Command-line Options

To see the options IPython accepts, use ipython --help (and you probably should run the output through a pager such as ipython --help | less for more convenient reading). This shows all the options that have a single-word alias to control them, but IPython lets you configure all of its objects from the command-line by passing the full class name and a corresponding value; type ipython --help-all to see this full list. For example:

ipython --matplotlib qt

is equivalent to:

ipython --TerminalIPythonApp.matplotlib='qt'

Note that in the second form, you must use the equal sign, as the expression is evaluated as an actual Python assignment. While in the above example the short form is more convenient, only the most common options have a short form, while any configurable variable in IPython can be set at the command-line by using the long form. This long form is the same syntax used in the configuration files, if you want to set these options permanently.

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 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.

Lines that begin with %% signal a cell magic: they take as arguments not only the rest of the current line, but all lines below them as well, in the current execution block. Cell magics can in fact make arbitrary modifications to the input they receive, which need not even be valid Python code at all. They receive the whole block as a single string.

As a line magic example, the %cd magic works just like the OS command of the same name:

In [8]: %cd
/home/fperez

The following uses the builtin timeit in cell mode:

In [10]: %%timeit x = range(10000)
    ...: min(x)
    ...: max(x)
    ...:
1000 loops, best of 3: 438 us per loop

In this case, x = range(10000) is called as the line argument, and the block with min(x) and max(x) is called as the cell body. The timeit magic receives both.

If you have 'automagic' enabled (as it by default), you don't need to type in the single % explicitly for line magics; 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':

In [9]: cd mydir
/home/fperez/mydir

Note that cell magics always require an explicit %% prefix, automagic calling only works for line magics.

The automagic system has the lowest possible precedence in name searches, so you can freely use variables with the same names as magic commands. If a magic command is 'shadowed' by a variable, you will need the explicit % prefix to use it:

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 "<ipython-input-3-9fedb3aff56c>", 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, automagic works again

In [6]: cd ipython

/home/fperez/ipython

from IPython.core.magic import (register_line_magic, register_cell_magic,
                                register_line_cell_magic)

@register_line_magic
def lmagic(line):
    "my line magic"
    return line

@register_cell_magic
def cmagic(line, cell):
    "my cell magic"
    return line, cell

@register_line_cell_magic
def lcmagic(line, cell=None):
    "Magic that works both as %lcmagic and as %%lcmagic"
    if cell is None:
        print("Called as line magic")
        return line
    else:
        print("Called as cell magic")
        return line, cell

# We delete these to avoid name conflicts for automagic to work
del lmagic, lcmagic

# This code can be put in any Python module, it does not require IPython
# itself to be running already.  It only creates the magics subclass but
# doesn't instantiate it yet.
from __future__ import print_function
from IPython.core.magic import (Magics, magics_class, line_magic,
                                cell_magic, line_cell_magic)

# The class MUST call this class decorator at creation time
@magics_class
class MyMagics(Magics):

    @line_magic
    def lmagic(self, line):
        "my line magic"
        print("Full access to the main IPython object:", self.shell)
        print("Variables in the user namespace:", list(self.shell.user_ns.keys()))
        return line

    @cell_magic
    def cmagic(self, line, cell):
        "my cell magic"
        return line, cell

    @line_cell_magic
    def lcmagic(self, line, cell=None):
        "Magic that works both as %lcmagic and as %%lcmagic"
        if cell is None:
            print("Called as line magic")
            return line
        else:
            print("Called as cell magic")
            return line, cell


# In order to actually use these magics, you must register them with a
# running IPython.  This code must be placed in a file that is loaded once
# IPython is up and running:
ip = get_ipython()
# You can register the class itself without instantiating it.  IPython will
# call the default constructor on it.
ip.register_magics(MyMagics)

@magics_class
class StatefulMagics(Magics):
    "Magics that hold additional state"

    def __init__(self, shell, data):
        # You must call the parent constructor
        super(StatefulMagics, self).__init__(shell)
        self.data = data

    # etc...

# This class must then be registered with a manually created instance,
# since its constructor has different arguments from the default:
ip = get_ipython()
magics = StatefulMagics(ip, some_data)
ip.register_magics(magics)

def func(self, line):
    print("Line magic called with line:", line)
    print("IPython object:", self.shell)

ip = get_ipython()
# Declare this function as the magic %mycommand
ip.define_magic('mycommand', func)

Access to the standard Python help

Simply type help() to access Python's standard help system. You can also type help(object) for information about a given object, or help('keyword') for information on a keyword. You may need to configure your PYTHONDOCS environment variable for this feature to work correctly.

Dynamic object information

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

If the information will not fit in the terminal, it is displayed in a pager (less if available, otherwise a basic internal pager).

Typing ??word or word?? gives access to the full information, including the source code where possible. Long strings are not snipped.

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 (%function_name?); 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 call signature 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) work on object attributes, as well as directly on variables. For example, after doing import os, you can use os.path.abspath??.

Readline-based features

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

# if you don't already have a ~/.inputrc file, you need this include:
$include /etc/inputrc

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

Session logging and restoring

You can log all input from a session either by starting IPython with the command line switch --logfile=foo.py (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 by running them as scripts 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 'ipython_log.py' in your current working directory, in 'rotate' mode (see below).

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

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

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

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

System shell access

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

Manual capture of command output

You can assign the result of a system command to a Python variable with the syntax myfiles = !ls. This gets machine readable output from stdout (e.g. without colours), and splits on newlines. To explicitly get this sort of output without assigning to a variable, use two exclamation marks (!!ls) or the %sx magic command.

The captured list has some convenience features. myfiles.n or myfiles.s returns a string delimited by newlines or spaces, respectively. myfiles.p produces path objects from the list items. See :ref:`string_lists` for details.

IPython also allows you to expand the value of python variables when making system calls. Wrap variables or expressions in {braces}:

In [1]: pyvar = 'Hello world'
In [2]: !echo "A python variable: {pyvar}"
A python variable: Hello world
In [3]: import math
In [4]: x = 8
In [5]: !echo {math.factorial(x)}
40320

For simple cases, you can alternatively prepend $ to a variable name:

In [6]: !echo $sys.argv
[/home/fperez/usr/bin/ipython]
In [7]: !echo "A system variable: $$HOME"  # Use $$ for literal $
A system variable: /home/fperez

System command aliases

The %alias magic function allows 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
ERROR: Alias <parts> requires 2 arguments, 1 given.

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

The %rehashx magic allows you to load your entire $PATH as ipython aliases. See its docstring for further details.

Recursive reload

The :mod:`IPython.lib.deepreload` module allows you to recursively reload a module: changes made to any of its dependencies will be reloaded without having to exit. To start using it, do:

from IPython.lib.deepreload import reload as dreload

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.

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

Input caching system

IPython offers numbered prompts (In/Out) with input and output caching (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 variables always exist:

• _i, _ii, _iii: store previous, next previous and next-next previous inputs.
• In, _ih : a list of all inputs; _ih[n] is the input from line n. 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), so _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.

You can also re-execute multiple lines of input easily by using the magic %rerun or %macro functions. The macro system also allows you to re-execute previous lines which include magic function calls (which require special processing). Type %macro? 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 is handy for searching for URLs, IP addresses, etc. You can bring history entries listed by '%hist -g' up for editing with the %recall command, or run them immediately with %rerun.

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 variables always exist:

• [_] (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 variables are also 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 configuration option InteractiveShell.cache_size. If you set it to 0, output caching is disabled. You can also use the %reset and %xdel magics to clear large items from memory.

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 conveniently 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.

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

In [1]: callable_ob arg1, arg2, arg3
------> callable_ob(arg1, arg2, arg3)

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

In [2]: /globals # becomes 'globals()'

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

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

but this will work:

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

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

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

In [1]: ,my_function /home/me  # becomes my_function("/home/me")

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

In [2]: ,my_function a b c    # becomes my_function("a","b","c")

In [3]: ;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:

In [4]: x = ,my_function /home/me # syntax error

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 for more details, including how to control where pdb will stop execution first.

For more information on the use of the pdb debugger, see :ref:`debugger-commands` in the Python documentation.

Post-mortem debugging

Going into a debugger when an exception occurs 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.

You can use the %debug magic after an exception has occurred to start post-mortem debugging. IPython can also call debugger every time your code triggers an uncaught exception. This feature can be toggled with the %pdb magic command, or you can start IPython with the --pdb option.

For a post-mortem debugger in your programs outside IPython, 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.

PyQt and PySide

When you use --gui=qt or --matplotlib=qt, IPython can work with either PyQt4 or PySide. There are three options for configuration here, because PyQt4 has two APIs for QString and QVariant - v1, which is the default on Python 2, and the more natural v2, which is the only API supported by PySide. v2 is also the default for PyQt4 on Python 3. IPython's code for the QtConsole uses v2, but you can still use any interface in your code, since the Qt frontend is in a different process.

The default will be to import PyQt4 without configuration of the APIs, thus matching what most applications would expect. It will fall back of PySide if PyQt4 is unavailable.

If specified, IPython will respect the environment variable QT_API used by ETS. ETS 4.0 also works with both PyQt4 and PySide, but it requires PyQt4 to use its v2 API. So if QT_API=pyside PySide will be used, and if QT_API=pyqt then PyQt4 will be used with the v2 API for QString and QVariant, so ETS codes like MayaVi will also work with IPython.

If you launch IPython in matplotlib mode with ipython --matplotlib=qt, then IPython will ask matplotlib which Qt library to use (only if QT_API is not set), via the 'backend.qt4' rcParam. If matplotlib is version 1.0.1 or older, then IPython will always use PyQt4 without setting the v2 APIs, since neither v2 PyQt nor PySide work.