update docs with new cl-arguments

docs/source/config/ipython.txt

@@ -1,136 +1,136 b''
 .. _configuring_ipython:
 
 ===========================================================
 Configuring the :command:`ipython` command line application
 ===========================================================
 
 This section contains information about how to configure the
 :command:`ipython` command line application. See the :ref:`configuration
 overview <config_overview>` for a more general description of the
 configuration system and configuration file format.
 
 The default configuration file for the :command:`ipython` command line application
 is :file:`ipython_config.py`.  By setting the attributes in this file, you
 can configure the application.   A sample is provided in
 :mod:`IPython.config.default.ipython_config`.  Simply copy this file to your
 :ref:`IPython directory <ipython_dir>` to start using it.
 
 Most configuration attributes that this file accepts are associated with
 classes that are subclasses of :class:`~IPython.core.component.Component`.
 
 A few configuration attributes are not associated with a particular 
 :class:`~IPython.core.component.Component` subclass.  These are application
 wide configuration attributes and are stored in the ``Global`` 
 sub-configuration section.  We begin with a description of these 
 attributes.
 
 Global configuration
 ====================
 
 Assuming that your configuration file has the following at the top::
 
     c = get_config()
 
 the following attributes can be set in the ``Global`` section.
 
-:attr:`c.Global.display_banner`
+:attr:`c.IPythonApp.display_banner`
     A boolean that determined if the banner is printer when :command:`ipython`
     is started.
 
-:attr:`c.Global.classic`
+:attr:`c.IPythonApp.classic`
     A boolean that determines if IPython starts in "classic" mode.  In this
     mode, the prompts and everything mimic that of the normal :command:`python`
     shell
 
-:attr:`c.Global.nosep`
+:attr:`c.IPythonApp.nosep`
     A boolean that determines if there should be no blank lines between
     prompts.
 
-:attr:`c.Global.log_level`
+:attr:`c.IPythonApp.log_level`
     An integer that sets the detail of the logging level during the startup
     of :command:`ipython`.  The default is 30 and the possible values are
     (0, 10, 20, 30, 40, 50).  Higher is quieter and lower is more verbose.
 
-:attr:`c.Global.extensions`
+:attr:`c.IPythonApp.extensions`
     A list of strings, each of which is an importable IPython extension. An
     IPython extension is a regular Python module or package that has a
     :func:`load_ipython_extension(ip)` method. This method gets called when
     the extension is loaded with the currently running
     :class:`~IPython.core.iplib.InteractiveShell` as its only argument. You
     can put your extensions anywhere they can be imported but we add the
     :file:`extensions` subdirectory of the ipython directory to ``sys.path``
     during extension loading, so you can put them there as well. Extensions
     are not executed in the user's interactive namespace and they must be pure
     Python code. Extensions are the recommended way of customizing
     :command:`ipython`. Extensions can provide an
     :func:`unload_ipython_extension` that will be called when the extension is
     unloaded.
 
-:attr:`c.Global.exec_lines`
+:attr:`c.IPythonApp.exec_lines`
     A list of strings, each of which is Python code that is run in the user's
     namespace after IPython start. These lines can contain full IPython syntax
     with magics, etc.
 
-:attr:`c.Global.exec_files`
+:attr:`c.IPythonApp.exec_files`
     A list of strings, each of which is the full pathname of a ``.py`` or
     ``.ipy`` file that will be executed as IPython starts. These files are run
     in IPython in the user's namespace. Files with a ``.py`` extension need to
     be pure Python. Files with a ``.ipy`` extension can have custom IPython
     syntax (magics, etc.). These files need to be in the cwd, the ipythondir
     or be absolute paths.
 
 Classes that can be configured
 ==============================
 
 The following classes can also be configured in the configuration file for
 :command:`ipython`:
 
 * :class:`~IPython.core.iplib.InteractiveShell`
 
 * :class:`~IPython.core.prefilter.PrefilterManager`
 
 * :class:`~IPython.core.alias.AliasManager`
 
 To see which attributes of these classes are configurable, please see the
 source code for these classes, the class docstrings or the sample
 configuration file :mod:`IPython.config.default.ipython_config`.
 
 Example
 =======
 
 For those who want to get a quick start, here is a sample
 :file:`ipython_config.py` that sets some of the common configuration
 attributes::
 
     # sample ipython_config.py
     c = get_config()
 
-    c.Global.display_banner = True
-    c.Global.log_level = 20
-    c.Global.extensions = [
+    c.IPythonApp.display_banner = True
+    c.IPythonApp.log_level = 20
+    c.IPythonApp.extensions = [
         'myextension'
     ]
-    c.Global.exec_lines = [
+    c.IPythonApp.exec_lines = [
         'import numpy',
         'import scipy'
     ]
-    c.Global.exec_files = [
+    c.IPythonApp.exec_files = [
         'mycode.py',
         'fancy.ipy'
     ]
     c.InteractiveShell.autoindent = True
     c.InteractiveShell.colors = 'LightBG'
     c.InteractiveShell.confirm_exit = False
     c.InteractiveShell.deep_reload = True
     c.InteractiveShell.editor = 'nano'
     c.InteractiveShell.prompt_in1 = 'In [\#]: '
     c.InteractiveShell.prompt_in2 = '   .\D.: '
     c.InteractiveShell.prompt_out = 'Out[\#]: '
     c.InteractiveShell.prompts_pad_left = True
     c.InteractiveShell.xmode = 'Context'
 
     c.PrefilterManager.multi_line_specials = True
 
     c.AliasManager.user_aliases = [
      ('la', 'ls -al')
     ]

docs/source/config/overview.txt

@@ -1,342 +1,342 b''
 .. _config_overview:
 
 ============================================
 Overview of the IPython configuration system
 ============================================
 
 This section describes the IPython configuration system. Starting with version
 0.11, IPython has a completely new configuration system that is quite
 different from the older :file:`ipythonrc` or :file:`ipy_user_conf.py`
 approaches. The new configuration system was designed from scratch to address
 the particular configuration needs of IPython. While there are many
 other excellent configuration systems out there, we found that none of them
 met our requirements.
 
 .. warning::
 
     If you are upgrading to version 0.11 of IPython, you will need to migrate
     your old :file:`ipythonrc` or :file:`ipy_user_conf.py` configuration files
     to the new system.  Read on for information on how to do this.
 
 The discussion that follows is focused on teaching user's how to configure
 IPython to their liking.  Developer's who want to know more about how they
 can enable their objects to take advantage of the configuration system
 should consult our :ref:`developer guide <developer_guide>`
 
 The main concepts
 =================
 
 There are a number of abstractions that the IPython configuration system uses.
 Each of these abstractions is represented by a Python class.
 
 Configuration object: :class:`~IPython.config.loader.Config`
     A configuration object is a simple dictionary-like class that holds
     configuration attributes and sub-configuration objects. These classes
     support dotted attribute style access (``Foo.bar``) in addition to the
     regular dictionary style access (``Foo['bar']``). Configuration objects
     are smart. They know how to merge themselves with other configuration
     objects and they automatically create sub-configuration objects.
 
 Application: :class:`~IPython.core.application.Application`
     An application is a process that does a specific job. The most obvious
     application is the :command:`ipython` command line program. Each
     application reads a *single* configuration file and command line options
     and then produces a master configuration object for the application. This
     configuration object is then passed to the configurable objects that the
     application creates. These configurable objects implement the actual logic
     of the application and know how to configure themselves given the
     configuration object.
 
 Component: :class:`~IPython.config.configurable.Configurable`
     A configurable is a regular Python class that serves as a base class for
     all main classes in an application. The
     :class:`~IPython.config.configurable.Configurable` base class is
     lightweight and only does one things.
 
     This :class:`~IPython.config.configurable.Configurable` is a subclass
     of :class:`~IPython.utils.traitlets.HasTraits` that knows how to configure
     itself. Class level traits with the metadata ``config=True`` become
     values that can be configured from the command line and configuration
     files.
     
     Developers create :class:`~IPython.config.configurable.Configurable`
     subclasses that implement all of the logic in the application. Each of
     these subclasses has its own configuration information that controls how
     instances are created.
 
 Having described these main concepts, we can now state the main idea in our
 configuration system: *"configuration" allows the default values of class
 attributes to be controlled on a class by class basis*. Thus all instances of
 a given class are configured in the same way. Furthermore, if two instances
 need to be configured differently, they need to be instances of two different
 classes. While this model may seem a bit restrictive, we have found that it
 expresses most things that need to be configured extremely well. However, it
 is possible to create two instances of the same class that have different
 trait values. This is done by overriding the configuration.
 
 Now, we show what our configuration objects and files look like.
 
 Configuration objects and files
 ===============================
 
 A configuration file is simply a pure Python file that sets the attributes
 of a global, pre-created configuration object.  This configuration object is a 
 :class:`~IPython.config.loader.Config` instance.  While in a configuration
 file, to get a reference to this object, simply call the :func:`get_config`
 function.  We inject this function into the global namespace that the 
 configuration file is executed in.
 
 Here is an example of a super simple configuration file that does nothing::
 
     c = get_config()
 
 Once you get a reference to the configuration object, you simply set
 attributes on it.  All you have to know is:
 
 * The name of each attribute.
 * The type of each attribute.
 
 The answers to these two questions are provided by the various
 :class:`~IPython.config.configurable.Configurable` subclasses that an
 application uses. Let's look at how this would work for a simple component
 subclass::
 
     # Sample component that can be configured.
     from IPython.config.configurable import Configurable
     from IPython.utils.traitlets import Int, Float, Str, Bool
     
     class MyClass(Configurable):
         name = Str('defaultname', config=True)
         ranking = Int(0, config=True)
         value = Float(99.0)
         # The rest of the class implementation would go here..
 
 In this example, we see that :class:`MyClass` has three attributes, two
 of whom (``name``, ``ranking``) can be configured.  All of the attributes
 are given types and default values.  If a :class:`MyClass` is instantiated,
 but not configured, these default values will be used.  But let's see how
 to configure this class in a configuration file::
 
     # Sample config file
     c = get_config()
     
     c.MyClass.name = 'coolname'
     c.MyClass.ranking = 10
 
 After this configuration file is loaded, the values set in it will override
 the class defaults anytime a :class:`MyClass` is created.  Furthermore,
 these attributes will be type checked and validated anytime they are set.
 This type checking is handled by the :mod:`IPython.utils.traitlets` module,
 which provides the :class:`Str`, :class:`Int` and :class:`Float` types.  In 
 addition to these traitlets, the :mod:`IPython.utils.traitlets` provides
 traitlets for a number of other types.
 
 .. note::
 
     Underneath the hood, the :class:`Configurable` base class is a subclass of
     :class:`IPython.utils.traitlets.HasTraits`. The
     :mod:`IPython.utils.traitlets` module is a lightweight version of
     :mod:`enthought.traits`. Our implementation is a pure Python subset
     (mostly API compatible) of :mod:`enthought.traits` that does not have any
     of the automatic GUI generation capabilities. Our plan is to achieve 100%
     API compatibility to enable the actual :mod:`enthought.traits` to
     eventually be used instead. Currently, we cannot use
     :mod:`enthought.traits` as we are committed to the core of IPython being
     pure Python.
 
 It should be very clear at this point what the naming convention is for 
 configuration attributes::
 
     c.ClassName.attribute_name = attribute_value
 
 Here, ``ClassName`` is the name of the class whose configuration attribute you
 want to set, ``attribute_name`` is the name of the attribute you want to set
 and ``attribute_value`` the the value you want it to have. The ``ClassName``
 attribute of ``c`` is not the actual class, but instead is another
 :class:`~IPython.config.loader.Config` instance.
 
 .. note::
 
     The careful reader may wonder how the ``ClassName`` (``MyClass`` in
     the above example) attribute of the configuration object ``c`` gets
     created. These attributes are created on the fly by the
     :class:`~IPython.config.loader.Config` instance, using a simple naming
     convention. Any attribute of a :class:`~IPython.config.loader.Config`
     instance whose name begins with an uppercase character is assumed to be a
     sub-configuration and a new empty :class:`~IPython.config.loader.Config`
     instance is dynamically created for that attribute. This allows deeply
     hierarchical information created easily (``c.Foo.Bar.value``) on the fly.
 
 Configuration files inheritance
 ===============================
 
 Let's say you want to have different configuration files for various purposes.
 Our configuration system makes it easy for one configuration file to inherit
 the information in another configuration file. The :func:`load_subconfig`
 command can be used in a configuration file for this purpose. Here is a simple
 example that loads all of the values from the file :file:`base_config.py`::
 
     # base_config.py
     c = get_config()
     c.MyClass.name = 'coolname'
     c.MyClass.ranking = 100
 
 into the configuration file :file:`main_config.py`::
 
     # main_config.py
     c = get_config()
     
     # Load everything from base_config.py
     load_subconfig('base_config.py')
     
     # Now override one of the values
     c.MyClass.name = 'bettername'
 
 In a situation like this the :func:`load_subconfig` makes sure that the
 search path for sub-configuration files is inherited from that of the parent.
 Thus, you can typically put the two in the same directory and everything will
 just work.
 
 Class based configuration inheritance
 =====================================
 
 There is another aspect of configuration where inheritance comes into play.
 Sometimes, your classes will have an inheritance hierarchy that you want
 to be reflected in the configuration system.  Here is a simple example::
 
     from IPython.config.configurable import Configurable
     from IPython.utils.traitlets import Int, Float, Str, Bool
     
     class Foo(Configurable):
         name = Str('fooname', config=True)
         value = Float(100.0, config=True)
     
     class Bar(Foo):
         name = Str('barname', config=True)
         othervalue = Int(0, config=True)
 
 Now, we can create a configuration file to configure instances of :class:`Foo`
 and :class:`Bar`::
 
     # config file
     c = get_config()
     
     c.Foo.name = 'bestname'
     c.Bar.othervalue = 10
 
 This class hierarchy and configuration file accomplishes the following:
 
 * The default value for :attr:`Foo.name` and :attr:`Bar.name` will be
   'bestname'.  Because :class:`Bar` is a :class:`Foo` subclass it also
   picks up the configuration information for :class:`Foo`.
 * The default value for :attr:`Foo.value` and :attr:`Bar.value` will be
   ``100.0``, which is the value specified as the class default.
 * The default value for :attr:`Bar.othervalue` will be 10 as set in the
   configuration file.  Because :class:`Foo` is the parent of :class:`Bar`
   it doesn't know anything about the :attr:`othervalue` attribute.
 
 
 .. _ipython_dir:
 
 Configuration file location
 ===========================
 
 So where should you put your configuration files?  By default, all IPython
 applications look in the so called "IPython directory".  The location of
 this directory is determined by the following algorithm:
 
-* If the ``--ipython-dir`` command line flag is given, its value is used.
+* If the ``ipython_dir`` command line flag is given, its value is used.
 
 * If not, the value returned by :func:`IPython.utils.path.get_ipython_dir`
   is used. This function will first look at the :envvar:`IPYTHON_DIR`
   environment variable and then default to a platform-specific default.
 
 On posix systems (Linux, Unix, etc.), IPython respects the ``$XDG_CONFIG_HOME``
 part of the `XDG Base Directory`_ specification. If ``$XDG_CONFIG_HOME`` is
 defined and exists ( ``XDG_CONFIG_HOME`` has a default interpretation of
 :file:`$HOME/.config`), then IPython's config directory will be located in
 :file:`$XDG_CONFIG_HOME/ipython`.  If users still have an IPython directory
 in :file:`$HOME/.ipython`, then that will be used. in preference to the 
 system default.
 
 For most users, the default value will simply be something like 
 :file:`$HOME/.config/ipython` on Linux, or :file:`$HOME/.ipython`
 elsewhere.
 
 Once the location of the IPython directory has been determined, you need to
 know what filename to use for the configuration file. The basic idea is that
 each application has its own default configuration filename. The default named
 used by the :command:`ipython` command line program is
-:file:`ipython_config.py`.  This value can be overriden by the ``-config_file``
+:file:`ipython_config.py`.  This value can be overriden by the ``config_file``
 command line flag.  A sample :file:`ipython_config.py` file can be found
 in :mod:`IPython.config.default.ipython_config.py`.  Simple copy it to your
 IPython directory to begin using it.
 
 .. _Profiles:
 
 Profiles
 ========
 
 A profile is simply a configuration file that follows a simple naming
 convention and can be loaded using a simplified syntax.  The idea is
 that users often want to maintain a set of configuration files for different
 purposes:  one for doing numerical computing with NumPy and SciPy and
 another for doing symbolic computing with SymPy.  Profiles make it easy
 to keep a separate configuration file for each of these purposes.
 
 Let's start by showing how a profile is used:
 
 .. code-block:: bash
 
-    $ ipython -p sympy
+    $ ipython profile=sympy
 
 This tells the :command:`ipython` command line program to get its
 configuration from the "sympy" profile. The search path for profiles is the
 same as that of regular configuration files. The only difference is that
 profiles are named in a special way. In the case above, the "sympy" profile
 would need to have the name :file:`ipython_config_sympy.py`.
 
-The general pattern is this: simply add ``_profilename`` to the end of the
-normal configuration file name. Then load the profile by adding ``-p
-profilename`` to your command line options.
+The general pattern is this: simply add ``<profilename>`` to the end of the
+normal configuration file name. Then load the profile by adding 
+``profile=<profilename>`` to your command line options.
 
 IPython ships with some sample profiles in :mod:`IPython.config.profile`.
 Simply copy these to your IPython directory to begin using them.
 
 Design requirements
 ===================
 
 Here are the main requirements we wanted our configuration system to have:
 
 * Support for hierarchical configuration information.
 
 * Full integration with command line option parsers.  Often, you want to read
   a configuration file, but then override some of the values with command line
   options.  Our configuration system automates this process and allows each
   command line option to be linked to a particular attribute in the 
   configuration hierarchy that it will override.
 
 * Configuration files that are themselves valid Python code. This accomplishes
   many things. First, it becomes possible to put logic in your configuration
   files that sets attributes based on your operating system, network setup,
   Python version, etc. Second, Python has a super simple syntax for accessing
   hierarchical data structures, namely regular attribute access
   (``Foo.Bar.Bam.name``). Third, using Python makes it easy for users to
   import configuration attributes from one configuration file to another.
   Forth, even though Python is dynamically typed, it does have types that can
   be checked at runtime. Thus, a ``1`` in a config file is the integer '1',
   while a ``'1'`` is a string.
 
 * A fully automated method for getting the configuration information to the
   classes that need it at runtime. Writing code that walks a configuration
   hierarchy to extract a particular attribute is painful. When you have
   complex configuration information with hundreds of attributes, this makes
   you want to cry.
 
 * Type checking and validation that doesn't require the entire configuration
   hierarchy to be specified statically before runtime. Python is a very
   dynamic language and you don't always know everything that needs to be
   configured when a program starts.
 
 
 .. _`XDG Base Directory`: http://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html

docs/source/interactive/reference.txt

@@ -1,1578 +1,1579 b''
 =================
 IPython reference
 =================
 
 .. warning::
 
     As of the 0.11 version of IPython, some of the features and APIs
     described in this section have been deprecated or are broken.  Our plan
     is to continue to support these features, but they need to be updated
     to take advantage of recent API changes.  Furthermore, this section
     of the documentation need to be updated to reflect all of these changes.
 
 .. _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
+you may have set in your ipython_config.py. 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 is typically 
 installed in the IPYTHON_DIR directory. For Linux
 users, this will be $HOME/.config/ipython, and for other users it will be
 $HOME/.ipython.  For Windows users, $HOME resolves to C:\\Documents and
 Settings\\YourUserName in most instances.
 
 
 
 
 Special Threading Options
 -------------------------
 
 Previously IPython had command line options for controlling GUI event loop
 integration (-gthread, -qthread, -q4thread, -wthread, -pylab). As of IPython
-version 0.11, these have been deprecated. Please see the new ``%gui``
+version 0.11, these have been removed. Please see the new ``%gui``
 magic command or :ref:`this section <gui_support>` for details on the new
-interface.
+interface, or specify the gui at the commandline::
+
+    $ ipython gui=qt
+
 
 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.
+(--no-option instead of --option) to turn the feature off.
 
-    -help  print a help message and exit.
+    -h, --help  print a help message and exit.
 
-    -pylab
-    Deprecated.  See :ref:`Matplotlib support <matplotlib_support>`
+    --pylab, pylab=<name>
+    See :ref:`Matplotlib support <matplotlib_support>`
     for more details.
 
-    -autocall <val>
+    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    
+    --[no-]autoindent    
 	Turn automatic indentation on/off.
 
-    -[no]automagic 
+    --[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 
+    --[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).
+    --[no-]banner		Print the initial information banner (default on).
 
-    -c <command>
+    c=<command>
 	execute the given command string. This is similar to the -c
 	option in the normal Python interpreter.
 
-    -cache_size, cs <n> 
+    cache_size=<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 
+    --classic
 	Gives IPython a similar feel to the classic Python
 	prompt.
 
-    -colors <scheme> 
+    colors=<scheme> 
 	Color scheme for prompts and exception reporting. Currently
 	implemented: NoColor, Linux and LightBG.
 
-    -[no]color_info 
+    --[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 
+    --[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: 
+    --[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>
+    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> 
+    ipython_dir=<name> 
 	name of your IPython configuration directory IPYTHON_DIR. This
 	can also be specified through the environment variable
 	IPYTHON_DIR.
 
     -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   
+    --[no-]messages   
 	Print messages which IPython collects about its startup
 	process (default on).
 
-    -[no]pdb
+    --[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
+    --pydb
 	Makes IPython use the third party "pydb" package as debugger,
 	instead of pdb. Requires that pydb is installed.
 	
-    -[no]pprint
+    --[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>
+    profile=<name>
 
 	assume that your config file is ipythonrc-<name> or
 	ipy_profile_<name>.py (looks in current dir first, then in
 	IPYTHON_DIR).  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
 	IPYTHON_DIR/ipythonrc file and then have other 'profiles' which
 	include this one and load extra things for particular
 	tasks. For example:
 
 	1. $IPYTHON_DIR/ipythonrc : load basic things you always want.
 	2. $IPYTHON_DIR/ipythonrc-math : load (1) and basic math-related modules.
 	3. $IPYTHON_DIR/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>
+    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 [\#]:'.  The :ref:`prompts section <prompts>`
 	discusses in detail all the available escapes to customize your
 	prompts.
 
-    -prompt_in2, pi2 <string>
+    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> 
+    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).
+    --quick
+    start in bare bones mode (no config file loaded).
 
-    -rcfile <name>   
+    config_file=<name>   
 	name of your IPython resource configuration file. Normally
-	IPython loads ipythonrc (from current directory) or
-	IPYTHON_DIR/ipythonrc.
+	IPython loads ipython_config.py (from current directory) or
+	IPYTHON_DIR/profile_default.
 
 	If the loading of your config file fails, IPython starts with
 	a bare bones configuration (no modules loaded at all).
 
-    -[no]readline
+    --[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>
+    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>
+    si=<string>
 
 	separator before input prompts.
 	Default: '\n'
 
-    -separate_out, so <string>  
+    so=<string>  
         separator before output prompts.
         Default: nothing.
 
-    -separate_out2, so2
+    so2=<string>
 	separator after output prompts.
 	Default: nothing.
 	For these three options, use the value 0 to specify no separator.
 
-    -nosep   
+    --nosep
 	shorthand for '-SeparateIn 0 -SeparateOut 0 -SeparateOut2
 	0'. Simply removes all input/output separators.
 
-    -upgrade 
-	allows you to upgrade your IPYTHON_DIR configuration when you
+    --init
+	allows you to initialize your IPYTHON_DIR 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
+	updated config 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> 
-    Deprecated.
+    --version    print version information and exit.
 
-    -xmode <modename>
+    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.
 
 The API documentation for the :mod:`IPython.Magic` module contains the full
 docstrings of all currently available magic commands.
 
 
 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 :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-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
 $IPYTHON_DIR/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 :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
 IPYTHON_DIR 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 system
 --------------------
 
 IPython offers numbered prompts (In/Out) with input and output caching
 (also referred to as 'input history'). All input is saved and can be 
 retrieved as variables (besides the usual arrow key recall), in 
 addition to the %rep magic command that brings a history entry
 up for editing on the next  command line.
 
 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.
 
 You can also search ('grep') through your history by typing 
 '%hist -g somestring'. This also searches through the so called *shadow history*,
 which remembers all the commands (apart from multiline code blocks)
 you have ever entered. Handy for searching for svn/bzr URL's, IP adrresses
 etc. You can bring shadow history entries listed by '%hist -g' up for editing 
 (or re-execution by just pressing ENTER) with %rep command. Shadow history 
 entries are not available as _iNUMBER variables, and they are identified by 
 the '0' prefix in %hist -g output. That is, history entry 12 is a normal 
 history entry, but 0231 is a shadow history entry.
 
 Shadow history was added because the readline history is inherently very
 unsafe - if you have multiple IPython sessions open, the last session 
 to close will overwrite the history of previountly closed session. Likewise,
 if a crash occurs, history is never saved, whereas shadow history entries
 are added after entering every command (so a command executed 
 in another IPython session is immediately available in other IPython 
 sessions that are open).
 
 To conserve space, a command can exist in shadow history only once - it doesn't 
 make sense to store a common line like "cd .." a thousand times. The idea is 
 mainly to provide a reliable place where valuable, hard-to-remember commands can 
 always be retrieved, as opposed to providing an exact sequence of commands
 you have entered in actual order.
 
 Because shadow history has all the commands you have ever executed,
 time taken by %hist -g will increase oven time. If it ever starts to take
 too long (or it ends up containing sensitive information like passwords), 
 clear the shadow history by `%clear shadow_nuke`.
 
 Time taken to add entries to shadow history should be negligible, but 
 in any case, if you start noticing performance degradation after using 
 IPython for a long time (or running a script that floods the shadow history!), 
 you can 'compress' the shadow history by executing 
 `%clear shadow_compress`. In practice, this should never be necessary
 in normal use.
 
 .. _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
     from IPython.core import ultratb
     sys.excepthook = 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
 
 .. _gui_support:
 
 GUI event loop support support
 ==============================
 
 .. versionadded:: 0.11
     The ``%gui`` magic and :mod:`IPython.lib.inputhook`.
 
 IPython has excellent support for working interactively with Graphical User
 Interface (GUI) toolkits, such as wxPython, PyQt4, PyGTK and Tk. This is
 implemented using Python's builtin ``PyOSInputHook`` hook. This implementation
 is extremely robust compared to our previous threaded based version. The
 advantages of this are:
 
 * GUIs can be enabled and disabled dynamically at runtime.
 * The active GUI can be switched dynamically at runtime.
 * In some cases, multiple GUIs can run simultaneously with no problems.
 * There is a developer API in :mod:`IPython.lib.inputhook` for customizing 
   all of these things.
 
 For users, enabling GUI event loop integration is simple.  You simple use the
 ``%gui`` magic as follows::
 
     %gui [-a] [GUINAME]
 
 With no arguments, ``%gui`` removes all GUI support.  Valid ``GUINAME``
 arguments are ``wx``, ``qt4``, ``gtk`` and ``tk``.  The ``-a`` option will
 create and return a running application object for the selected GUI toolkit.
 
 Thus, to use wxPython interactively and create a running :class:`wx.App`
 object, do::
 
     %gui -a wx
 
 For information on IPython's Matplotlib integration (and the ``pylab`` mode)
 see :ref:`this section <matplotlib_support>`.
 
 For developers that want to use IPython's GUI event loop integration in
 the form of a library, these capabilities are exposed in library form
 in the :mod:`IPython.lib.inputhook`.  Interested developers should see the
 module docstrings for more information, but there are a few points that
 should be mentioned here.
 
 First, the ``PyOSInputHook`` approach only works in command line settings 
 where readline is activated.
 
 Second, when using the ``PyOSInputHook`` approach, a GUI application should
 *not* start its event loop. Instead all of this is handled by the
 ``PyOSInputHook``. This means that applications that are meant to be used both
 in IPython and as standalone apps need to have special code to detects how the
 application is being run. We highly recommend using IPython's
 :func:`appstart_` functions for this. Here is a simple example that shows the
 recommended code that should be at the bottom of a wxPython using GUI
 application::
 
   try:
       from IPython import appstart_wx
       appstart_wx(app)
   except ImportError:
       app.MainLoop()
 
 This pattern should be used instead of the simple ``app.MainLoop()`` code
 that a standalone wxPython application would have.
 
 Third, unlike previous versions of IPython, we no longer "hijack" (replace
 them with no-ops) the event loops. This is done to allow applications that
 actually need to run the real event loops to do so. This is often needed to
 process pending events at critical points.
 
 Finally, we also have a number of examples in our source directory
 :file:`docs/examples/lib` that demonstrate these capabilities.
 
 .. _matplotlib_support:
 
 Plotting with matplotlib
 ========================
 
 
 `Matplotlib`_ provides high quality 2D and
 3D plotting for Python. Matplotlib can produce plots on screen using a variety
 of GUI toolkits, including Tk, PyGTK, PyQt4 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.
 
 Many IPython users have come to rely on IPython's ``-pylab`` mode which
 automates the integration of Matplotlib with IPython. We are still in the
 process of working with the Matplotlib developers to finalize the new pylab
 API, but for now you can use Matplotlib interactively using the following
 commands::
 
     %gui -a wx
     import matplotlib
     matplotlib.use('wxagg')
     from matplotlib import pylab
     pylab.interactive(True)
 
 All of this will soon be automated as Matplotlib beings to include
 new logic that uses our new GUI support.
 
 .. _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] Matplotlib. http://matplotlib.sourceforge.net
 

docs/source/interactive/tutorial.txt

@@ -1,336 +1,336 b''
 .. _tutorial:
 
 ======================
 Quick IPython tutorial
 ======================
 
 .. warning::
 
     As of the 0.11 version of IPython, some of the features and APIs
     described in this section have been deprecated or are broken.  Our plan
     is to continue to support these features, but they need to be updated
     to take advantage of recent API changes.  Furthermore, this section
     of the documentation need to be updated to reflect all of these changes.
 
 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 :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 :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 :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.  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 :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 :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.
 
 In particular, note taht the %rep magic function can repeat a command or get a
 command to the input line for further editing::
 
         $ l = ["hei", "vaan"]       
         $ "".join(l)        
         ==> heivaan        
         $ %rep        
         $ heivaan_ <== cursor blinking    
    
 For more details, type ``%rep?`` as usual.
 	
 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 :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. :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 :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 :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" 
+    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!