Contents:
This is the official documentation for IPython 0.x series (i.e. what we are used to refer to just as “IPython”). The original text of the manual (most of which is still in place) has been authored by Fernando Perez, but as recommended usage patterns and new features have emerged, this manual has been updated to reflect that fact. Most of the additions have been authored by Ville M. Vainio.
The manual has been generated from reStructuredText source markup with Sphinx, which should make it much easier to keep it up-to-date in the future. Some reST artifacts and bugs may still be apparent in the documentation, but this should improve as the toolchain matures.
One of Python’s most useful features is its interactive interpreter. This system allows very fast testing of ideas without the overhead of creating test files as is typical in most programming languages. However, the interpreter supplied with the standard Python distribution is somewhat limited for extended interactive use.
IPython is a free software project (released under the BSD license) which tries to:
- Provide an interactive shell superior to Python’s default. IPython has many features for object introspection, system shell access, and its own special command system for adding functionality when working interactively. It tries to be a very efficient environment both for Python code development and for exploration of problems using Python objects (in situations like data analysis).
- Serve as an embeddable, ready to use interpreter for your own programs. IPython can be started with a single call from inside another program, providing access to the current namespace. This can be very useful both for debugging purposes and for situations where a blend of batch-processing and interactive exploration are needed.
- Offer a flexible framework which can be used as the base environment for other systems with Python as the underlying language. Specifically scientific environments like Mathematica, IDL and Matlab inspired its design, but similar ideas can be useful in many fields.
- Allow interactive testing of threaded graphical toolkits. IPython has support for interactive, non-blocking control of GTK, Qt and WX applications via special threading flags. The normal Python shell can only do this for Tkinter applications.
Python requirements: IPython requires with Python version 2.3 or newer. If you are still using Python 2.2 and can not upgrade, the last version of IPython which worked with Python 2.2 was 0.6.15, so you will have to use that.
IPython is developed under Linux, but it should work in any reasonable Unix-type system (tested OK under Solaris and the BSD family, for which a port exists thanks to Dryice Liu).
Mac OS X: it works, apparently without any problems (thanks to Jim Boyle at Lawrence Livermore for the information). Thanks to Andrea Riciputi, Fink support is available.
CygWin: it works mostly OK, though some users have reported problems with prompt coloring. No satisfactory solution to this has been found so far, you may want to disable colors permanently in the ipythonrc configuration file if you experience problems. If you have proper color support under cygwin, please post to the IPython mailing list so this issue can be resolved for all users.
Windows: it works well under Windows Vista/XP/2k, and I suspect NT should behave similarly. Section “Installation under windows” describes installation details for Windows, including some additional tools needed on this platform.
Windows 9x support is present, and has been reported to work fine (at least on WinME).
IPython is generously hosted at http://ipython.scipy.org by the Enthought, Inc and the SciPy project. This site offers downloads, subversion access, mailing lists and a bug tracking system. I am very grateful to Enthought (http://www.enthought.com) and all of the SciPy team for their contribution.
If you are of the impatient kind, under Linux/Unix simply untar/unzip the download, then install with ‘python setup.py install’. Under Windows, double-click on the provided .exe binary installer.
Then, take a look at Customization section for configuring things optimally and Quick tips for quick tips on efficient use of IPython. You can later refer to the rest of the manual for all the gory details.
See the notes in upgrading section for upgrading IPython versions.
Detailed Unix instructions (Linux, Mac OS X, etc.)
For RPM based systems, simply install the supplied package in the usual manner. If you download the tar archive, the process is:
Unzip/untar the ipython-XXX.tar.gz file wherever you want (XXX is the version number). It will make a directory called ipython-XXX. Change into that directory where you will find the files README and setup.py. Once you’ve completed the installation, you can safely remove this directory.
If you are installing over a previous installation of version 0.2.0 or earlier, first remove your $HOME/.ipython directory, since the configuration file format has changed somewhat (the ‘=’ were removed from all option specifications). Or you can call ipython with the -upgrade option and it will do this automatically for you.
IPython uses distutils, so you can install it by simply typing at the system prompt (don’t type the $):
$ python setup.py installNote that this assumes you have root access to your machine. If you don’t have root access or don’t want IPython to go in the default python directories, you’ll need to use the --home option (or --prefix). For example:
$ python setup.py install --home $HOME/localwill install IPython into $HOME/local and its subdirectories (creating them if necessary). You can type:
$ python setup.py --helpfor more details.
Note that if you change the default location for --home at installation, IPython may end up installed at a location which is not part of your $PYTHONPATH environment variable. In this case, you’ll need to configure this variable to include the actual directory where the IPython/ directory ended (typically the value you give to --home plus /lib/python).
Under OSX, there is a choice you need to make. Apple ships its own build of Python, which lives in the core OSX filesystem hierarchy. You can also manually install a separate Python, either purely by hand (typically in /usr/local) or by using Fink, which puts everything under /sw. Which route to follow is a matter of personal preference, as I’ve seen users who favor each of the approaches. Here I will simply list the known installation issues under OSX, along with their solutions.
This page: http://geosci.uchicago.edu/~tobis/pylab.html contains information on this topic, with additional details on how to make IPython and matplotlib play nicely under OSX.
To run IPython and readline on OSX “Leopard” system python, see the wiki page at http://ipython.scipy.org/moin/InstallationOSXLeopard
The following instructions apply to an install of IPython under OSX from unpacking the .tar.gz distribution and installing it for the default Python interpreter shipped by Apple. If you are using a fink install, fink will take care of these details for you, by installing IPython against fink’s Python.
IPython offers various forms of support for interacting with graphical applications from the command line, from simple Tk apps (which are in principle always supported by Python) to interactive control of WX, Qt and GTK apps. Under OSX, however, this requires that ipython is installed by calling the special pythonw script at installation time, which takes care of coordinating things with Apple’s graphical environment.
So when installing under OSX, it is best to use the following command:
$ sudo pythonw setup.py install --install-scripts=/usr/local/bin
or
$ sudo pythonw setup.py install –install-scripts=/usr/bin
depending on where you like to keep hand-installed executables.
The resulting script will have an appropriate shebang line (the first line in the script whic begins with #!...) such that the ipython interpreter can interact with the OS X GUI. If the installed version does not work and has a shebang line that points to, for example, just /usr/bin/python, then you might have a stale, cached version in your build/scripts-<python-version> directory. Delete that directory and rerun the setup.py.
It is also a good idea to use the special flag --install-scripts as indicated above, to ensure that the ipython scripts end up in a location which is part of your $PATH. Otherwise Apple’s Python will put the scripts in an internal directory not available by default at the command line (if you use /usr/local/bin, you need to make sure this is in your $PATH, which may not be true by default).
By default, the Python version shipped by Apple does not include the readline library, so central to IPython’s behavior. If you install IPython against Apple’s Python, you will not have arrow keys, tab completion, etc. For Mac OSX 10.3 (Panther), you can find a prebuilt readline library here: http://pythonmac.org/packages/readline-5.0-py2.3-macosx10.3.zip
If you are using OSX 10.4 (Tiger), after installing this package you need to either:
- move readline.so from /Library/Python/2.3 to /Library/Python/2.3/site-packages, or
- install http://pythonmac.org/packages/TigerPython23Compat.pkg.zip
Users installing against Fink’s Python or a properly hand-built one should not have this problem.
I report here a message from an OSX user, who suggests an alternative means of using IPython under this operating system with good results. Please let me know of any updates that may be useful for this section. His message is reproduced verbatim below:
From: Markus Banfi <markus.banfi-AT-mospheira.net>
As a MacOS X (10.4.2) user I prefer to install software using DawinPorts instead of Fink. I had no problems installing ipython with DarwinPorts. It’s just:
sudo port install py-ipython
It automatically resolved all dependencies (python24, readline, py-readline). So far I did not encounter any problems with the DarwinPorts port of ipython.
Some of IPython’s very useful features are:
- Integrated readline support (Tab-based file, object and attribute completion, input history across sessions, editable command line, etc.)
- Coloring of prompts, code and tracebacks.
These, by default, are only available under Unix-like operating systems. However, thanks to Gary Bishop’s work, Windows XP/2k users can also benefit from them. His readline library originally implemented both GNU readline functionality and color support, so that IPython under Windows XP/2k can be as friendly and powerful as under Unix-like environments.
This library, now named PyReadline, has been absorbed by the IPython team (Jörgen Stenarson, in particular), and it continues to be developed with new features, as well as being distributed directly from the IPython site.
The PyReadline extension requires CTypes and the windows IPython installer needs PyWin32, so in all you need:
- PyWin32 from http://sourceforge.net/projects/pywin32.
- PyReadline for Windows from http://ipython.scipy.org/moin/PyReadline/Intro. That page contains further details on using and configuring the system to your liking.
- Finally, only if you are using Python 2.3 or 2.4, you need CTypes from http://starship.python.net/crew/theller/ctypes(you must use version 0.9.1 or newer). This package is included in Python 2.5, so you don’t need to manually get it if your Python version is 2.5 or newer.
Warning about a broken readline-like library: several users have reported problems stemming from using the pseudo-readline library at http://newcenturycomputers.net/projects/readline.html. This is a broken library which, while called readline, only implements an incomplete subset of the readline API. Since it is still called readline, it fools IPython’s detection mechanisms and causes unpredictable crashes later. If you wish to use IPython under Windows, you must NOT use this library, which for all purposes is (at least as of version 1.6) terminally broken.
Once you have the above installed, from the IPython download directory grab the ipython-XXX.win32.exe file, where XXX represents the version number. This is a regular windows executable installer, which you can simply double-click to install. It will add an entry for IPython to your Start Menu, as well as registering IPython in the Windows list of applications, so you can later uninstall it from the Control Panel.
IPython tries to install the configuration information in a directory named .ipython (_ipython under Windows) located in your ‘home’ directory. IPython sets this directory by looking for a HOME environment variable; if such a variable does not exist, it uses HOMEDRIVEHOMEPATH (these are always defined by Windows). This typically gives something like C:Documents and SettingsYourUserName, but your local details may vary. In this directory you will find all the files that configure IPython’s defaults, and you can put there your profiles and extensions. This directory is automatically added by IPython to sys.path, so anything you place there can be found by import statements.
For an IPython upgrade, you should first uninstall the previous version. This will ensure that all files and directories (such as the documentation) which carry embedded version strings in their names are properly removed.
In case the automatic installer does not work for some reason, you can download the ipython-XXX.tar.gz file, which contains the full IPython source distribution (the popular WinZip can read .tar.gz files). After uncompressing the archive, you can install it at a command terminal just like any other Python module, by using ‘python setup.py install’.
After the installation, run the supplied win32_manual_post_install.py script, which creates the necessary Start Menu shortcuts for you.
If you are upgrading from a previous version of IPython, you may want to upgrade the contents of your ~/.ipython directory. Just run %upgrade, look at the diffs and delete the suggested files manually, if you think you can lose the old versions. %upgrade will never overwrite or delete anything.
This section will help you set various things in your environment for your IPython sessions to be as efficient as possible. All of IPython’s configuration information, along with several example files, is stored in a directory named by default $HOME/.ipython. You can change this by defining the environment variable IPYTHONDIR, or at runtime with the command line option -ipythondir.
If all goes well, the first time you run IPython it should automatically create a user copy of the config directory for you, based on its builtin defaults. You can look at the files it creates to learn more about configuring the system. The main file you will modify to configure IPython’s behavior is called ipythonrc (with a .ini extension under Windows), included for reference in ipythonrc section. This file is very commented and has many variables you can change to suit your taste, you can find more details in Sec. customization. Here we discuss the basic things you will want to make sure things are working properly from the beginning.
This is true for Python in general (not just for IPython): you should have an environment variable called PYTHONDOCS pointing to the directory where your HTML Python documentation lives. In my system it’s /usr/share/doc/python-docs-2.3.4/html, check your local details or ask your systems administrator.
This is the directory which holds the HTML version of the Python manuals. Unfortunately it seems that different Linux distributions package these files differently, so you may have to look around a bit. Below I show the contents of this directory on my system for reference:
[html]> ls about.dat acks.html dist/ ext/ index.html lib/ modindex.html stdabout.dat tut/ about.html api/ doc/ icons/ inst/ mac/ ref/ style.css
You should really make sure this variable is correctly set so that Python’s pydoc-based help system works. It is a powerful and convenient system with full access to the Python manuals and all modules accessible to you.
Under Windows it seems that pydoc finds the documentation automatically, so no extra setup appears necessary.
The %edit command (and its alias %ed) will invoke the editor set in your environment as EDITOR. If this variable is not set, it will default to vi under Linux/Unix and to notepad under Windows. You may want to set this variable properly and to a lightweight editor which doesn’t take too long to start (that is, something other than a new instance of Emacs). This way you can edit multi-line code quickly and with the power of a real editor right inside IPython.
If you are a dedicated Emacs user, you should set up the Emacs server so that new requests are handled by the original process. This means that almost no time is spent in handling the request (assuming an Emacs process is already running). For this to work, you need to set your EDITOR environment variable to ‘emacsclient’. The code below, supplied by Francois Pinard, can then be used in your .emacs file to enable the server:
(defvar server-buffer-clients)
(when (and (fboundp 'server-start) (string-equal (getenv "TERM") 'xterm))
(server-start)
(defun fp-kill-server-with-buffer-routine ()
(and server-buffer-clients (server-done)))
(add-hook 'kill-buffer-hook 'fp-kill-server-with-buffer-routine))
You can also set the value of this editor via the commmand-line option ‘-editor’ or in your ipythonrc file. This is useful if you wish to use specifically for IPython an editor different from your typical default (and for Windows users who tend to use fewer environment variables).
The default IPython configuration has most bells and whistles turned on (they’re pretty safe). But there’s one that may cause problems on some systems: the use of color on screen for displaying information. This is very useful, since IPython can show prompts and exception tracebacks with various colors, display syntax-highlighted source code, and in general make it easier to visually parse information.
The following terminals seem to handle the color sequences fine:
- Linux main text console, KDE Konsole, Gnome Terminal, E-term, rxvt, xterm.
- CDE terminal (tested under Solaris). This one boldfaces light colors.
- (X)Emacs buffers. See the emacs section for more details on using IPython with (X)Emacs.
- A Windows (XP/2k) command prompt with pyreadline.
- A Windows (XP/2k) CygWin shell. Although some users have reported problems; it is not clear whether there is an issue for everyone or only under specific configurations. If you have full color support under cygwin, please post to the IPython mailing list so this issue can be resolved for all users.
These have shown problems:
- Windows command prompt in WinXP/2k logged into a Linux machine via telnet or ssh.
- Windows native command prompt in WinXP/2k, without Gary Bishop’s extensions. Once Gary’s readline library is installed, the normal WinXP/2k command prompt works perfectly.
Currently the following color schemes are available:
- NoColor: uses no color escapes at all (all escapes are empty ‘’ ‘’ strings). This ‘scheme’ is thus fully safe to use in any terminal.
- Linux: works well in Linux console type environments: dark background with light fonts. It uses bright colors for information, so it is difficult to read if you have a light colored background.
- LightBG: the basic colors are similar to those in the Linux scheme but darker. It is easy to read in terminals with light backgrounds.
IPython uses colors for two main groups of things: prompts and tracebacks which are directly printed to the terminal, and the object introspection system which passes large sets of data through a pager.
You can test whether the colored prompts and tracebacks work on your system interactively by typing ‘%colors Linux’ at the prompt (use ‘%colors LightBG’ if your terminal has a light background). If the input prompt shows garbage like:
[0;32mIn [[1;32m1[0;32m]: [0;00m
instead of (in color) something like:
In [1]:
this means that your terminal doesn’t properly handle color escape sequences. You can go to a ‘no color’ mode by typing ‘%colors NoColor’.
You can try using a different terminal emulator program (Emacs users, see below). To permanently set your color preferences, edit the file $HOME/.ipython/ipythonrc and set the colors option to the desired value.
IPython has a set of special functions for studying the objects you are working with, discussed in detail in Sec. dynamic object information. But this system relies on passing information which is longer than your screen through a data pager, such as the common Unix less and more programs. In order to be able to see this information in color, your pager needs to be properly configured. I strongly recommend using less instead of more, as it seems that more simply can not understand colored text correctly.
In order to configure less as your default pager, do the following:
- Set the environment PAGER variable to less.
- Set the environment LESS variable to -r (plus any other options you always want to pass to less by default). This tells less to properly interpret control sequences, which is how color information is given to your terminal.
For the csh or tcsh shells, add to your ~/.cshrc file the lines:
setenv PAGER less setenv LESS -r
There is similar syntax for other Unix shells, look at your system documentation for details.
If you are on a system which lacks proper data pagers (such as Windows), IPython will use a very limited builtin pager.
Thanks to the work of Alexander Schmolck and Prabhu Ramachandran, currently (X)Emacs and IPython get along very well.
Important note: You will need to use a recent enough version of python-mode.el, along with the file ipython.el. You can check that the version you have of python-mode.el is new enough by either looking at the revision number in the file itself, or asking for it in (X)Emacs via M-x py-version. Versions 4.68 and newer contain the necessary fixes for proper IPython support.
The file ipython.el is included with the IPython distribution, in the documentation directory (where this manual resides in PDF and HTML formats).
Once you put these files in your Emacs path, all you need in your .emacs file is:
(require 'ipython)
This should give you full support for executing code snippets via IPython, opening IPython as your Python shell via C-c !, etc.
If you happen to get garbage instead of colored prompts as described in the previous section, you may need to set also in your .emacs file:
(setq ansi-color-for-comint-mode t)
Notes:
- There is one caveat you should be aware of: you must start the IPython shell before attempting to execute any code regions via C-c |. Simply type C-c ! to start IPython before passing any code regions to the interpreter, and you shouldn’t experience any problems. This is due to a bug in Python itself, which has been fixed for Python 2.3, but exists as of Python 2.2.2 (reported as SF bug [ 737947 ]).
- The (X)Emacs support is maintained by Alexander Schmolck, so all comments/requests should be directed to him through the IPython mailing lists.
- This code is still somewhat experimental so it’s a bit rough around the edges (although in practice, it works quite well).
- Be aware that if you customize py-python-command previously, this value will override what ipython.el does (because loading the customization variables comes later).
IPython can be used as an improved replacement for the Python prompt, and for that you don’t really need to read any more of this manual. But in this section we’ll try to summarize a few tips on how to make the most effective use of it for everyday Python development, highlighting things you might miss in the rest of the manual (which is getting long). We’ll give references to parts in the manual which provide more detail when appropriate.
The following article by Jeremy Jones provides an introductory tutorial about IPython: http://www.onlamp.com/pub/a/python/2005/01/27/ipython.html
- The TAB key. TAB-completion, especially for attributes, is a convenient way to explore the structure of any object you’re dealing with. Simply type object_name.<TAB> and a list of the object’s attributes will be printed (see readline for more). Tab completion also works on file and directory names, which combined with IPython’s alias system allows you to do from within IPython many of the things you normally would need the system shell for.
- Explore your objects. Typing object_name? will print all sorts of details about any object, including docstrings, function definition lines (for call arguments) and constructor details for classes. The magic commands %pdoc, %pdef, %psource and %pfile will respectively print the docstring, function definition line, full source code and the complete file for any object (when they can be found). If automagic is on (it is by default), you don’t need to type the ‘%’ explicitly. See sec. dynamic object information for more.
- The %run magic command allows you to run any python script and load all of its data directly into the interactive namespace. Since the file is re-read from disk each time, changes you make to it are reflected immediately (in contrast to the behavior of import). I rarely use import for code I am testing, relying on %run instead. See magic section for more on this and other magic commands, or type the name of any magic command and ? to get details on it. See also sec. dreload for a recursive reload command. %run also has special flags for timing the execution of your scripts (-t) and for executing them under the control of either Python’s pdb debugger (-d) or profiler (-p). With all of these, %run can be used as the main tool for efficient interactive development of code which you write in your editor of choice.
- Use the Python debugger, pdb. The %pdb command allows you to toggle on and off the automatic invocation of an IPython-enhanced pdb debugger (with coloring, tab completion and more) at any uncaught exception. The advantage of this is that pdb starts inside the function where the exception occurred, with all data still available. You can print variables, see code, execute statements and even walk up and down the call stack to track down the true source of the problem (which often is many layers in the stack above where the exception gets triggered). Running programs with %run and pdb active can be an efficient to develop and debug code, in many cases eliminating the need for print statements or external debugging tools. I often simply put a 1/0 in a place where I want to take a look so that pdb gets called, quickly view whatever variables I need to or test various pieces of code and then remove the 1/0. Note also that ‘%run -d’ activates pdb and automatically sets initial breakpoints for you to step through your code, watch variables, etc. See Sec. Output caching for details.
- Use the output cache. All output results are automatically stored in a global dictionary named Out and variables named _1, _2, etc. alias them. For example, the result of input line 4 is available either as Out[4] or as _4. Additionally, three variables named _, __ and ___ are always kept updated with the for the last three results. This allows you to recall any previous result and further use it for new calculations. See Sec. Output caching for more.
- Put a ‘;’ at the end of a line to supress the printing of output. This is useful when doing calculations which generate long output you are not interested in seeing. The _* variables and the Out[] list do get updated with the contents of the output, even if it is not printed. You can thus still access the generated results this way for further processing.
- A similar system exists for caching input. All input is stored in a global list called In , so you can re-execute lines 22 through 28 plus line 34 by typing ‘exec In[22:29]+In[34]’ (using Python slicing notation). If you need to execute the same set of lines often, you can assign them to a macro with the %macro function. See sec. Input caching for more.
- Use your input history. The %hist command can show you all previous input, without line numbers if desired (option -n) so you can directly copy and paste code either back in IPython or in a text editor. You can also save all your history by turning on logging via %logstart; these logs can later be either reloaded as IPython sessions or used as code for your programs.
- Define your own system aliases. Even though IPython gives you access to your system shell via the ! prefix, it is convenient to have aliases to the system commands you use most often. This allows you to work seamlessly from inside IPython with the same commands you are used to in your system shell. IPython comes with some pre-defined aliases and a complete system for changing directories, both via a stack (see %pushd, %popd and %dhist) and via direct %cd. The latter keeps a history of visited directories and allows you to go to any previously visited one.
- Use Python to manipulate the results of system commands. The ‘!!’ special syntax, and the %sc and %sx magic commands allow you to capture system output into Python variables.
- Expand python variables when calling the shell (either via ‘!’ and ‘!!’ or via aliases) by prepending a $ in front of them. You can also expand complete python expressions. See System shell access for more.
- Use profiles to maintain different configurations (modules to load, function definitions, option settings) for particular tasks. You can then have customized versions of IPython for specific purposes. See sec. profiles for more.
- Embed IPython in your programs. A few lines of code are enough to load a complete IPython inside your own programs, giving you the ability to work with your data interactively after automatic processing has been completed. See sec. embedding for more.
- Use the Python profiler. When dealing with performance issues, the %run command with a -p option allows you to run complete programs under the control of the Python profiler. The %prun command does a similar job for single Python expressions (like function calls).
- Use the IPython.demo.Demo class to load any Python script as an interactive demo. With a minimal amount of simple markup, you can control the execution of the script, stopping as needed. See sec. interactive demos for more.
- Run your doctests from within IPython for development and debugging. The special %doctest_mode command toggles a mode where the prompt, output and exceptions display matches as closely as possible that of the default Python interpreter. In addition, this mode allows you to directly paste in code that contains leading ‘>>>’ prompts, even if they have extra leading whitespace (as is common in doctest files). This combined with the ‘%history -tn’ call to see your translated history (with these extra prompts removed and no line numbers) allows for an easy doctest workflow, where you can go from doctest to interactive execution to pasting into valid Python code as needed.
IPython is a line-oriented program, without full control of the terminal. Therefore, it doesn’t support true multiline editing. However, it has a number of useful tools to help you in dealing effectively with more complex editing.
The %edit command gives a reasonable approximation of multiline editing, by invoking your favorite editor on the spot. IPython will execute the code you type in there as if it were typed interactively. Type %edit? for the full details on the edit command.
If you have typed various commands during a session, which you’d like to reuse, IPython provides you with a number of tools. Start by using %hist to see your input history, so you can see the line numbers of all input. Let us say that you’d like to reuse lines 10 through 20, plus lines 24 and 28. All the commands below can operate on these with the syntax:
%command 10-20 24 28
where the command given can be:
- %macro <macroname>: this stores the lines into a variable which, when called at the prompt, re-executes the input. Macros can be edited later using ‘%edit macroname’, and they can be stored persistently across sessions with ‘%store macroname’ (the storage system is per-profile). The combination of quick macros, persistent storage and editing, allows you to easily refine quick-and-dirty interactive input into permanent utilities, always available both in IPython and as files for general reuse.
- %edit: this will open a text editor with those lines pre-loaded for further modification. It will then execute the resulting file’s contents as if you had typed it at the prompt.
- %save <filename>: this saves the lines directly to a named file on disk.
While %macro saves input lines into memory for interactive re-execution, sometimes you’d like to save your input directly to a file. The %save magic does this: its input sytnax is the same as %macro, but it saves your input directly to a Python file. Note that the %logstart command also saves input, but it logs all input to disk (though you can temporarily suspend it and reactivate it with %logoff/%logon); %save allows you to select which lines of input you need to save.
When you call %edit with no arguments, IPython opens an empty editor with a temporary file, and it returns the contents of your editing session as a string variable. Thanks to IPython’s output caching mechanism, this is automatically stored:
In [1]: %edit IPython will make a temporary file named: /tmp/ipython_edit_yR-HCN.py Editing... done. Executing edited code... hello - this is a temporary file Out[1]: "print 'hello - this is a temporary file'\n"
Now, if you call ‘%edit -p’, IPython tries to open an editor with the same data as the last time you used %edit. So if you haven’t used %edit in the meantime, this same contents will reopen; however, it will be done in a new file. This means that if you make changes and you later want to find an old version, you can always retrieve it by using its output number, via ‘%edit _NN’, where NN is the number of the output prompt.
Continuing with the example above, this should illustrate this idea:
In [2]: edit -p IPython will make a temporary file named: /tmp/ipython_edit_nA09Qk.py Editing... done. Executing edited code... hello - now I made some changes Out[2]: "print 'hello - now I made some changes'\n" In [3]: edit _1 IPython will make a temporary file named: /tmp/ipython_edit_gy6-zD.py Editing... done. Executing edited code... hello - this is a temporary file IPython version control at work :) Out[3]: "print 'hello - this is a temporary file'\nprint 'IPython version control at work :)'\n"
This section was written after a contribution by Alexander Belchenko on the IPython user list.
A very useful suggestion sent in by Robert Kern follows:
I recently happened on a nifty way to keep tidy per-project log files. I made a profile for my project (which is called “parkfield”).
include ipythonrc
# cancel earlier logfile invocation:
logfile ‘’
execute import time
execute __cmd = ‘/Users/kern/research/logfiles/parkfield-%s.log rotate’
execute __IP.magic_logstart(__cmd % time.strftime(‘%Y-%m-%d’))
I also added a shell alias for convenience:
alias parkfield=”ipython -pylab -profile parkfield”
Now I have a nice little directory with everything I ever type in, organized by project and date.
Contribute your own: If you have your own favorite tip on using IPython efficiently for a certain task (especially things which can’t be done in the normal Python interpreter), don’t hesitate to send it!
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.
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.
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.
- -[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:
- $HOME/.ipython/ipythonrc : load basic things you always want.
- $HOME/.ipython/ipythonrc-math : load (1) and basic math-related modules.
- $HOME/.ipython/ipythonrc-numeric : load (1) and Numeric and plotting modules.
Since it is possible to create an endless loop by having circular file inclusions, IPython will stop if it reaches 15 recursive inclusions.
- -prompt_in1, pi1 <string>
- Specify the string used for input prompts. Note that if you are using numbered prompts, the number is represented with a ‘#’ in the string. Don’t forget to quote strings with spaces embedded in them. Default: ‘In [#]:’. Sec. Prompts discusses in detail all the available escapes to customize your prompts.
- -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).
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.
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
IPython will treat any line whose first character is a % as a special call to a ‘magic’ function. These allow you to control the behavior of IPython itself, plus a lot of system-type features. They are all prefixed with a % character, but parameters are given without parentheses or quotes.
Example: typing ‘%cd mydir’ (without the quotes) changes you working directory to ‘mydir’, if it exists.
If you have ‘automagic’ enabled (in your ipythonrc file, via the command line option -automagic or with the %automagic function), you don’t need to type in the % explicitly. IPython will scan its internal list of magic functions and call one if it exists. With automagic on you can then just type ‘cd mydir’ to go to directory ‘mydir’. The automagic system has the lowest possible precedence in name searches, so defining an identifier with the same name as an existing magic function will shadow it for automagic use. You can still access the shadowed magic function by explicitly using the % character at the beginning of the line.
An example (with automagic on) should clarify all this:
In [1]: cd ipython # %cd is called by automagic
/home/fperez/ipython
In [2]: cd=1 # now cd is just a variable
In [3]: cd .. # and doesn't work as a function anymore
------------------------------
File "<console>", line 1
cd ..
^
SyntaxError: invalid syntax
In [4]: %cd .. # but %cd always works
/home/fperez
In [5]: del cd # if you remove the cd variable
In [6]: cd ipython # automagic can work again
/home/fperez/ipython
You can define your own magic functions to extend the system. The following example defines a new magic command, %impall:
import IPython.ipapi
ip = IPython.ipapi.get()
def doimp(self, arg):
ip = self.api
ip.ex("import %s; reload(%s); from %s import *" % (
arg,arg,arg)
)
ip.expose_magic('impall', doimp)
You can also define your own aliased names for magic functions. In your ipythonrc file, placing a line like:
execute __IP.magic_cl = __IP.magic_clear
will define %cl as a new name for %clear.
Type %magic for more information, including a list of all available magic functions at any time and their docstrings. You can also type %magic_function_name? (see sec. 6.4 <#sec:dyn-object-info> for information on the ‘?’ system) to get information about any particular magic function you are interested in.
The rest of this section is automatically generated for each release from the docstrings in the IPython code. Therefore the formatting is somewhat minimal, but this method has the advantage of having information always in sync with the code.
A list of all the magic commands available in IPython’s default installation follows. This is similar to what you’ll see by simply typing %magic at the prompt, but that will also give you information about magic commands you may have added as part of your personal customizations.
%Exit:
Exit IPython without confirmation.
%Pprint:
Toggle pretty printing on/off.
%alias:
Define an alias for a system command. '%alias alias_name cmd' defines 'alias_name' as an alias for 'cmd' Then, typing 'alias_name params' will execute the system command 'cmd params' (from your underlying operating system). Aliases have lower precedence than magic functions and Python normal variables, so if 'foo' is both a Python variable and an alias, the alias can not be executed until 'del foo' removes the Python variable. You can use the %l specifier in an alias definition to represent the whole line when the alias is called. For example: In [2]: alias all echo "Input in brackets: <%l>"\ In [3]: all hello world\ Input in brackets: <hello world> You can also define aliases with parameters using %s specifiers (one per parameter): In [1]: alias parts echo first %s second %s\ In [2]: %parts A B\ first A second B\ In [3]: %parts A\ Incorrect number of arguments: 2 expected.\ parts is an alias to: 'echo first %s second %s' Note that %l and %s are mutually exclusive. You can only use one or the other in your aliases. Aliases expand Python variables just like system calls using ! or !! do: all expressions prefixed with '$' get expanded. For details of the semantic rules, see PEP-215: http://www.python.org/peps/pep-0215.html. This is the library used by IPython for variable expansion. If you want to access a true shell variable, an extra $ is necessary to prevent its expansion by IPython: In [6]: alias show echo\ In [7]: PATH='A Python string'\ In [8]: show $PATH\ A Python string\ In [9]: show $$PATH\ /usr/local/lf9560/bin:/usr/local/intel/compiler70/ia32/bin:... You can use the alias facility to acess all of $PATH. See the %rehash and %rehashx functions, which automatically create aliases for the contents of your $PATH. If called with no parameters, %alias prints the current alias table.
%autocall:
Make functions callable without having to type parentheses.
Usage:
%autocall [mode]
The mode can be one of: 0->Off, 1->Smart, 2->Full. If not given, the
value is toggled on and off (remembering the previous state).
In more detail, these values mean:
0 -> fully disabled
1 -> active, but do not apply if there are no arguments on the line.
In this mode, you get:
In [1]: callable
Out[1]: <built-in function callable>
In [2]: callable 'hello'
------> callable('hello')
Out[2]: False
2 -> Active always. Even if no arguments are present, the callable
object is called:
In [4]: callable
------> callable()
Note that even with autocall off, you can still use '/' at the start of
a line to treat the first argument on the command line as a function
and add parentheses to it:
In [8]: /str 43
------> str(43)
Out[8]: '43'
%autoindent:
Toggle autoindent on/off (if available).
%automagic:
Make magic functions callable without having to type the initial %. Without argumentsl toggles on/off (when off, you must call it as %automagic, of course). With arguments it sets the value, and you can use any of (case insensitive): - on,1,True: to activate - off,0,False: to deactivate. Note that magic functions have lowest priority, so if there's a variable whose name collides with that of a magic fn, automagic won't work for that function (you get the variable instead). However, if you delete the variable (del var), the previously shadowed magic function becomes visible to automagic again.
%bg:
Run a job in the background, in a separate thread. For example, %bg myfunc(x,y,z=1) will execute 'myfunc(x,y,z=1)' in a background thread. As soon as the execution starts, a message will be printed indicating the job number. If your job number is 5, you can use myvar = jobs.result(5) or myvar = jobs[5].result to assign this result to variable 'myvar'. IPython has a job manager, accessible via the 'jobs' object. You can type jobs? to get more information about it, and use jobs.<TAB> to see its attributes. All attributes not starting with an underscore are meant for public use. In particular, look at the jobs.new() method, which is used to create new jobs. This magic %bg function is just a convenience wrapper around jobs.new(), for expression-based jobs. If you want to create a new job with an explicit function object and arguments, you must call jobs.new() directly. The jobs.new docstring also describes in detail several important caveats associated with a thread-based model for background job execution. Type jobs.new? for details. You can check the status of all jobs with jobs.status(). The jobs variable is set by IPython into the Python builtin namespace. If you ever declare a variable named 'jobs', you will shadow this name. You can either delete your global jobs variable to regain access to the job manager, or make a new name and assign it manually to the manager (stored in IPython's namespace). For example, to assign the job manager to the Jobs name, use: Jobs = __builtins__.jobs
%bookmark:
Manage IPython's bookmark system. %bookmark <name> - set bookmark to current dir %bookmark <name> <dir> - set bookmark to <dir> %bookmark -l - list all bookmarks %bookmark -d <name> - remove bookmark %bookmark -r - remove all bookmarks You can later on access a bookmarked folder with: %cd -b <name> or simply '%cd <name>' if there is no directory called <name> AND there is such a bookmark defined. Your bookmarks persist through IPython sessions, but they are associated with each profile.
%cd:
Change the current working directory.
This command automatically maintains an internal list of directories
you visit during your IPython session, in the variable _dh. The
command %dhist shows this history nicely formatted. You can also
do 'cd -<tab>' to see directory history conveniently.
Usage:
cd 'dir': changes to directory 'dir'.
cd -: changes to the last visited directory.
cd -<n>: changes to the n-th directory in the directory history.
cd -b <bookmark_name>: jump to a bookmark set by %bookmark
(note: cd <bookmark_name> is enough if there is no
directory <bookmark_name>, but a bookmark with the name exists.)
'cd -b <tab>' allows you to tab-complete bookmark names.
Options:
-q: quiet. Do not print the working directory after the cd command is
executed. By default IPython's cd command does print this directory,
since the default prompts do not display path information.
Note that !cd doesn't work for this purpose because the shell where
!command runs is immediately discarded after executing 'command'.
%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 mo