it yourself. Otherwise don't change the default.
    * [-separate_in|si <string>:] separator before input prompts.
      Default: '\n'
    * [-separate_out|so <string>:] separator before output prompts.
      Default: nothing.
    * [-separate_out2|so2 <string>:] separator after output prompts.
      Default: nothing.
    * [ ] For these three options, use the value 0 to specify no separator.
    * [-nosep:] shorthand for '-SeparateIn 0 -SeparateOut 0
      -SeparateOut2 0'. Simply removes all input/output separators.
    * [-upgrade:] allows you to upgrade your IPYTHONDIR configuration
      when you install a new version of IPython. Since new versions may
      include new command line options or example files, this copies
      updated ipythonrc-type files. However, it backs up (with a .old
      extension) all files which it overwrites so that you can merge
      back any customizations you might have in your personal files.
    * [-Version:] print version information and exit.
    * [-wxversion <string>:] Select a specific version of wxPython (used
      in conjunction with -wthread). Requires the wxversion module, part
      of recent wxPython distributions
    * [-xmode <modename>:] Mode for exception reporting.
    * [ ] Valid modes: Plain, Context and Verbose.
    * [ ] Plain: similar to python's normal traceback printing.
    * [ ] Context: prints 5 lines of context source code around each
      line in the traceback.
    * [ ] Verbose: similar to Context, but additionally prints the
      variables currently visible where the exception happened
      (shortening their strings if too long). This can potentially be
      very slow, if you happen to have a huge data structure whose
      string representation is complex to compute. Your computer may
      appear to freeze for a while with cpu usage at 100%. If this
      occurs, you can cancel the traceback with Ctrl-C (maybe hitting it
      more than once).

Interactive use
===============

Warning: IPython relies on the existence of a global variable called
__IP which controls the shell itself. If you redefine __IP to anything,
bizarre behavior will quickly occur.

Other than the above warning, IPython is meant to work as a drop-in
replacement for the standard interactive interpreter. As such, any code
which is valid python should execute normally under IPython (cases where
this is not true should be reported as bugs). It does, however, offer
many features which are not available at a standard python prompt. What
follows is a list of these.


Caution for Windows users
-------------------------

Windows, unfortunately, uses the '\' character as a path separator. This
is a terrible choice, because '\' also represents the escape character
in most modern programming languages, including Python. For this reason,
issuing many of the commands discussed below (especially magics which
affect the filesystem) with '\' in them will cause strange errors.

A partial solution is to use instead the '/' character as a path
separator, which Windows recognizes in most situations. However, in
Windows commands '/' flags options, so you can not use it for the root
directory. This means that paths beginning at the root must be typed in
a contrived manner like:
%copy \opt/foo/bar.txt \tmp

There is no sensible thing IPython can do to truly work around this flaw
in Windows^3 <footnode.html#foot878>.



Magic command system
--------------------

IPython will treat any line whose first character is a % as a special
call to a 'magic' function. These allow you to control the behavior of
IPython itself, plus a lot of system-type features. They are all
prefixed with a % character, but parameters are given without
parentheses or quotes.

Example: typing '%cd mydir' (without the quotes) changes you working
directory to 'mydir', if it exists.

If you have 'automagic' enabled (in your ipythonrc file, via the command
line option -automagic or with the %automagic function), you don't need
to type in the % explicitly. IPython will scan its internal list of
magic functions and call one if it exists. With automagic on you can
then just type 'cd mydir' to go to directory 'mydir'. The automagic
system has the lowest possible precedence in name searches, so defining
an identifier with the same name as an existing magic function will
shadow it for automagic use. You can still access the shadowed magic
function by explicitly using the % character at the beginning of the line.

An example (with automagic on) should clarify all this::

    In [1]: cd ipython # %cd is called by automagic

    /home/fperez/ipython

    In [2]: cd=1 # now cd is just a variable

    In [3]: cd .. # and doesn't work as a function anymore

    ------------------------------

        File "<console>", line 1

          cd ..

              ^

    SyntaxError: invalid syntax

    In [4]: %cd .. # but %cd always works

    /home/fperez

    In [5]: del cd # if you remove the cd variable

    In [6]: cd ipython # automagic can work again

    /home/fperez/ipython

You can define your own magic functions to extend the system. The
following example defines a new magic command, %impall::

    import IPython.ipapi 

    ip = IPython.ipapi.get()

    def doimp(self, arg):

        ip = self.api

        ip.ex("import %s; reload(%s); from %s import *" % (

        arg,arg,arg)

        )

    ip.expose_magic('impall', doimp)

You can also define your own aliased names for magic functions. In your
ipythonrc file, placing a line like:

execute __IP.magic_cl = __IP.magic_clear

will define %cl as a new name for %clear.

Type %magic for more information, including a list of all available
magic functions at any time and their docstrings. You can also type
%magic_function_name? (see sec. 6.4 <#sec:dyn-object-info> for
information on the '?' system) to get information about any particular
magic function you are interested in.


Magic commands
--------------

The rest of this section is automatically generated for each release
from the docstrings in the IPython code. Therefore the formatting is
somewhat minimal, but this method has the advantage of having
information always in sync with the code.

A list of all the magic commands available in IPython's default
installation follows. This is similar to what you'll see by simply
typing %magic at the prompt, but that will also give you information
about magic commands you may have added as part of your personal
customizations.

::

	%Exit: Exit IPython without confirmation.
	
	
	%Pprint: Toggle pretty printing on/off.
	
	
	%alias: Define an alias for a system command.
	
	'%alias alias_name cmd' defines 'alias_name' as an alias for 'cmd'
	
	Then, typing 'alias_name params' will execute the system command 'cmd
	params' (from your underlying operating system).
	
	Aliases have lower precedence than magic functions and Python normal
	variables, so if 'foo' is both a Python variable and an alias, the alias
	can not be executed until 'del foo' removes the Python variable.
	
	You can use the %l specifier in an alias definition to represent the
	whole line when the alias is called. For example:
	
	In [2]: alias all echo "Input in brackets: <%l>"
	In [3]: all hello world
	Input in brackets: <hello world>
	
	You can also define aliases with parameters using %s specifiers (one per
	parameter):
	
	In [1]: alias parts echo first %s second %s
	In [2]: %parts A B
	first A second B
	In [3]: %parts A
	Incorrect number of arguments: 2 expected.
	parts is an alias to: 'echo first %s second %s'
	
	Note that %l and %s are mutually exclusive. You can only use one or the
	other in your aliases.
	
	Aliases expand Python variables just like system calls using ! or !! do:
	all expressions prefixed with '$' get expanded. For details of the
	semantic rules, see PEP-215: http://www.python.org/peps/pep-0215.html.
	This is the library used by IPython for variable expansion. If you want
	to access a true shell variable, an extra $ is necessary to prevent its
	expansion by IPython:
	
	In [6]: alias show echo
	In [7]: PATH='A Python string'
	In [8]: show $PATH
	A Python string
	In [9]: show $$PATH
	/usr/local/lf9560/bin:/usr/local/intel/compiler70/ia32/bin:...
	
	You can use the alias facility to acess all of $PATH. See the %rehash
	and %rehashx functions, which automatically create aliases for the
	contents of your $PATH.
	
	If called with no parameters, %alias prints the current alias table.
	
	
	%autocall: Make functions callable without having to type parentheses.
	
	Usage:
	
	%autocall [mode]
	
	The mode can be one of: 0->Off, 1->Smart, 2->Full. If not given, the
	value is toggled on and off (remembering the previous state).
	
	In more detail, these values mean:
	
	0 -> fully disabled
	
	1 -> active, but do not apply if there are no arguments on the line.
	
	In this mode, you get:
	
	In [1]: callable Out[1]: <built-in function callable>
	
	In [2]: callable 'hello' ---> callable('hello') Out[2]: False
	
	2 -> Active always. Even if no arguments are present, the callable
	object is called:
	
	In [4]: callable ---> callable()
	
	Note that even with autocall off, you can still use '/' at the start of
	a line to treat the first argument on the command line as a function and
	add parentheses to it:
	
	In [8]: /str 43 ---> str(43) Out[8]: '43'
	
	
	%autoindent: Toggle autoindent on/off (if available).
	
	
	%automagic: Make magic functions callable without having to type the
	initial %.
	
	Without argumentsl toggles on/off (when off, you must call it as
	%automagic, of course). With arguments it sets the value, and you can
	use any of (case insensitive):
	
	- on,1,True: to activate
	
	- off,0,False: to deactivate.
	
	Note that magic functions have lowest priority, so if there's a variable
	whose name collides with that of a magic fn, automagic won't work for
	that function (you get the variable instead). However, if you delete the
	variable (del var), the previously shadowed magic function becomes
	visible to automagic again.
	
	
	%bg: Run a job in the background, in a separate thread.
	
	For example,
	
	%bg myfunc(x,y,z=1)
	
	will execute 'myfunc(x,y,z=1)' in a background thread. As soon as the
	execution starts, a message will be printed indicating the job number.
	If your job number is 5, you can use
	
	myvar = jobs.result(5) or myvar = jobs[5].result
	
	to assign this result to variable 'myvar'.
	
	IPython has a job manager, accessible via the 'jobs' object. You can
	type jobs? to get more information about it, and use jobs.<TAB> to see
	its attributes. All attributes not starting with an underscore are meant
	for public use.
	
	In particular, look at the jobs.new() method, which is used to create
	new jobs. This magic %bg function is just a convenience wrapper around
	jobs.new(), for expression-based jobs. If you want to create a new job
	with an explicit function object and arguments, you must call jobs.new()
	directly.
	
	The jobs.new docstring also describes in detail several important
	caveats associated with a thread-based model for background job
	execution. Type jobs.new? for details.
	
	You can check the status of all jobs with jobs.status().
	
	The jobs variable is set by IPython into the Python builtin namespace.
	If you ever declare a variable named 'jobs', you will shadow this name.
	You can either delete your global jobs variable to regain access to the
	job manager, or make a new name and assign it manually to the manager
	(stored in IPython's namespace). For example, to assign the job manager
	to the Jobs name, use:
	
	Jobs = __builtins__.jobs
	
	
	%bookmark: Manage IPython's bookmark system.
	
	%bookmark <name> - set bookmark to current dir %bookmark <name> <dir> -
	set bookmark to <dir> %bookmark -l - list all bookmarks %bookmark -d
	<name> - remove bookmark %bookmark -r - remove all bookmarks
	
	You can later on access a bookmarked folder with: %cd -b <name> or
	simply '%cd <name>' if there is no directory called <name> AND there is
	such a bookmark defined.
	
	Your bookmarks persist through IPython sessions, but they are associated
	with each profile.
	
	
	%cd: Change the current working directory.
	
	This command automatically maintains an internal list of directories you
	visit during your IPython session, in the variable _dh. The command
	%dhist shows this history nicely formatted. You can also do 'cd -<tab>'
	to see directory history conveniently.
	
	Usage:
	
	cd 'dir': changes to directory 'dir'.
	
	cd -: changes to the last visited directory.
	
	cd -<n>: changes to the n-th directory in the directory history.
	
	cd -b <bookmark_name>: jump to a bookmark set by %bookmark (note: cd
	<bookmark_name> is enough if there is no directory <bookmark_name>, but
	a bookmark with the name exists.) 'cd -b <tab>' allows you to
	tab-complete bookmark names.
	
	Options:
	
	-q: quiet. Do not print the working directory after the cd command is
	executed. By default IPython's cd command does print this directory,
	since the default prompts do not display path information.
	
	Note that !cd doesn't work for this purpose because the shell where
	!command runs is immediately discarded after executing 'command'.
	
	
	%color_info: Toggle color_info.
	
	The color_info configuration parameter controls whether colors are used
	for displaying object details (by things like %psource, %pfile or the
	'?' system). This function toggles this value with each call.
	
	Note that unless you have a fairly recent pager (less works better than
	more) in your system, using colored object information displays will not
	work properly. Test it and see.
	
	
	%colors: Switch color scheme for prompts, info system and exception
	handlers.
	
	Currently implemented schemes: NoColor, Linux, LightBG.
	
	Color scheme names are not case-sensitive.
	
	
	%cpaste: Allows you to paste & execute a pre-formatted code block from
	clipboard
	
	You must terminate the block with '-' (two minus-signs) alone on the
	line. You can also provide your own sentinel with '%paste -s %%' ('%%'
	is the new sentinel for this operation)
	
	The block is dedented prior to execution to enable execution of method
	definitions. '>' and '+' characters at the beginning of a line are
	ignored, to allow pasting directly from e-mails or diff files. The
	executed block is also assigned to variable named 'pasted_block' for
	later editing with '%edit pasted_block'.
	
	You can also pass a variable name as an argument, e.g. '%cpaste foo'.
	This assigns the pasted block to variable 'foo' as string, without
	dedenting or executing it.
	
	Do not be alarmed by garbled output on Windows (it's a readline bug).
	Just press enter and type - (and press enter again) and the block will
	be what was just pasted.
	
	IPython statements (magics, shell escapes) are not supported (yet).
	
	
	%debug: Activate the interactive debugger in post-mortem mode.
	
	If an exception has just occurred, this lets you inspect its stack
	frames interactively. Note that this will always work only on the last
	traceback that occurred, so you must call this quickly after an
	exception that you wish to inspect has fired, because if another one
	occurs, it clobbers the previous one.
	
	If you want IPython to automatically do this on every exception, see the
	%pdb magic for more details.
	
	
	%dhist: Print your history of visited directories.
	
	%dhist -> print full history
	%dhist n -> print last n entries only
	%dhist n1 n2 -> print entries between n1 and n2 (n1 not included)
	
	This history is automatically maintained by the %cd command, and always
	available as the global list variable _dh. You can use %cd -<n> to go to
	directory number <n>.
	
	Note that most of time, you should view directory history by entering cd
	-<TAB>.
	
	
	%dirs: Return the current directory stack.
	
	
	%doctest_mode: Toggle doctest mode on and off.
	
	This mode allows you to toggle the prompt behavior between normal
	IPython prompts and ones that are as similar to the default IPython
	interpreter as possible.
	
	It also supports the pasting of code snippets that have leading '»>' and
	'...' prompts in them. This means that you can paste doctests from files
	or docstrings (even if they have leading whitespace), and the code will
	execute correctly. You can then use '%history -tn' to see the translated
	history without line numbers; this will give you the input after removal
	of all the leading prompts and whitespace, which can be pasted back into
	an editor.
	
	With these features, you can switch into this mode easily whenever you
	need to do testing and changes to doctests, without having to leave your
	existing IPython session.
	
	
	%ed: Alias to %edit.
	
	
	%edit: Bring up an editor and execute the resulting code.
	
	Usage: %edit [options] [args]
	
	%edit runs IPython's editor hook. The default version of this hook is
	set to call the __IPYTHON__.rc.editor command. This is read from your
	environment variable $EDITOR. If this isn't found, it will default to vi
	under Linux/Unix and to notepad under Windows. See the end of this
	docstring for how to change the editor hook.
	
	You can also set the value of this editor via the command line option
	'-editor' or in your ipythonrc file. This is useful if you wish to use
	specifically for IPython an editor different from your typical default
	(and for Windows users who typically don't set environment variables).
	
	This command allows you to conveniently edit multi-line code right in
	your IPython session.
	
	If called without arguments, %edit opens up an empty editor with a
	temporary file and will execute the contents of this file when you close
	it (don't forget to save it!).
	
	Options:
	
	-n <number>: open the editor at a specified line number. By default, the
	IPython editor hook uses the unix syntax 'editor +N filename', but you
	can configure this by providing your own modified hook if your favorite
	editor supports line-number specifications with a different syntax.
	
	-p: this will call the editor with the same data as the previous time it
	was used, regardless of how long ago (in your current session) it was.
	
	-r: use 'raw' input. This option only applies to input taken from the
	user's history. By default, the 'processed' history is used, so that
	magics are loaded in their transformed version to valid Python. If this
	option is given, the raw input as typed as the command line is used
	instead. When you exit the editor, it will be executed by IPython's own
	processor.
	
	-x: do not execute the edited code immediately upon exit. This is mainly
	useful if you are editing programs which need to be called with command
	line arguments, which you can then do using %run.
	
	Arguments:
	
	If arguments are given, the following possibilites exist:
	
	    - The arguments are numbers or pairs of dash-separated numbers (like 1
	      4-8 9). These are interpreted as lines of previous input to be loaded
	      into the editor. The syntax is the same of the %macro command.
	
	    - If the argument doesn't start with a number, it is evaluated as a
	      variable and its contents loaded into the editor. You can thus edit any
	      string which contains python code (including the result of previous edits).
	
	    - If the argument is the name of an object (other than a string),
	      IPython will try to locate the file where it was defined and open the
	      editor at the point where it is defined. You can use '%edit function' to
	      load an editor exactly at the point where 'function' is defined, edit it
	      and have the file be executed automatically.
	
	If the object is a macro (see %macro for details), this opens up your
	specified editor with a temporary file containing the macro's data. Upon
	exit, the macro is reloaded with the contents of the file.
	
	Note: opening at an exact line is only supported under Unix, and some
	editors (like kedit and gedit up to Gnome 2.8) do not understand the
	'+NUMBER' parameter necessary for this feature. Good editors like
	(X)Emacs, vi, jed, pico and joe all do.
	
	If the argument is not found as a variable, IPython will look for a
	file with that name (adding .py if necessary) and load it into the
	editor. It will execute its contents with execfile() when you exit,
	loading any code in the file into your interactive namespace.
	
	After executing your code, %edit will return as output the code you
	typed in the editor (except when it was an existing file). This way you
	can reload the code in further invocations of %edit as a variable, via
	_<NUMBER> or Out[<NUMBER>], where <NUMBER> is the prompt number of the
	output.
	
	Note that %edit is also available through the alias %ed.
	
	This is an example of creating a simple function inside the editor and
	then modifying it. First, start up the editor::
	
	    In [1]: ed
	    Editing... done. Executing edited code...
	    Out[1]: 'def foo():\n print "foo() was defined in an editing session"\n'
	
	    We can then call the function foo():
	
	    In [2]: foo()
	    foo() was defined in an editing session
	
	    Now we edit foo. IPython automatically loads the editor with the
	    (temporary) file where foo() was previously defined:
	
	    In [3]: ed foo
	    Editing... done. Executing edited code...
	
	    And if we call foo() again we get the modified version:
	
	    In [4]: foo()
	    foo() has now been changed!
	
	    Here is an example of how to edit a code snippet successive times. First
	    we call the editor:
	
	    In [8]: ed
	    Editing... done. Executing edited code...
	    hello
	    Out[8]: "print 'hello'\n"
	
	    Now we call it again with the previous output (stored in _):
	
	    In [9]: ed _
	    Editing... done. Executing edited code...
	    hello world
	    Out[9]: "print 'hello world'\n"
	
	    Now we call it with the output #8 (stored in _8, also as Out[8]):
	
	    In [10]: ed _8
	    Editing... done. Executing edited code...
	    hello again
	    Out[10]: "print 'hello again'\n"
	
	Changing the default editor hook:
	
	If you wish to write your own editor hook, you can put it in a
	configuration file which you load at startup time. The default hook is
	defined in the IPython.hooks module, and you can use that as a starting
	example for further modifications. That file also has general
	instructions on how to set a new hook for use once you've defined it.
	
	
	%env: List environment variables.
	
	
	%exit: Exit IPython, confirming if configured to do so.
	
	You can configure whether IPython asks for confirmation upon exit by
	setting the confirm_exit flag in the ipythonrc file.
	
	
	%logoff: Temporarily stop logging.
	
	You must have previously started logging.
	
	
	%logon: Restart logging.
	
	This function is for restarting logging which you've temporarily stopped
	with %logoff. For starting logging for the first time, you must use the
	%logstart function, which allows you to specify an optional log filename.
	
	
	%logstart: Start logging anywhere in a session.
	
	%logstart [-o|-r|-t] [log_name [log_mode]]
	
	If no name is given, it defaults to a file named 'ipython_log.py' in
	your current directory, in 'rotate' mode (see below).
	
	'%logstart name' saves to file 'name' in 'backup' mode. It saves your
	history up to that point and then continues logging.
	
	%logstart takes a second optional parameter: logging mode. This can be
	one of (note that the modes are given unquoted):
	append: well, that says it.
	backup: rename (if exists) to name  and start name.
	global: single logfile in your home dir, appended to.
	over : overwrite existing log.
	rotate: create rotating logs name.1 , name.2 , etc.
	
	Options:
	
	-o: log also IPython's output. In this mode, all commands which generate
	an Out[NN] prompt are recorded to the logfile, right after their
	corresponding input line. The output lines are always prepended with a
	'#[Out]# ' marker, so that the log remains valid Python code.
	
	Since this marker is always the same, filtering only the output from a
	log is very easy, using for example a simple awk call:
	
	awk -F'#
	
	\begin{displaymath}Out\end{displaymath}
	
	# ' 'if($2) print $2' ipython_log.py
	
	-r: log 'raw' input. Normally, IPython's logs contain the processed
	input, so that user lines are logged in their final form, converted into
	valid Python. For example, %Exit is logged as '_ip.magic("Exit"). If the
	-r flag is given, all input is logged exactly as typed, with no
	transformations applied.
	
	-t: put timestamps before each input line logged (these are put in
	comments).
	
	
	%logstate: Print the status of the logging system.
	
	
	%logstop: Fully stop logging and close log file.
	
	In order to start logging again, a new %logstart call needs to be made,
	possibly (though not necessarily) with a new filename, mode and other
	options.
	
	
	%lsmagic: List currently available magic functions.
	
	
	%macro: Define a set of input lines as a macro for future re-execution.
	
	Usage:
	%macro [options] name n1-n2 n3-n4 ... n5 .. n6 ...
	
	Options:
	
	-r: use 'raw' input. By default, the 'processed' history is used, so
	that magics are loaded in their transformed version to valid Python. If
	this option is given, the raw input as typed as the command line is used
	instead.
	
	This will define a global variable called 'name' which is a string made
	of joining the slices and lines you specify (n1,n2,... numbers above)
	from your input history into a single string. This variable acts like an
	automatic function which re-executes those lines as if you had typed
	them. You just type 'name' at the prompt and the code executes.
	
	The notation for indicating number ranges is: n1-n2 means 'use line
	numbers n1,...n2' (the endpoint is included). That is, '5-7' means using
	the lines numbered 5,6 and 7.
	
	Note: as a 'hidden' feature, you can also use traditional python slice
	notation, where N:M means numbers N through M-1.
	
	For example, if your history contains (%hist prints it):
	
	44: x=1
	45: y=3
	46: z=x+y
	47: print x
	48: a=5
	49: print 'x',x,'y',y
	
	you can create a macro with lines 44 through 47 (included) and line 49
	called my_macro with:
	
	In [51]: %macro my_macro 44-47 49
	
	Now, typing 'my_macro' (without quotes) will re-execute all this code in
	one pass.
	
	You don't need to give the line-numbers in order, and any given line
	number can appear multiple times. You can assemble macros with any lines
	from your input history in any order.
	
	The macro is a simple object which holds its value in an attribute, but
	IPython's display system checks for macros and executes them as code
	instead of printing them when you type their name.
	
	You can view a macro's contents by explicitly printing it with:
	
	'print macro_name'.
	
	For one-off cases which DON'T contain magic function calls in them you
	can obtain similar results by explicitly executing slices from your
	input history with:
	
	In [60]: exec In[44:48]+In[49]
	
	
	%magic: Print information about the magic function system.
	
	
	%page: Pretty print the object and display it through a pager.
	
	%page [options] OBJECT
	
	If no object is given, use _ (last output).
	
	Options:
	
	-r: page str(object), don't pretty-print it.
	
	
	%pdb: Control the automatic calling of the pdb interactive debugger.
	
	Call as '%pdb on', '%pdb 1', '%pdb off' or '%pdb 0'. If called without
	argument it works as a toggle.
	
	When an exception is triggered, IPython can optionally call the
	interactive pdb debugger after the traceback printout. %pdb toggles this
	feature on and off.
	
	The initial state of this feature is set in your ipythonrc configuration
	file (the variable is called 'pdb').
	
	If you want to just activate the debugger AFTER an exception has fired,
	without having to type '%pdb on' and rerunning your code, you can use
	the %debug magic.
	
	
	%pdef: Print the definition header for any callable object.
	
	If the object is a class, print the constructor information.
	
	
	%pdoc: Print the docstring for an object.
	
	If the given object is a class, it will print both the class and the
	constructor docstrings.
	
	
	%pfile: Print (or run through pager) the file where an object is defined.
	
	The file opens at the line where the object definition begins. IPython
	will honor the environment variable PAGER if set, and otherwise will do
	its best to print the file in a convenient form.
	
	If the given argument is not an object currently defined, IPython will
	try to interpret it as a filename (automatically adding a .py extension
	if needed). You can thus use %pfile as a syntax highlighting code viewer.
	
	
	%pinfo: Provide detailed information about an object.
	
	'%pinfo object' is just a synonym for object? or ?object.
	
	
	%popd: Change to directory popped off the top of the stack.
	
	
	%profile: Print your currently active IPyhton profile.
	
	
	%prun: Run a statement through the python code profiler.
	
	Usage:
	%prun [options] statement
	
	The given statement (which doesn't require quote marks) is run via the
	python profiler in a manner similar to the profile.run() function.
	Namespaces are internally managed to work correctly; profile.run cannot
	be used in IPython because it makes certain assumptions about namespaces
	which do not hold under IPython.
	
	Options:
	
	-l <limit>: you can place restrictions on what or how much of the
	profile gets printed. The limit value can be:
	
	 * A string: only information for function names containing this string
	   is printed.
	
	 * An integer: only these many lines are printed.
	
	 * A float (between 0 and 1): this fraction of the report is printed (for
	  example, use a limit of 0.4 to see the topmost 40% only).
	
	You can combine several limits with repeated use of the option. For
	example, '-l __init__ -l 5' will print only the topmost 5 lines of
	information about class constructors.
	
	-r: return the pstats.Stats object generated by the profiling. This
	object has all the information about the profile in it, and you can
	later use it for further analysis or in other functions.
	
	-s <key>: sort profile by given key. You can provide more than one key
	by using the option several times: '-s key1 -s key2 -s key3...'. The
	default sorting key is 'time'.
	
	The following is copied verbatim from the profile documentation
	referenced below:
	
	When more than one key is provided, additional keys are used as
	secondary criteria when the there is equality in all keys selected
	before them.
	
	Abbreviations can be used for any key names, as long as the abbreviation
	is unambiguous. The following are the keys currently defined:
	
	Valid Arg Meaning
	"calls" call count
	"cumulative" cumulative time
	"file" file name
	"module" file name
	"pcalls" primitive call count
	"line" line number
	"name" function name
	"nfl" name/file/line
	"stdname" standard name
	"time" internal time
	
	Note that all sorts on statistics are in descending order (placing most
	time consuming items first), where as name, file, and line number
	searches are in ascending order (i.e., alphabetical). The subtle
	distinction between "nfl" and "stdname" is that the standard name is a
	sort of the name as printed, which means that the embedded line numbers
	get compared in an odd way. For example, lines 3, 20, and 40 would (if
	the file names were the same) appear in the string order "20" "3" and
	"40". In contrast, "nfl" does a numeric compare of the line numbers. In
	fact, sort_stats("nfl") is the same as sort_stats("name", "file", "line").
	
	-T <filename>: save profile results as shown on screen to a text file.
	The profile is still shown on screen.
	
	-D <filename>: save (via dump_stats) profile statistics to given
	filename. This data is in a format understod by the pstats module, and
	is generated by a call to the dump_stats() method of profile objects.
	The profile is still shown on screen.
	
	If you want to run complete programs under the profiler's control, use
	'%run -p [prof_opts] filename.py [args to program]' where prof_opts
	contains profiler specific options as described here.
	
	You can read the complete documentation for the profile module with:
	In [1]: import profile; profile.help()
	
	
	%psearch: Search for object in namespaces by wildcard.
	
	%psearch [options] PATTERN [OBJECT TYPE]
	
	Note: ? can be used as a synonym for %psearch, at the beginning or at
	the end: both a*? and ?a* are equivalent to '%psearch a*'. Still, the
	rest of the command line must be unchanged (options come first), so for
	example the following forms are equivalent
	
	%psearch -i a* function -i a* function? ?-i a* function
	
	Arguments:
	
	PATTERN
	
	where PATTERN is a string containing * as a wildcard similar to its use
	in a shell. The pattern is matched in all namespaces on the search path.
	By default objects starting with a single _ are not matched, many
	IPython generated objects have a single underscore. The default is case
	insensitive matching. Matching is also done on the attributes of objects
	and not only on the objects in a module.
	
	[OBJECT TYPE]
	
	Is the name of a python type from the types module. The name is given in
	lowercase without the ending type, ex. StringType is written string. By
	adding a type here only objects matching the given type are matched.
	Using all here makes the pattern match all types (this is the default).
	
	Options:
	
	-a: makes the pattern match even objects whose names start with a single
	underscore. These names are normally ommitted from the search.
	
	-i/-c: make the pattern case insensitive/sensitive. If neither of these
	options is given, the default is read from your ipythonrc file. The
	option name which sets this value is 'wildcards_case_sensitive'. If this
	option is not specified in your ipythonrc file, IPython's internal
	default is to do a case sensitive search.
	
	-e/-s NAMESPACE: exclude/search a given namespace. The pattern you
	specifiy can be searched in any of the following namespaces: 'builtin',
	'user', 'user_global','internal', 'alias', where 'builtin' and 'user'
	are the search defaults. Note that you should not use quotes when
	specifying namespaces.
	
	'Builtin' contains the python module builtin, 'user' contains all user
	data, 'alias' only contain the shell aliases and no python objects,
	'internal' contains objects used by IPython. The 'user_global' namespace
	is only used by embedded IPython instances, and it contains module-level
	globals. You can add namespaces to the search with -s or exclude them
	with -e (these options can be given more than once).
	
	Examples:
	
	%psearch a* -> objects beginning with an a %psearch -e builtin a* ->
	objects NOT in the builtin space starting in a %psearch a* function ->
	all functions beginning with an a %psearch re.e* -> objects beginning
	with an e in module re %psearch r*.e* -> objects that start with e in
	modules starting in r %psearch r*.* string -> all strings in modules
	beginning with r
	
	Case sensitve search:
	
	%psearch -c a* list all object beginning with lower case a
	
	Show objects beginning with a single _:
	
	%psearch -a _* list objects beginning with a single underscore
	
	
	%psource: Print (or run through pager) the source code for an object.
	
	
	%pushd: Place the current dir on stack and change directory.
	
	Usage:
	%pushd ['dirname']
	
	
	%pwd: Return the current working directory path.
	
	
	%pycat: Show a syntax-highlighted file through a pager.
	
	This magic is similar to the cat utility, but it will assume the file to
	be Python source and will show it with syntax highlighting.
	
	
	%quickref: Show a quick reference sheet
	
	
	%quit: Exit IPython, confirming if configured to do so (like %exit)
	
	
	%r: Repeat previous input.
	
	Note: Consider using the more powerfull %rep instead!
	
	If given an argument, repeats the previous command which starts with the
	same string, otherwise it just repeats the previous input.
	
	Shell escaped commands (with ! as first character) are not recognized by
	this system, only pure python code and magic commands.
	
	
	%rehashx: Update the alias table with all executable files in $PATH.
	
	This version explicitly checks that every entry in $PATH is a file with
	execute access (os.X_OK), so it is much slower than %rehash.
	
	Under Windows, it checks executability as a match agains a ``|``-separated
	string of extensions, stored in the IPython config variable
	win_exec_ext. This defaults to ``exe|com|bat``.
	
	This function also resets the root module cache of module completer,
	used on slow filesystems.
	
	
	%reset: Resets the namespace by removing all names defined by the user.
	
	Input/Output history are left around in case you need them.
	
	
	%run: Run the named file inside IPython as a program.
	
	Usage:
	%run [-n -i -t [-N<N>] -d [-b<N>] -p [profile options]] file [args]
	
	Parameters after the filename are passed as command-line arguments to
	the program (put in sys.argv). Then, control returns to IPython's prompt.
	
	This is similar to running at a system prompt:
	$ python file args
	but with the advantage of giving you IPython's tracebacks, and of
	loading all variables into your interactive namespace for further use
	(unless -p is used, see below).
	
	The file is executed in a namespace initially consisting only of
	__name__=='__main__' and sys.argv constructed as indicated. It thus sees
	its environment as if it were being run as a stand-alone program (except
	for sharing global objects such as previously imported modules). But
	after execution, the IPython interactive namespace gets updated with all
	variables defined in the program (except for __name__ and sys.argv).
	This allows for very convenient loading of code for interactive work,
	while giving each program a 'clean sheet' to run in.
	
	Options:
	
	-n: __name__ is NOT set to '__main__', but to the running file's name
	without extension (as python does under import). This allows running
	scripts and reloading the definitions in them without calling code
	protected by an ' if __name__ == "__main__" ' clause.
	
	-i: run the file in IPython's namespace instead of an empty one. This is
	useful if you are experimenting with code written in a text editor which
	depends on variables defined interactively.
	
	-e: ignore sys.exit() calls or SystemExit exceptions in the script being
	run. This is particularly useful if IPython is being used to run
	unittests, which always exit with a sys.exit() call. In such cases you
	are interested in the output of the test results, not in seeing a
	traceback of the unittest module.
	
	-t: print timing information at the end of the run. IPython will give
	you an estimated CPU time consumption for your script, which under Unix
	uses the resource module to avoid the wraparound problems of
	time.clock(). Under Unix, an estimate of time spent on system tasks is
	also given (for Windows platforms this is reported as 0.0).
	
	If -t is given, an additional -N<N> option can be given, where <N> must
	be an integer indicating how many times you want the script to run. The
	final timing report will include total and per run results.
	
	For example (testing the script uniq_stable.py):
	
	In [1]: run -t uniq_stable
	
	IPython CPU timings (estimated):
	User : 0.19597 s.
	System: 0.0 s.
	
	In [2]: run -t -N5 uniq_stable
	
	IPython CPU timings (estimated):
	Total runs performed: 5
	Times : Total Per run
	User : 0.910862 s, 0.1821724 s.
	System: 0.0 s, 0.0 s.
	
	-d: run your program under the control of pdb, the Python debugger. This
	allows you to execute your program step by step, watch variables, etc.
	Internally, what IPython does is similar to calling:
	
	pdb.run('execfile("YOURFILENAME")')
	
	with a breakpoint set on line 1 of your file. You can change the line
	number for this automatic breakpoint to be <N> by using the -bN option
	(where N must be an integer). For example:
	
	%run -d -b40 myscript
	
	will set the first breakpoint at line 40 in myscript.py. Note that the
	first breakpoint must be set on a line which actually does something
	(not a comment or docstring) for it to stop execution.
	
	When the pdb debugger starts, you will see a (Pdb) prompt. You must
	first enter 'c' (without qoutes) to start execution up to the first
	breakpoint.
	
	Entering 'help' gives information about the use of the debugger. You can
	easily see pdb's full documentation with "import pdb;pdb.help()" at a
	prompt.
	
	-p: run program under the control of the Python profiler module (which
	prints a detailed report of execution times, function calls, etc).
	
	You can pass other options after -p which affect the behavior of the
	profiler itself. See the docs for %prun for details.
	
	In this mode, the program's variables do NOT propagate back to the
	IPython interactive namespace (because they remain in the namespace
	where the profiler executes them).
	
	Internally this triggers a call to %prun, see its documentation for
	details on the options available specifically for profiling.
	
	There is one special usage for which the text above doesn't apply: if
	the filename ends with .ipy, the file is run as ipython script, just as
	if the commands were written on IPython prompt.
	
	
	%runlog: Run files as logs.
	
	Usage:
	%runlog file1 file2 ...
	
	Run the named files (treating them as log files) in sequence inside the
	interpreter, and return to the prompt. This is much slower than %run
	because each line is executed in a try/except block, but it allows
	running files with syntax errors in them.
	
	Normally IPython will guess when a file is one of its own logfiles, so
	you can typically use %run even for logs. This shorthand allows you to
	force any file to be treated as a log file.
	
	
	%save: Save a set of lines to a given filename.
	
	Usage:
	%save [options] filename n1-n2 n3-n4 ... n5 .. n6 ...
	
	Options:
	
	-r: use 'raw' input. By default, the 'processed' history is used, so
	that magics are loaded in their transformed version to valid Python. If
	this option is given, the raw input as typed as the command line is used
	instead.
	
	This function uses the same syntax as %macro for line extraction, but
	instead of creating a macro it saves the resulting string to the
	filename you specify.
	
	It adds a '.py' extension to the file if you don't do so yourself, and
	it asks for confirmation before overwriting existing files.
	
	
	%sc: Shell capture - execute a shell command and capture its output.
	
	DEPRECATED. Suboptimal, retained for backwards compatibility.
	
	You should use the form 'var = !command' instead. Example:
	
	"%sc -l myfiles = ls " should now be written as
	
	"myfiles = !ls "
	
	myfiles.s, myfiles.l and myfiles.n still apply as documented below.
	
	- %sc [options] varname=command
	
	IPython will run the given command using commands.getoutput(), and will
	then update the user's interactive namespace with a variable called
	varname, containing the value of the call. Your command can contain
	shell wildcards, pipes, etc.
	
	The '=' sign in the syntax is mandatory, and the variable name you
	supply must follow Python's standard conventions for valid names.
	
	(A special format without variable name exists for internal use)
	
	Options:
	
	-l: list output. Split the output on newlines into a list before
	assigning it to the given variable. By default the output is stored as a
	single string.
	
	-v: verbose. Print the contents of the variable.
	
	In most cases you should not need to split as a list, because the
	returned value is a special type of string which can automatically
	provide its contents either as a list (split on newlines) or as a
	space-separated string. These are convenient, respectively, either for
	sequential processing or to be passed to a shell command.
	
	For example:
	
	# Capture into variable a In [9]: sc a=ls *py
	
	# a is a string with embedded newlines In [10]: a Out[10]: 'setup.py
	win32_manual_post_install.py'
	
	# which can be seen as a list: In [11]: a.l Out[11]: ['setup.py',
	'win32_manual_post_install.py']
	
	# or as a whitespace-separated string: In [12]: a.s Out[12]: 'setup.py
	win32_manual_post_install.py'
	
	# a.s is useful to pass as a single command line: In [13]: !wc -l $a.s
	146 setup.py 130 win32_manual_post_install.py 276 total
	
	# while the list form is useful to loop over: In [14]: for f in a.l:
	....: !wc -l $f ....: 146 setup.py 130 win32_manual_post_install.py
	
	Similiarly, the lists returned by the -l option are also special, in the
	sense that you can equally invoke the .s attribute on them to
	automatically get a whitespace-separated string from their contents:
	
	In [1]: sc -l b=ls *py
	
	In [2]: b Out[2]: ['setup.py', 'win32_manual_post_install.py']
	
	In [3]: b.s Out[3]: 'setup.py win32_manual_post_install.py'
	
	In summary, both the lists and strings used for ouptut capture have the
	following special attributes:
	
	.l (or .list) : value as list. .n (or .nlstr): value as
	newline-separated string. .s (or .spstr): value as space-separated string.
	
	
	%sx: Shell execute - run a shell command and capture its output.
	
	%sx command
	
	IPython will run the given command using commands.getoutput(), and
	return the result formatted as a list (split on '\n'). Since the output
	is _returned_, it will be stored in ipython's regular output cache
	Out[N] and in the '_N' automatic variables.
	
	Notes:
	
	1) If an input line begins with '!!', then %sx is automatically invoked.
	That is, while: !ls causes ipython to simply issue system('ls'), typing
	!!ls is a shorthand equivalent to: %sx ls
	
	2) %sx differs from %sc in that %sx automatically splits into a list,
	like '%sc -l'. The reason for this is to make it as easy as possible to
	process line-oriented shell output via further python commands. %sc is
	meant to provide much finer control, but requires more typing.
	
	3) Just like %sc -l, this is a list with special attributes:
	
	.l (or .list) : value as list. .n (or .nlstr): value as
	newline-separated string. .s (or .spstr): value as whitespace-separated
	string.
	
	This is very useful when trying to use such lists as arguments to system
	commands.
	
	
	%system_verbose: Set verbose printing of system calls.
	
	If called without an argument, act as a toggle
	
	
	%time: Time execution of a Python statement or expression.
	
	The CPU and wall clock times are printed, and the value of the
	expression (if any) is returned. Note that under Win32, system time is
	always reported as 0, since it can not be measured.
	
	This function provides very basic timing functionality. In Python 2.3,
	the timeit module offers more control and sophistication, so this could
	be rewritten to use it (patches welcome).
	
	Some examples:
	
	In [1]: time 2**128 CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
	Wall time: 0.00 Out[1]: 340282366920938463463374607431768211456L
	
	In [2]: n = 1000000
	
	In [3]: time sum(range(n)) CPU times: user 1.20 s, sys: 0.05 s, total:
	1.25 s Wall time: 1.37 Out[3]: 499999500000L
	
	In [4]: time print 'hello world' hello world CPU times: user 0.00 s,
	sys: 0.00 s, total: 0.00 s Wall time: 0.00
	
	Note that the time needed by Python to compile the given expression will
	be reported if it is more than 0.1s. In this example, the actual
	exponentiation is done by Python at compilation time, so while the
	expression can take a noticeable amount of time to compute, that time is
	purely due to the compilation:
	
	In [5]: time 3**9999; CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
	Wall time: 0.00 s
	
	In [6]: time 3**999999; CPU times: user 0.00 s, sys: 0.00 s, total: 0.00
	s Wall time: 0.00 s Compiler : 0.78 s
	
	
	%timeit: Time execution of a Python statement or expression
	
	Usage:
	%timeit [-n<N> -r<R> [-t|-c]] statement
	
	Time execution of a Python statement or expression using the timeit module.
	
	Options: -n<N>: execute the given statement <N> times in a loop. If this
	value is not given, a fitting value is chosen.
	
	-r<R>: repeat the loop iteration <R> times and take the best result.
	Default: 3
	
	-t: use time.time to measure the time, which is the default on Unix.
	This function measures wall time.
	
	-c: use time.clock to measure the time, which is the default on Windows
	and measures wall time. On Unix, resource.getrusage is used instead and
	returns the CPU user time.
	
	-p<P>: use a precision of <P> digits to display the timing result.
	Default: 3
	
	Examples:
	In [1]: %timeit pass 10000000 loops, best of 3: 53.3 ns per loop
	
	In [2]: u = None
	
	In [3]: %timeit u is None 10000000 loops, best of 3: 184 ns per loop
	
	In [4]: %timeit -r 4 u == None 1000000 loops, best of 4: 242 ns per loop
	
	In [5]: import time
	
	In [6]: %timeit -n1 time.sleep(2) 1 loops, best of 3: 2 s per loop
	
	The times reported by %timeit will be slightly higher than those
	reported by the timeit.py script when variables are accessed. This is
	due to the fact that %timeit executes the statement in the namespace of
	the shell, compared with timeit.py, which uses a single setup statement
	to import function or create variables. Generally, the bias does not
	matter as long as results from timeit.py are not mixed with those from
	%timeit.
	
	
	%unalias: Remove an alias
	
	
	%upgrade: Upgrade your IPython installation
	
	This will copy the config files that don't yet exist in your ipython dir
	from the system config dir. Use this after upgrading IPython if you
	don't wish to delete your .ipython dir.
	
	Call with -nolegacy to get rid of ipythonrc* files (recommended for new
	users)
	
	
	%who: Print all interactive variables, with some minimal formatting.
	
	If any arguments are given, only variables whose type matches one of
	these are printed. For example:
	
	%who function str
	
	will only list functions and strings, excluding all other types of
	variables. To find the proper type names, simply use type(var) at a
	command line to see how python prints type names. For example:
	
	In [1]: type('hello')
	Out[1]: <type 'str'>
	
	indicates that the type name for strings is 'str'.
	
	%who always excludes executed names loaded through your configuration
	file and things which are internal to IPython.
	
	This is deliberate, as typically you may load many modules and the
	purpose of %who is to show you only what you've manually defined.
	
	
	%who_ls: Return a sorted list of all interactive variables.
	
	If arguments are given, only variables of types matching these arguments
	are returned.
	
	
	%whos: Like %who, but gives some extra information about each variable.
	
	The same type filtering of %who can be applied here.
	
	For all variables, the type is printed. Additionally it prints:
	
	- For ,[],(): their length.
	
	- For numpy and Numeric arrays, a summary with shape, number of
	elements, typecode and size in memory.
	
	- Everything else: a string representation, snipping their middle if too
	long.
	
	
	%xmode: Switch modes for the exception handlers.
	
	Valid modes: Plain, Context and Verbose.
	
	If called without arguments, acts as a toggle.


Access to the standard Python help
----------------------------------

As of Python 2.1, a help system is available with access to object
docstrings and the Python manuals. Simply type 'help' (no quotes) to
access it. You can also type help(object) to obtain information about a
given object, and help('keyword') for information on a keyword. As noted
in sec. 3.1 <node3.html#sec:help-access>, you need to properly configure
your environment variable PYTHONDOCS for this feature to work correctly.



Dynamic object information
--------------------------

Typing ?word or word? prints detailed information about an object. If
certain strings in the object are too long (docstrings, code, etc.) they
get snipped in the center for brevity. This system gives access variable
types and values, full source code for any object (if available),
function prototypes and other useful information.

Typing ??word or word?? gives access to the full information without
snipping long strings. Long strings are sent to the screen through the
less pager if longer than the screen and printed otherwise. On systems
lacking the less command, IPython uses a very basic internal pager.

The following magic functions are particularly useful for gathering
information about your working environment. You can get more details by
typing %magic or querying them individually (use %function_name? with or
without the %), this is just a summary:

    * [%pdoc <object>:] Print (or run through a pager if too long) the
      docstring for an object. If the given object is a class, it will
      print both the class and the constructor docstrings.
    * [%pdef <object>:] Print the definition header for any callable
      object. If the object is a class, print the constructor information.
    * [%psource <object>:] Print (or run through a pager if too long)
      the source code for an object.
    * [%pfile <object>:] Show the entire source file where an object was
      defined via a pager, opening it at the line where the object
      definition begins.
    * [%who/%whos:] These functions give information about identifiers
      you have defined interactively (not things you loaded or defined
      in your configuration files). %who just prints a list of
      identifiers and %whos prints a table with some basic details about
      each identifier.

Note that the dynamic object information functions (?/??, %pdoc, %pfile,
%pdef, %psource) give you access to documentation even on things which
are not really defined as separate identifiers. Try for example typing
{}.get? or after doing import os, type os.path.abspath??.



Readline-based features
-----------------------

These features require the GNU readline library, so they won't work if
your Python installation lacks readline support. We will first describe
the default behavior IPython uses, and then how to change it to suit
your preferences.


Command line completion
-----------------------

At any time, hitting TAB will complete any available python commands or
variable names, and show you a list of the possible completions if
there's no unambiguous one. It will also complete filenames in the
current directory if no python names match what you've typed so far.


Search command history
----------------------

IPython provides two ways for searching through previous input and thus
reduce the need for repetitive typing:

   1. Start typing, and then use Ctrl-p (previous,up) and Ctrl-n
      (next,down) to search through only the history items that match
      what you've typed so far. If you use Ctrl-p/Ctrl-n at a blank
      prompt, they just behave like normal arrow keys.
   2. Hit Ctrl-r: opens a search prompt. Begin typing and the system
      searches your history for lines that contain what you've typed so
      far, completing as much as it can.


Persistent command history across sessions
------------------------------------------

IPython will save your input history when it leaves and reload it next
time you restart it. By default, the history file is named
$IPYTHONDIR/history, but if you've loaded a named profile,
'-PROFILE_NAME' is appended to the name. This allows you to keep
separate histories related to various tasks: commands related to
numerical work will not be clobbered by a system shell history, for
example.


Autoindent
----------

IPython can recognize lines ending in ':' and indent the next line,
while also un-indenting automatically after 'raise' or 'return'.

This feature uses the readline library, so it will honor your ~/.inputrc
configuration (or whatever file your INPUTRC variable points to). Adding
the following lines to your .inputrc file can make indenting/unindenting
more convenient (M-i indents, M-u unindents)::

    $if Python 
    "\M-i": "    "  
    "\M-u": "\d\d\d\d"  
    $endif

Note that there are 4 spaces between the quote marks after "M-i" above.

Warning: this feature is ON by default, but it can cause problems with
the pasting of multi-line indented code (the pasted code gets
re-indented on each line). A magic function %autoindent allows you to
toggle it on/off at runtime. You can also disable it permanently on in
your ipythonrc file (set autoindent 0).


Customizing readline behavior
-----------------------------

All these features are based on the GNU readline library, which has an
extremely customizable interface. Normally, readline is configured via a
file which defines the behavior of the library; the details of the
syntax for this can be found in the readline documentation available
with your system or on the Internet. IPython doesn't read this file (if
it exists) directly, but it does support passing to readline valid
options via a simple interface. In brief, you can customize readline by
setting the following options in your ipythonrc configuration file (note
that these options can not be specified at the command line):

    * [readline_parse_and_bind:] this option can appear as many times as
      you want, each time defining a string to be executed via a
      readline.parse_and_bind() command. The syntax for valid commands
      of this kind can be found by reading the documentation for the GNU
      readline library, as these commands are of the kind which readline
      accepts in its configuration file.
    * [readline_remove_delims:] a string of characters to be removed
      from the default word-delimiters list used by readline, so that
      completions may be performed on strings which contain them. Do not
      change the default value unless you know what you're doing.
    * [readline_omit__names:] when tab-completion is enabled, hitting
      <tab> after a '.' in a name will complete all attributes of an
      object, including all the special methods whose names include
      double underscores (like __getitem__ or __class__). If you'd
      rather not see these names by default, you can set this option to
      1. Note that even when this option is set, you can still see those
      names by explicitly typing a _ after the period and hitting <tab>:
      'name._<tab>' will always complete attribute names starting with '_'.
    * [ ] This option is off by default so that new users see all
      attributes of any objects they are dealing with.

You will find the default values along with a corresponding detailed
explanation in your ipythonrc file.


Session logging and restoring
-----------------------------

You can log all input from a session either by starting IPython with the
command line switches -log or -logfile (see sec. 5.2
<node5.html#sec:cmd-line-opts>)or by activating the logging at any
moment with the magic function %logstart.

Log files can later be reloaded with the -logplay option and IPython
will attempt to 'replay' the log by executing all the lines in it, thus
restoring the state of a previous session. This feature is not quite
perfect, but can still be useful in many cases.

The log files can also be used as a way to have a permanent record of
any code you wrote while experimenting. Log files are regular text files
which you can later open in your favorite text editor to extract code or
to 'clean them up' before using them to replay a session.

The %logstart function for activating logging in mid-session is used as
follows:

%logstart [log_name [log_mode]]

If no name is given, it defaults to a file named 'log' in your
IPYTHONDIR directory, in 'rotate' mode (see below).

'%logstart name' saves to file 'name' in 'backup' mode. It saves your
history up to that point and then continues logging.

%logstart takes a second optional parameter: logging mode. This can be
one of (note that the modes are given unquoted):

    * [over:] overwrite existing log_name.
    * [backup:] rename (if exists) to log_name~ and start log_name.
    * [append:] well, that says it.
    * [rotate:] create rotating logs log_name.1~, log_name.2~, etc.

The %logoff and %logon functions allow you to temporarily stop and
resume logging to a file which had previously been started with
%logstart. They will fail (with an explanation) if you try to use them
before logging has been started.



System shell access
-------------------

Any input line beginning with a ! character is passed verbatim (minus
the !, of course) to the underlying operating system. For example,
typing !ls will run 'ls' in the current directory.

Manual capture of command output
--------------------------------

If the input line begins with two exclamation marks, !!, the command is
executed but its output is captured and returned as a python list, split
on newlines. Any output sent by the subprocess to standard error is
printed separately, so that the resulting list only captures standard
output. The !! syntax is a shorthand for the %sx magic command.

Finally, the %sc magic (short for 'shell capture') is similar to %sx,
but allowing more fine-grained control of the capture details, and
storing the result directly into a named variable. The direct use of 
%sc is now deprecated, and you should ise the ``var = !cmd`` syntax
instead.

IPython also allows you to expand the value of python variables when
making system calls. Any python variable or expression which you prepend
with $ will get expanded before the system call is made::

    In [1]: pyvar='Hello world' 
    In [2]: !echo "A python variable: $pyvar"  
    A python variable: Hello world

If you want the shell to actually see a literal $, you need to type it
twice::

    In [3]: !echo "A system variable: $$HOME"  
    A system variable: /home/fperez

You can pass arbitrary expressions, though you'll need to delimit them
with {} if there is ambiguity as to the extent of the expression::

    In [5]: x=10 
    In [6]: y=20 
    In [13]: !echo $x+y  
    10+y  
    In [7]: !echo ${x+y}  
    30

Even object attributes can be expanded::

    In [12]: !echo $sys.argv  
    [/home/fperez/usr/bin/ipython]


System command aliases
----------------------

The %alias magic function and the alias option in the ipythonrc
configuration file allow you to define magic functions which are in fact
system shell commands. These aliases can have parameters.

'%alias alias_name cmd' defines 'alias_name' as an alias for 'cmd'

Then, typing '%alias_name params' will execute the system command 'cmd
params' (from your underlying operating system).

You can also define aliases with parameters using %s specifiers (one per
parameter). The following example defines the %parts function as an
alias to the command 'echo first %s second %s' where each %s will be
replaced by a positional parameter to the call to %parts::

    In [1]: alias parts echo first %s second %s 
    In [2]: %parts A B 
    first A second B  
    In [3]: %parts A  
    Incorrect number of arguments: 2 expected.  
    parts is an alias to: 'echo first %s second %s'

If called with no parameters, %alias prints the table of currently
defined aliases.

The %rehash/rehashx magics allow you to load your entire $PATH as
ipython aliases. See their respective docstrings (or sec. 6.2
<#sec:magic> for further details).



Recursive reload
----------------

The dreload function does a recursive reload of a module: changes made
to the module since you imported will actually be available without
having to exit.


Verbose and colored exception traceback printouts
-------------------------------------------------

IPython provides the option to see very detailed exception tracebacks,
which can be especially useful when debugging large programs. You can
run any Python file with the %run function to benefit from these
detailed tracebacks. Furthermore, both normal and verbose tracebacks can
be colored (if your terminal supports it) which makes them much easier
to parse visually.

See the magic xmode and colors functions for details (just type %magic).

These features are basically a terminal version of Ka-Ping Yee's cgitb
module, now part of the standard Python library.



Input caching system
--------------------

IPython offers numbered prompts (In/Out) with input and output caching.
All input is saved and can be retrieved as variables (besides the usual
arrow key recall).

The following GLOBAL variables always exist (so don't overwrite them!):
_i: stores previous input. _ii: next previous. _iii: next-next previous.
_ih : a list of all input _ih[n] is the input from line n and this list
is aliased to the global variable In. If you overwrite In with a
variable of your own, you can remake the assignment to the internal list
with a simple 'In=_ih'.

Additionally, global variables named _i<n> are dynamically created (<n>
being the prompt counter), such that
_i<n> == _ih[<n>] == In[<n>].

For example, what you typed at prompt 14 is available as _i14, _ih[14]
and In[14].

This allows you to easily cut and paste multi line interactive prompts
by printing them out: they print like a clean string, without prompt
characters. You can also manipulate them like regular variables (they
are strings), modify or exec them (typing 'exec _i9' will re-execute the
contents of input prompt 9, 'exec In[9:14]+In[18]' will re-execute lines
9 through 13 and line 18).

You can also re-execute multiple lines of input easily by using the
magic %macro function (which automates the process and allows
re-execution without having to type 'exec' every time). The macro system
also allows you to re-execute previous lines which include magic
function calls (which require special processing). Type %macro? or see
sec. 6.2 <#sec:magic> for more details on the macro system.

A history function %hist allows you to see any part of your input
history by printing a range of the _i variables.

Output caching system
---------------------

For output that is returned from actions, a system similar to the input
cache exists but using _ instead of _i. Only actions that produce a
result (NOT assignments, for example) are cached. If you are familiar
with Mathematica, IPython's _ variables behave exactly like
Mathematica's % variables.

The following GLOBAL variables always exist (so don't overwrite them!):

    * [_] (a single underscore) : stores previous output, like Python's
      default interpreter.
    * [__] (two underscores): next previous.
    * [___] (three underscores): next-next previous.

Additionally, global variables named _<n> are dynamically created (<n>
being the prompt counter), such that the result of output <n> is always
available as _<n> (don't use the angle brackets, just the number, e.g.
_21).

These global variables are all stored in a global dictionary (not a
list, since it only has entries for lines which returned a result)
available under the names _oh and Out (similar to _ih and In). So the
output from line 12 can be obtained as _12, Out[12] or _oh[12]. If you
accidentally overwrite the Out variable you can recover it by typing
'Out=_oh' at the prompt.

This system obviously can potentially put heavy memory demands on your
system, since it prevents Python's garbage collector from removing any
previously computed results. You can control how many results are kept
in memory with the option (at the command line or in your ipythonrc
file) cache_size. If you set it to 0, the whole system is completely
disabled and the prompts revert to the classic '>>>' of normal Python.


Directory history
-----------------

Your history of visited directories is kept in the global list _dh, and
the magic %cd command can be used to go to any entry in that list. The
%dhist command allows you to view this history. do ``cd -<TAB`` to
conventiently view the directory history.


Automatic parentheses and quotes
--------------------------------

These features were adapted from Nathan Gray's LazyPython. They are
meant to allow less typing for common situations.


Automatic parentheses
---------------------

Callable objects (i.e. functions, methods, etc) can be invoked like this
(notice the commas between the arguments)::

    >>> callable_ob arg1, arg2, arg3

and the input will be translated to this::

    -> callable_ob(arg1, arg2, arg3)

You can force automatic parentheses by using '/' as the first character
of a line. For example::

    >>> /globals # becomes 'globals()'

Note that the '/' MUST be the first character on the line! This won't work::

    >>> print /globals # syntax error

In most cases the automatic algorithm should work, so you should rarely
need to explicitly invoke /. One notable exception is if you are trying
to call a function with a list of tuples as arguments (the parenthesis
will confuse IPython)::

    In [1]: zip (1,2,3),(4,5,6) # won't work

but this will work::

    In [2]: /zip (1,2,3),(4,5,6) 
    ---> zip ((1,2,3),(4,5,6))  
    Out[2]= [(1, 4), (2, 5), (3, 6)]

IPython tells you that it has altered your command line by displaying
the new command line preceded by ->. e.g.::

    In [18]: callable list 
    ----> callable (list)


Automatic quoting
-----------------

You can force automatic quoting of a function's arguments by using ','
or ';' as the first character of a line. For example::

    >>> ,my_function /home/me # becomes my_function("/home/me")

If you use ';' instead, the whole argument is quoted as a single string
(while ',' splits on whitespace)::

    >>> ,my_function a b c # becomes my_function("a","b","c")

    >>> ;my_function a b c # becomes my_function("a b c")

Note that the ',' or ';' MUST be the first character on the line! This
won't work::

    >>> x = ,my_function /home/me # syntax error

Customization
=============

There are 2 ways to configure IPython - the old way of using ipythonrc
files (an INI-file like format), and the new way that involves editing
your ipy_user_conf.py. Both configuration systems work at the same
time, so you can set your options in both, but if you are hesitating
about which alternative to choose, we recommend the ipy_user_conf.py
approach, as it will give you more power and control in the long
run. However, there are few options such as pylab_import_all that can
only be specified in ipythonrc file or command line - the reason for
this is that they are needed before IPython has been started up, and
the IPApi object used in ipy_user_conf.py is not yet available at that
time. A hybrid approach of specifying a few options in ipythonrc and
doing the more advanced configuration in ipy_user_conf.py is also
possible.

The ipythonrc approach
----------------------

As we've already mentioned, IPython reads a configuration file which can
be specified at the command line (-rcfile) or which by default is
assumed to be called ipythonrc. Such a file is looked for in the current
directory where IPython is started and then in your IPYTHONDIR, which
allows you to have local configuration files for specific projects. In
this section we will call these types of configuration files simply
rcfiles (short for resource configuration file).

The syntax of an rcfile is one of key-value pairs separated by
whitespace, one per line. Lines beginning with a # are ignored as
comments, but comments can not be put on lines with data (the parser is
fairly primitive). Note that these are not python files, and this is
deliberate, because it allows us to do some things which would be quite
tricky to implement if they were normal python files.

First, an rcfile can contain permanent default values for almost all
command line options (except things like -help or -Version). Sec 5.2
<node5.html#sec:cmd-line-opts> contains a description of all
command-line options. However, values you explicitly specify at the
command line override the values defined in the rcfile.

Besides command line option values, the rcfile can specify values for
certain extra special options which are not available at the command
line. These options are briefly described below.

Each of these options may appear as many times as you need it in the file.

    * [include <file1> <file2> ...:] you can name other rcfiles you want
      to recursively load up to 15 levels (don't use the <> brackets in
      your names!). This feature allows you to define a 'base' rcfile
      with general options and special-purpose files which can be loaded
      only when needed with particular configuration options. To make
      this more convenient, IPython accepts the -profile <name> option
      (abbreviates to -p <name>) which tells it to look for an rcfile
      named ipythonrc-<name>.
    * [import_mod <mod1> <mod2> ...:] import modules with 'import
      <mod1>,<mod2>,...'
    * [import_some <mod> <f1> <f2> ...:] import functions with 'from
      <mod> import <f1>,<f2>,...'
    * [import_all <mod1> <mod2> ...:] for each module listed import
      functions with ``from <mod> import *``.
    * [execute <python code>:] give any single-line python code to be
      executed.
    * [execfile <filename>:] execute the python file given with an
      'execfile(filename)' command. Username expansion is performed on
      the given names. So if you need any amount of extra fancy
      customization that won't fit in any of the above 'canned' options,
      you can just put it in a separate python file and execute it.
    * [alias <alias_def>:] this is equivalent to calling
      '%alias <alias_def>' at the IPython command line. This way, from
      within IPython you can do common system tasks without having to
      exit it or use the ! escape. IPython isn't meant to be a shell
      replacement, but it is often very useful to be able to do things
      with files while testing code. This gives you the flexibility to
      have within IPython any aliases you may be used to under your
      normal system shell.


Sample ipythonrc file
---------------------

The default rcfile, called ipythonrc and supplied in your IPYTHONDIR
directory contains lots of comments on all of these options. We
reproduce it here for reference::


    # -*- Mode: Shell-Script -*-  Not really, but shows comments correctly
    # $Id: ipythonrc 2156 2007-03-19 02:32:19Z fperez $

    #***************************************************************************
    #
    # Configuration file for IPython -- ipythonrc format
    #
    # ===========================================================
    # Deprecation note: you should look into modifying ipy_user_conf.py (located 
    # in ~/.ipython or ~/_ipython, depending on your platform) instead, it's a 
    # more flexible and robust (and better supported!) configuration
    # method.
    # ===========================================================
    #
    # The format of this file is simply one of 'key value' lines.
    # Lines containing only whitespace at the beginning and then a # are ignored
    # as comments. But comments can NOT be put on lines with data.

    # The meaning and use of each key are explained below.

    #---------------------------------------------------------------------------
    # Section: included files

    # Put one or more *config* files (with the syntax of this file) you want to
    # include. For keys with a unique value the outermost file has precedence. For
    # keys with multiple values, they all get assembled into a list which then
    # gets loaded by IPython.

    # In this file, all lists of things should simply be space-separated.

    # This allows you to build hierarchies of files which recursively load
    # lower-level services. If this is your main ~/.ipython/ipythonrc file, you
    # should only keep here basic things you always want available. Then you can
    # include it in every other special-purpose config file you create.
    include 

    #---------------------------------------------------------------------------
    # Section: startup setup

    # These are mostly things which parallel a command line option of the same
    # name.

    # Keys in this section should only appear once. If any key from this section
    # is encountered more than once, the last value remains, all earlier ones get
    # discarded.


    # Automatic calling of callable objects.  If set to 1 or 2, callable objects
    # are automatically called when invoked at the command line, even if you don't
    # type parentheses.  IPython adds the parentheses for you.  For example:

    #In [1]: str 45
    #------> str(45)
    #Out[1]: '45'

    # IPython reprints your line with '---->' indicating that it added
    # parentheses.  While this option is very convenient for interactive use, it
    # may occasionally cause problems with objects which have side-effects if
    # called unexpectedly.

    # The valid values for autocall are:

    # autocall 0 -> disabled (you can toggle it at runtime with the %autocall magic)

    # autocall 1 -> active, but do not apply if there are no arguments on the line.

    # In this mode, you get:

    #In [1]: callable
    #Out[1]: <built-in function callable>

    #In [2]: callable 'hello'
    #------> callable('hello')
    #Out[2]: False

    # 2 -> Active always.  Even if no arguments are present, the callable object
    # is called:

    #In [4]: callable
    #------> callable()

    # Note that even with autocall off, you can still use '/' at the start of a
    # line to treat the first argument on the command line as a function and add
    # parentheses to it:

    #In [8]: /str 43
    #------> str(43)
    #Out[8]: '43'

    autocall 1

    # Auto-edit syntax errors.  When you use the %edit magic in ipython to edit
    # source code (see the 'editor' variable below), it is possible that you save
    # a file with syntax errors in it.  If this variable is true, IPython will ask
    # you whether to re-open the editor immediately to correct such an error.

    autoedit_syntax 0

    # Auto-indent. IPython can recognize lines ending in ':' and indent the next
    # line, while also un-indenting automatically after 'raise' or 'return'.  

    # This feature uses the readline library, so it will honor your ~/.inputrc
    # configuration (or whatever file your INPUTRC variable points to).  Adding
    # the following lines to your .inputrc file can make indent/unindenting more
    # convenient (M-i indents, M-u unindents):

    #  $if Python
    #  "\M-i": "    "
    #  "\M-u": "\d\d\d\d"
    #  $endif

    # The feature is potentially a bit dangerous, because it can cause problems
    # with pasting of indented code (the pasted code gets re-indented on each
    # line).  But it's a huge time-saver when working interactively.  The magic
    # function %autoindent allows you to toggle it on/off at runtime.

    autoindent 1

    # Auto-magic. This gives you access to all the magic functions without having
    # to prepend them with an % sign. If you define a variable with the same name
    # as a magic function (say who=1), you will need to access the magic function
    # with % (%who in this example). However, if later you delete your variable
    # (del who), you'll recover the automagic calling form.

    # Considering that many magic functions provide a lot of shell-like
    # functionality, automagic gives you something close to a full Python+system
    # shell environment (and you can extend it further if you want).

    automagic 1

    # Size of the output cache. After this many entries are stored, the cache will
    # get flushed. Depending on the size of your intermediate calculations, you
    # may have memory problems if you make it too big, since keeping things in the
    # cache prevents Python from reclaiming the memory for old results. Experiment
    # with a value that works well for you.

    # If you choose cache_size 0 IPython will revert to python's regular >>>
    # unnumbered prompt. You will still have _, __ and ___ for your last three
    # results, but that will be it.  No dynamic _1, _2, etc. will be created. If
    # you are running on a slow machine or with very limited memory, this may
    # help.

    cache_size 1000

    # Classic mode: Setting 'classic 1' you lose many of IPython niceties,
    # but that's your choice! Classic 1 -> same as IPython -classic.
    # Note that this is _not_ the normal python interpreter, it's simply
    # IPython emulating most of the classic interpreter's behavior.
    classic 0

    # colors - Coloring option for prompts and traceback printouts.

    # Currently available schemes: NoColor, Linux, LightBG.

    # This option allows coloring the prompts and traceback printouts. This
    # requires a terminal which can properly handle color escape sequences. If you
    # are having problems with this, use the NoColor scheme (uses no color escapes
    # at all).

    # The Linux option works well in linux console type environments: dark
    # background with light fonts.

    # LightBG is similar to Linux but swaps dark/light colors to be more readable
    # in light background terminals.

    # keep uncommented only the one you want:
    colors Linux
    #colors LightBG
    #colors NoColor

    ########################
    # Note to Windows users
    #
    # Color and readline support is avaialble to Windows users via Gary Bishop's
    # readline library.  You can find Gary's tools at
    # http://sourceforge.net/projects/uncpythontools.
    # Note that his readline module requires in turn the ctypes library, available
    # at http://starship.python.net/crew/theller/ctypes.
    ########################

    # color_info: IPython can display information about objects via a set of
    # functions, and optionally can use colors for this, syntax highlighting
    # source code and various other elements. This information is passed through a
    # pager (it defaults to 'less' if $PAGER is not set). 

    # If your pager has problems, try to setting it to properly handle escapes
    # (see the less manpage for detail), or disable this option.  The magic
    # function %color_info allows you to toggle this interactively for testing.

    color_info 1

    # confirm_exit: set to 1 if you want IPython to confirm when you try to exit
    # with an EOF (Control-d in Unix, Control-Z/Enter in Windows). Note that using
    # the magic functions %Exit or %Quit you can force a direct exit, bypassing
    # any confirmation.

    confirm_exit 1

    # Use deep_reload() as a substitute for reload() by default. deep_reload() is
    # still available as dreload() and appears as a builtin.

    deep_reload 0

    # Which editor to use with the %edit command. If you leave this at 0, IPython
    # will honor your EDITOR environment variable. Since this editor is invoked on
    # the fly by ipython and is meant for editing small code snippets, you may
    # want to use a small, lightweight editor here.

    # For Emacs users, setting up your Emacs server properly as described in the
    # manual is a good idea. An alternative is to use jed, a very light editor
    # with much of the feel of Emacs (though not as powerful for heavy-duty work).

    editor 0

    # log 1 -> same as ipython -log. This automatically logs to ./ipython.log
    log 0

    # Same as ipython -Logfile YourLogfileName. 
    # Don't use with log 1 (use one or the other)
    logfile ''

    # banner 0 -> same as ipython -nobanner
    banner 1

    # messages 0 -> same as ipython -nomessages
    messages 1

    # Automatically call the pdb debugger after every uncaught exception. If you
    # are used to debugging using pdb, this puts you automatically inside of it
    # after any call (either in IPython or in code called by it) which triggers an
    # exception which goes uncaught.
    pdb 0

    # Enable the pprint module for printing. pprint tends to give a more readable
    # display (than print) for complex nested data structures.
    pprint 1

    # Prompt strings

    # Most bash-like escapes can be used to customize IPython's prompts, as well as
    # a few additional ones which are IPython-specific.  All valid prompt escapes
    # are described in detail in the Customization section of the IPython HTML/PDF
    # manual.

    # Use \# to represent the current prompt number, and quote them to protect
    # spaces.
    prompt_in1 'In [\#]: '

    # \D is replaced by as many dots as there are digits in the
    # current value of \#.
    prompt_in2 '   .\D.: '

    prompt_out 'Out[\#]: '

    # Select whether to left-pad the output prompts to match the length of the
    # input ones.  This allows you for example to use a simple '>' as an output
    # prompt, and yet have the output line up with the input.  If set to false,
    # the output prompts will be unpadded (flush left).
    prompts_pad_left 1

    # Pylab support: when ipython is started with the -pylab switch, by default it
    # executes 'from matplotlib.pylab import *'.  Set this variable to false if you
    # want to disable this behavior.

    # For details on pylab, see the matplotlib website:
    # http://matplotlib.sf.net
    pylab_import_all 1


    # quick 1 -> same as ipython -quick
    quick 0

    # Use the readline library (1) or not (0). Most users will want this on, but
    # if you experience strange problems with line management (mainly when using
    # IPython inside Emacs buffers) you may try disabling it. Not having it on
    # prevents you from getting command history with the arrow keys, searching and
    # name completion using TAB.

    readline 1

    # Screen Length: number of lines of your screen. This is used to control
    # printing of very long strings. Strings longer than this number of lines will
    # be paged with the less command instead of directly printed.

    # The default value for this is 0, which means IPython will auto-detect your
    # screen size every time it needs to print. If for some reason this isn't
    # working well (it needs curses support), specify it yourself. Otherwise don't
    # change the default.

    screen_length 0

    # Prompt separators for input and output.
    # Use \n for newline explicitly, without quotes.
    # Use 0 (like at the cmd line) to turn off a given separator.

    # The structure of prompt printing is:
    # (SeparateIn)Input....
    # (SeparateOut)Output...
    # (SeparateOut2),   # that is, no newline is printed after Out2
    # By choosing these you can organize your output any way you want.

    separate_in \n
    separate_out 0
    separate_out2 0

    # 'nosep 1' is a shorthand for '-SeparateIn 0 -SeparateOut 0 -SeparateOut2 0'.
    # Simply removes all input/output separators, overriding the choices above.
    nosep 0

    # Wildcard searches - IPython has a system for searching names using
    # shell-like wildcards; type %psearch? for details.  This variables sets
    # whether by default such searches should be case sensitive or not.  You can
    # always override the default at the system command line or the IPython
    # prompt.

    wildcards_case_sensitive 1

    # Object information: at what level of detail to display the string form of an
    # object.  If set to 0, ipython will compute the string form of any object X,
    # by calling str(X), when X? is typed.  If set to 1, str(X) will only be
    # computed when X?? is given, and if set to 2 or higher, it will never be
    # computed (there is no X??? level of detail).  This is mostly of use to
    # people who frequently manipulate objects whose string representation is
    # extremely expensive to compute.

    object_info_string_level 0

    # xmode - Exception reporting mode. 

    # Valid modes: Plain, Context and Verbose.

    # Plain: similar to python's normal traceback printing.

    # Context: prints 5 lines of context source code around each line in the
    # traceback.

    # Verbose: similar to Context, but additionally prints the variables currently
    # visible where the exception happened (shortening their strings if too
    # long). This can potentially be very slow, if you happen to have a huge data
    # structure whose string representation is complex to compute. Your computer
    # may appear to freeze for a while with cpu usage at 100%. If this occurs, you
    # can cancel the traceback with Ctrl-C (maybe hitting it more than once).

    #xmode Plain
    xmode Context
    #xmode Verbose

    # multi_line_specials: if true, allow magics, aliases and shell escapes (via
    # !cmd) to be used in multi-line input (like for loops).  For example, if you
    # have this active, the following is valid in IPython:
    #
    #In [17]: for i in range(3):
    #   ....:     mkdir $i
    #   ....:     !touch $i/hello
    #   ....:     ls -l $i

    multi_line_specials 1


    # System calls: When IPython makes system calls (e.g. via special syntax like
    # !cmd or !!cmd, or magics like %sc or %sx), it can print the command it is
    # executing to standard output, prefixed by a header string.

    system_header "IPython system call: "

    system_verbose 1

    # wxversion: request a specific wxPython version (used for -wthread)

    # Set this to the value of wxPython you want to use, but note that this
    # feature requires you to have the wxversion Python module to work.  If you
    # don't have the wxversion module (try 'import wxversion' at the prompt to
    # check) or simply want to leave the system to pick up the default, leave this
    # variable at 0.

    wxversion 0

    #---------------------------------------------------------------------------
    # Section: Readline configuration (readline is not available for MS-Windows)

    # This is done via the following options:

    # (i) readline_parse_and_bind: this option can appear as many times as you
    # want, each time defining a string to be executed via a
    # readline.parse_and_bind() command. The syntax for valid commands of this
    # kind can be found by reading the documentation for the GNU readline library,
    # as these commands are of the kind which readline accepts in its
    # configuration file.

    # The TAB key can be used to complete names at the command line in one of two
    # ways: 'complete' and 'menu-complete'. The difference is that 'complete' only
    # completes as much as possible while 'menu-complete' cycles through all
    # possible completions. Leave the one you prefer uncommented.

    readline_parse_and_bind tab: complete
    #readline_parse_and_bind tab: menu-complete

    # This binds Control-l to printing the list of all possible completions when
    # there is more than one (what 'complete' does when hitting TAB twice, or at
    # the first TAB if show-all-if-ambiguous is on)
    readline_parse_and_bind "\C-l": possible-completions

    # This forces readline to automatically print the above list when tab
    # completion is set to 'complete'. You can still get this list manually by
    # using the key bound to 'possible-completions' (Control-l by default) or by
    # hitting TAB twice. Turning this on makes the printing happen at the first
    # TAB.
    readline_parse_and_bind set show-all-if-ambiguous on

    # If you have TAB set to complete names, you can rebind any key (Control-o by
    # default) to insert a true TAB character.
    readline_parse_and_bind "\C-o": tab-insert

    # These commands allow you to indent/unindent easily, with the 4-space
    # convention of the Python coding standards.  Since IPython's internal
    # auto-indent system also uses 4 spaces, you should not change the number of
    # spaces in the code below.
    readline_parse_and_bind "\M-i": "    "
    readline_parse_and_bind "\M-o": "\d\d\d\d"
    readline_parse_and_bind "\M-I": "\d\d\d\d"

    # Bindings for incremental searches in the history. These searches use the
    # string typed so far on the command line and search anything in the previous
    # input history containing them.
    readline_parse_and_bind "\C-r": reverse-search-history
    readline_parse_and_bind "\C-s": forward-search-history

    # Bindings for completing the current line in the history of previous
    # commands. This allows you to recall any previous command by typing its first
    # few letters and hitting Control-p, bypassing all intermediate commands which
    # may be in the history (much faster than hitting up-arrow 50 times!)
    readline_parse_and_bind "\C-p": history-search-backward
    readline_parse_and_bind "\C-n": history-search-forward

    # I also like to have the same functionality on the plain arrow keys. If you'd
    # rather have the arrows use all the history (and not just match what you've
    # typed so far), comment out or delete the next two lines.
    readline_parse_and_bind "\e[A": history-search-backward
    readline_parse_and_bind "\e[B": history-search-forward

    # These are typically on by default under *nix, but not win32.
    readline_parse_and_bind "\C-k": kill-line
    readline_parse_and_bind "\C-u": unix-line-discard

    # (ii) readline_remove_delims: a string of characters to be removed from the
    # default word-delimiters list used by readline, so that completions may be
    # performed on strings which contain them.

    readline_remove_delims -/~

    # (iii) readline_merge_completions: whether to merge the result of all
    # possible completions or not.  If true, IPython will complete filenames,
    # python names and aliases and return all possible completions.  If you set it
    # to false, each completer is used at a time, and only if it doesn't return
    # any completions is the next one used.

    # The default order is: [python_matches, file_matches, alias_matches]

    readline_merge_completions 1

    # (iv) readline_omit__names: normally hitting <tab> after a '.' in a name
    # will complete all attributes of an object, including all the special methods
    # whose names start with single or double underscores (like __getitem__ or
    # __class__).

    # This variable allows you to control this completion behavior:

    # readline_omit__names 1 -> completion will omit showing any names starting
    # with two __, but it will still show names starting with one _.

    # readline_omit__names 2 -> completion will omit all names beginning with one
    # _ (which obviously means filtering out the double __ ones).

    # Even when this option is set, you can still see those names by explicitly
    # typing a _ after the period and hitting <tab>: 'name._<tab>' will always
    # complete attribute names starting with '_'.

    # This option is off by default so that new users see all attributes of any
    # objects they are dealing with.

    readline_omit__names 0

    #---------------------------------------------------------------------------
    # Section: modules to be loaded with 'import ...'

    # List, separated by spaces, the names of the modules you want to import

    # Example:
    # import_mod sys os
    # will produce internally the statements
    # import sys
    # import os

    # Each import is executed in its own try/except block, so if one module
    # fails to load the others will still be ok.

    import_mod 

    #---------------------------------------------------------------------------
    # Section: modules to import some functions from: 'from ... import ...'

    # List, one per line, the modules for which you want only to import some
    # functions. Give the module name first and then the name of functions to be
    # imported from that module.

    # Example:

    # import_some IPython.genutils timing timings
    # will produce internally the statement
    # from IPython.genutils import timing, timings

    # timing() and timings() are two IPython utilities for timing the execution of
    # your own functions, which you may find useful.  Just commment out the above
    # line if you want to test them.

    # If you have more than one modules_some line, each gets its own try/except
    # block (like modules, see above).

    import_some 

    #---------------------------------------------------------------------------
    # Section: modules to import all from : 'from ... import *'

    # List (same syntax as import_mod above) those modules for which you want to
    # import all functions. Remember, this is a potentially dangerous thing to do,
    # since it is very easy to overwrite names of things you need. Use with
    # caution.

    # Example:
    # import_all sys os
    # will produce internally the statements
    # from sys import *
    # from os import *

    # As before, each will be called in a separate try/except block.

    import_all 

    #---------------------------------------------------------------------------
    # Section: Python code to execute.

    # Put here code to be explicitly executed (keep it simple!)
    # Put one line of python code per line. All whitespace is removed (this is a
    # feature, not a bug), so don't get fancy building loops here.
    # This is just for quick convenient creation of things you want available.

    # Example:
    # execute x = 1
    # execute print 'hello world'; y = z = 'a'
    # will produce internally
    # x = 1
    # print 'hello world'; y = z = 'a'
    # and each *line* (not each statement, we don't do python syntax parsing) is
    # executed in its own try/except block.

    execute 

    # Note for the adventurous: you can use this to define your own names for the
    # magic functions, by playing some namespace tricks:

    # execute __IPYTHON__.magic_pf = __IPYTHON__.magic_profile

    # defines %pf as a new name for %profile.

    #---------------------------------------------------------------------------
    # Section: Pyhton files to load and execute.

    # Put here the full names of files you want executed with execfile(file).  If
    # you want complicated initialization, just write whatever you want in a
    # regular python file and load it from here.

    # Filenames defined here (which *must* include the extension) are searched for
    # through all of sys.path. Since IPython adds your .ipython directory to
    # sys.path, they can also be placed in your .ipython dir and will be
    # found. Otherwise (if you want to execute things not in .ipyton nor in
    # sys.path) give a full path (you can use ~, it gets expanded)

    # Example:
    # execfile file1.py ~/file2.py
    # will generate
    # execfile('file1.py')
    # execfile('_path_to_your_home/file2.py')

    # As before, each file gets its own try/except block.

    execfile

    # If you are feeling adventurous, you can even add functionality to IPython
    # through here. IPython works through a global variable called __ip which
    # exists at the time when these files are read. If you know what you are doing
    # (read the source) you can add functions to __ip in files loaded here. 

    # The file example-magic.py contains a simple but correct example. Try it:

    # execfile example-magic.py

    # Look at the examples in IPython/iplib.py for more details on how these magic
    # functions need to process their arguments.

    #---------------------------------------------------------------------------
    # Section: aliases for system shell commands

    # Here you can define your own names for system commands. The syntax is
    # similar to that of the builtin %alias function:

    # alias alias_name command_string

    # The resulting aliases are auto-generated magic functions (hence usable as
    # %alias_name)

    # For example:

    # alias myls ls -la

    # will define 'myls' as an alias for executing the system command 'ls -la'.
    # This allows you to customize IPython's environment to have the same aliases
    # you are accustomed to from your own shell.

    # You can also define aliases with parameters using %s specifiers (one per
    # parameter):

    # alias parts echo first %s second %s

    # will give you in IPython:
    # >>> %parts A B
    # first A second B

    # Use one 'alias' statement per alias you wish to define.

    # alias 

    #************************* end of file <ipythonrc> ************************


ipy_user_conf.py
----------------

There should be a simple template ipy_user_conf.py file in your
~/.ipython directory. It is a plain python module that is imported
during IPython startup, so you can do pretty much what you want there
- import modules, configure extensions, change options, define magic
commands, put variables and functions in the IPython namespace,
etc. You use the IPython extension api object, acquired by
IPython.ipapi.get() and documented in the "IPython extension API"
chapter, to interact with IPython. A sample ipy_user_conf.py is listed
below for reference::

    # Most of your config files and extensions will probably start
    # with this import

    import IPython.ipapi
    ip = IPython.ipapi.get()

    # You probably want to uncomment this if you did %upgrade -nolegacy
    # import ipy_defaults    

    import os   

    def main():   

        #ip.dbg.debugmode = True
        ip.dbg.debug_stack()

        # uncomment if you want to get ipython -p sh behaviour
        # without having to use command line switches  
        import ipy_profile_sh
        import jobctrl

        # Configure your favourite editor?
        # Good idea e.g. for %edit os.path.isfile

        #import ipy_editors

        # Choose one of these:

        #ipy_editors.scite()
        #ipy_editors.scite('c:/opt/scite/scite.exe')
        #ipy_editors.komodo()
        #ipy_editors.idle()
        # ... or many others, try 'ipy_editors??' after import to see them

        # Or roll your own:
        #ipy_editors.install_editor("c:/opt/jed +$line $file")


        o = ip.options
        # An example on how to set options
        #o.autocall = 1
        o.system_verbose = 0

        #import_all("os sys")
        #execf('~/_ipython/ns.py')


        # -- prompt
        # A different, more compact set of prompts from the default ones, that
        # always show your current location in the filesystem:

        #o.prompt_in1 = r'\C_LightBlue[\C_LightCyan\Y2\C_LightBlue]\C_Normal\n\C_Green|\#>'
        #o.prompt_in2 = r'.\D: '
        #o.prompt_out = r'[\#] '

        # Try one of these color settings if you can't read the text easily
        # autoexec is a list of IPython commands to execute on startup
        #o.autoexec.append('%colors LightBG')
        #o.autoexec.append('%colors NoColor')
        o.autoexec.append('%colors Linux')


    # some config helper functions you can use 
    def import_all(modules):
        """ Usage: import_all("os sys") """ 
        for m in modules.split():
            ip.ex("from %s import *" % m)

    def execf(fname):
        """ Execute a file in user namespace """
        ip.ex('execfile("%s")' % os.path.expanduser(fname))

    main()



Fine-tuning your prompt
-----------------------

IPython's prompts can be customized using a syntax similar to that of
the bash shell. Many of bash's escapes are supported, as well as a few
additional ones. We list them below::

    \#
        the prompt/history count number. This escape is automatically
        wrapped in the coloring codes for the currently active color scheme. 
    \N
        the 'naked' prompt/history count number: this is just the number
        itself, without any coloring applied to it. This lets you produce
        numbered prompts with your own colors. 
    \D
        the prompt/history count, with the actual digits replaced by dots.
        Used mainly in continuation prompts (prompt_in2) 
    \w
        the current working directory 
    \W
        the basename of current working directory 
    \Xn
        where $n=0\ldots5.$ The current working directory, with $HOME
        replaced by ~, and filtered out to contain only $n$ path elements 
    \Yn
        Similar to \Xn, but with the $n+1$ element included if it is ~ (this
        is similar to the behavior of the %cn escapes in tcsh) 
    \u
        the username of the current user 
    \$
        if the effective UID is 0, a #, otherwise a $ 
    \h
        the hostname up to the first '.' 
    \H
        the hostname 
    \n
        a newline 
    \r
        a carriage return 
    \v
        IPython version string 

In addition to these, ANSI color escapes can be insterted into the
prompts, as \C_ColorName. The list of valid color names is: Black, Blue,
Brown, Cyan, DarkGray, Green, LightBlue, LightCyan, LightGray,
LightGreen, LightPurple, LightRed, NoColor, Normal, Purple, Red, White,
Yellow.

Finally, IPython supports the evaluation of arbitrary expressions in
your prompt string. The prompt strings are evaluated through the syntax
of PEP 215, but basically you can use $x.y to expand the value of x.y,
and for more complicated expressions you can use braces: ${foo()+x} will
call function foo and add to it the value of x, before putting the
result into your prompt. For example, using
prompt_in1 '${commands.getoutput("uptime")}\nIn [\#]: ' 
will print the result of the uptime command on each prompt (assuming the
commands module has been imported in your ipythonrc file).


      Prompt examples

The following options in an ipythonrc file will give you IPython's
default prompts::

    prompt_in1 'In [\#]:' 
    prompt_in2 '   .\D.:' 
    prompt_out 'Out[\#]:'

which look like this::

    In [1]: 1+2 
    Out[1]: 3

    In [2]: for i in (1,2,3): 
       ...:    print i, 
       ...: 
    1 2 3

These will give you a very colorful prompt with path information::

    #prompt_in1 '\C_Red\u\C_Blue[\C_Cyan\Y1\C_Blue]\C_LightGreen\#>' 
    prompt_in2 ' ..\D>' 
    prompt_out '<\#>'

which look like this::

    fperez[~/ipython]1> 1+2 
                    <1> 3 
    fperez[~/ipython]2> for i in (1,2,3): 
                   ...>     print i, 
                   ...> 
    1 2 3



IPython profiles
----------------

As we already mentioned, IPython supports the -profile command-line
option (see sec. 5.2 <node5.html#sec:cmd-line-opts>). A profile is
nothing more than a particular configuration file like your basic
ipythonrc one, but with particular customizations for a specific
purpose. When you start IPython with 'ipython -profile <name>', it
assumes that in your IPYTHONDIR there is a file called ipythonrc-<name>,
and loads it instead of the normal ipythonrc.

This system allows you to maintain multiple configurations which load
modules, set options, define functions, etc. suitable for different
tasks and activate them in a very simple manner. In order to avoid
having to repeat all of your basic options (common things that don't
change such as your color preferences, for example), any profile can
include another configuration file. The most common way to use profiles
is then to have each one include your basic ipythonrc file as a starting
point, and then add further customizations.

In sections 11 <node11.html#sec:syntax-extensions> and 16
<node16.html#sec:Gnuplot> we discuss some particular profiles which come
as part of the standard IPython distribution. You may also look in your
IPYTHONDIR directory, any file whose name begins with ipythonrc- is a
profile. You can use those as examples for further customizations to
suit your own needs.

IPython as your default Python environment
==========================================

Python honors the environment variable PYTHONSTARTUP and will execute at
startup the file referenced by this variable. If you put at the end of
this file the following two lines of code::

    import IPython 
    IPython.Shell.IPShell().mainloop(sys_exit=1)

then IPython will be your working environment anytime you start Python.
The sys_exit=1 is needed to have IPython issue a call to sys.exit() when
it finishes, otherwise you'll be back at the normal Python '>>>'
prompt^4 <footnode.html#foot2368>.

This is probably useful to developers who manage multiple Python
versions and don't want to have correspondingly multiple IPython
versions. Note that in this mode, there is no way to pass IPython any
command-line options, as those are trapped first by Python itself.

Embedding IPython
=================

It is possible to start an IPython instance inside your own Python
programs. This allows you to evaluate dynamically the state of your
code, operate with your variables, analyze them, etc. Note however that
any changes you make to values while in the shell do not propagate back
to the running code, so it is safe to modify your values because you
won't break your code in bizarre ways by doing so.

This feature allows you to easily have a fully functional python
environment for doing object introspection anywhere in your code with a
simple function call. In some cases a simple print statement is enough,
but if you need to do more detailed analysis of a code fragment this
feature can be very valuable.

It can also be useful in scientific computing situations where it is
common to need to do some automatic, computationally intensive part and
then stop to look at data, plots, etc^5 <footnode.html#foot3206>.
Opening an IPython instance will give you full access to your data and
functions, and you can resume program execution once you are done with
the interactive part (perhaps to stop again later, as many times as
needed).

The following code snippet is the bare minimum you need to include in
your Python programs for this to work (detailed examples follow later)::

    from IPython.Shell import IPShellEmbed

    ipshell = IPShellEmbed()

    ipshell() # this call anywhere in your program will start IPython

You can run embedded instances even in code which is itself being run at
the IPython interactive prompt with '%run <filename>'. Since it's easy
to get lost as to where you are (in your top-level IPython or in your
embedded one), it's a good idea in such cases to set the in/out prompts
to something different for the embedded instances. The code examples
below illustrate this.

You can also have multiple IPython instances in your program and open
them separately, for example with different options for data
presentation. If you close and open the same instance multiple times,
its prompt counters simply continue from each execution to the next.

Please look at the docstrings in the Shell.py module for more details on
the use of this system.

The following sample file illustrating how to use the embedding
functionality is provided in the examples directory as example-embed.py.
It should be fairly self-explanatory::


    #!/usr/bin/env python

    """An example of how to embed an IPython shell into a running program.

    Please see the documentation in the IPython.Shell module for more details.

    The accompanying file example-embed-short.py has quick code fragments for
    embedding which you can cut and paste in your code once you understand how
    things work.

    The code in this file is deliberately extra-verbose, meant for learning."""

    # The basics to get you going:

    # IPython sets the __IPYTHON__ variable so you can know if you have nested
    # copies running.

    # Try running this code both at the command line and from inside IPython (with
    # %run example-embed.py)
    try:
        __IPYTHON__
    except NameError:
        nested = 0
        args = ['']
    else:
        print "Running nested copies of IPython."
        print "The prompts for the nested copy have been modified"
        nested = 1
        # what the embedded instance will see as sys.argv:
        args = ['-pi1','In <\\#>: ','-pi2','   .\\D.: ',
                '-po','Out<\\#>: ','-nosep']

    # First import the embeddable shell class
    from IPython.Shell import IPShellEmbed

    # Now create an instance of the embeddable shell. The first argument is a
    # string with options exactly as you would type them if you were starting
    # IPython at the system command line. Any parameters you want to define for
    # configuration can thus be specified here.
    ipshell = IPShellEmbed(args,
                           banner = 'Dropping into IPython',
                           exit_msg = 'Leaving Interpreter, back to program.')

    # Make a second instance, you can have as many as you want.
    if nested:
        args[1] = 'In2<\\#>'
    else:
        args = ['-pi1','In2<\\#>: ','-pi2','   .\\D.: ',
                '-po','Out<\\#>: ','-nosep']
    ipshell2 = IPShellEmbed(args,banner = 'Second IPython instance.')

    print '\nHello. This is printed from the main controller program.\n'

    # You can then call ipshell() anywhere you need it (with an optional
    # message):
    ipshell('***Called from top level. '
            'Hit Ctrl-D to exit interpreter and continue program.\n'
            'Note that if you use %kill_embedded, you can fully deactivate\n'
            'This embedded instance so it will never turn on again')

    print '\nBack in caller program, moving along...\n'

    #---------------------------------------------------------------------------
    # More details:

    # IPShellEmbed instances don't print the standard system banner and
    # messages. The IPython banner (which actually may contain initialization
    # messages) is available as <instance>.IP.BANNER in case you want it.

    # IPShellEmbed instances print the following information everytime they
    # start:

    # - A global startup banner.

    # - A call-specific header string, which you can use to indicate where in the
    # execution flow the shell is starting.

    # They also print an exit message every time they exit.

    # Both the startup banner and the exit message default to None, and can be set
    # either at the instance constructor or at any other time with the
    # set_banner() and set_exit_msg() methods.

    # The shell instance can be also put in 'dummy' mode globally or on a per-call
    # basis. This gives you fine control for debugging without having to change
    # code all over the place.

    # The code below illustrates all this.


    # This is how the global banner and exit_msg can be reset at any point
    ipshell.set_banner('Entering interpreter - New Banner')
    ipshell.set_exit_msg('Leaving interpreter - New exit_msg')

    def foo(m):
        s = 'spam'
        ipshell('***In foo(). Try @whos, or print s or m:')
        print 'foo says m = ',m

    def bar(n):
        s = 'eggs'
        ipshell('***In bar(). Try @whos, or print s or n:')
        print 'bar says n = ',n

    # Some calls to the above functions which will trigger IPython:
    print 'Main program calling foo("eggs")\n'
    foo('eggs')

    # The shell can be put in 'dummy' mode where calls to it silently return. This
    # allows you, for example, to globally turn off debugging for a program with a
    # single call.
    ipshell.set_dummy_mode(1)
    print '\nTrying to call IPython which is now "dummy":'
    ipshell()
    print 'Nothing happened...'
    # The global 'dummy' mode can still be overridden for a single call
    print '\nOverriding dummy mode manually:'
    ipshell(dummy=0)

    # Reactivate the IPython shell
    ipshell.set_dummy_mode(0)

    print 'You can even have multiple embedded instances:'
    ipshell2()

    print '\nMain program calling bar("spam")\n'
    bar('spam')

    print 'Main program finished. Bye!'

    #********************** End of file <example-embed.py> ***********************

Once you understand how the system functions, you can use the following
code fragments in your programs which are ready for cut and paste::


    """Quick code snippets for embedding IPython into other programs.

    See example-embed.py for full details, this file has the bare minimum code for
    cut and paste use once you understand how to use the system."""

    #---------------------------------------------------------------------------
    # This code loads IPython but modifies a few things if it detects it's running
    # embedded in another IPython session (helps avoid confusion)

    try:
        __IPYTHON__
    except NameError:
        argv = ['']
        banner = exit_msg = ''
    else:
        # Command-line options for IPython (a list like sys.argv)
        argv = ['-pi1','In <\\#>:','-pi2','   .\\D.:','-po','Out<\\#>:']
        banner = '*** Nested interpreter ***'
        exit_msg = '*** Back in main IPython ***'

    # First import the embeddable shell class
    from IPython.Shell import IPShellEmbed
    # Now create the IPython shell instance. Put ipshell() anywhere in your code
    # where you want it to open.
    ipshell = IPShellEmbed(argv,banner=banner,exit_msg=exit_msg)

    #---------------------------------------------------------------------------
    # This code will load an embeddable IPython shell always with no changes for
    # nested embededings.

    from IPython.Shell import IPShellEmbed
    ipshell = IPShellEmbed()
    # Now ipshell() will open IPython anywhere in the code.

    #---------------------------------------------------------------------------
    # This code loads an embeddable shell only if NOT running inside
    # IPython. Inside IPython, the embeddable shell variable ipshell is just a
    # dummy function.

    try:
        __IPYTHON__
    except NameError:
        from IPython.Shell import IPShellEmbed
        ipshell = IPShellEmbed()
        # Now ipshell() will open IPython anywhere in the code
    else:
        # Define a dummy ipshell() so the same code doesn't crash inside an
        # interactive IPython
        def ipshell(): pass

    #******************* End of file <example-embed-short.py> ********************

Using the Python debugger (pdb)
===============================

Running entire programs via pdb
-------------------------------

pdb, the Python debugger, is a powerful interactive debugger which
allows you to step through code, set breakpoints, watch variables, etc.
IPython makes it very easy to start any script under the control of pdb,
regardless of whether you have wrapped it into a 'main()' function or
not. For this, simply type '%run -d myscript' at an IPython prompt. See
the %run command's documentation (via '%run?' or in Sec. 6.2
<node6.html#sec:magic>) for more details, including how to control where
pdb will stop execution first.

For more information on the use of the pdb debugger, read the included
pdb.doc file (part of the standard Python distribution). On a stock
Linux system it is located at /usr/lib/python2.3/pdb.doc, but the
easiest way to read it is by using the help() function of the pdb module
as follows (in an IPython prompt):

In [1]: import pdb 
In [2]: pdb.help()

This will load the pdb.doc document in a file viewer for you automatically.


Automatic invocation of pdb on exceptions
-----------------------------------------

IPython, if started with the -pdb option (or if the option is set in
your rc file) can call the Python pdb debugger every time your code
triggers an uncaught exception^6 <footnode.html#foot2403>. This feature
can also be toggled at any time with the %pdb magic command. This can be
extremely useful in order to find the origin of subtle bugs, because pdb
opens up at the point in your code which triggered the exception, and
while your program is at this point 'dead', all the data is still
available and you can walk up and down the stack frame and understand
the origin of the problem.

Furthermore, you can use these debugging facilities both with the
embedded IPython mode and without IPython at all. For an embedded shell
(see sec. 9 <node9.html#sec:embed>), simply call the constructor with
'-pdb' in the argument string and automatically pdb will be called if an
uncaught exception is triggered by your code.

For stand-alone use of the feature in your programs which do not use
IPython at all, put the following lines toward the top of your 'main'
routine::

    import sys,IPython.ultraTB  
    sys.excepthook = IPython.ultraTB.FormattedTB(mode='Verbose',
    color_scheme='Linux', call_pdb=1)

The mode keyword can be either 'Verbose' or 'Plain', giving either very
detailed or normal tracebacks respectively. The color_scheme keyword can
be one of 'NoColor', 'Linux' (default) or 'LightBG'. These are the same
options which can be set in IPython with -colors and -xmode.

This will give any of your programs detailed, colored tracebacks with
automatic invocation of pdb.


Extensions for syntax processing
================================

This isn't for the faint of heart, because the potential for breaking
things is quite high. But it can be a very powerful and useful feature.
In a nutshell, you can redefine the way IPython processes the user input
line to accept new, special extensions to the syntax without needing to
change any of IPython's own code.

In the IPython/Extensions directory you will find some examples
supplied, which we will briefly describe now. These can be used 'as is'
(and both provide very useful functionality), or you can use them as a
starting point for writing your own extensions.


Pasting of code starting with '>>> ' or '... '
----------------------------------------------

In the python tutorial it is common to find code examples which have
been taken from real python sessions. The problem with those is that all
the lines begin with either '>>> ' or '... ', which makes it impossible
to paste them all at once. One must instead do a line by line manual
copying, carefully removing the leading extraneous characters.

This extension identifies those starting characters and removes them
from the input automatically, so that one can paste multi-line examples
directly into IPython, saving a lot of time. Please look at the file
InterpreterPasteInput.py in the IPython/Extensions directory for details
on how this is done.

IPython comes with a special profile enabling this feature, called
tutorial. Simply start IPython via 'ipython -p tutorial' and the feature
will be available. In a normal IPython session you can activate the
feature by importing the corresponding module with:
In [1]: import IPython.Extensions.InterpreterPasteInput

The following is a 'screenshot' of how things work when this extension
is on, copying an example from the standard tutorial::

    IPython profile: tutorial 

    *** Pasting of code with ">>>" or "..." has been enabled. 

    In [1]: >>> def fib2(n): # return Fibonacci series up to n 
       ...: ...     """Return a list containing the Fibonacci series up to
    n.""" 
       ...: ...     result = [] 
       ...: ...     a, b = 0, 1 
       ...: ...     while b < n: 
       ...: ...         result.append(b)    # see below 
       ...: ...         a, b = b, a+b 
       ...: ...     return result 
       ...: 

    In [2]: fib2(10) 
    Out[2]: [1, 1, 2, 3, 5, 8]

Note that as currently written, this extension does not recognize
IPython's prompts for pasting. Those are more complicated, since the
user can change them very easily, they involve numbers and can vary in
length. One could however extract all the relevant information from the
IPython instance and build an appropriate regular expression. This is
left as an exercise for the reader.


Input of physical quantities with units
---------------------------------------

The module PhysicalQInput allows a simplified form of input for physical
quantities with units. This file is meant to be used in conjunction with
the PhysicalQInteractive module (in the same directory) and
Physics.PhysicalQuantities from Konrad Hinsen's ScientificPython
(http://dirac.cnrs-orleans.fr/ScientificPython/).

The Physics.PhysicalQuantities module defines PhysicalQuantity objects,
but these must be declared as instances of a class. For example, to
define v as a velocity of 3 m/s, normally you would write::

    In [1]: v = PhysicalQuantity(3,'m/s')

Using the PhysicalQ_Input extension this can be input instead as: 
In [1]: v = 3 m/s
which is much more convenient for interactive use (even though it is
blatantly invalid Python syntax).

The physics profile supplied with IPython (enabled via 'ipython -p
physics') uses these extensions, which you can also activate with:

from math import * # math MUST be imported BEFORE PhysicalQInteractive 
from IPython.Extensions.PhysicalQInteractive import * 
import IPython.Extensions.PhysicalQInput


IPython as a system shell - the 'Sh' profile
============================================

The 'sh' profile optimizes IPython for system shell usage. Apart from
certain job control functionality that is present in unix (ctrl+z does
"suspend"), the sh profile should provide you with most of the
functionality you use daily in system shell, and more. Invoke IPython
in 'sh' profile by doing 'ipython -p sh', or (in win32) by launching
the "pysh" shortcut in start menu.

If you want to use the features of sh profile as your defaults (which
might be a good idea if you use other profiles a lot of the time but
still want the convenience of sh profile), add ``import ipy_profile_sh``
to your ~/.ipython/ipy_user_conf.py.

The 'sh' profile is different from the default profile in that:

 * Prompt shows the current directory
 * Spacing between prompts and input is more compact (no padding with
   empty lines). The startup banner is more compact as well.
 * System commands are directly available (in alias table) without
   requesting %rehashx - however, if you install new programs along
   your PATH, you might want to run %rehashx to update the persistent
   alias table
 * Macros are stored in raw format by default. That is, instead of
   '_ip.system("cat foo"), the macro will contain text 'cat foo')
 * Autocall is in full mode
 * Calling "up" does "cd .."

The 'sh' profile is different from the now-obsolete (and unavailable)
'pysh' profile in that:

 * '$$var = command' and '$var = command' syntax is not supported
 * anymore. Use 'var = !command' instead (incidentally, this is
 * available in all IPython profiles). Note that !!command *will*
 * work.

Aliases
-------

All of your $PATH has been loaded as IPython aliases, so you should be
able to type any normal system command and have it executed. See
%alias?  and %unalias? for details on the alias facilities. See also
%rehashx? for details on the mechanism used to load $PATH.


Directory management
--------------------

Since each command passed by ipython to the underlying system is executed
in a subshell which exits immediately, you can NOT use !cd to navigate
the filesystem.

IPython provides its own builtin '%cd' magic command to move in the
filesystem (the % is not required with automagic on). It also maintains
a list of visited directories (use %dhist to see it) and allows direct
switching to any of them. Type 'cd?' for more details.

%pushd, %popd and %dirs are provided for directory stack handling.


Enabled extensions
------------------

Some extensions, listed below, are enabled as default in this profile.

envpersist
++++++++++

%env can be used to "remember" environment variable manipulations. Examples::

	%env - Show all environment variables
	%env VISUAL=jed  - set VISUAL to jed
	%env PATH+=;/foo - append ;foo to PATH
	%env PATH+=;/bar - also append ;bar to PATH
	%env PATH-=/wbin; - prepend /wbin; to PATH
	%env -d VISUAL   - forget VISUAL persistent val
	%env -p          - print all persistent env modifications

ipy_which
+++++++++

%which magic command. Like 'which' in unix, but knows about ipython aliases.

Example::

 [C:/ipython]|14> %which st
 st -> start .
 [C:/ipython]|15> %which d
 d -> dir /w /og /on
 [C:/ipython]|16> %which cp
 cp -> cp
   == c:\bin\cp.exe
 c:\bin\cp.exe

ipy_app_completers
++++++++++++++++++

Custom tab completers for some apps like svn, hg, bzr, apt-get. Try 'apt-get install <TAB>' in debian/ubuntu.

ipy_rehashdir
+++++++++++++

Allows you to add system command aliases for commands that are not along your path. Let's say that you just installed Putty and want to be able to invoke it without adding it to path, you can create the alias for it with rehashdir::

 [~]|22> cd c:/opt/PuTTY/
 [c:opt/PuTTY]|23> rehashdir .
              <23> ['pageant', 'plink', 'pscp', 'psftp', 'putty', 'puttygen', 'unins000']

Now, you can execute any of those commams directly::

 [c:opt/PuTTY]|24> cd
 [~]|25> putty

(the putty window opens).

If you want to store the alias so that it will always be available, do '%store putty'. If you want to %store all these aliases persistently, just do it in a for loop::

 [~]|27> for a in _23:
    |..>     %store $a
    |..>
    |..>
 Alias stored: pageant (0, 'c:\\opt\\PuTTY\\pageant.exe')
 Alias stored: plink (0, 'c:\\opt\\PuTTY\\plink.exe')
 Alias stored: pscp (0, 'c:\\opt\\PuTTY\\pscp.exe')
 Alias stored: psftp (0, 'c:\\opt\\PuTTY\\psftp.exe')
 ...

mglob
+++++

Provide the magic function %mglob, which makes it easier (than the 'find' command) to collect (possibly recursive) file lists. Examples::

 [c:/ipython]|9> mglob *.py
 [c:/ipython]|10> mglob *.py rec:*.txt
 [c:/ipython]|19> workfiles = %mglob !.svn/ !.hg/ !*_Data/ !*.bak rec:.

Note that the first 2 calls will put the file list in result history (_, _9, _10), and the last one will assign it to 'workfiles'.


Prompt customization
--------------------

The sh profile uses the following prompt configurations::

    o.prompt_in1= r'\C_LightBlue[\C_LightCyan\Y2\C_LightBlue]\C_Green|\#>'
    o.prompt_in2= r'\C_Green|\C_LightGreen\D\C_Green>'

You can change the prompt configuration to your liking by editing
ipy_user_conf.py.  

String lists
============

String lists (IPython.genutils.SList) are handy way to process output
from system commands. They are produced by ``var = !cmd`` syntax.

First, we acquire the output of 'ls -l'::

    [Q:doc/examples]|2> lines = !ls -l
     ==
    ['total 23',
     '-rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py',
     '-rw-rw-rw- 1 ville None 1927 Sep 30  2006 example-embed-short.py',
     '-rwxrwxrwx 1 ville None 4606 Sep  1 17:15 example-embed.py',
     '-rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py',
     '-rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py',
     '-rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py',
     '-rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc']

Now, let's take a look at the contents of 'lines' (the first number is
the list element number)::

    [Q:doc/examples]|3> lines
                    <3> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:

    0: total 23
    1: -rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py
    2: -rw-rw-rw- 1 ville None 1927 Sep 30  2006 example-embed-short.py
    3: -rwxrwxrwx 1 ville None 4606 Sep  1 17:15 example-embed.py
    4: -rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py
    5: -rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py
    6: -rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py
    7: -rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc

Now, let's filter out the 'embed' lines::

    [Q:doc/examples]|4> l2 = lines.grep('embed',prune=1)
    [Q:doc/examples]|5> l2
                    <5> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:

    0: total 23
    1: -rw-rw-rw- 1 ville None 1163 Sep 30  2006 example-demo.py
    2: -rwxrwxrwx 1 ville None 1017 Sep 30  2006 example-gnuplot.py
    3: -rwxrwxrwx 1 ville None  339 Jun 11 18:01 extension.py
    4: -rwxrwxrwx 1 ville None  113 Dec 20  2006 seteditor.py
    5: -rwxrwxrwx 1 ville None  245 Dec 12  2006 seteditor.pyc

Now, we want strings having just file names and permissions::

    [Q:doc/examples]|6> l2.fields(8,0)
                    <6> SList (.p, .n, .l, .s, .grep(), .fields() available). Value:

    0: total
    1: example-demo.py -rw-rw-rw-
    2: example-gnuplot.py -rwxrwxrwx
    3: extension.py -rwxrwxrwx
    4: seteditor.py -rwxrwxrwx
    5: seteditor.pyc -rwxrwxrwx

Note how the line with 'total' does not raise IndexError.

If you want to split these (yielding lists), call fields() without
arguments::

    [Q:doc/examples]|7> _.fields()
                    <7>
    [['total'],
     ['example-demo.py', '-rw-rw-rw-'],
     ['example-gnuplot.py', '-rwxrwxrwx'],
     ['extension.py', '-rwxrwxrwx'],
     ['seteditor.py', '-rwxrwxrwx'],
     ['seteditor.pyc', '-rwxrwxrwx']]

If you want to pass these separated with spaces to a command (typical
for lists if files), use the .s property::


    [Q:doc/examples]|13> files = l2.fields(8).s
    [Q:doc/examples]|14> files
                    <14> 'example-demo.py example-gnuplot.py extension.py seteditor.py seteditor.pyc'
    [Q:doc/examples]|15> ls $files
    example-demo.py  example-gnuplot.py  extension.py  seteditor.py  seteditor.pyc

SLists are inherited from normal python lists, so every list method is
available::

    [Q:doc/examples]|21> lines.append('hey')


Real world example: remove all files outside version control
------------------------------------------------------------

First, capture output of "hg status"::

    [Q:/ipython]|28> out = !hg status
     ==
    ['M IPython\\Extensions\\ipy_kitcfg.py',
     'M IPython\\Extensions\\ipy_rehashdir.py',
    ...
     '? build\\lib\\IPython\\Debugger.py',
     '? build\\lib\\IPython\\Extensions\\InterpreterExec.py',
     '? build\\lib\\IPython\\Extensions\\InterpreterPasteInput.py',
    ...

(lines starting with ? are not under version control).

::

    [Q:/ipython]|35> junk = out.grep(r'^\?').fields(1)
    [Q:/ipython]|36> junk
                <36> SList (.p, .n, .l, .s, .grep(), .fields() availab
    ...
    10: build\bdist.win32\winexe\temp\_ctypes.py
    11: build\bdist.win32\winexe\temp\_hashlib.py
    12: build\bdist.win32\winexe\temp\_socket.py

Now we can just remove these files by doing 'rm $junk.s'. 

The .s, .n, .p properties
-------------------------

The '.s' property returns one string where lines are separated by
single space (for convenient passing to system commands). The '.n'
property return one string where the lines are separated by '\n'
(i.e. the original output of the function). If the items in string
list are file names, '.p' can be used to get a list of "path" objects
for convenient file manipulation.


Threading support
=================

WARNING: The threading support is still somewhat experimental, and it
has only seen reasonable testing under Linux. Threaded code is
particularly tricky to debug, and it tends to show extremely
platform-dependent behavior. Since I only have access to Linux machines,
I will have to rely on user's experiences and assistance for this area
of IPython to improve under other platforms.

IPython, via the -gthread , -qthread, -q4thread and -wthread options
(described in Sec. 5.1 <node5.html#sec:threading-opts>), can run in
multithreaded mode to support pyGTK, Qt3, Qt4 and WXPython applications
respectively. These GUI toolkits need to control the python main loop of
execution, so under a normal Python interpreter, starting a pyGTK, Qt3,
Qt4 or WXPython application will immediately freeze the shell.

IPython, with one of these options (you can only use one at a time),
separates the graphical loop and IPython's code execution run into
different threads. This allows you to test interactively (with %run, for
example) your GUI code without blocking.

A nice mini-tutorial on using IPython along with the Qt Designer
application is available at the SciPy wiki:
http://www.scipy.org/Cookbook/Matplotlib/Qt_with_IPython_and_Designer.


Tk issues
---------

As indicated in Sec. 5.1 <node5.html#sec:threading-opts>, a special -tk
option is provided to try and allow Tk graphical applications to coexist
interactively with WX, Qt or GTK ones. Whether this works at all,
however, is very platform and configuration dependent. Please experiment
with simple test cases before committing to using this combination of Tk
and GTK/Qt/WX threading in a production environment.


I/O pitfalls
------------

Be mindful that the Python interpreter switches between threads every
$N$ bytecodes, where the default value as of Python 2.3 is $N=100.$ This
value can be read by using the sys.getcheckinterval() function, and it
can be reset via sys.setcheckinterval(N). This switching of threads can
cause subtly confusing effects if one of your threads is doing file I/O.
In text mode, most systems only flush file buffers when they encounter a
'\n'. An instruction as simple as:: 

  print >> filehandle, ''hello world''

actually consists of several bytecodes, so it is possible that the
newline does not reach your file before the next thread switch.
Similarly, if you are writing to a file in binary mode, the file won't
be flushed until the buffer fills, and your other thread may see
apparently truncated files.

For this reason, if you are using IPython's thread support and have (for
example) a GUI application which will read data generated by files
written to from the IPython thread, the safest approach is to open all
of your files in unbuffered mode (the third argument to the file/open
function is the buffering value)::

  filehandle = open(filename,mode,0)

This is obviously a brute force way of avoiding race conditions with the
file buffering. If you want to do it cleanly, and you have a resource
which is being shared by the interactive IPython loop and your GUI
thread, you should really handle it with thread locking and
syncrhonization properties. The Python documentation discusses these.

Interactive demos with IPython
==============================

IPython ships with a basic system for running scripts interactively in
sections, useful when presenting code to audiences. A few tags embedded
in comments (so that the script remains valid Python code) divide a file
into separate blocks, and the demo can be run one block at a time, with
IPython printing (with syntax highlighting) the block before executing
it, and returning to the interactive prompt after each block. The
interactive namespace is updated after each block is run with the
contents of the demo's namespace.

This allows you to show a piece of code, run it and then execute
interactively commands based on the variables just created. Once you
want to continue, you simply execute the next block of the demo. The
following listing shows the markup necessary for dividing a script into
sections for execution as a demo::


    """A simple interactive demo to illustrate the use of IPython's Demo class.

    Any python script can be run as a demo, but that does little more than showing
    it on-screen, syntax-highlighted in one shot.  If you add a little simple
    markup, you can stop at specified intervals and return to the ipython prompt,
    resuming execution later.
    """

    print 'Hello, welcome to an interactive IPython demo.'
    print 'Executing this block should require confirmation before proceeding,'
    print 'unless auto_all has been set to true in the demo object'

    # The mark below defines a block boundary, which is a point where IPython will
    # stop execution and return to the interactive prompt.
    # Note that in actual interactive execution, 
    # <demo> --- stop ---

    x = 1
    y = 2

    # <demo> --- stop ---

    # the mark below makes this block as silent
    # <demo> silent

    print 'This is a silent block, which gets executed but not printed.'

    # <demo> --- stop ---
    # <demo> auto
    print 'This is an automatic block.'
    print 'It is executed without asking for confirmation, but printed.'
    z = x+y

    print 'z=',x

    # <demo> --- stop ---
    # This is just another normal block.
    print 'z is now:', z

    print 'bye!'

In order to run a file as a demo, you must first make a Demo object out
of it. If the file is named myscript.py, the following code will make a
demo::

    from IPython.demo import Demo

    mydemo = Demo('myscript.py')

This creates the mydemo object, whose blocks you run one at a time by
simply calling the object with no arguments. If you have autocall active
in IPython (the default), all you need to do is type::

    mydemo 

and IPython will call it, executing each block. Demo objects can be
restarted, you can move forward or back skipping blocks, re-execute the
last block, etc. Simply use the Tab key on a demo object to see its
methods, and call '?' on them to see their docstrings for more usage
details. In addition, the demo module itself contains a comprehensive
docstring, which you can access via::

    from IPython import demo

    demo?

Limitations: It is important to note that these demos are limited to
fairly simple uses. In particular, you can not put division marks in
indented code (loops, if statements, function definitions, etc.)
Supporting something like this would basically require tracking the
internal execution state of the Python interpreter, so only top-level
divisions are allowed. If you want to be able to open an IPython
instance at an arbitrary point in a program, you can use IPython's
embedding facilities, described in detail in Sec. 9


Plotting with matplotlib
========================

The matplotlib library (http://matplotlib.sourceforge.net
http://matplotlib.sourceforge.net) provides high quality 2D plotting for
Python. Matplotlib can produce plots on screen using a variety of GUI
toolkits, including Tk, GTK and WXPython. It also provides a number of
commands useful for scientific computing, all with a syntax compatible
with that of the popular Matlab program.

IPython accepts the special option -pylab (Sec. 5.2
<node5.html#sec:cmd-line-opts>). This configures it to support
matplotlib, honoring the settings in the .matplotlibrc file. IPython
will detect the user's choice of matplotlib GUI backend, and
automatically select the proper threading model to prevent blocking. It
also sets matplotlib in interactive mode and modifies %run slightly, so
that any matplotlib-based script can be executed using %run and the
final show() command does not block the interactive shell.

The -pylab option must be given first in order for IPython to configure
its threading mode. However, you can still issue other options
afterwards. This allows you to have a matplotlib-based environment
customized with additional modules using the standard IPython profile
mechanism (Sec. 7.3 <node7.html#sec:profiles>): ''ipython -pylab -p
myprofile'' will load the profile defined in ipythonrc-myprofile after
configuring matplotlib.

IPython Extension Api
=====================

IPython api (defined in IPython/ipapi.py) is the public api that
should be used for

 * Configuration of user preferences (.ipython/ipy_user_conf.py)
 * Creating new profiles (.ipython/ipy_profile_PROFILENAME.py)
 * Writing extensions 

Note that by using the extension api for configuration (editing
ipy_user_conf.py instead of ipythonrc), you get better validity checks
and get richer functionality - for example, you can import an
extension and call functions in it to configure it for your purposes.

For an example extension (the 'sh' profile), see
IPython/Extensions/ipy_profile_sh.py.

For the last word on what's available, see the source code of
IPython/ipapi.py.


Getting started
---------------

If you want to define an extension, create a normal python module that
can be imported. The module will access IPython functionality through
the 'ip' object defined below.

If you are creating a new profile (e.g. foobar), name the module as
'ipy_profile_foobar.py' and put it in your ~/.ipython directory. Then,
when you start ipython with the '-p foobar' argument, the module is
automatically imported on ipython startup.

If you are just doing some per-user configuration, you can either 

 * Put the commands directly into ipy_user_conf.py. 

 * Create a new module with your customization code and import *that*
   module in ipy_user_conf.py. This is preferable to the first approach,
   because now you can reuse and distribute your customization code.

Getting a handle to the api
---------------------------

Put this in the start of your module::

    #!python
    import IPython.ipapi
    ip = IPython.ipapi.get()

The 'ip' object will then be used for accessing IPython
functionality. 'ip' will mean this api object in all the following
code snippets. The same 'ip' that we just acquired is always
accessible in interactive IPython sessions by the name _ip - play with
it like this::

    [~\_ipython]|81> a = 10
    [~\_ipython]|82> _ip.e
    _ip.ev           _ip.ex           _ip.expose_magic
    [~\_ipython]|82> _ip.ev('a+13')
                <82> 23

The _ip object is also used in some examples in this document - it can
be substituted by 'ip' in non-interactive use.

Changing options
----------------

The ip object has 'options' attribute that can be used te get/set
configuration options (just as in the ipythonrc file)::

    o = ip.options
    o.autocall = 2
    o.automagic = 1

Executing statements in IPython namespace with 'ex' and 'ev'
------------------------------------------------------------

Often, you want to e.g. import some module or define something that
should be visible in IPython namespace. Use ``ip.ev`` to
*evaluate* (calculate the value of) expression and ``ip.ex`` to
'''execute''' a statement::

    # path module will be visible to the interactive session
    ip.ex("from path import path" )

    # define a handy function 'up' that changes the working directory

    ip.ex('import os')
    ip.ex("def up(): os.chdir('..')")


    # _i2 has the input history entry #2, print its value in uppercase.
    print ip.ev('_i2.upper()')

Accessing the IPython namespace
-------------------------------

ip.user_ns attribute has a dictionary containing the IPython global
namespace (the namespace visible in the interactive session).

::

    [~\_ipython]|84> tauno = 555
    [~\_ipython]|85> _ip.user_ns['tauno']
                <85> 555

Defining new magic commands
---------------------------

The following example defines a new magic command, %impall. What the
command does should be obvious::

    def doimp(self, arg):
        ip = self.api
        ip.ex("import %s; reload(%s); from %s import *" % (
        arg,arg,arg)
        )

    ip.expose_magic('impall', doimp)

Things to observe in this example:

 * Define a function that implements the magic command using the 
   ipapi methods defined in this document
 * The first argument of the function is 'self', i.e. the 
   interpreter object. It shouldn't be used directly. however. 
   The interpreter object is probably *not* going to remain stable 
   through IPython versions.
 * Access the ipapi through 'self.api' instead of the global 'ip' object.
 * All the text following the magic command on the command line is 
   contained in the second argument
 * Expose the magic by ip.expose_magic()


Calling magic functions and system commands
-------------------------------------------

Use ip.magic() to execute a magic function, and ip.system() to execute
a system command::

    # go to a bookmark
    ip.magic('%cd -b relfiles')

    # execute 'ls -F' system command. Interchangeable with os.system('ls'), really.
    ip.system('ls -F')

Launching IPython instance from normal python code
--------------------------------------------------

Use ipapi.launch_new_instance() with an argument that specifies the
namespace to use. This can be useful for trivially embedding IPython
into your program. Here's an example of normal python program test.py
('''without''' an existing IPython session) that launches an IPython
interpreter and regains control when the interpreter is exited::

    [ipython]|1> cat test.py
    my_ns = dict(
        kissa = 15,
        koira = 16)
    import IPython.ipapi
    print "launching IPython instance"
    IPython.ipapi.launch_new_instance(my_ns)
    print "Exited IPython instance!"
    print "New vals:",my_ns['kissa'], my_ns['koira']

And here's what it looks like when run (note how we don't start it
from an ipython session)::

    Q:\ipython>python test.py
    launching IPython instance
    Py 2.5 (r25:51908, Sep 19 2006, 09:52:17) [MSC v.1310 32 bit (Intel)] IPy 0.7.3b3.r1975
    [ipython]|1> kissa = 444
    [ipython]|2> koira = 555
    [ipython]|3> Exit
    Exited IPython instance!
    New vals: 444 555

Accessing unexposed functionality
---------------------------------

There are still many features that are not exposed via the ipapi. If
you can't avoid using them, you can use the functionality in
InteractiveShell object (central IPython session class, defined in
iplib.py) through ip.IP.

For example::

    [~]|7> _ip.IP.expand_aliases('np','myfile.py')
       <7> 'c:/opt/Notepad++/notepad++.exe myfile.py'
    [~]|8>

Still, it's preferable that if you encounter such a feature, contact
the IPython team and request that the functionality be exposed in a
future version of IPython. Things not in ipapi are more likely to
change over time.

Provided extensions
===================

You can see the list of available extensions (and profiles) by doing
``import ipy_<TAB>``. Some extensions don't have the ``ipy_`` prefix in
module name, so you may need to see the contents of IPython/Extensions
folder to see what's available.

You can see a brief documentation of an extension by looking at the
module docstring::

    [c:p/ipython_main]|190> import ipy_fsops
    [c:p/ipython_main]|191> ipy_fsops?

    ...

    Docstring:
        File system operations

    Contains: Simple variants of normal unix shell commands (icp, imv, irm,
    imkdir, igrep).

You can also install your own extensions - the recommended way is to
just copy the module to ~/.ipython. Extensions are typically enabled
by just importing them (e.g. in ipy_user_conf.py), but some extensions
require additional steps, for example::

    [c:p]|192> import ipy_traits_completer
    [c:p]|193> ipy_traits_completer.activate()    

Note that extensions, even if provided in the stock IPython
installation, are not guaranteed to have the same requirements as the
rest of IPython - an extension may require external libraries or a
newer version of Python than what IPython officially requires. An
extension may also be under a more restrictive license than IPython
(e.g. ipy_bzr is under GPL).

Just for reference, the list of bundled extensions at the time of
writing is below:

astyle.py clearcmd.py envpersist.py ext_rescapture.py ibrowse.py
igrid.py InterpreterExec.py InterpreterPasteInput.py ipipe.py
ipy_app_completers.py ipy_autoreload.py ipy_bzr.py ipy_completers.py
ipy_constants.py ipy_defaults.py ipy_editors.py ipy_exportdb.py
ipy_extutil.py ipy_fsops.py ipy_gnuglobal.py ipy_kitcfg.py
ipy_legacy.py ipy_leo.py ipy_p4.py ipy_profile_doctest.py
ipy_profile_none.py ipy_profile_scipy.py ipy_profile_sh.py
ipy_profile_zope.py ipy_pydb.py ipy_rehashdir.py ipy_render.py
ipy_server.py ipy_signals.py ipy_stock_completers.py
ipy_system_conf.py ipy_traits_completer.py ipy_vimserver.py
ipy_which.py ipy_workdir.py jobctrl.py ledit.py numeric_formats.py
PhysicalQInput.py PhysicalQInteractive.py pickleshare.py
pspersistence.py win32clip.py __init__.py

Reporting bugs
==============

Automatic crash reports
-----------------------

Ideally, IPython itself shouldn't crash. It will catch exceptions
produced by you, but bugs in its internals will still crash it.

In such a situation, IPython will leave a file named
IPython_crash_report.txt in your IPYTHONDIR directory (that way if
crashes happen several times it won't litter many directories, the
post-mortem file is always located in the same place and new occurrences
just overwrite the previous one). If you can mail this file to the
developers (see sec. 20 <node20.html#sec:credits> for names and
addresses), it will help us a lot in understanding the cause of the
problem and fixing it sooner.


The bug tracker
---------------

IPython also has an online bug-tracker, located at
http://projects.scipy.org/ipython/ipython/report/1. In addition to
mailing the developers, it would be a good idea to file a bug report
here. This will ensure that the issue is properly followed to
conclusion. To report new bugs you will have to register first.

You can also use this bug tracker to file feature requests.

Brief history
=============


Origins
-------

The current IPython system grew out of the following three projects:

    * [ipython] by Fernando Pérez. I was working on adding
      Mathematica-type prompts and a flexible configuration system
      (something better than $PYTHONSTARTUP) to the standard Python
      interactive interpreter.
    * [IPP] by Janko Hauser. Very well organized, great usability. Had
      an old help system. IPP was used as the 'container' code into
      which I added the functionality from ipython and LazyPython.
    * [LazyPython] by Nathan Gray. Simple but very powerful. The quick
      syntax (auto parens, auto quotes) and verbose/colored tracebacks
      were all taken from here.

When I found out (see sec. 20 <node20.html#figgins>) about IPP and
LazyPython I tried to join all three into a unified system. I thought
this could provide a very nice working environment, both for regular
programming and scientific computing: shell-like features, IDL/Matlab
numerics, Mathematica-type prompt history and great object introspection
and help facilities. I think it worked reasonably well, though it was a
lot more work than I had initially planned.


Current status
--------------

The above listed features work, and quite well for the most part. But
until a major internal restructuring is done (see below), only bug
fixing will be done, no other features will be added (unless very minor
and well localized in the cleaner parts of the code).

IPython consists of some 18000 lines of pure python code, of which
roughly two thirds is reasonably clean. The rest is, messy code which
needs a massive restructuring before any further major work is done.
Even the messy code is fairly well documented though, and most of the
problems in the (non-existent) class design are well pointed to by a
PyChecker run. So the rewriting work isn't that bad, it will just be
time-consuming.


Future
------

See the separate new_design document for details. Ultimately, I would
like to see IPython become part of the standard Python distribution as a
'big brother with batteries' to the standard Python interactive
interpreter. But that will never happen with the current state of the
code, so all contributions are welcome.

License
=======

IPython is released under the terms of the BSD license, whose general
form can be found at:
http://www.opensource.org/licenses/bsd-license.php. The full text of the
IPython license is reproduced below::

    IPython is released under a BSD-type license.

    Copyright (c) 2001, 2002, 2003, 2004 Fernando Perez
    <[e-mail]>.

    Copyright (c) 2001 Janko Hauser <[e-mail]> and  
    Nathaniel Gray <[e-mail]>.

    All rights reserved.

    Redistribution and use in source and binary forms, with or without
    modification, are permitted provided that the following conditions
    are met:

    a. Redistributions of source code must retain the above copyright
    notice, this list of conditions and the following disclaimer.

    b. Redistributions in binary form must reproduce the above copyright
    notice, this list of conditions and the following disclaimer in the
    documentation and/or other materials provided with the distribution.

    c. Neither the name of the copyright holders nor the names of any
    contributors to this software may be used to endorse or promote
    products derived from this software without specific prior written
    permission.

    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
    "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
    LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
    FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
    REGENTS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
    INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
    BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
    LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
    CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
    LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
    ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
    POSSIBILITY OF SUCH DAMAGE. 

Individual authors are the holders of the copyright for their code and
are listed in each file.

Some files (DPyGetOpt.py, for example) may be licensed under different
conditions. Ultimately each file indicates clearly the conditions under
which its author/authors have decided to publish the code.

Versions of IPython up to and including 0.6.3 were released under the
GNU Lesser General Public License (LGPL), available at
http://www.gnu.org/copyleft/lesser.html.

Credits
=======

IPython is mainly developed by Fernando Pérez
<[e-mail]>, but the project was born from mixing in
Fernando's code with the IPP project by Janko Hauser
<jhauser-AT-zscout.de> and LazyPython by Nathan Gray
<n8gray-AT-caltech.edu>. For all IPython-related requests, please
contact Fernando.

As of early 2006, the following developers have joined the core team:

    * [Robert Kern] <rkern-AT-enthought.com>: co-mentored the 2005
      Google Summer of Code project to develop python interactive
      notebooks (XML documents) and graphical interface. This project
      was awarded to the students Tzanko Matev <tsanko-AT-gmail.com> and
      Toni Alatalo <antont-AT-an.org>
    * [Brian Granger] <bgranger-AT-scu.edu>: extending IPython to allow
      support for interactive parallel computing.
    * [Ville Vainio] <vivainio-AT-gmail.com>: Ville is the new
      maintainer for the main trunk of IPython after version 0.7.1.

User or development help should be requested via the IPython mailing lists:

*User list:*
    http://scipy.net/mailman/listinfo/ipython-user 
*Developer's list:*
    http://scipy.net/mailman/listinfo/ipython-dev 

The IPython project is also very grateful to^7 <footnode.html#foot2913>:

Bill Bumgarner <bbum-AT-friday.com>: for providing the DPyGetOpt module
which gives very powerful and convenient handling of command-line
options (light years ahead of what Python 2.1.1's getopt module does).

Ka-Ping Yee <ping-AT-lfw.org>: for providing the Itpl module for
convenient and powerful string interpolation with a much nicer syntax
than formatting through the '%' operator.

Arnd Baecker <baecker-AT-physik.tu-dresden.de>: for his many very useful
suggestions and comments, and lots of help with testing and
documentation checking. Many of IPython's newer features are a result of
discussions with him (bugs are still my fault, not his).

Obviously Guido van Rossum and the whole Python development team, that
goes without saying.

IPython's website is generously hosted at http://ipython.scipy.orgby
Enthought (http://www.enthought.com). I am very grateful to them and all
of the SciPy team for their contribution.

Fernando would also like to thank Stephen Figgins <fig-AT-monitor.net>,
an O'Reilly Python editor. His Oct/11/2001 article about IPP and
LazyPython, was what got this project started. You can read it at:
http://www.onlamp.com/pub/a/python/2001/10/11/pythonnews.html.

And last but not least, all the kind IPython users who have emailed new
code, bug reports, fixes, comments and ideas. A brief list follows,
please let me know if I have ommitted your name by accident:

    * [Jack Moffit] <jack-AT-xiph.org> Bug fixes, including the infamous
      color problem. This bug alone caused many lost hours and
      frustration, many thanks to him for the fix. I've always been a
      fan of Ogg & friends, now I have one more reason to like these folks.
      Jack is also contributing with Debian packaging and many other
      things.
    * [Alexander Schmolck] <a.schmolck-AT-gmx.net> Emacs work, bug
      reports, bug fixes, ideas, lots more. The ipython.el mode for
      (X)Emacs is Alex's code, providing full support for IPython under
      (X)Emacs.
    * [Andrea Riciputi] <andrea.riciputi-AT-libero.it> Mac OSX
      information, Fink package management.
    * [Gary Bishop] <gb-AT-cs.unc.edu> Bug reports, and patches to work
      around the exception handling idiosyncracies of WxPython. Readline
      and color support for Windows.
    * [Jeffrey Collins] <Jeff.Collins-AT-vexcel.com> Bug reports. Much
      improved readline support, including fixes for Python 2.3.
    * [Dryice Liu] <dryice-AT-liu.com.cn> FreeBSD port.
    * [Mike Heeter] <korora-AT-SDF.LONESTAR.ORG>
    * [Christopher Hart] <hart-AT-caltech.edu> PDB integration.
    * [Milan Zamazal] <pdm-AT-zamazal.org> Emacs info.
    * [Philip Hisley] <compsys-AT-starpower.net>
    * [Holger Krekel] <pyth-AT-devel.trillke.net> Tab completion, lots
      more.
    * [Robin Siebler] <robinsiebler-AT-starband.net>
    * [Ralf Ahlbrink] <ralf_ahlbrink-AT-web.de>
    * [Thorsten Kampe] <thorsten-AT-thorstenkampe.de>
    * [Fredrik Kant] <fredrik.kant-AT-front.com> Windows setup.
    * [Syver Enstad] <syver-en-AT-online.no> Windows setup.
    * [Richard] <rxe-AT-renre-europe.com> Global embedding.
    * [Hayden Callow] <h.callow-AT-elec.canterbury.ac.nz> Gnuplot.py 1.6
      compatibility.
    * [Leonardo Santagada] <retype-AT-terra.com.br> Fixes for Windows
      installation.
    * [Christopher Armstrong] <radix-AT-twistedmatrix.com> Bugfixes.
    * [Francois Pinard] <pinard-AT-iro.umontreal.ca> Code and
      documentation fixes.
    * [Cory Dodt] <cdodt-AT-fcoe.k12.ca.us> Bug reports and Windows
      ideas. Patches for Windows installer.
    * [Olivier Aubert] <oaubert-AT-bat710.univ-lyon1.fr> New magics.
    * [King C. Shu] <kingshu-AT-myrealbox.com> Autoindent patch.
    * [Chris Drexler] <chris-AT-ac-drexler.de> Readline packages for
      Win32/CygWin.
    * [Gustavo Cordova Avila] <gcordova-AT-sismex.com> EvalDict code for
      nice, lightweight string interpolation.
    * [Kasper Souren] <Kasper.Souren-AT-ircam.fr> Bug reports, ideas.
    * [Gever Tulley] <gever-AT-helium.com> Code contributions.
    * [Ralf Schmitt] <ralf-AT-brainbot.com> Bug reports & fixes.
    * [Oliver Sander] <osander-AT-gmx.de> Bug reports.
    * [Rod Holland] <rhh-AT-structurelabs.com> Bug reports and fixes to
      logging module.
    * [Daniel 'Dang' Griffith] <pythondev-dang-AT-lazytwinacres.net>
      Fixes, enhancement suggestions for system shell use.
    * [Viktor Ransmayr] <viktor.ransmayr-AT-t-online.de> Tests and
      reports on Windows installation issues. Contributed a true Windows
      binary installer.
    * [Mike Salib] <msalib-AT-mit.edu> Help fixing a subtle bug related
      to traceback printing.
    * [W.J. van der Laan] <gnufnork-AT-hetdigitalegat.nl> Bash-like
      prompt specials.
    * [Antoon Pardon] <Antoon.Pardon-AT-rece.vub.ac.be> Critical fix for
      the multithreaded IPython.
    * [John Hunter] <jdhunter-AT-nitace.bsd.uchicago.edu> Matplotlib
      author, helped with all the development of support for matplotlib
      in IPyhton, including making necessary changes to matplotlib itself.
    * [Matthew Arnison] <maffew-AT-cat.org.au> Bug reports, '%run -d' idea.
    * [Prabhu Ramachandran] <prabhu_r-AT-users.sourceforge.net> Help
      with (X)Emacs support, threading patches, ideas...
    * [Norbert Tretkowski] <tretkowski-AT-inittab.de> help with Debian
      packaging and distribution.
    * [George Sakkis] <gsakkis-AT-eden.rutgers.edu> New matcher for
      tab-completing named arguments of user-defined functions.
    * [Jörgen Stenarson] <jorgen.stenarson-AT-bostream.nu> Wildcard
      support implementation for searching namespaces.
    * [Vivian De Smedt] <vivian-AT-vdesmedt.com> Debugger enhancements,
      so that when pdb is activated from within IPython, coloring, tab
      completion and other features continue to work seamlessly.
    * [Scott Tsai] <scottt958-AT-yahoo.com.tw> Support for automatic
      editor invocation on syntax errors (see
      http://www.scipy.net/roundup/ipython/issue36).
    * [Alexander Belchenko] <bialix-AT-ukr.net> Improvements for win32
      paging system.
    * [Will Maier] <willmaier-AT-ml1.net> Official OpenBSD port.