Many fixes to the documentation prior to release 0.9.

- Moved unused files to an 'attic' directory in the doc sources to
prevent sphinx warnings.

- Fixed all HTML sphinx warnings for missing targets, duplicates,
missing files, etc.  Currently on my system the html builds with zero
warnings, I still get two small ones on the PDF.

- Many other small fixes to the docs in various places.

docs/source/conf.py

@@ -1,177 +1,186 b''
 # -*- coding: utf-8 -*-
 #
-# IPython documentation build configuration file, created by
-# sphinx-quickstart on Thu May  8 16:45:02 2008.
+# IPython documentation build configuration file.
 
 # NOTE: This file has been edited manually from the auto-generated one from
 # sphinx.  Do NOT delete and re-generate.  If any changes from sphinx are
 # needed, generate a scratch one and merge by hand any new fields needed.
 
 #
 # This file is execfile()d with the current directory set to its containing dir.
 #
 # The contents of this file are pickled, so don't put values in the namespace
 # that aren't pickleable (module imports are okay, they're removed automatically).
 #
 # All configuration values have a default value; values that are commented out
 # serve to show the default value.
 
 import sys, os
 
 # If your extensions are in another directory, add it here. If the directory
 # is relative to the documentation root, use os.path.abspath to make it
 # absolute, like shown here.
-#sys.path.append(os.path.abspath('some/directory'))
+sys.path.append(os.path.abspath('../sphinxext'))
+
+# Import support for ipython console session syntax highlighting (lives
+# in the sphinxext directory defined above)
+import ipython_console_highlighting
 
 # We load the ipython release info into a dict by explicit execution
 iprelease = {}
 execfile('../../IPython/Release.py',iprelease)
 
 # General configuration
 # ---------------------
 
 # Add any Sphinx extension module names here, as strings. They can be extensions
 # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
-#extensions = []
+extensions = ['sphinx.ext.autodoc',
+              'inheritance_diagram', 'only_directives', 'plot_directive',
+              'ipython_console_highlighting', 
+              ]
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 
 # The suffix of source filenames.
 source_suffix = '.txt'
 
 # The master toctree document.
 master_doc = 'index'
 
 # General substitutions.
 project = 'IPython'
 copyright = '2008, The IPython Development Team'
 
 # The default replacements for |version| and |release|, also used in various
 # other places throughout the built documents.
 #
 # The full version, including alpha/beta/rc tags.
 release = iprelease['version']
 # The short X.Y version.
 version = '.'.join(release.split('.',2)[:2])
 
 
 # There are two options for replacing |today|: either, you set today to some
 # non-false value, then it is used:
 #today = ''
 # Else, today_fmt is used as the format for a strftime call.
 today_fmt = '%B %d, %Y'
 
 # List of documents that shouldn't be included in the build.
 #unused_docs = []
 
 # List of directories, relative to source directories, that shouldn't be searched
 # for source files.
-#exclude_dirs = []
+exclude_dirs = ['attic']
 
 # If true, '()' will be appended to :func: etc. cross-reference text.
 #add_function_parentheses = True
 
 # If true, the current module name will be prepended to all description
 # unit titles (such as .. function::).
 #add_module_names = True
 
 # If true, sectionauthor and moduleauthor directives will be shown in the
 # output. They are ignored by default.
 #show_authors = False
 
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = 'sphinx'
 
 
 # Options for HTML output
 # -----------------------
 
 # The style sheet to use for HTML and HTML Help pages. A file of that name
 # must exist either in Sphinx' static/ path, or in one of the custom paths
 # given in html_static_path.
 html_style = 'default.css'
 
 # The name for this set of Sphinx documents.  If None, it defaults to
 # "<project> v<release> documentation".
 #html_title = None
 
 # The name of an image file (within the static path) to place at the top of
 # the sidebar.
 #html_logo = None
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
 html_static_path = ['_static']
 
 # If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
 # using the given strftime format.
 html_last_updated_fmt = '%b %d, %Y'
 
 # If true, SmartyPants will be used to convert quotes and dashes to
 # typographically correct entities.
 #html_use_smartypants = True
 
 # Custom sidebar templates, maps document names to template names.
 #html_sidebars = {}
 
 # Additional templates that should be rendered to pages, maps page names to
 # template names.
 #html_additional_pages = {}
 
 # If false, no module index is generated.
 #html_use_modindex = True
 
 # If true, the reST sources are included in the HTML build as _sources/<name>.
 #html_copy_source = True
 
 # If true, an OpenSearch description file will be output, and all pages will
 # contain a <link> tag referring to it.  The value of this option must be the
 # base URL from which the finished HTML is served.
 #html_use_opensearch = ''
 
 # If nonempty, this is the file name suffix for HTML files (e.g. ".xhtml").
 #html_file_suffix = ''
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = 'IPythondoc'
+htmlhelp_basename = 'ipythondoc'
 
 
 # Options for LaTeX output
 # ------------------------
 
 # The paper size ('letter' or 'a4').
 latex_paper_size = 'letter'
 
 # The font size ('10pt', '11pt' or '12pt').
 latex_font_size = '11pt'
 
 # Grouping the document tree into LaTeX files. List of tuples
 # (source start file, target name, title, author, document class [howto/manual]).
 
 latex_documents = [ ('index', 'ipython.tex', 'IPython Documentation',
                      ur"""The IPython Development Team""",
                      'manual'),
                     ]
 
 # The name of an image file (relative to this directory) to place at the top of
 # the title page.
 #latex_logo = None
 
 # For "manual" documents, if this is true, then toplevel headings are parts,
 # not chapters.
 #latex_use_parts = False
 
 # Additional stuff for the LaTeX preamble.
 #latex_preamble = ''
 
 # Documents to append as an appendix to all manuals.
 #latex_appendices = []
 
 # If false, no module index is generated.
 #latex_use_modindex = True
 
 
-# Cleanup: delete release info to avoid pickling errors from sphinx
+# Cleanup
+# -------
+# delete release info to avoid pickling errors from sphinx
+
 del iprelease

docs/source/config/customization.txt

@@ -1,284 +1,286 b''
 .. _customization:
 
 ========================
 Customization of IPython
 ========================
 
 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.
 
+.. _ipythonrc:
+
 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
-`command line options`_ contains a description of all command-line
-options. However, values you explicitly specify at the command line
-override the values defined in the rcfile.
+First, an rcfile can contain permanent default values for almost all command
+line options (except things like -help or -Version). :ref:`This section
+<command_line_options>` 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.
 
 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()
 
 .. _Prompts:
 
 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
 
 
 .. _Profiles:
 
 IPython profiles
 ================
 
-As we already mentioned, IPython supports the -profile command-line
-option (see sec. `command line options`_). 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> or
-ipy_profile_<name>.py, and loads it instead of the normal ipythonrc.
+As we already mentioned, IPython supports the -profile command-line option (see
+:ref:`here <command_line_options>`).  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> or ipy_profile_<name>.py, 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.
  No newline at end of file

docs/source/config/initial_config.txt

@@ -1,243 +1,244 b''
 .. _initial config:
 
 =========================================
 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 `ipythonrc`_
-section. This file is very commented and has many variables you can
-change to suit your taste, you can find more details in
-Sec. customization_. Here we discuss the basic things you will want to
-make sure things are working properly from the beginning.
+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
+:ref:`here <ipythonrc>`. This file is very commented and has many variables you
+can change to suit your taste, you can find more details :ref:`here
+<customization>`. Here we discuss the basic things you will want to make sure
+things are working properly from the beginning.
 
 
-.. _Accessing help:
+.. _accessing_help:
 
 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 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
+:file:`/usr/share/doc/python-doc/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
+    about.html  dist/  icons/      lib/           python2.5.devhelp.gz  whatsnew/
+    acks.html   doc/   index.html  mac/           ref/
+    api/        ext/   inst/       modindex.html  tut/
 
 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 the emacs_ section for more details on
       using IPython with (X)Emacs.
     * A Windows (XP/2k) command prompt with pyreadline_.
     * 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.
 
+.. _pyreadline: https://code.launchpad.net/pyreadline
+      
 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. `dynamic object
-information`_. 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
+IPython has a set of special functions for studying the objects you are working
+with, discussed in detail :ref:`here <dynamic_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.
 
 .. _emacs:
 
 (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.
 
 You can customize the arguments passed to the IPython instance at startup by
 setting the ``py-python-command-args`` variable.  For example, to start always
 in ``pylab`` mode with hardcoded light-background colors, you can use::
 
     (setq py-python-command-args '("-pylab" "-colors" "LightBG"))
 
 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).

docs/source/development/development.txt

@@ -1,397 +1,402 b''
 .. _development:
 
 ==================================
 IPython development guidelines
 ==================================
 
 .. contents::
 
 
 Overview
 ========
 
 IPython is the next generation of IPython.  It is named such for two reasons:
 
 - Eventually, IPython will become IPython version 1.0.
 - This new code base needs to be able to co-exist with the existing IPython until
   it is a full replacement for it.  Thus we needed a different name.  We couldn't
   use ``ipython`` (lowercase) as some files systems are case insensitive.
 
 There are two, no three, main goals of the IPython effort:
 
 1. Clean up the existing codebase and write lots of tests.
 2. Separate the core functionality of IPython from the terminal to enable IPython
    to be used from within a variety of GUI applications.
 3. Implement a system for interactive parallel computing.
 
 While the third goal may seem a bit unrelated to the main focus of IPython, it turns
 out that the technologies required for this goal are nearly identical with those
 required for goal two. This is the main reason the interactive parallel computing
 capabilities are being put into IPython proper. Currently the third of these goals is
 furthest along.
 
 This document describes IPython from the perspective of developers.  
 
 
 Project organization
 ====================
 
 Subpackages
 -----------
 
 IPython is organized into semi self-contained subpackages.  Each of the subpackages will have its own:
 
 - **Dependencies**.  One of the most important things to keep in mind in
   partitioning code amongst subpackages, is that they should be used to cleanly
   encapsulate dependencies.  
 - **Tests**.  Each subpackage shoud have its own ``tests`` subdirectory that
   contains all of the tests for that package.  For information about writing tests
   for IPython, see the `Testing System`_ section of this document.
 - **Configuration**.  Each subpackage should have its own ``config`` subdirectory
   that contains the configuration information for the components of the 
   subpackage.  For information about how the IPython configuration system
   works, see the `Configuration System`_ section of this document.
 - **Scripts**.  Each subpackage should have its own ``scripts`` subdirectory that
   contains all of the command line scripts associated with the subpackage.
 
 Installation and dependencies
 -----------------------------
    
 IPython will not use `setuptools`_ for installation. Instead, we will use standard
 ``setup.py`` scripts that use `distutils`_. While there are a number a extremely nice
 features that `setuptools`_ has (like namespace packages), the current implementation
 of `setuptools`_ has performance problems, particularly on shared file systems. In
 particular, when Python packages are installed on NSF file systems, import times
 become much too long (up towards 10 seconds). 
 
 Because IPython is being used extensively in the context of high performance
 computing, where performance is critical but shared file systems are common, we feel
 these performance hits are not acceptable. Thus, until the performance problems
 associated with `setuptools`_ are addressed, we will stick with plain `distutils`_. We
 are hopeful that these problems will be addressed and that we will eventually begin
 using `setuptools`_. Because of this, we are trying to organize IPython in a way that
 will make the eventual transition to `setuptools`_ as painless as possible.
 
 Because we will be using `distutils`_, there will be no method for automatically installing dependencies.  Instead, we are following the approach of `Matplotlib`_ which can be summarized as follows:
 
 - Distinguish between required and optional dependencies.  However, the required
   dependencies for IPython should be only the Python standard library.
 - Upon installation check to see which optional dependencies are present and tell
   the user which parts of IPython need which optional dependencies.
 
 It is absolutely critical that each subpackage of IPython has a clearly specified set
 of dependencies and that dependencies are not carelessly inherited from other IPython
 subpackages. Furthermore, tests that have certain dependencies should not fail if
 those dependencies are not present. Instead they should be skipped and print a
 message.
 
 .. _setuptools: http://peak.telecommunity.com/DevCenter/setuptools
 .. _distutils: http://docs.python.org/lib/module-distutils.html
 .. _Matplotlib: http://matplotlib.sourceforge.net/
 
 Specific subpackages
 --------------------
 
 ``core``
     This is the core functionality of IPython that is independent of the
     terminal, network and GUIs.  Most of the code that is in the current
     IPython trunk will be refactored, cleaned up and moved here.
 
 ``kernel``
     The enables the IPython core to be expose to a the network.  This is
     also where all of the parallel computing capabilities are to be found.
     
 ``config``
     The configuration package used by IPython.
 
 ``frontends``
     The various frontends for IPython.  A frontend is the end-user application
     that exposes the capabilities of IPython to the user.  The most basic frontend
     will simply be a terminal based application that looks just like today 's 
     IPython.  Other frontends will likely be more powerful and based on GUI toolkits.
 
 ``notebook``
     An application that allows users to work with IPython notebooks.
 
 ``tools``
     This is where general utilities go.
 
 
 Version control
 ===============
 
 In the past, IPython development has been done using `Subversion`__.  Recently, we made the transition to using `Bazaar`__ and `Launchpad`__.  This makes it much easier for people
 to contribute code to IPython.  Here is a sketch of how to use Bazaar for IPython
 development.  First, you should install Bazaar.  After you have done that, make
 sure that it is working by getting the latest main branch of IPython::
 
     $ bzr branch lp:ipython
 
 Now you can create a new branch for you to do your work in::
 
     $ bzr branch ipython ipython-mybranch
 
 The typical work cycle in this branch will be to make changes in `ipython-mybranch`
 and then commit those changes using the commit command::
 
     $ ...do work in ipython-mybranch...
     $ bzr ci -m "the commit message goes here"
 
 Please note that since we now don't use an old-style linear ChangeLog
 (that tends to cause problems with distributed version control
 systems), you should ensure that your log messages are reasonably
 detailed.  Use a docstring-like approach in the commit messages
 (including the second line being left *blank*)::
 
   Single line summary of  changes being committed.
 
   - more details when warranted ...
   - including crediting outside contributors if they sent the
     code/bug/idea!
 
 If we couple this with a policy of making single commits for each
 reasonably atomic change, the bzr log should give an excellent view of
 the project, and the `--short` log option becomes a nice summary.
 
 While working with this branch, it is a good idea to merge in changes that have been
 made upstream in the parent branch.  This can be done by doing::
 
     $ bzr pull
     
 If this command shows that the branches have diverged, then you should do a merge
 instead::
 
     $ bzr merge lp:ipython
 
 If you want others to be able to see your branch, you can create an account with
 launchpad and push the branch to your own workspace::
 
     $ bzr push bzr+ssh://<me>@bazaar.launchpad.net/~<me>/+junk/ipython-mybranch
 
 Finally, once the work in your branch is done, you can merge your changes back into
 the `ipython` branch by using merge::
 
     $ cd ipython
     $ merge ../ipython-mybranch
     [resolve any conflicts]
     $ bzr ci -m "Fixing that bug"
     $ bzr push
 
 But this will require you to have write permissions to the `ipython` branch.  It you don't
 you can tell one of the IPython devs about your branch and they can do the merge for you.
 
 More information about Bazaar workflows can be found `here`__.
 
 .. __: http://subversion.tigris.org/
 .. __: http://bazaar-vcs.org/
 .. __: http://www.launchpad.net/ipython
 .. __: http://doc.bazaar-vcs.org/bzr.dev/en/user-guide/index.html
 
 Documentation
 =============
 
 Standalone documentation
 ------------------------
 
 All standalone documentation should be written in plain text (``.txt``) files using
 `reStructuredText`_ for markup and formatting. All such documentation should be placed
 in the top level directory ``docs`` of the IPython source tree. Or, when appropriate,
 a suitably named subdirectory should be used. The documentation in this location will
 serve as the main source for IPython documentation and all existing documentation
 should be converted to this format.
 
 In the future, the text files in the ``docs`` directory will be used to generate all
 forms of documentation for IPython. This include documentation on the IPython website
 as well as *pdf* documentation.
 
 .. _reStructuredText: http://docutils.sourceforge.net/rst.html
 
 Docstring format
 ----------------
 
 Good docstrings are very important. All new code will use `Epydoc`_ for generating API
 docs, so we will follow the `Epydoc`_ conventions. More specifically, we will use
 `reStructuredText`_ for markup and formatting, since it is understood by a wide
 variety of tools. This means that if in the future we have any reason to change from
 `Epydoc`_ to something else, we'll have fewer transition pains.
 
 Details about using `reStructuredText`_ for docstrings can be found `here
 <http://epydoc.sourceforge.net/manual-othermarkup.html>`_.
 
 .. _Epydoc: http://epydoc.sourceforge.net/
 
 Additional PEPs of interest regarding documentation of code:
 
 - `Docstring Conventions <http://www.python.org/peps/pep-0257.html>`_
 - `Docstring Processing System Framework <http://www.python.org/peps/pep-0256.html>`_
 - `Docutils Design Specification <http://www.python.org/peps/pep-0258.html>`_
 
 
 Coding conventions
 ==================
 
 General
 -------
 
 In general, we'll try to follow the standard Python style conventions as described here:
 
 - `Style Guide for Python Code  <http://www.python.org/peps/pep-0008.html>`_  
 
 
 Other comments:
 
 - In a large file, top level classes and functions should be 
   separated by 2-3 lines to make it easier to separate them visually.
 - Use 4 spaces for indentation.
 - Keep the ordering of methods the same in classes that have the same 
   methods.  This is particularly true for classes that implement 
   similar interfaces and for interfaces that are similar.
 
 Naming conventions
 ------------------
 
 In terms of naming conventions, we'll follow the guidelines from the `Style Guide for
 Python Code`_.
 
 For all new IPython code (and much existing code is being refactored), we'll use:
 
 - All ``lowercase`` module names.
 
 - ``CamelCase`` for class names.
 
 - ``lowercase_with_underscores`` for methods, functions, variables and attributes.
 
 This may be confusing as most of the existing IPython codebase uses a different convention (``lowerCamelCase`` for methods and attributes).  Slowly, we will move IPython over to the new
 convention, providing shadow names for backward compatibility in public interfaces. 
 
 There are, however, some important exceptions to these rules.  In some cases, IPython
 code will interface with packages (Twisted, Wx, Qt) that use other conventions.  At some level this makes it impossible to adhere to our own standards at all times.  In particular, when subclassing classes that use other naming conventions, you must follow their naming conventions.  To deal with cases like this, we propose the following policy:
 
 - If you are subclassing a class that uses different conventions, use its
   naming conventions throughout your subclass.  Thus, if you are creating a 
   Twisted Protocol class, used Twisted's ``namingSchemeForMethodsAndAttributes.``
 
 - All IPython's official interfaces should use our conventions.  In some cases 
   this will mean that you need to provide shadow names (first implement ``fooBar``
   and then ``foo_bar = fooBar``).  We want to avoid this at all costs, but it 
   will probably be necessary at times.  But, please use this sparingly!
 
 Implementation-specific *private* methods will use ``_single_underscore_prefix``.
 Names with a leading double underscore will *only* be used in special cases, as they
 makes subclassing difficult (such names are not easily seen by child classes).
 
 Occasionally some run-in lowercase names are used, but mostly for very short names or
 where we are implementing methods very similar to existing ones in a base class (like
 ``runlines()`` where ``runsource()`` and ``runcode()`` had established precedent).
 
 The old IPython codebase has a big mix of classes and modules prefixed with an
 explicit ``IP``. In Python this is mostly unnecessary, redundant and frowned upon, as
 namespaces offer cleaner prefixing. The only case where this approach is justified is
 for classes which are expected to be imported into external namespaces and a very
 generic name (like Shell) is too likely to clash with something else. We'll need to
 revisit this issue as we clean up and refactor the code, but in general we should
 remove as many unnecessary ``IP``/``ip`` prefixes as possible. However, if a prefix
 seems absolutely necessary the more specific ``IPY`` or ``ipy`` are preferred.
 
 .. _devel_testing:
 
 Testing system
 ==============
 
 It is extremely important that all code contributed to IPython has tests. Tests should
 be written as unittests, doctests or as entities that the `Nose`_ testing package will
 find. Regardless of how the tests are written, we will use `Nose`_ for discovering and
 running the tests. `Nose`_ will be required to run the IPython test suite, but will
 not be required to simply use IPython.
 
 .. _Nose: http://code.google.com/p/python-nose/
 
 Tests of `Twisted`__ using code should be written by subclassing the ``TestCase`` class
 that comes with ``twisted.trial.unittest``. When this is done, `Nose`_ will be able to
 run the tests and the twisted reactor will be handled correctly.
 
 .. __: http://www.twistedmatrix.com
 
 Each subpackage in IPython should have its own ``tests`` directory that contains all
 of the tests for that subpackage. This allows each subpackage to be self-contained. If
 a subpackage has any dependencies beyond the Python standard library, the tests for
 that subpackage should be skipped if the dependencies are not found. This is very
 important so users don't get tests failing simply because they don't have dependencies.
 
 We also need to look into use Noses ability to tag tests to allow a more modular
 approach of running tests.
 
 .. _devel_config:
 
 Configuration system
 ====================
 
 IPython uses `.ini`_ files for configuration purposes. This represents a huge
 improvement over the configuration system used in IPython. IPython works with these
 files using the `ConfigObj`_ package, which IPython includes as
 ``ipython1/external/configobj.py``.
 
 Currently, we are using raw `ConfigObj`_ objects themselves. Each subpackage of IPython
 should contain a ``config`` subdirectory that contains all of the configuration
 information for the subpackage. To see how configuration information is defined (along
 with defaults) see at the examples in ``ipython1/kernel/config`` and
 ``ipython1/core/config``. Likewise, to see how the configuration information is used,
 see examples in ``ipython1/kernel/scripts/ipengine.py``.
 
 Eventually, we will add a new layer on top of the raw `ConfigObj`_ objects. We are
 calling this new layer, ``tconfig``, as it will use a `Traits`_-like validation model.
 We won't actually use `Traits`_, but will implement something similar in pure Python.
 But, even in this new system, we will still use `ConfigObj`_ and `.ini`_ files
 underneath the hood. Talk to Fernando if you are interested in working on this part of
 IPython. The current prototype of ``tconfig`` is located in the IPython sandbox.
 
 .. _.ini: http://docs.python.org/lib/module-ConfigParser.html
 .. _ConfigObj: http://www.voidspace.org.uk/python/configobj.html
 .. _Traits: http://code.enthought.com/traits/
 
 Installation and testing scenarios
 ==================================
 
 This section outlines the various scenarios that we need to test before we release an IPython version.  These scenarios represent different ways of installing IPython and its dependencies.
 
 Installation scenarios under Linux and OS X
 -------------------------------------------
 
-    1.  Install from tarball using `python setup.py install`.
+    1.  Install from tarball using ``python setup.py install``.
         a.  With only readline+nose dependencies installed.
-        b.  With all dependencies installed (readline, zope.interface,
-            Twisted, foolscap, Sphinx, nose, pyOpenSSL).
+        b.  With all dependencies installed (readline, zope.interface, Twisted,
+        foolscap, Sphinx, nose, pyOpenSSL).
+	    
     2.  Install using easy_install.
+
         a.  With only readline+nose dependencies installed.
-            i.  Default dependencies: `easy_install ipython-0.9.beta3-py2.5.egg`
-            ii. Optional dependency sets: `easy_install -f ipython-0.9.beta3-py2.5.egg IPython[kernel,doc,test,security]`
+            i.  Default dependencies: ``easy_install ipython-0.9.beta3-py2.5.egg``
+            ii. Optional dependency sets: ``easy_install -f ipython-0.9.beta3-py2.5.egg IPython[kernel,doc,test,security]``
+
         b.  With all dependencies already installed.
+	
 
 Installation scenarios under Win32
 ----------------------------------
 
 	1.  Install everything from .exe installers
 	2.  easy_install?
 
 
 Tests to run for these scenarios
 --------------------------------
 
     1.  Run the full test suite.
     2.  Start a controller and engines and try a few things by hand.
         a.  Using ipcluster.
         b.  Using ipcontroller/ipengine by hand.
+
     3.  Run a few of the parallel examples.
     4.  Try the kernel with and without security with and without PyOpenSSL
         installed.
     5.  Beat on the IPython terminal a bunch.
     6.  Make sure that furl files are being put in proper locations.
 
 
 
 
 
 
 
 
 

docs/source/interactive/reference.txt

@@ -1,3163 +1,3162 b''
 .. 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.
 
 =================
 IPython reference
 =================
 
 .. contents::
 
-.. _Command line options:
+.. _command_line_options:
 
 Command-line usage
 ==================
 
 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.
 
 .. _Threading options:
 
 
 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.ne), 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 `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. 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.
 
     -pydb
 	Makes IPython use the third party "pydb" package as debugger,
 	instead of pdb. Requires that pydb is installed.
 	
     -[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> or
 	ipy_profile_<name>.py (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. Prompts_
-	discusses in detail all the available escapes to customize
-	your prompts.
+
+        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 [\#]:'.  The :ref:`prompts section <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
 	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. Note that you should probably use %upgrade instead,
 	it's a safer alternative.
 
 
     -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, using '/' character is recommended if you
 have problems with ``\``.  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``
 
 .. _magic:
 
 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.
 
 .. magic_start
 
 **%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'.
 
 **%clear**::
 
 	 Clear various data (e.g. stored history data)
     
     %clear out - clear output history
     %clear in  - clear input history
     %clear shadow_compress - Compresses shadow history (to speed up ipython)
     %clear shadow_nuke - permanently erase all entries in shadow history
     %clear dhist - clear dir history
 
 **%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 colon-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.
 
 **%hist**::
 
 	Alternate name for %history.
 
 **%history**::
 
 	Print input history (_i<n> variables), with most recent last.
     
     %history       -> print at most 40 inputs (some may be multi-line)\
     %history n     -> print at most n inputs\
     %history n1 n2 -> print inputs between n1 and n2 (n2 not included)\
     
     Each input's number <n> is shown, and is accessible as the
     automatically generated variable _i<n>.  Multi-line statements are
     printed starting at a new line for easy copy/paste.
     
 
     Options:
 
       -n: do NOT print line numbers. This is useful if you want to get a
       printout of many lines which can be directly pasted into a text
       editor.
 
       This feature is only available if numbered prompts are in use.
 
       -t: (default) print the 'translated' history, as IPython understands it.
       IPython filters your input and converts it all into valid Python source
       before executing it (things like magics or aliases are turned into
       function calls, for example). With this option, you'll see the native
       history instead of the user-entered version: '%cd /' will be seen as
       '_ip.magic("%cd /")' instead of '%cd /'.
       
       -r: print the 'raw' history, i.e. the actual commands you typed.
       
       -g: treat the arg as a pattern to grep for in (full) history.
       This includes the "shadow history" (almost all commands ever written).
       Use '%hist -g' to show full shadow history (may be very long).
       In shadow history, every index nuwber starts with 0.
 
       -f FILENAME: instead of printing the output to the screen, redirect it to
        the given file.  The file is always overwritten, though IPython asks for
        confirmation first if it already exists.
 
 **%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'#\[Out\]# ' '{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.
 
 **%mglob**::
 
 	    This program allows specifying filenames with "mglob" mechanism.
     Supported syntax in globs (wilcard matching patterns)::
     
      *.cpp ?ellowo*                
          - obvious. Differs from normal glob in that dirs are not included.
            Unix users might want to write this as: "*.cpp" "?ellowo*"
      rec:/usr/share=*.txt,*.doc    
          - get all *.txt and *.doc under /usr/share, 
            recursively
      rec:/usr/share
          - All files under /usr/share, recursively
      rec:*.py
          - All .py files under current working dir, recursively
      foo                           
          - File or dir foo
      !*.bak readme*                   
          - readme*, exclude files ending with .bak
      !.svn/ !.hg/ !*_Data/ rec:.
          - Skip .svn, .hg, foo_Data dirs (and their subdirs) in recurse.
            Trailing / is the key, \ does not work!
      dir:foo                       
          - the directory foo if it exists (not files in foo)
      dir:*                         
          - all directories in current folder
      foo.py bar.* !h* rec:*.py
          - Obvious. !h* exclusion only applies for rec:*.py.
            foo.py is *not* included twice.
      @filelist.txt
          - All files listed in 'filelist.txt' file, on separate lines.
 
 **%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.
 
 **%rehashdir**::
 
 	 Add executables in all specified dirs to alias table
      
     Usage:
 
     %rehashdir c:/bin;c:/tools
       - Add all executables under c:/bin and c:/tools to alias table, in 
       order to make them directly executable from any directory.
         
       Without arguments, add all executables in current directory.
 
 **%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.
 
 **%rep**::
 
 	 Repeat a command, or get command to input line for editing
 
     - %rep (no arguments):
     
     Place a string version of last computation result (stored in the special '_'
     variable) to the next input prompt. Allows you to create elaborate command
     lines without using copy-paste::
     
         $ l = ["hei", "vaan"]       
         $ "".join(l)        
         ==> heivaan        
         $ %rep        
         $ heivaan_ <== cursor blinking    
     
     %rep 45
     
     Place history line 45 to next input prompt. Use %hist to find out the
     number.
     
     %rep 1-4 6-7 3
     
     Repeat the specified lines immediately. Input slice syntax is the same as
     in %macro and %save.
     
     %rep foo
     
     Place the most recent line that has the substring "foo" to next input.
     (e.g. 'svn ci -m foobar').
 
 **%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.
 
 **%store**::
 
 	Lightweight persistence for python variables.
 
     Example:
     
     ville@badger[~]|1> A = ['hello',10,'world']\
     ville@badger[~]|2> %store A\
     ville@badger[~]|3> Exit
     
     (IPython session is closed and started again...)
     
     ville@badger:~$ ipython -p pysh\
     ville@badger[~]|1> print A
     
     ['hello', 10, 'world']
     
     Usage:
     
     %store          - Show list of all variables and their current values\
     %store <var>    - Store the *current* value of the variable to disk\
     %store -d <var> - Remove the variable and its value from storage\
     %store -z       - Remove all variables from storage\
     %store -r       - Refresh all variables from store (delete current vals)\
     %store foo >a.txt  - Store value of foo to new file a.txt\
     %store foo >>a.txt - Append value of foo to file a.txt\   
     
     It should be noted that if you change the value of a variable, you
     need to %store it again if you want to persist the new value.
     
     Note also that the variables will need to be pickleable; most basic
     python types can be safely %stored.
     
     Also aliases can be %store'd across sessions.
 
 **%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)
 
 **%which**::
 
 	 %which <cmd> => search PATH for files matching cmd. Also scans aliases.
 
     Traverses PATH and prints all files (not just executables!) that match the
     pattern on command line. Probably more useful in finding stuff
     interactively than 'which', which only prints the first matching item.
     
     Also discovers and expands aliases, so you'll see what will be executed
     when you call an alias.
     
     Example:
     
     [~]|62> %which d
     d -> ls -F --color=auto
       == c:\cygwin\bin\ls.exe
     c:\cygwin\bin\d.exe
     
     [~]|64> %which diff*
     diff3 -> diff3
       == c:\cygwin\bin\diff3.exe
     diff -> diff
       == c:\cygwin\bin\diff.exe
     c:\cygwin\bin\diff.exe
     c:\cygwin\bin\diff3.exe
 
 **%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.
 
 .. magic_end
 
 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. `accessing help`_, you need to properly configure
-your environment variable PYTHONDOCS for this feature to work correctly.
+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 :ref:`here
+<accessing_help>`, you need to properly configure your environment variable
+PYTHONDOCS for this feature to work correctly.
 
+.. _dynamic_object_info:
 
 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:
+.. _readline:
 
 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. `command line
-options`_) or by activating the logging at any moment with the magic
-function %logstart.
+You can log all input from a session either by starting IPython with the
+command line switches -log or -logfile (see :ref:`here <command_line_options>`)
+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:
+
 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).
 
 
 .. _dreload:
 
 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:
+.. _input_caching:
 
 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:
+.. _output_caching:
 
 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
 
 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.
 
 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:
 
 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.
 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. 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. 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. Embedding_), 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
 
 
 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. `Threading options`_), 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. `Threading options`_, 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:
+.. _interactive_demos:
 
 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
 
 
 .. _Matplotlib support:
 
 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. `Command line
-options`_). 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. Profiles_): ''ipython -pylab -p
-myprofile'' will load the profile defined in ipythonrc-myprofile after
-configuring matplotlib.
-
-
+IPython accepts the special option -pylab (see :ref:`here
+<command_line_options>`). 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 (see :ref:`here
+<profiles>`): ``ipython -pylab -p myprofile`` will load the profile defined in
+ipythonrc-myprofile after configuring matplotlib.

docs/source/interactive/tutorial.txt

@@ -1,315 +1,317 b''
 .. _tutorial:
 
 ======================
 Quick IPython tutorial
 ======================
 
 .. contents::
 
 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
 
 Highlights
 ==========
 
 Tab completion
 --------------
 
 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 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.
+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 :ref:`the readline
+section <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. `dynamic object information`_ for more.
+explicitly. See :ref:`this section <dynamic_object_info>` for more.
 
 The `%run` magic command
 ------------------------
 
-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 magic_ section 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. dreload_ for a recursive reload command. %run
+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 :ref:`this section <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 :ref:`this section <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.
 
 Debug a Python script
 ---------------------
 
-Use the Python debugger, pdb. 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. `Output caching`_ for details.
+Use the Python debugger, pdb. 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.  The :ref:`output caching section
+<output_caching>` has more 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. `Output caching`_ for more.
+new calculations. See :ref:`the output caching section <output_caching>` for
+more.
 
 Suppress output
 ---------------
 
 Put a ';' at the end of a line to suppress 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.
 
 Input cache
 -----------
 
 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. `Input caching`_ for more.
+the %macro function. See :ref:`here <input_caching>` 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.
 
 Call system shell commands
 --------------------------
 
 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.
 
 Use Python variables when calling the shell
 -------------------------------------------
 
-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 `System shell access`_ for more.
+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 :ref:`our shell section <system_shell_access>` for
+more details.
 
 Use profiles
 ------------
 
 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. profiles_ for
-more.
+customized versions of IPython for specific purposes. :ref:`This section
+<profiles>` has more details.
 
 
 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. embedding_ for more.
+automatic processing has been completed. See :ref:`here <embedding>` 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 IPython to present interactive demos
 ----------------------------------------
 
 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. `interactive demos`_ for more.
+demo. With a minimal amount of simple markup, you can control the execution of
+the script, stopping as needed. See :ref:`here <interactive_demos>` for more.
 
 Run doctests
 ------------
 
 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!