upstream/ipython Files · docs/source/interactive/reference.txt

Brian E Granger

r1258

.. IPython documentation master file, created by sphinx-quickstart.py on Mon Mar 24 17:01:34 2008.

You can adapt this file completely to your liking, but it should at least

contain the root 'toctree' directive.

=================

IPython reference

=================

.. contents::

Fernando Perez

r1695

.. _command_line_options:

Brian E Granger

r1258

Command-line usage

==================

You start IPython with the command::

$ ipython [options] files

If invoked with no options, it executes all the files listed in sequence

and drops you into the interpreter while still acknowledging any options

you may have set in your ipythonrc file. This behavior is different from

standard Python, which when called as python -i will only execute one

file and ignore your configuration setup.

Please note that some of the configuration options are not available at

the command line, simply because they are not practical here. Look into

your ipythonrc configuration file for details on those. This file

typically installed in the $HOME/.ipython directory. For Windows users,

$HOME resolves to C:\\Documents and Settings\\YourUserName in most

instances. In the rest of this text, we will refer to this directory as

IPYTHONDIR.

.. _Threading options:

Special Threading Options

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

The following special options are ONLY valid at the beginning of the

command line, and not later. This is because they control the initial-

ization of ipython itself, before the normal option-handling mechanism

is active.

-gthread, -qthread, -q4thread, -wthread, -pylab:

Only one of these can be given, and it can only be given as

the first option passed to IPython (it will have no effect in

any other position). They provide threading support for the

GTK, Qt (versions 3 and 4) and WXPython toolkits, and for the

matplotlib library.

With any of the first four options, IPython starts running a

separate thread for the graphical toolkit's operation, so that

you can open and control graphical elements from within an

IPython command line, without blocking. All four provide

essentially the same functionality, respectively for GTK, Qt3,

Qt4 and WXWidgets (via their Python interfaces).

Note that with -wthread, you can additionally use the

-wxversion option to request a specific version of wx to be

used. This requires that you have the wxversion Python module

installed, which is part of recent wxPython distributions.

If -pylab is given, IPython loads special support for the mat

plotlib library (http://matplotlib.sourceforge.net), allowing

interactive usage of any of its backends as defined in the

user's ~/.matplotlib/matplotlibrc file. It automatically

activates GTK, Qt or WX threading for IPyhton if the choice of

matplotlib backend requires it. It also modifies the %run

command to correctly execute (without blocking) any

matplotlib-based script which calls show() at the end.

-tk

The -g/q/q4/wthread options, and -pylab (if matplotlib is

configured to use GTK, Qt3, Qt4 or WX), will normally block Tk

graphical interfaces. This means that when either GTK, Qt or WX

threading is active, any attempt to open a Tk GUI will result in a

dead window, and possibly cause the Python interpreter to crash.

An extra option, -tk, is available to address this issue. It can

only be given as a second option after any of the above (-gthread,

-wthread or -pylab).

If -tk is given, IPython will try to coordinate Tk threading

with GTK, Qt or WX. This is however potentially unreliable, and

you will have to test on your platform and Python configuration to

determine whether it works for you. Debian users have reported

success, apparently due to the fact that Debian builds all of Tcl,

Tk, Tkinter and Python with pthreads support. Under other Linux

environments (such as Fedora Core 2/3), this option has caused

random crashes and lockups of the Python interpreter. Under other

operating systems (Mac OSX and Windows), you'll need to try it to

find out, since currently no user reports are available.

There is unfortunately no way for IPython to determine at run time

whether -tk will work reliably or not, so you will need to do some

experiments before relying on it for regular work.

Regular Options

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

After the above threading options have been given, regular options can

follow in any order. All options can be abbreviated to their shortest

non-ambiguous form and are case-sensitive. One or two dashes can be

used. Some options have an alternate short form, indicated after a ``|``.

Most options can also be set from your ipythonrc configuration file. See

the provided example for more details on what the options do. Options

given at the command line override the values set in the ipythonrc file.

All options with a [no] prepended can be specified in negated form

(-nooption instead of -option) to turn the feature off.

-help print a help message and exit.

-pylab

this can only be given as the first option passed to IPython

(it will have no effect in any other position). It adds

special support for the matplotlib library

(http://matplotlib.sourceforge.ne), allowing interactive usage

of any of its backends as defined in the user's .matplotlibrc

file. It automatically activates GTK or WX threading for

IPyhton if the choice of matplotlib backend requires it. It

also modifies the %run command to correctly execute (without

blocking) any matplotlib-based script which calls show() at

the end. See `Matplotlib support`_ for more details.

-autocall <val>

Make IPython automatically call any callable object even if you

didn't type explicit parentheses. For example, 'str 43' becomes

'str(43)' automatically. The value can be '0' to disable the feature,

'1' for smart autocall, where it is not applied if there are no more

arguments on the line, and '2' for full autocall, where all callable

objects are automatically called (even if no arguments are

present). The default is '1'.

-[no]autoindent

Turn automatic indentation on/off.

-[no]automagic

make magic commands automatic (without needing their first character

to be %). Type %magic at the IPython prompt for more information.

-[no]autoedit_syntax

When a syntax error occurs after editing a file, automatically

open the file to the trouble causing line for convenient

fixing.

-[no]banner Print the initial information banner (default on).

-c <command>

execute the given command string. This is similar to the -c

option in the normal Python interpreter.

-cache_size, cs <n>

size of the output cache (maximum number of entries to hold in

memory). The default is 1000, you can change it permanently in your

config file. Setting it to 0 completely disables the caching system,

and the minimum value accepted is 20 (if you provide a value less than

20, it is reset to 0 and a warning is issued) This limit is defined

because otherwise you'll spend more time re-flushing a too small cache

than working.

-classic, cl

Gives IPython a similar feel to the classic Python

prompt.

-colors <scheme>

Color scheme for prompts and exception reporting. Currently

implemented: NoColor, Linux and LightBG.

-[no]color_info

IPython can display information about objects via a set of functions,

and optionally can use colors for this, syntax highlighting source

code and various other elements. However, because this information is

passed through a pager (like 'less') and many pagers get confused with

color codes, this option is off by default. You can test it and turn

it on permanently in your ipythonrc file if it works for you. As a

reference, the 'less' pager supplied with Mandrake 8.2 works ok, but

that in RedHat 7.2 doesn't.

Test it and turn it on permanently if it works with your

system. The magic function %color_info allows you to toggle this

interactively for testing.

-[no]debug

Show information about the loading process. Very useful to pin down

problems with your configuration files or to get details about

session restores.

-[no]deep_reload:

IPython can use the deep_reload module which reloads changes in

modules recursively (it replaces the reload() function, so you don't

need to change anything to use it). deep_reload() forces a full

reload of modules whose code may have changed, which the default

reload() function does not.

When deep_reload is off, IPython will use the normal reload(),

but deep_reload will still be available as dreload(). This

feature is off by default [which means that you have both

normal reload() and dreload()].

-editor <name>

Which editor to use with the %edit command. By default,

IPython will honor your EDITOR environment variable (if not

set, vi is the Unix default and notepad the Windows one).

Since this editor is invoked on the fly by IPython and is

meant for editing small code snippets, you may want to use a

small, lightweight editor here (in case your default EDITOR is

something like Emacs).

-ipythondir <name>

name of your IPython configuration directory IPYTHONDIR. This

can also be specified through the environment variable

IPYTHONDIR.

-log, l

generate a log file of all input. The file is named

ipython_log.py in your current directory (which prevents logs

from multiple IPython sessions from trampling each other). You

can use this to later restore a session by loading your

logfile as a file to be executed with option -logplay (see

below).

-logfile, lf <name> specify the name of your logfile.

-logplay, lp <name>

you can replay a previous log. For restoring a session as close as

possible to the state you left it in, use this option (don't just run

the logfile). With -logplay, IPython will try to reconstruct the

previous working environment in full, not just execute the commands in

the logfile.

When a session is restored, logging is automatically turned on

again with the name of the logfile it was invoked with (it is

read from the log header). So once you've turned logging on for

a session, you can quit IPython and reload it as many times as

you want and it will continue to log its history and restore

from the beginning every time.

Caveats: there are limitations in this option. The history

variables _i*,_* and _dh don't get restored properly. In the

future we will try to implement full session saving by writing

and retrieving a 'snapshot' of the memory state of IPython. But

our first attempts failed because of inherent limitations of

Python's Pickle module, so this may have to wait.

-[no]messages

Print messages which IPython collects about its startup

process (default on).

-[no]pdb

Automatically call the pdb debugger after every uncaught

exception. If you are used to debugging using pdb, this puts

you automatically inside of it after any call (either in

IPython or in code called by it) which triggers an exception

which goes uncaught.

-pydb

Makes IPython use the third party "pydb" package as debugger,

instead of pdb. Requires that pydb is installed.

-[no]pprint

ipython can optionally use the pprint (pretty printer) module

for displaying results. pprint tends to give a nicer display

of nested data structures. If you like it, you can turn it on

permanently in your config file (default off).

-profile, p <name>

assume that your config file is ipythonrc-<name> or

ipy_profile_<name>.py (looks in current dir first, then in

IPYTHONDIR). This is a quick way to keep and load multiple

config files for different tasks, especially if you use the

include option of config files. You can keep a basic

IPYTHONDIR/ipythonrc file and then have other 'profiles' which

include this one and load extra things for particular

tasks. For example:

1. $HOME/.ipython/ipythonrc : load basic things you always want.

2. $HOME/.ipython/ipythonrc-math : load (1) and basic math-related modules.

3. $HOME/.ipython/ipythonrc-numeric : load (1) and Numeric and plotting modules.

Since it is possible to create an endless loop by having

circular file inclusions, IPython will stop if it reaches 15

recursive inclusions.

-prompt_in1, pi1 <string>

Fernando Perez

r1695

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.

Brian E Granger

r1258

-prompt_in2, pi2 <string>

Similar to the previous option, but used for the continuation

prompts. The special sequence '\D' is similar to '\#', but

with all digits replaced dots (so you can have your

continuation prompt aligned with your input prompt). Default:

' .\D.:' (note three spaces at the start for alignment with

'In [\#]').

-prompt_out,po <string>

String used for output prompts, also uses numbers like

prompt_in1. Default: 'Out[\#]:'

-quick start in bare bones mode (no config file loaded).

-rcfile <name>

name of your IPython resource configuration file. Normally

IPython loads ipythonrc (from current directory) or

IPYTHONDIR/ipythonrc.

If the loading of your config file fails, IPython starts with

a bare bones configuration (no modules loaded at all).

-[no]readline

use the readline library, which is needed to support name

completion and command history, among other things. It is

enabled by default, but may cause problems for users of

X/Emacs in Python comint or shell buffers.

Note that X/Emacs 'eterm' buffers (opened with M-x term) support

IPython's readline and syntax coloring fine, only 'emacs' (M-x

shell and C-c !) buffers do not.

-screen_length, sl <n>

number of lines of your screen. This is used to control

printing of very long strings. Strings longer than this number

of lines will be sent through a pager instead of directly

printed.

The default value for this is 0, which means IPython will

auto-detect your screen size every time it needs to print certain

potentially long strings (this doesn't change the behavior of the

'print' keyword, it's only triggered internally). If for some

reason this isn't working well (it needs curses support), specify

it yourself. Otherwise don't change the default.

-separate_in, si <string>

separator before input prompts.

Default: '\n'

-separate_out, so <string>

separator before output prompts.

Default: nothing.

-separate_out2, so2

separator after output prompts.

Default: nothing.

For these three options, use the value 0 to specify no separator.

-nosep

shorthand for '-SeparateIn 0 -SeparateOut 0 -SeparateOut2

0'. Simply removes all input/output separators.

-upgrade

allows you to upgrade your IPYTHONDIR configuration when you

install a new version of IPython. Since new versions may

include new command line options or example files, this copies

updated ipythonrc-type files. However, it backs up (with a

.old extension) all files which it overwrites so that you can

merge back any customizations you might have in your personal

files. Note that you should probably use %upgrade instead,

it's a safer alternative.

-Version print version information and exit.

-wxversion <string>

Select a specific version of wxPython (used in conjunction

with -wthread). Requires the wxversion module, part of recent

wxPython distributions

-xmode <modename>

Mode for exception reporting.

Valid modes: Plain, Context and Verbose.

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

* Context: prints 5 lines of context source code around each

line in the traceback.

* Verbose: similar to Context, but additionally prints the

variables currently visible where the exception happened

(shortening their strings if too long). This can potentially be

very slow, if you happen to have a huge data structure whose

string representation is complex to compute. Your computer may

appear to freeze for a while with cpu usage at 100%. If this

occurs, you can cancel the traceback with Ctrl-C (maybe hitting it

more than once).

Interactive use

===============

Warning: IPython relies on the existence of a global variable called

_ip which controls the shell itself. If you redefine _ip to anything,

bizarre behavior will quickly occur.

Other than the above warning, IPython is meant to work as a drop-in

replacement for the standard interactive interpreter. As such, any code

which is valid python should execute normally under IPython (cases where

this is not true should be reported as bugs). It does, however, offer

many features which are not available at a standard python prompt. What

follows is a list of these.

Caution for Windows users

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

Windows, unfortunately, uses the '\' character as a path

separator. This is a terrible choice, because '\' also represents the

escape character in most modern programming languages, including

Python. For this reason, using '/' character is recommended if you

have problems with ``\``. However, in Windows commands '/' flags

options, so you can not use it for the root directory. This means that

paths beginning at the root must be typed in a contrived manner like:

``%copy \opt/foo/bar.txt \tmp``

.. _magic:

Magic command system

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

IPython will treat any line whose first character is a % as a special

call to a 'magic' function. These allow you to control the behavior of

IPython itself, plus a lot of system-type features. They are all

prefixed with a % character, but parameters are given without

parentheses or quotes.

Example: typing '%cd mydir' (without the quotes) changes you working

directory to 'mydir', if it exists.

If you have 'automagic' enabled (in your ipythonrc file, via the command

line option -automagic or with the %automagic function), you don't need

to type in the % explicitly. IPython will scan its internal list of

magic functions and call one if it exists. With automagic on you can

then just type 'cd mydir' to go to directory 'mydir'. The automagic

system has the lowest possible precedence in name searches, so defining

an identifier with the same name as an existing magic function will

shadow it for automagic use. You can still access the shadowed magic

function by explicitly using the % character at the beginning of the line.

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

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

/home/fperez/ipython

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

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

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

File "<console>", line 1

cd ..

^

SyntaxError: invalid syntax

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

/home/fperez

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

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

/home/fperez/ipython

You can define your own magic functions to extend the system. The

following example defines a new magic command, %impall::

import IPython.ipapi

ip = IPython.ipapi.get()

def doimp(self, arg):

ip = self.api

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

arg,arg,arg)

)

ip.expose_magic('impall', doimp)

You can also define your own aliased names for magic functions. In your

ipythonrc file, placing a line like:

execute __IP.magic_cl = __IP.magic_clear

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

Type %magic for more information, including a list of all available

magic functions at any time and their docstrings. You can also type

%magic_function_name? (see sec. 6.4 <#sec:dyn-object-info> for

information on the '?' system) to get information about any particular

magic function you are interested in.

Magic commands

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

The rest of this section is automatically generated for each release

from the docstrings in the IPython code. Therefore the formatting is

somewhat minimal, but this method has the advantage of having

information always in sync with the code.

A list of all the magic commands available in IPython's default

installation follows. This is similar to what you'll see by simply

typing %magic at the prompt, but that will also give you information

about magic commands you may have added as part of your personal

customizations.

.. magic_start

**%Exit**::

Exit IPython without confirmation.

**%Pprint**::

Toggle pretty printing on/off.

**%alias**::

Define an alias for a system command.

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

Then, typing 'alias_name params' will execute the system command 'cmd

params' (from your underlying operating system).

Aliases have lower precedence than magic functions and Python normal

variables, so if 'foo' is both a Python variable and an alias, the

alias can not be executed until 'del foo' removes the Python variable.

You can use the %l specifier in an alias definition to represent the

whole line when the alias is called. For example:

In [2]: alias all echo "Input in brackets: <%l>"\

In [3]: all hello world\

Input in brackets: <hello world>

You can also define aliases with parameters using %s specifiers (one

per parameter):

In [1]: alias parts echo first %s second %s\

In [2]: %parts A B\

first A second B\

In [3]: %parts A\

Incorrect number of arguments: 2 expected.\

parts is an alias to: 'echo first %s second %s'

Note that %l and %s are mutually exclusive. You can only use one or

the other in your aliases.

Aliases expand Python variables just like system calls using ! or !!

do: all expressions prefixed with '$' get expanded. For details of

the semantic rules, see PEP-215:

http://www.python.org/peps/pep-0215.html. This is the library used by

IPython for variable expansion. If you want to access a true shell

variable, an extra $ is necessary to prevent its expansion by IPython:

In [6]: alias show echo\

In [7]: PATH='A Python string'\

In [8]: show $PATH\

A Python string\

In [9]: show $$PATH\

/usr/local/lf9560/bin:/usr/local/intel/compiler70/ia32/bin:...

You can use the alias facility to acess all of $PATH. See the %rehash

and %rehashx functions, which automatically create aliases for the

contents of your $PATH.

If called with no parameters, %alias prints the current alias table.

**%autocall**::

Make functions callable without having to type parentheses.

Usage:

%autocall [mode]

The mode can be one of: 0->Off, 1->Smart, 2->Full. If not given, the

value is toggled on and off (remembering the previous state).

In more detail, these values mean:

0 -> fully disabled

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

In this mode, you get:

In [1]: callable

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

In [2]: callable 'hello'

------> callable('hello')

Out[2]: False

2 -> Active always. Even if no arguments are present, the callable

object is called:

In [4]: callable

------> callable()

Note that even with autocall off, you can still use '/' at the start of

a line to treat the first argument on the command line as a function

and add parentheses to it:

In [8]: /str 43

------> str(43)

Out[8]: '43'

**%autoindent**::

Toggle autoindent on/off (if available).

**%automagic**::

Make magic functions callable without having to type the initial %.

Without argumentsl toggles on/off (when off, you must call it as

%automagic, of course). With arguments it sets the value, and you can

use any of (case insensitive):

- on,1,True: to activate

- off,0,False: to deactivate.

Note that magic functions have lowest priority, so if there's a

variable whose name collides with that of a magic fn, automagic won't

work for that function (you get the variable instead). However, if you

delete the variable (del var), the previously shadowed magic function

becomes visible to automagic again.

**%bg**::

Run a job in the background, in a separate thread.

For example,

%bg myfunc(x,y,z=1)

will execute 'myfunc(x,y,z=1)' in a background thread. As soon as the

execution starts, a message will be printed indicating the job

number. If your job number is 5, you can use

myvar = jobs.result(5) or myvar = jobs[5].result

to assign this result to variable 'myvar'.

IPython has a job manager, accessible via the 'jobs' object. You can

type jobs? to get more information about it, and use jobs.<TAB> to see

its attributes. All attributes not starting with an underscore are

meant for public use.

In particular, look at the jobs.new() method, which is used to create

new jobs. This magic %bg function is just a convenience wrapper

around jobs.new(), for expression-based jobs. If you want to create a

new job with an explicit function object and arguments, you must call

jobs.new() directly.

The jobs.new docstring also describes in detail several important

caveats associated with a thread-based model for background job

execution. Type jobs.new? for details.

You can check the status of all jobs with jobs.status().

The jobs variable is set by IPython into the Python builtin namespace.

If you ever declare a variable named 'jobs', you will shadow this

name. You can either delete your global jobs variable to regain

access to the job manager, or make a new name and assign it manually

to the manager (stored in IPython's namespace). For example, to

assign the job manager to the Jobs name, use:

Jobs = __builtins__.jobs

**%bookmark**::

Manage IPython's bookmark system.

%bookmark <name> - set bookmark to current dir

%bookmark <name> <dir> - set bookmark to <dir>

%bookmark -l - list all bookmarks

%bookmark -d <name> - remove bookmark

%bookmark -r - remove all bookmarks

You can later on access a bookmarked folder with:

%cd -b <name>

or simply '%cd <name>' if there is no directory called <name> AND

there is such a bookmark defined.

Your bookmarks persist through IPython sessions, but they are

associated with each profile.

**%cd**::

Change the current working directory.

This command automatically maintains an internal list of directories

you visit during your IPython session, in the variable _dh. The

command %dhist shows this history nicely formatted. You can also

do 'cd -<tab>' to see directory history conveniently.

Usage:

cd 'dir': changes to directory 'dir'.

cd -: changes to the last visited directory.

cd -<n>: changes to the n-th directory in the directory history.

cd -b <bookmark_name>: jump to a bookmark set by %bookmark

(note: cd <bookmark_name> is enough if there is no

directory <bookmark_name>, but a bookmark with the name exists.)

'cd -b <tab>' allows you to tab-complete bookmark names.

Options:

-q: quiet. Do not print the working directory after the cd command is

executed. By default IPython's cd command does print this directory,

since the default prompts do not display path information.

Note that !cd doesn't work for this purpose because the shell where

!command runs is immediately discarded after executing 'command'.

**%clear**::

Clear various data (e.g. stored history data)

%clear out - clear output history

%clear in - clear input history

%clear shadow_compress - Compresses shadow history (to speed up ipython)

%clear shadow_nuke - permanently erase all entries in shadow history

%clear dhist - clear dir history

**%color_info**::

Toggle color_info.

The color_info configuration parameter controls whether colors are

used for displaying object details (by things like %psource, %pfile or

the '?' system). This function toggles this value with each call.

Note that unless you have a fairly recent pager (less works better

than more) in your system, using colored object information displays

will not work properly. Test it and see.

**%colors**::

Switch color scheme for prompts, info system and exception handlers.

Currently implemented schemes: NoColor, Linux, LightBG.

Color scheme names are not case-sensitive.

**%cpaste**::

Allows you to paste & execute a pre-formatted code block from clipboard

You must terminate the block with '--' (two minus-signs) alone on the

line. You can also provide your own sentinel with '%paste -s %%' ('%%'

is the new sentinel for this operation)

The block is dedented prior to execution to enable execution of method

definitions. '>' and '+' characters at the beginning of a line are

ignored, to allow pasting directly from e-mails or diff files. The

executed block is also assigned to variable named 'pasted_block' for

later editing with '%edit pasted_block'.

You can also pass a variable name as an argument, e.g. '%cpaste foo'.

This assigns the pasted block to variable 'foo' as string, without

dedenting or executing it.

Do not be alarmed by garbled output on Windows (it's a readline bug).

Just press enter and type -- (and press enter again) and the block

will be what was just pasted.

IPython statements (magics, shell escapes) are not supported (yet).

**%debug**::

Activate the interactive debugger in post-mortem mode.

If an exception has just occurred, this lets you inspect its stack

frames interactively. Note that this will always work only on the last

traceback that occurred, so you must call this quickly after an

exception that you wish to inspect has fired, because if another one

occurs, it clobbers the previous one.

If you want IPython to automatically do this on every exception, see

the %pdb magic for more details.

**%dhist**::

Print your history of visited directories.

%dhist -> print full history\

%dhist n -> print last n entries only\

%dhist n1 n2 -> print entries between n1 and n2 (n1 not included)\

This history is automatically maintained by the %cd command, and

always available as the global list variable _dh. You can use %cd -<n>

to go to directory number <n>.

Note that most of time, you should view directory history by entering

cd -<TAB>.

**%dirs**::

Return the current directory stack.

**%doctest_mode**::

Toggle doctest mode on and off.

This mode allows you to toggle the prompt behavior between normal

IPython prompts and ones that are as similar to the default IPython

interpreter as possible.

It also supports the pasting of code snippets that have leading '>>>'

and '...' prompts in them. This means that you can paste doctests from

files or docstrings (even if they have leading whitespace), and the

code will execute correctly. You can then use '%history -tn' to see

the translated history without line numbers; this will give you the

input after removal of all the leading prompts and whitespace, which

can be pasted back into an editor.

With these features, you can switch into this mode easily whenever you

need to do testing and changes to doctests, without having to leave

your existing IPython session.

**%ed**::

Alias to %edit.

**%edit**::

Bring up an editor and execute the resulting code.

Usage:

%edit [options] [args]

%edit runs IPython's editor hook. The default version of this hook is

set to call the __IPYTHON__.rc.editor command. This is read from your

environment variable $EDITOR. If this isn't found, it will default to

vi under Linux/Unix and to notepad under Windows. See the end of this

docstring for how to change the editor hook.

You can also set the value of this editor via the command line option

'-editor' or in your ipythonrc file. This is useful if you wish to use

specifically for IPython an editor different from your typical default

(and for Windows users who typically don't set environment variables).

This command allows you to conveniently edit multi-line code right in

your IPython session.

If called without arguments, %edit opens up an empty editor with a

temporary file and will execute the contents of this file when you

close it (don't forget to save it!).

Options:

-n <number>: open the editor at a specified line number. By default,

the IPython editor hook uses the unix syntax 'editor +N filename', but

you can configure this by providing your own modified hook if your

favorite editor supports line-number specifications with a different

syntax.

-p: this will call the editor with the same data as the previous time

it was used, regardless of how long ago (in your current session) it

was.

-r: use 'raw' input. This option only applies to input taken from the

user's history. By default, the 'processed' history is used, so that

magics are loaded in their transformed version to valid Python. If

this option is given, the raw input as typed as the command line is

used instead. When you exit the editor, it will be executed by

IPython's own processor.

-x: do not execute the edited code immediately upon exit. This is

mainly useful if you are editing programs which need to be called with

command line arguments, which you can then do using %run.

Arguments:

If arguments are given, the following possibilites exist:

- The arguments are numbers or pairs of colon-separated numbers (like

1 4:8 9). These are interpreted as lines of previous input to be

loaded into the editor. The syntax is the same of the %macro command.

- If the argument doesn't start with a number, it is evaluated as a

variable and its contents loaded into the editor. You can thus edit

any string which contains python code (including the result of

previous edits).

- If the argument is the name of an object (other than a string),

IPython will try to locate the file where it was defined and open the

editor at the point where it is defined. You can use `%edit function`

to load an editor exactly at the point where 'function' is defined,

edit it and have the file be executed automatically.

If the object is a macro (see %macro for details), this opens up your

specified editor with a temporary file containing the macro's data.

Upon exit, the macro is reloaded with the contents of the file.

Note: opening at an exact line is only supported under Unix, and some

editors (like kedit and gedit up to Gnome 2.8) do not understand the

'+NUMBER' parameter necessary for this feature. Good editors like

(X)Emacs, vi, jed, pico and joe all do.

- If the argument is not found as a variable, IPython will look for a

file with that name (adding .py if necessary) and load it into the

editor. It will execute its contents with execfile() when you exit,

loading any code in the file into your interactive namespace.

After executing your code, %edit will return as output the code you

typed in the editor (except when it was an existing file). This way

you can reload the code in further invocations of %edit as a variable,

via _<NUMBER> or Out[<NUMBER>], where <NUMBER> is the prompt number of

the output.

Note that %edit is also available through the alias %ed.

This is an example of creating a simple function inside the editor and

then modifying it. First, start up the editor:

In [1]: ed\

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

Out[1]: 'def foo():\n print "foo() was defined in an editing session"\n'

We can then call the function foo():

In [2]: foo()\

foo() was defined in an editing session

Now we edit foo. IPython automatically loads the editor with the

(temporary) file where foo() was previously defined:

In [3]: ed foo\

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

And if we call foo() again we get the modified version:

In [4]: foo()\

foo() has now been changed!

Here is an example of how to edit a code snippet successive

times. First we call the editor:

In [8]: ed\

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

hello\

Out[8]: "print 'hello'\n"

Now we call it again with the previous output (stored in _):

In [9]: ed _\

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

hello world\

Out[9]: "print 'hello world'\n"

Now we call it with the output #8 (stored in _8, also as Out[8]):

In [10]: ed _8\

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

hello again\

Out[10]: "print 'hello again'\n"

Changing the default editor hook:

If you wish to write your own editor hook, you can put it in a

configuration file which you load at startup time. The default hook

is defined in the IPython.hooks module, and you can use that as a

starting example for further modifications. That file also has

general instructions on how to set a new hook for use once you've

defined it.

**%env**::

List environment variables.

**%exit**::

Exit IPython, confirming if configured to do so.

You can configure whether IPython asks for confirmation upon exit by

setting the confirm_exit flag in the ipythonrc file.

**%hist**::

Alternate name for %history.

**%history**::

Print input history (_i<n> variables), with most recent last.

%history -> print at most 40 inputs (some may be multi-line)\

%history n -> print at most n inputs\

%history n1 n2 -> print inputs between n1 and n2 (n2 not included)\

Each input's number <n> is shown, and is accessible as the

automatically generated variable _i<n>. Multi-line statements are

printed starting at a new line for easy copy/paste.

Options:

-n: do NOT print line numbers. This is useful if you want to get a

printout of many lines which can be directly pasted into a text

editor.

This feature is only available if numbered prompts are in use.

-t: (default) print the 'translated' history, as IPython understands it.

IPython filters your input and converts it all into valid Python source

before executing it (things like magics or aliases are turned into

function calls, for example). With this option, you'll see the native

history instead of the user-entered version: '%cd /' will be seen as

'_ip.magic("%cd /")' instead of '%cd /'.

-r: print the 'raw' history, i.e. the actual commands you typed.

-g: treat the arg as a pattern to grep for in (full) history.

This includes the "shadow history" (almost all commands ever written).

Use '%hist -g' to show full shadow history (may be very long).

In shadow history, every index nuwber starts with 0.

-f FILENAME: instead of printing the output to the screen, redirect it to

the given file. The file is always overwritten, though IPython asks for

confirmation first if it already exists.

**%logoff**::

Temporarily stop logging.

You must have previously started logging.

**%logon**::

Restart logging.

This function is for restarting logging which you've temporarily

stopped with %logoff. For starting logging for the first time, you

must use the %logstart function, which allows you to specify an

optional log filename.

**%logstart**::

Start logging anywhere in a session.

%logstart [-o|-r|-t] [log_name [log_mode]]

If no name is given, it defaults to a file named 'ipython_log.py' in your

current directory, in 'rotate' mode (see below).

'%logstart name' saves to file 'name' in 'backup' mode. It saves your

history up to that point and then continues logging.

%logstart takes a second optional parameter: logging mode. This can be one

of (note that the modes are given unquoted):\

append: well, that says it.\

backup: rename (if exists) to name~ and start name.\

global: single logfile in your home dir, appended to.\

over : overwrite existing log.\

rotate: create rotating logs name.1~, name.2~, etc.

Options:

-o: log also IPython's output. In this mode, all commands which

generate an Out[NN] prompt are recorded to the logfile, right after

their corresponding input line. The output lines are always

prepended with a '#[Out]# ' marker, so that the log remains valid

Python code.

Since this marker is always the same, filtering only the output from

a log is very easy, using for example a simple awk call:

awk -F'#\[Out\]# ' '{if($2) {print $2}}' ipython_log.py

-r: log 'raw' input. Normally, IPython's logs contain the processed

input, so that user lines are logged in their final form, converted

into valid Python. For example, %Exit is logged as

'_ip.magic("Exit"). If the -r flag is given, all input is logged

exactly as typed, with no transformations applied.

-t: put timestamps before each input line logged (these are put in

comments).

**%logstate**::

Print the status of the logging system.

**%logstop**::

Fully stop logging and close log file.

In order to start logging again, a new %logstart call needs to be made,

possibly (though not necessarily) with a new filename, mode and other

options.

**%lsmagic**::

List currently available magic functions.

**%macro**::

Define a set of input lines as a macro for future re-execution.

Usage:\

%macro [options] name n1-n2 n3-n4 ... n5 .. n6 ...

Options:

-r: use 'raw' input. By default, the 'processed' history is used,

so that magics are loaded in their transformed version to valid

Python. If this option is given, the raw input as typed as the

command line is used instead.

This will define a global variable called `name` which is a string

made of joining the slices and lines you specify (n1,n2,... numbers

above) from your input history into a single string. This variable

acts like an automatic function which re-executes those lines as if

you had typed them. You just type 'name' at the prompt and the code

executes.

The notation for indicating number ranges is: n1-n2 means 'use line

numbers n1,...n2' (the endpoint is included). That is, '5-7' means

using the lines numbered 5,6 and 7.

Note: as a 'hidden' feature, you can also use traditional python slice

notation, where N:M means numbers N through M-1.

For example, if your history contains (%hist prints it):

44: x=1\

45: y=3\

46: z=x+y\

47: print x\

48: a=5\

49: print 'x',x,'y',y\

you can create a macro with lines 44 through 47 (included) and line 49

called my_macro with:

In [51]: %macro my_macro 44-47 49

Now, typing `my_macro` (without quotes) will re-execute all this code

in one pass.

You don't need to give the line-numbers in order, and any given line

number can appear multiple times. You can assemble macros with any

lines from your input history in any order.

The macro is a simple object which holds its value in an attribute,

but IPython's display system checks for macros and executes them as

code instead of printing them when you type their name.

You can view a macro's contents by explicitly printing it with:

'print macro_name'.

For one-off cases which DON'T contain magic function calls in them you

can obtain similar results by explicitly executing slices from your

input history with:

In [60]: exec In[44:48]+In[49]

**%magic**::

Print information about the magic function system.

**%mglob**::

This program allows specifying filenames with "mglob" mechanism.

Supported syntax in globs (wilcard matching patterns)::

*.cpp ?ellowo*

- obvious. Differs from normal glob in that dirs are not included.

Unix users might want to write this as: "*.cpp" "?ellowo*"

rec:/usr/share=*.txt,*.doc

- get all *.txt and *.doc under /usr/share,

recursively

rec:/usr/share

- All files under /usr/share, recursively

rec:*.py

- All .py files under current working dir, recursively

foo

- File or dir foo

!*.bak readme*

- readme*, exclude files ending with .bak

!.svn/ !.hg/ !*_Data/ rec:.

- Skip .svn, .hg, foo_Data dirs (and their subdirs) in recurse.

Trailing / is the key, \ does not work!

dir:foo

- the directory foo if it exists (not files in foo)

dir:*

- all directories in current folder

foo.py bar.* !h* rec:*.py

- Obvious. !h* exclusion only applies for rec:*.py.

foo.py is *not* included twice.

@filelist.txt

- All files listed in 'filelist.txt' file, on separate lines.

**%page**::

Pretty print the object and display it through a pager.

%page [options] OBJECT

If no object is given, use _ (last output).

Options:

-r: page str(object), don't pretty-print it.

**%pdb**::

Control the automatic calling of the pdb interactive debugger.

Call as '%pdb on', '%pdb 1', '%pdb off' or '%pdb 0'. If called without

argument it works as a toggle.

When an exception is triggered, IPython can optionally call the

interactive pdb debugger after the traceback printout. %pdb toggles

this feature on and off.

The initial state of this feature is set in your ipythonrc

configuration file (the variable is called 'pdb').

If you want to just activate the debugger AFTER an exception has fired,

without having to type '%pdb on' and rerunning your code, you can use

the %debug magic.

**%pdef**::

Print the definition header for any callable object.

If the object is a class, print the constructor information.

**%pdoc**::

Print the docstring for an object.

If the given object is a class, it will print both the class and the

constructor docstrings.

**%pfile**::

Print (or run through pager) the file where an object is defined.

The file opens at the line where the object definition begins. IPython

will honor the environment variable PAGER if set, and otherwise will

do its best to print the file in a convenient form.

If the given argument is not an object currently defined, IPython will

try to interpret it as a filename (automatically adding a .py extension

if needed). You can thus use %pfile as a syntax highlighting code

viewer.

**%pinfo**::

Provide detailed information about an object.

'%pinfo object' is just a synonym for object? or ?object.

**%popd**::

Change to directory popped off the top of the stack.

**%profile**::

Print your currently active IPyhton profile.

**%prun**::

Run a statement through the python code profiler.

Usage:\

%prun [options] statement

The given statement (which doesn't require quote marks) is run via the

python profiler in a manner similar to the profile.run() function.

Namespaces are internally managed to work correctly; profile.run

cannot be used in IPython because it makes certain assumptions about

namespaces which do not hold under IPython.

Options:

-l <limit>: you can place restrictions on what or how much of the

profile gets printed. The limit value can be:

* A string: only information for function names containing this string

is printed.

* An integer: only these many lines are printed.

* A float (between 0 and 1): this fraction of the report is printed

(for example, use a limit of 0.4 to see the topmost 40% only).

You can combine several limits with repeated use of the option. For

example, '-l __init__ -l 5' will print only the topmost 5 lines of

information about class constructors.

-r: return the pstats.Stats object generated by the profiling. This

object has all the information about the profile in it, and you can

later use it for further analysis or in other functions.

-s <key>: sort profile by given key. You can provide more than one key

by using the option several times: '-s key1 -s key2 -s key3...'. The

default sorting key is 'time'.

The following is copied verbatim from the profile documentation

referenced below:

When more than one key is provided, additional keys are used as

secondary criteria when the there is equality in all keys selected

before them.

Abbreviations can be used for any key names, as long as the

abbreviation is unambiguous. The following are the keys currently

defined:

Valid Arg Meaning\

"calls" call count\

"cumulative" cumulative time\

"file" file name\

"module" file name\

"pcalls" primitive call count\

"line" line number\

"name" function name\

"nfl" name/file/line\

"stdname" standard name\

"time" internal time

Note that all sorts on statistics are in descending order (placing

most time consuming items first), where as name, file, and line number

searches are in ascending order (i.e., alphabetical). The subtle

distinction between "nfl" and "stdname" is that the standard name is a

sort of the name as printed, which means that the embedded line

numbers get compared in an odd way. For example, lines 3, 20, and 40

would (if the file names were the same) appear in the string order

"20" "3" and "40". In contrast, "nfl" does a numeric compare of the

line numbers. In fact, sort_stats("nfl") is the same as

sort_stats("name", "file", "line").

-T <filename>: save profile results as shown on screen to a text

file. The profile is still shown on screen.

-D <filename>: save (via dump_stats) profile statistics to given

filename. This data is in a format understod by the pstats module, and

is generated by a call to the dump_stats() method of profile

objects. The profile is still shown on screen.

If you want to run complete programs under the profiler's control, use

'%run -p [prof_opts] filename.py [args to program]' where prof_opts

contains profiler specific options as described here.

You can read the complete documentation for the profile module with:\

In [1]: import profile; profile.help()

**%psearch**::

Search for object in namespaces by wildcard.

%psearch [options] PATTERN [OBJECT TYPE]

Note: ? can be used as a synonym for %psearch, at the beginning or at

the end: both a*? and ?a* are equivalent to '%psearch a*'. Still, the

rest of the command line must be unchanged (options come first), so

for example the following forms are equivalent

%psearch -i a* function

-i a* function?

?-i a* function

Arguments:

PATTERN

where PATTERN is a string containing * as a wildcard similar to its

use in a shell. The pattern is matched in all namespaces on the

search path. By default objects starting with a single _ are not

matched, many IPython generated objects have a single

underscore. The default is case insensitive matching. Matching is

also done on the attributes of objects and not only on the objects

in a module.

[OBJECT TYPE]

Is the name of a python type from the types module. The name is

given in lowercase without the ending type, ex. StringType is

written string. By adding a type here only objects matching the

given type are matched. Using all here makes the pattern match all

types (this is the default).

Options:

-a: makes the pattern match even objects whose names start with a

single underscore. These names are normally ommitted from the

search.

-i/-c: make the pattern case insensitive/sensitive. If neither of

these options is given, the default is read from your ipythonrc

file. The option name which sets this value is

'wildcards_case_sensitive'. If this option is not specified in your

ipythonrc file, IPython's internal default is to do a case sensitive

search.

-e/-s NAMESPACE: exclude/search a given namespace. The pattern you

specifiy can be searched in any of the following namespaces:

'builtin', 'user', 'user_global','internal', 'alias', where

'builtin' and 'user' are the search defaults. Note that you should

not use quotes when specifying namespaces.

'Builtin' contains the python module builtin, 'user' contains all

user data, 'alias' only contain the shell aliases and no python

objects, 'internal' contains objects used by IPython. The

'user_global' namespace is only used by embedded IPython instances,

and it contains module-level globals. You can add namespaces to the

search with -s or exclude them with -e (these options can be given

more than once).

Examples:

%psearch a* -> objects beginning with an a

%psearch -e builtin a* -> objects NOT in the builtin space starting in a

%psearch a* function -> all functions beginning with an a

%psearch re.e* -> objects beginning with an e in module re

%psearch r*.e* -> objects that start with e in modules starting in r

%psearch r*.* string -> all strings in modules beginning with r

Case sensitve search:

%psearch -c a* list all object beginning with lower case a

Show objects beginning with a single _:

%psearch -a _* list objects beginning with a single underscore

**%psource**::

Print (or run through pager) the source code for an object.

**%pushd**::

Place the current dir on stack and change directory.

Usage:\

%pushd ['dirname']

**%pwd**::

Return the current working directory path.

**%pycat**::

Show a syntax-highlighted file through a pager.

This magic is similar to the cat utility, but it will assume the file

to be Python source and will show it with syntax highlighting.

**%quickref**::

Show a quick reference sheet

**%quit**::

Exit IPython, confirming if configured to do so (like %exit)

**%r**::

Repeat previous input.

Note: Consider using the more powerfull %rep instead!

If given an argument, repeats the previous command which starts with

the same string, otherwise it just repeats the previous input.

Shell escaped commands (with ! as first character) are not recognized

by this system, only pure python code and magic commands.

**%rehashdir**::

Add executables in all specified dirs to alias table

Usage:

%rehashdir c:/bin;c:/tools

- Add all executables under c:/bin and c:/tools to alias table, in

order to make them directly executable from any directory.

Without arguments, add all executables in current directory.

**%rehashx**::

Update the alias table with all executable files in $PATH.

This version explicitly checks that every entry in $PATH is a file

with execute access (os.X_OK), so it is much slower than %rehash.

Under Windows, it checks executability as a match agains a

'|'-separated string of extensions, stored in the IPython config

variable win_exec_ext. This defaults to 'exe|com|bat'.

This function also resets the root module cache of module completer,

used on slow filesystems.

**%rep**::

Repeat a command, or get command to input line for editing

- %rep (no arguments):

Place a string version of last computation result (stored in the special '_'

variable) to the next input prompt. Allows you to create elaborate command

lines without using copy-paste::

$ l = ["hei", "vaan"]

$ "".join(l)

==> heivaan

$ %rep

$ heivaan_ <== cursor blinking

%rep 45

Place history line 45 to next input prompt. Use %hist to find out the

number.

%rep 1-4 6-7 3

Repeat the specified lines immediately. Input slice syntax is the same as

in %macro and %save.

%rep foo

Place the most recent line that has the substring "foo" to next input.

(e.g. 'svn ci -m foobar').

**%reset**::

Resets the namespace by removing all names defined by the user.

Input/Output history are left around in case you need them.

**%run**::

Run the named file inside IPython as a program.

Usage:\

%run [-n -i -t [-N<N>] -d [-b<N>] -p [profile options]] file [args]

Parameters after the filename are passed as command-line arguments to

the program (put in sys.argv). Then, control returns to IPython's

prompt.

This is similar to running at a system prompt:\

$ python file args\

but with the advantage of giving you IPython's tracebacks, and of

loading all variables into your interactive namespace for further use

(unless -p is used, see below).

The file is executed in a namespace initially consisting only of

__name__=='__main__' and sys.argv constructed as indicated. It thus

sees its environment as if it were being run as a stand-alone program

(except for sharing global objects such as previously imported

modules). But after execution, the IPython interactive namespace gets

updated with all variables defined in the program (except for __name__

and sys.argv). This allows for very convenient loading of code for

interactive work, while giving each program a 'clean sheet' to run in.

Options:

-n: __name__ is NOT set to '__main__', but to the running file's name

without extension (as python does under import). This allows running

scripts and reloading the definitions in them without calling code

protected by an ' if __name__ == "__main__" ' clause.

-i: run the file in IPython's namespace instead of an empty one. This

is useful if you are experimenting with code written in a text editor

which depends on variables defined interactively.

-e: ignore sys.exit() calls or SystemExit exceptions in the script

being run. This is particularly useful if IPython is being used to

run unittests, which always exit with a sys.exit() call. In such

cases you are interested in the output of the test results, not in

seeing a traceback of the unittest module.

-t: print timing information at the end of the run. IPython will give

you an estimated CPU time consumption for your script, which under

Unix uses the resource module to avoid the wraparound problems of

time.clock(). Under Unix, an estimate of time spent on system tasks

is also given (for Windows platforms this is reported as 0.0).

If -t is given, an additional -N<N> option can be given, where <N>

must be an integer indicating how many times you want the script to

run. The final timing report will include total and per run results.

For example (testing the script uniq_stable.py):

In [1]: run -t uniq_stable

IPython CPU timings (estimated):\

User : 0.19597 s.\

System: 0.0 s.\

In [2]: run -t -N5 uniq_stable

IPython CPU timings (estimated):\

Total runs performed: 5\

Times : Total Per run\

User : 0.910862 s, 0.1821724 s.\

System: 0.0 s, 0.0 s.

-d: run your program under the control of pdb, the Python debugger.

This allows you to execute your program step by step, watch variables,

etc. Internally, what IPython does is similar to calling:

pdb.run('execfile("YOURFILENAME")')

with a breakpoint set on line 1 of your file. You can change the line

number for this automatic breakpoint to be <N> by using the -bN option

(where N must be an integer). For example:

%run -d -b40 myscript

will set the first breakpoint at line 40 in myscript.py. Note that

the first breakpoint must be set on a line which actually does

something (not a comment or docstring) for it to stop execution.

When the pdb debugger starts, you will see a (Pdb) prompt. You must

first enter 'c' (without qoutes) to start execution up to the first

breakpoint.

Entering 'help' gives information about the use of the debugger. You

can easily see pdb's full documentation with "import pdb;pdb.help()"

at a prompt.

-p: run program under the control of the Python profiler module (which

prints a detailed report of execution times, function calls, etc).

You can pass other options after -p which affect the behavior of the

profiler itself. See the docs for %prun for details.

In this mode, the program's variables do NOT propagate back to the

IPython interactive namespace (because they remain in the namespace

where the profiler executes them).

Internally this triggers a call to %prun, see its documentation for

details on the options available specifically for profiling.

There is one special usage for which the text above doesn't apply:

if the filename ends with .ipy, the file is run as ipython script,

just as if the commands were written on IPython prompt.

**%runlog**::

Run files as logs.

Usage:\

%runlog file1 file2 ...

Run the named files (treating them as log files) in sequence inside

the interpreter, and return to the prompt. This is much slower than

%run because each line is executed in a try/except block, but it

allows running files with syntax errors in them.

Normally IPython will guess when a file is one of its own logfiles, so

you can typically use %run even for logs. This shorthand allows you to

force any file to be treated as a log file.

**%save**::

Save a set of lines to a given filename.

Usage:\

%save [options] filename n1-n2 n3-n4 ... n5 .. n6 ...

Options:

-r: use 'raw' input. By default, the 'processed' history is used,

so that magics are loaded in their transformed version to valid

Python. If this option is given, the raw input as typed as the

command line is used instead.

This function uses the same syntax as %macro for line extraction, but

instead of creating a macro it saves the resulting string to the

filename you specify.

It adds a '.py' extension to the file if you don't do so yourself, and

it asks for confirmation before overwriting existing files.

**%sc**::

Shell capture - execute a shell command and capture its output.

DEPRECATED. Suboptimal, retained for backwards compatibility.

You should use the form 'var = !command' instead. Example:

"%sc -l myfiles = ls ~" should now be written as

"myfiles = !ls ~"

myfiles.s, myfiles.l and myfiles.n still apply as documented

below.

--

%sc [options] varname=command

IPython will run the given command using commands.getoutput(), and

will then update the user's interactive namespace with a variable

called varname, containing the value of the call. Your command can

contain shell wildcards, pipes, etc.

The '=' sign in the syntax is mandatory, and the variable name you

supply must follow Python's standard conventions for valid names.

(A special format without variable name exists for internal use)

Options:

-l: list output. Split the output on newlines into a list before

assigning it to the given variable. By default the output is stored

as a single string.

-v: verbose. Print the contents of the variable.

In most cases you should not need to split as a list, because the

returned value is a special type of string which can automatically

provide its contents either as a list (split on newlines) or as a

space-separated string. These are convenient, respectively, either

for sequential processing or to be passed to a shell command.

For example:

# Capture into variable a

In [9]: sc a=ls *py

# a is a string with embedded newlines

In [10]: a

Out[10]: 'setup.py win32_manual_post_install.py'

# which can be seen as a list:

In [11]: a.l

Out[11]: ['setup.py', 'win32_manual_post_install.py']

# or as a whitespace-separated string:

In [12]: a.s

Out[12]: 'setup.py win32_manual_post_install.py'

# a.s is useful to pass as a single command line:

In [13]: !wc -l $a.s

146 setup.py

130 win32_manual_post_install.py

276 total

# while the list form is useful to loop over:

In [14]: for f in a.l:

....: !wc -l $f

....:

146 setup.py

130 win32_manual_post_install.py

Similiarly, the lists returned by the -l option are also special, in

the sense that you can equally invoke the .s attribute on them to

automatically get a whitespace-separated string from their contents:

In [1]: sc -l b=ls *py

In [2]: b

Out[2]: ['setup.py', 'win32_manual_post_install.py']

In [3]: b.s

Out[3]: 'setup.py win32_manual_post_install.py'

In summary, both the lists and strings used for ouptut capture have

the following special attributes:

.l (or .list) : value as list.

.n (or .nlstr): value as newline-separated string.

.s (or .spstr): value as space-separated string.

**%store**::

Lightweight persistence for python variables.

Example:

ville@badger[~]|1> A = ['hello',10,'world']\

ville@badger[~]|2> %store A\

ville@badger[~]|3> Exit

(IPython session is closed and started again...)

ville@badger:~$ ipython -p pysh\

ville@badger[~]|1> print A

['hello', 10, 'world']

Usage:

%store - Show list of all variables and their current values\

%store <var> - Store the *current* value of the variable to disk\

%store -d <var> - Remove the variable and its value from storage\

%store -z - Remove all variables from storage\

%store -r - Refresh all variables from store (delete current vals)\

%store foo >a.txt - Store value of foo to new file a.txt\

%store foo >>a.txt - Append value of foo to file a.txt\

It should be noted that if you change the value of a variable, you

need to %store it again if you want to persist the new value.

Note also that the variables will need to be pickleable; most basic

python types can be safely %stored.

Also aliases can be %store'd across sessions.

**%sx**::

Shell execute - run a shell command and capture its output.

%sx command

IPython will run the given command using commands.getoutput(), and

return the result formatted as a list (split on '\n'). Since the

output is _returned_, it will be stored in ipython's regular output

cache Out[N] and in the '_N' automatic variables.

Notes:

1) If an input line begins with '!!', then %sx is automatically

invoked. That is, while:

!ls

causes ipython to simply issue system('ls'), typing

!!ls

is a shorthand equivalent to:

%sx ls

2) %sx differs from %sc in that %sx automatically splits into a list,

like '%sc -l'. The reason for this is to make it as easy as possible

to process line-oriented shell output via further python commands.

%sc is meant to provide much finer control, but requires more

typing.

3) Just like %sc -l, this is a list with special attributes:

.l (or .list) : value as list.

.n (or .nlstr): value as newline-separated string.

.s (or .spstr): value as whitespace-separated string.

This is very useful when trying to use such lists as arguments to

system commands.

**%system_verbose**::

Set verbose printing of system calls.

If called without an argument, act as a toggle

**%time**::

Time execution of a Python statement or expression.

The CPU and wall clock times are printed, and the value of the

expression (if any) is returned. Note that under Win32, system time

is always reported as 0, since it can not be measured.

This function provides very basic timing functionality. In Python

2.3, the timeit module offers more control and sophistication, so this

could be rewritten to use it (patches welcome).

Some examples:

In [1]: time 2**128

CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s

Wall time: 0.00

Out[1]: 340282366920938463463374607431768211456L

In [2]: n = 1000000

In [3]: time sum(range(n))

CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s

Wall time: 1.37

Out[3]: 499999500000L

In [4]: time print 'hello world'

hello world

CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s

Wall time: 0.00

Note that the time needed by Python to compile the given expression

will be reported if it is more than 0.1s. In this example, the

actual exponentiation is done by Python at compilation time, so while

the expression can take a noticeable amount of time to compute, that

time is purely due to the compilation:

In [5]: time 3**9999;

CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s

Wall time: 0.00 s

In [6]: time 3**999999;

CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s

Wall time: 0.00 s

Compiler : 0.78 s

**%timeit**::

Time execution of a Python statement or expression

Usage:\

%timeit [-n<N> -r<R> [-t|-c]] statement

Time execution of a Python statement or expression using the timeit

module.

Options:

-n<N>: execute the given statement <N> times in a loop. If this value

is not given, a fitting value is chosen.

-r<R>: repeat the loop iteration <R> times and take the best result.

Default: 3

-t: use time.time to measure the time, which is the default on Unix.

This function measures wall time.

-c: use time.clock to measure the time, which is the default on

Windows and measures wall time. On Unix, resource.getrusage is used

instead and returns the CPU user time.

-p<P>: use a precision of <P> digits to display the timing result.

Default: 3

Examples:\

In [1]: %timeit pass

10000000 loops, best of 3: 53.3 ns per loop

In [2]: u = None

In [3]: %timeit u is None

10000000 loops, best of 3: 184 ns per loop

In [4]: %timeit -r 4 u == None

1000000 loops, best of 4: 242 ns per loop

In [5]: import time

In [6]: %timeit -n1 time.sleep(2)

1 loops, best of 3: 2 s per loop

The times reported by %timeit will be slightly higher than those

reported by the timeit.py script when variables are accessed. This is

due to the fact that %timeit executes the statement in the namespace

of the shell, compared with timeit.py, which uses a single setup

statement to import function or create variables. Generally, the bias

does not matter as long as results from timeit.py are not mixed with

those from %timeit.

**%unalias**::

Remove an alias

**%upgrade**::

Upgrade your IPython installation

This will copy the config files that don't yet exist in your

ipython dir from the system config dir. Use this after upgrading

IPython if you don't wish to delete your .ipython dir.

Call with -nolegacy to get rid of ipythonrc* files (recommended for

new users)

**%which**::

%which <cmd> => search PATH for files matching cmd. Also scans aliases.

Traverses PATH and prints all files (not just executables!) that match the

pattern on command line. Probably more useful in finding stuff

interactively than 'which', which only prints the first matching item.

Also discovers and expands aliases, so you'll see what will be executed

when you call an alias.

Example:

[~]|62> %which d

d -> ls -F --color=auto

== c:\cygwin\bin\ls.exe

c:\cygwin\bin\d.exe

[~]|64> %which diff*

diff3 -> diff3

== c:\cygwin\bin\diff3.exe

diff -> diff

== c:\cygwin\bin\diff.exe

c:\cygwin\bin\diff.exe

c:\cygwin\bin\diff3.exe

**%who**::

Print all interactive variables, with some minimal formatting.

If any arguments are given, only variables whose type matches one of

these are printed. For example:

%who function str

will only list functions and strings, excluding all other types of

variables. To find the proper type names, simply use type(var) at a

command line to see how python prints type names. For example:

In [1]: type('hello')\

Out[1]: <type 'str'>

indicates that the type name for strings is 'str'.

%who always excludes executed names loaded through your configuration

file and things which are internal to IPython.

This is deliberate, as typically you may load many modules and the

purpose of %who is to show you only what you've manually defined.

**%who_ls**::

Return a sorted list of all interactive variables.

If arguments are given, only variables of types matching these

arguments are returned.

**%whos**::

Like %who, but gives some extra information about each variable.

The same type filtering of %who can be applied here.

For all variables, the type is printed. Additionally it prints:

- For {},[],(): their length.

- For numpy and Numeric arrays, a summary with shape, number of

elements, typecode and size in memory.

- Everything else: a string representation, snipping their middle if

too long.

**%xmode**::

Switch modes for the exception handlers.

Valid modes: Plain, Context and Verbose.

If called without arguments, acts as a toggle.

.. magic_end

Access to the standard Python help

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

Fernando Perez

r1695

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.

Brian E Granger

r1258

Fernando Perez

r1695

.. _dynamic_object_info:

Brian E Granger

r1258

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??.

Fernando Perez

r1695

.. _readline:

Brian E Granger

r1258

Readline-based features

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

These features require the GNU readline library, so they won't work if

your Python installation lacks readline support. We will first describe

the default behavior IPython uses, and then how to change it to suit

your preferences.

Command line completion

+++++++++++++++++++++++

At any time, hitting TAB will complete any available python commands or

variable names, and show you a list of the possible completions if

there's no unambiguous one. It will also complete filenames in the

current directory if no python names match what you've typed so far.

Search command history

++++++++++++++++++++++

IPython provides two ways for searching through previous input and thus

reduce the need for repetitive typing:

1. Start typing, and then use Ctrl-p (previous,up) and Ctrl-n

(next,down) to search through only the history items that match

what you've typed so far. If you use Ctrl-p/Ctrl-n at a blank

prompt, they just behave like normal arrow keys.

2. Hit Ctrl-r: opens a search prompt. Begin typing and the system

searches your history for lines that contain what you've typed so

far, completing as much as it can.

Persistent command history across sessions

++++++++++++++++++++++++++++++++++++++++++

IPython will save your input history when it leaves and reload it next

time you restart it. By default, the history file is named

$IPYTHONDIR/history, but if you've loaded a named profile,

'-PROFILE_NAME' is appended to the name. This allows you to keep

separate histories related to various tasks: commands related to

numerical work will not be clobbered by a system shell history, for

example.

Autoindent

++++++++++

IPython can recognize lines ending in ':' and indent the next line,

while also un-indenting automatically after 'raise' or 'return'.

This feature uses the readline library, so it will honor your ~/.inputrc

configuration (or whatever file your INPUTRC variable points to). Adding

the following lines to your .inputrc file can make indenting/unindenting

more convenient (M-i indents, M-u unindents)::

$if Python

"\M-i": " "

"\M-u": "\d\d\d\d"

$endif

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

Warning: this feature is ON by default, but it can cause problems with

the pasting of multi-line indented code (the pasted code gets

re-indented on each line). A magic function %autoindent allows you to

toggle it on/off at runtime. You can also disable it permanently on in

your ipythonrc file (set autoindent 0).

Customizing readline behavior

+++++++++++++++++++++++++++++

All these features are based on the GNU readline library, which has an

extremely customizable interface. Normally, readline is configured via a

file which defines the behavior of the library; the details of the

syntax for this can be found in the readline documentation available

with your system or on the Internet. IPython doesn't read this file (if

it exists) directly, but it does support passing to readline valid

options via a simple interface. In brief, you can customize readline by

setting the following options in your ipythonrc configuration file (note

that these options can not be specified at the command line):

* **readline_parse_and_bind**: this option can appear as many times as

you want, each time defining a string to be executed via a

readline.parse_and_bind() command. The syntax for valid commands

of this kind can be found by reading the documentation for the GNU

readline library, as these commands are of the kind which readline

accepts in its configuration file.

* **readline_remove_delims**: a string of characters to be removed

from the default word-delimiters list used by readline, so that

completions may be performed on strings which contain them. Do not

change the default value unless you know what you're doing.

* **readline_omit__names**: when tab-completion is enabled, hitting

<tab> after a '.' in a name will complete all attributes of an

object, including all the special methods whose names include

double underscores (like __getitem__ or __class__). If you'd

rather not see these names by default, you can set this option to

1. Note that even when this option is set, you can still see those

names by explicitly typing a _ after the period and hitting <tab>:

'name._<tab>' will always complete attribute names starting with '_'.

This option is off by default so that new users see all

attributes of any objects they are dealing with.

You will find the default values along with a corresponding detailed

explanation in your ipythonrc file.

Session logging and restoring

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

Fernando Perez

r1695

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.

Brian E Granger

r1258

Log files can later be reloaded with the -logplay option and IPython

will attempt to 'replay' the log by executing all the lines in it, thus

restoring the state of a previous session. This feature is not quite

perfect, but can still be useful in many cases.

The log files can also be used as a way to have a permanent record of

any code you wrote while experimenting. Log files are regular text files

which you can later open in your favorite text editor to extract code or

to 'clean them up' before using them to replay a session.

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

follows:

%logstart [log_name [log_mode]]

If no name is given, it defaults to a file named 'log' in your

IPYTHONDIR directory, in 'rotate' mode (see below).

'%logstart name' saves to file 'name' in 'backup' mode. It saves your

history up to that point and then continues logging.

%logstart takes a second optional parameter: logging mode. This can be

one of (note that the modes are given unquoted):

* [over:] overwrite existing log_name.

* [backup:] rename (if exists) to log_name~ and start log_name.

* [append:] well, that says it.

* [rotate:] create rotating logs log_name.1~, log_name.2~, etc.

The %logoff and %logon functions allow you to temporarily stop and

resume logging to a file which had previously been started with

%logstart. They will fail (with an explanation) if you try to use them

before logging has been started.

Fernando Perez

r1695

.. _system_shell_access:

Brian E Granger

r1258

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.

Fernando Perez

r1695

.. _input_caching:

Brian E Granger

r1258

Input caching system

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

IPython offers numbered prompts (In/Out) with input and output caching.

All input is saved and can be retrieved as variables (besides the usual

arrow key recall).

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

_i: stores previous input. _ii: next previous. _iii: next-next previous.

_ih : a list of all input _ih[n] is the input from line n and this list

is aliased to the global variable In. If you overwrite In with a

variable of your own, you can remake the assignment to the internal list

with a simple 'In=_ih'.

Additionally, global variables named _i<n> are dynamically created (<n>

being the prompt counter), such that

_i<n> == _ih[<n>] == In[<n>].

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

and In[14].

This allows you to easily cut and paste multi line interactive prompts

by printing them out: they print like a clean string, without prompt

characters. You can also manipulate them like regular variables (they

are strings), modify or exec them (typing 'exec _i9' will re-execute the

contents of input prompt 9, 'exec In[9:14]+In[18]' will re-execute lines

9 through 13 and line 18).

You can also re-execute multiple lines of input easily by using the

magic %macro function (which automates the process and allows

re-execution without having to type 'exec' every time). The macro system

also allows you to re-execute previous lines which include magic

function calls (which require special processing). Type %macro? or see

sec. 6.2 <#sec:magic> for more details on the macro system.

A history function %hist allows you to see any part of your input

history by printing a range of the _i variables.

Fernando Perez

r1695

.. _output_caching:

Brian E Granger

r1258

Output caching system

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

For output that is returned from actions, a system similar to the input

cache exists but using _ instead of _i. Only actions that produce a

result (NOT assignments, for example) are cached. If you are familiar

with Mathematica, IPython's _ variables behave exactly like

Mathematica's % variables.

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

* [_] (a single underscore) : stores previous output, like Python's

default interpreter.

* [__] (two underscores): next previous.

* [___] (three underscores): next-next previous.

Additionally, global variables named _<n> are dynamically created (<n>

being the prompt counter), such that the result of output <n> is always

available as _<n> (don't use the angle brackets, just the number, e.g.

_21).

These global variables are all stored in a global dictionary (not a

list, since it only has entries for lines which returned a result)

available under the names _oh and Out (similar to _ih and In). So the

output from line 12 can be obtained as _12, Out[12] or _oh[12]. If you

accidentally overwrite the Out variable you can recover it by typing

'Out=_oh' at the prompt.

This system obviously can potentially put heavy memory demands on your

system, since it prevents Python's garbage collector from removing any

previously computed results. You can control how many results are kept

in memory with the option (at the command line or in your ipythonrc

file) cache_size. If you set it to 0, the whole system is completely

disabled and the prompts revert to the classic '>>>' of normal Python.

Directory history

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

Your history of visited directories is kept in the global list _dh, and

the magic %cd command can be used to go to any entry in that list. The

%dhist command allows you to view this history. do ``cd -<TAB`` to

conventiently view the directory history.

Automatic parentheses and quotes

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

These features were adapted from Nathan Gray's LazyPython. They are

meant to allow less typing for common situations.

Automatic parentheses

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

Callable objects (i.e. functions, methods, etc) can be invoked like this

(notice the commas between the arguments)::

>>> callable_ob arg1, arg2, arg3

and the input will be translated to this::

-> callable_ob(arg1, arg2, arg3)

You can force automatic parentheses by using '/' as the first character

of a line. For example::

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

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

>>> print /globals # syntax error

In most cases the automatic algorithm should work, so you should rarely

need to explicitly invoke /. One notable exception is if you are trying

to call a function with a list of tuples as arguments (the parenthesis

will confuse IPython)::

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

but this will work::

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

---> zip ((1,2,3),(4,5,6))

Out[2]= [(1, 4), (2, 5), (3, 6)]

IPython tells you that it has altered your command line by displaying

the new command line preceded by ->. e.g.::

In [18]: callable list

----> callable (list)

Automatic quoting

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

You can force automatic quoting of a function's arguments by using ','

or ';' as the first character of a line. For example::

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

If you use ';' instead, the whole argument is quoted as a single string

(while ',' splits on whitespace)::

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

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

Note that the ',' or ';' MUST be the first character on the line! This

won't work::

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

IPython as your default Python environment

==========================================

Python honors the environment variable PYTHONSTARTUP and will execute at

startup the file referenced by this variable. If you put at the end of

this file the following two lines of code::

import IPython

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

then IPython will be your working environment anytime you start Python.

The sys_exit=1 is needed to have IPython issue a call to sys.exit() when

it finishes, otherwise you'll be back at the normal Python '>>>'

prompt.

This is probably useful to developers who manage multiple Python

versions and don't want to have correspondingly multiple IPython

versions. Note that in this mode, there is no way to pass IPython any

command-line options, as those are trapped first by Python itself.

.. _Embedding:

Embedding IPython

=================

It is possible to start an IPython instance inside your own Python

programs. This allows you to evaluate dynamically the state of your

code, operate with your variables, analyze them, etc. Note however that

any changes you make to values while in the shell do not propagate back

to the running code, so it is safe to modify your values because you

won't break your code in bizarre ways by doing so.

This feature allows you to easily have a fully functional python

environment for doing object introspection anywhere in your code with a

simple function call. In some cases a simple print statement is enough,

but if you need to do more detailed analysis of a code fragment this

feature can be very valuable.

It can also be useful in scientific computing situations where it is

common to need to do some automatic, computationally intensive part and

then stop to look at data, plots, etc.

Opening an IPython instance will give you full access to your data and

functions, and you can resume program execution once you are done with

the interactive part (perhaps to stop again later, as many times as

needed).

The following code snippet is the bare minimum you need to include in

your Python programs for this to work (detailed examples follow later)::

from IPython.Shell import IPShellEmbed

ipshell = IPShellEmbed()

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

You can run embedded instances even in code which is itself being run at

the IPython interactive prompt with '%run <filename>'. Since it's easy

to get lost as to where you are (in your top-level IPython or in your

embedded one), it's a good idea in such cases to set the in/out prompts

to something different for the embedded instances. The code examples

below illustrate this.

You can also have multiple IPython instances in your program and open

them separately, for example with different options for data

presentation. If you close and open the same instance multiple times,

its prompt counters simply continue from each execution to the next.

Please look at the docstrings in the Shell.py module for more details on

the use of this system.

The following sample file illustrating how to use the embedding

functionality is provided in the examples directory as example-embed.py.

It should be fairly self-explanatory::

#!/usr/bin/env python

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

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

The accompanying file example-embed-short.py has quick code fragments for

embedding which you can cut and paste in your code once you understand how

things work.

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

# The basics to get you going:

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

# copies running.

# Try running this code both at the command line and from inside IPython (with

# %run example-embed.py)

try:

__IPYTHON__

except NameError:

nested = 0

args = ['']

else:

print "Running nested copies of IPython."

print "The prompts for the nested copy have been modified"

nested = 1

# what the embedded instance will see as sys.argv:

args = ['-pi1','In <\\#>: ','-pi2',' .\\D.: ',

'-po','Out<\\#>: ','-nosep']

# First import the embeddable shell class

from IPython.Shell import IPShellEmbed

# Now create an instance of the embeddable shell. The first argument is a

# string with options exactly as you would type them if you were starting

# IPython at the system command line. Any parameters you want to define for

# configuration can thus be specified here.

ipshell = IPShellEmbed(args,

banner = 'Dropping into IPython',

exit_msg = 'Leaving Interpreter, back to program.')

# Make a second instance, you can have as many as you want.

if nested:

args[1] = 'In2<\\#>'

else:

args = ['-pi1','In2<\\#>: ','-pi2',' .\\D.: ',

'-po','Out<\\#>: ','-nosep']

ipshell2 = IPShellEmbed(args,banner = 'Second IPython instance.')

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

# You can then call ipshell() anywhere you need it (with an optional

# message):

ipshell('***Called from top level. '

'Hit Ctrl-D to exit interpreter and continue program.\n'

'Note that if you use %kill_embedded, you can fully deactivate\n'

'This embedded instance so it will never turn on again')

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

#---------------------------------------------------------------------------

# More details:

# IPShellEmbed instances don't print the standard system banner and

# messages. The IPython banner (which actually may contain initialization

# messages) is available as <instance>.IP.BANNER in case you want it.

# IPShellEmbed instances print the following information everytime they

# start:

# - A global startup banner.

# - A call-specific header string, which you can use to indicate where in the

# execution flow the shell is starting.

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

# Both the startup banner and the exit message default to None, and can be set

# either at the instance constructor or at any other time with the

# set_banner() and set_exit_msg() methods.

# The shell instance can be also put in 'dummy' mode globally or on a per-call

# basis. This gives you fine control for debugging without having to change

# code all over the place.

# The code below illustrates all this.

# This is how the global banner and exit_msg can be reset at any point

ipshell.set_banner('Entering interpreter - New Banner')

ipshell.set_exit_msg('Leaving interpreter - New exit_msg')

def foo(m):

s = 'spam'

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

print 'foo says m = ',m

def bar(n):

s = 'eggs'

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

print 'bar says n = ',n

# Some calls to the above functions which will trigger IPython:

print 'Main program calling foo("eggs")\n'

foo('eggs')

# The shell can be put in 'dummy' mode where calls to it silently return. This

# allows you, for example, to globally turn off debugging for a program with a

# single call.

ipshell.set_dummy_mode(1)

print '\nTrying to call IPython which is now "dummy":'

ipshell()

print 'Nothing happened...'

# The global 'dummy' mode can still be overridden for a single call

print '\nOverriding dummy mode manually:'

ipshell(dummy=0)

# Reactivate the IPython shell

ipshell.set_dummy_mode(0)

print 'You can even have multiple embedded instances:'

ipshell2()

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

bar('spam')

print 'Main program finished. Bye!'

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

Once you understand how the system functions, you can use the following

code fragments in your programs which are ready for cut and paste::

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

See example-embed.py for full details, this file has the bare minimum code for

cut and paste use once you understand how to use the system."""

#---------------------------------------------------------------------------

# This code loads IPython but modifies a few things if it detects it's running

# embedded in another IPython session (helps avoid confusion)

try:

__IPYTHON__

except NameError:

argv = ['']

banner = exit_msg = ''

else:

# Command-line options for IPython (a list like sys.argv)

argv = ['-pi1','In <\\#>:','-pi2',' .\\D.:','-po','Out<\\#>:']

banner = '*** Nested interpreter ***'

exit_msg = '*** Back in main IPython ***'

# First import the embeddable shell class

from IPython.Shell import IPShellEmbed

# Now create the IPython shell instance. Put ipshell() anywhere in your code

# where you want it to open.

ipshell = IPShellEmbed(argv,banner=banner,exit_msg=exit_msg)

#---------------------------------------------------------------------------

# This code will load an embeddable IPython shell always with no changes for

# nested embededings.

from IPython.Shell import IPShellEmbed

ipshell = IPShellEmbed()

# Now ipshell() will open IPython anywhere in the code.

#---------------------------------------------------------------------------

# This code loads an embeddable shell only if NOT running inside

# IPython. Inside IPython, the embeddable shell variable ipshell is just a

# dummy function.

try:

__IPYTHON__

except NameError:

from IPython.Shell import IPShellEmbed

ipshell = IPShellEmbed()

# Now ipshell() will open IPython anywhere in the code

else:

# Define a dummy ipshell() so the same code doesn't crash inside an

# interactive IPython

def ipshell(): pass

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

Using the Python debugger (pdb)

===============================

Running entire programs via pdb

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

pdb, the Python debugger, is a powerful interactive debugger which

allows you to step through code, set breakpoints, watch variables,

etc. IPython makes it very easy to start any script under the control

of pdb, regardless of whether you have wrapped it into a 'main()'

function or not. For this, simply type '%run -d myscript' at an

IPython prompt. See the %run command's documentation (via '%run?' or

in Sec. magic_ for more details, including how to control where pdb

will stop execution first.

For more information on the use of the pdb debugger, read the included

pdb.doc file (part of the standard Python distribution). On a stock

Linux system it is located at /usr/lib/python2.3/pdb.doc, but the

easiest way to read it is by using the help() function of the pdb module

as follows (in an IPython prompt):

In [1]: import pdb

In [2]: pdb.help()

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

Automatic invocation of pdb on exceptions

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

IPython, if started with the -pdb option (or if the option is set in

your rc file) can call the Python pdb debugger every time your code

triggers an uncaught exception. This feature

can also be toggled at any time with the %pdb magic command. This can be

extremely useful in order to find the origin of subtle bugs, because pdb

opens up at the point in your code which triggered the exception, and

while your program is at this point 'dead', all the data is still

available and you can walk up and down the stack frame and understand

the origin of the problem.

Furthermore, you can use these debugging facilities both with the

embedded IPython mode and without IPython at all. For an embedded shell

(see sec. Embedding_), simply call the constructor with

'-pdb' in the argument string and automatically pdb will be called if an

uncaught exception is triggered by your code.

For stand-alone use of the feature in your programs which do not use

IPython at all, put the following lines toward the top of your 'main'

routine::

import sys,IPython.ultraTB

sys.excepthook = IPython.ultraTB.FormattedTB(mode='Verbose',

color_scheme='Linux', call_pdb=1)

The mode keyword can be either 'Verbose' or 'Plain', giving either very

detailed or normal tracebacks respectively. The color_scheme keyword can

be one of 'NoColor', 'Linux' (default) or 'LightBG'. These are the same

options which can be set in IPython with -colors and -xmode.

This will give any of your programs detailed, colored tracebacks with

automatic invocation of pdb.

Extensions for syntax processing

================================

This isn't for the faint of heart, because the potential for breaking

things is quite high. But it can be a very powerful and useful feature.

In a nutshell, you can redefine the way IPython processes the user input

line to accept new, special extensions to the syntax without needing to

change any of IPython's own code.

In the IPython/Extensions directory you will find some examples

supplied, which we will briefly describe now. These can be used 'as is'

(and both provide very useful functionality), or you can use them as a

starting point for writing your own extensions.

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

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

In the python tutorial it is common to find code examples which have

been taken from real python sessions. The problem with those is that all

the lines begin with either '>>> ' or '... ', which makes it impossible

to paste them all at once. One must instead do a line by line manual

copying, carefully removing the leading extraneous characters.

This extension identifies those starting characters and removes them

from the input automatically, so that one can paste multi-line examples

directly into IPython, saving a lot of time. Please look at the file

InterpreterPasteInput.py in the IPython/Extensions directory for details

on how this is done.

IPython comes with a special profile enabling this feature, called

tutorial. Simply start IPython via 'ipython -p tutorial' and the feature

will be available. In a normal IPython session you can activate the

feature by importing the corresponding module with:

In [1]: import IPython.Extensions.InterpreterPasteInput

The following is a 'screenshot' of how things work when this extension

is on, copying an example from the standard tutorial::

IPython profile: tutorial

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

In [1]: >>> def fib2(n): # return Fibonacci series up to n

...: ... """Return a list containing the Fibonacci series up to

n."""

...: ... result = []

...: ... a, b = 0, 1

...: ... while b < n:

...: ... result.append(b) # see below

...: ... a, b = b, a+b

...: ... return result

...:

In [2]: fib2(10)

Out[2]: [1, 1, 2, 3, 5, 8]

Note that as currently written, this extension does not recognize

IPython's prompts for pasting. Those are more complicated, since the

user can change them very easily, they involve numbers and can vary in

length. One could however extract all the relevant information from the

IPython instance and build an appropriate regular expression. This is

left as an exercise for the reader.

Input of physical quantities with units

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

The module PhysicalQInput allows a simplified form of input for physical

quantities with units. This file is meant to be used in conjunction with

the PhysicalQInteractive module (in the same directory) and

Physics.PhysicalQuantities from Konrad Hinsen's ScientificPython

(http://dirac.cnrs-orleans.fr/ScientificPython/).

The Physics.PhysicalQuantities module defines PhysicalQuantity objects,

but these must be declared as instances of a class. For example, to

define v as a velocity of 3 m/s, normally you would write::

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

Using the PhysicalQ_Input extension this can be input instead as:

In [1]: v = 3 m/s

which is much more convenient for interactive use (even though it is

blatantly invalid Python syntax).

The physics profile supplied with IPython (enabled via 'ipython -p

physics') uses these extensions, which you can also activate with:

from math import * # math MUST be imported BEFORE PhysicalQInteractive

from IPython.Extensions.PhysicalQInteractive import *

import IPython.Extensions.PhysicalQInput

Threading support

=================

WARNING: The threading support is still somewhat experimental, and it

has only seen reasonable testing under Linux. Threaded code is

particularly tricky to debug, and it tends to show extremely

platform-dependent behavior. Since I only have access to Linux machines,

I will have to rely on user's experiences and assistance for this area

of IPython to improve under other platforms.

IPython, via the -gthread , -qthread, -q4thread and -wthread options

(described in Sec. `Threading options`_), can run in

multithreaded mode to support pyGTK, Qt3, Qt4 and WXPython applications

respectively. These GUI toolkits need to control the python main loop of

execution, so under a normal Python interpreter, starting a pyGTK, Qt3,

Qt4 or WXPython application will immediately freeze the shell.

IPython, with one of these options (you can only use one at a time),

separates the graphical loop and IPython's code execution run into

different threads. This allows you to test interactively (with %run, for

example) your GUI code without blocking.

A nice mini-tutorial on using IPython along with the Qt Designer

application is available at the SciPy wiki:

http://www.scipy.org/Cookbook/Matplotlib/Qt_with_IPython_and_Designer.

Tk issues

---------

As indicated in Sec. `Threading options`_, a special -tk option is

provided to try and allow Tk graphical applications to coexist

interactively with WX, Qt or GTK ones. Whether this works at all,

however, is very platform and configuration dependent. Please

experiment with simple test cases before committing to using this

combination of Tk and GTK/Qt/WX threading in a production environment.

I/O pitfalls

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

Be mindful that the Python interpreter switches between threads every

$N$ bytecodes, where the default value as of Python 2.3 is $N=100.$ This

value can be read by using the sys.getcheckinterval() function, and it

can be reset via sys.setcheckinterval(N). This switching of threads can

cause subtly confusing effects if one of your threads is doing file I/O.

In text mode, most systems only flush file buffers when they encounter a

'\n'. An instruction as simple as::

print >> filehandle, ''hello world''

actually consists of several bytecodes, so it is possible that the

newline does not reach your file before the next thread switch.

Similarly, if you are writing to a file in binary mode, the file won't

be flushed until the buffer fills, and your other thread may see

apparently truncated files.

For this reason, if you are using IPython's thread support and have (for

example) a GUI application which will read data generated by files

written to from the IPython thread, the safest approach is to open all

of your files in unbuffered mode (the third argument to the file/open

function is the buffering value)::

filehandle = open(filename,mode,0)

This is obviously a brute force way of avoiding race conditions with the

file buffering. If you want to do it cleanly, and you have a resource

which is being shared by the interactive IPython loop and your GUI

thread, you should really handle it with thread locking and

syncrhonization properties. The Python documentation discusses these.

Fernando Perez

r1695

.. _interactive_demos:

Brian E Granger

r1258

Interactive demos with IPython

==============================

IPython ships with a basic system for running scripts interactively in

sections, useful when presenting code to audiences. A few tags embedded

in comments (so that the script remains valid Python code) divide a file

into separate blocks, and the demo can be run one block at a time, with

IPython printing (with syntax highlighting) the block before executing

it, and returning to the interactive prompt after each block. The

interactive namespace is updated after each block is run with the

contents of the demo's namespace.

This allows you to show a piece of code, run it and then execute

interactively commands based on the variables just created. Once you

want to continue, you simply execute the next block of the demo. The

following listing shows the markup necessary for dividing a script into

sections for execution as a demo::

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

Any python script can be run as a demo, but that does little more than showing

it on-screen, syntax-highlighted in one shot. If you add a little simple

markup, you can stop at specified intervals and return to the ipython prompt,

resuming execution later.

"""

print 'Hello, welcome to an interactive IPython demo.'

print 'Executing this block should require confirmation before proceeding,'

print 'unless auto_all has been set to true in the demo object'

# The mark below defines a block boundary, which is a point where IPython will

# stop execution and return to the interactive prompt.

# Note that in actual interactive execution,

# <demo> --- stop ---

x = 1

y = 2

# <demo> --- stop ---

# the mark below makes this block as silent

# <demo> silent

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

# <demo> --- stop ---

# <demo> auto

print 'This is an automatic block.'

print 'It is executed without asking for confirmation, but printed.'

z = x+y

print 'z=',x

# <demo> --- stop ---

# This is just another normal block.

print 'z is now:', z

print 'bye!'

In order to run a file as a demo, you must first make a Demo object out

of it. If the file is named myscript.py, the following code will make a

demo::

from IPython.demo import Demo

mydemo = Demo('myscript.py')

This creates the mydemo object, whose blocks you run one at a time by

simply calling the object with no arguments. If you have autocall active

in IPython (the default), all you need to do is type::

mydemo

and IPython will call it, executing each block. Demo objects can be

restarted, you can move forward or back skipping blocks, re-execute the

last block, etc. Simply use the Tab key on a demo object to see its

methods, and call '?' on them to see their docstrings for more usage

details. In addition, the demo module itself contains a comprehensive

docstring, which you can access via::

from IPython import demo

demo?

Limitations: It is important to note that these demos are limited to

fairly simple uses. In particular, you can not put division marks in

indented code (loops, if statements, function definitions, etc.)

Supporting something like this would basically require tracking the

internal execution state of the Python interpreter, so only top-level

divisions are allowed. If you want to be able to open an IPython

instance at an arbitrary point in a program, you can use IPython's

embedding facilities, described in detail in Sec. 9

.. _Matplotlib support:

Plotting with matplotlib

========================

The matplotlib library (http://matplotlib.sourceforge.net

http://matplotlib.sourceforge.net) provides high quality 2D plotting for

Python. Matplotlib can produce plots on screen using a variety of GUI

toolkits, including Tk, GTK and WXPython. It also provides a number of

commands useful for scientific computing, all with a syntax compatible

with that of the popular Matlab program.

Fernando Perez

r1695

IPython accepts the special option -pylab (see :ref:`here

<command_line_options>`). This configures it to support matplotlib, honoring

the settings in the .matplotlibrc file. IPython will detect the user's choice

of matplotlib GUI backend, and automatically select the proper threading model

to prevent blocking. It also sets matplotlib in interactive mode and modifies

%run slightly, so that any matplotlib-based script can be executed using %run

and the final show() command does not block the interactive shell.

The -pylab option must be given first in order for IPython to configure its

threading mode. However, you can still issue other options afterwards. This

allows you to have a matplotlib-based environment customized with additional

modules using the standard IPython profile mechanism (see :ref:`here

<profiles>`): ``ipython -pylab -p myprofile`` will load the profile defined in

ipythonrc-myprofile after configuring matplotlib.

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