Overview One of Python’s most useful features is its interactive interpreter. It allows for 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. The goal of IPython is to create a comprehensive environment for interactive and exploratory computing.

To support this goal, IPython has three main components:. An enhanced interactive Python shell. A decoupled, which allows for multiple clients to connect to a computation kernel, most notably the web-based notebook.

An architecture for interactive parallel computing. All of IPython is open source (released under the revised BSD license). Enhanced interactive Python shell IPython’s interactive shell ( ipython), has the following goals, amongst others:. Provide an interactive shell superior to Python’s default.

IPython has many features for tab-completion, object introspection, system shell access, command history retrieval across sessions, 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. An interactive IPython shell 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 working with other systems, with Python as the underlying bridge 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, WX, GLUT, and OS X applications via special threading flags. The normal Python shell can only do this for Tkinter applications. Main features of the interactive shell. Dynamic object introspection.

One can access docstrings, function definition prototypes, source code, source files and other details of any object accessible to the interpreter with a single keystroke (?, and using?? Provides additional detail). Searching through modules and namespaces with. wildcards, both when using the?

System and via the%psearch command. Completion in the local namespace, by typing TAB at the prompt. This works for keywords, modules, methods, variables and files in the current directory.

This is supported via the readline library, and full access to configuring readline’s behavior is provided. Custom completers can be implemented easily for different purposes (system commands, magic arguments etc.). Numbered input/output prompts with command history (persistent across sessions and tied to each profile), full searching in this history and caching of all input and output. User-extensible ‘magic’ commands. A set of commands prefixed with% is available for controlling IPython itself and provides directory control, namespace information and many aliases to common system shell commands. Alias facility for defining your own system aliases. Complete system shell access.

Lines starting with! Are passed directly to the system shell, and using!! Or var =!cmd captures shell output into python variables for further use. The ability to expand python variables when calling the system shell. In a shell command, any python variable prefixed with $ is expanded. A double $$ allows passing a literal $ to the shell (for access to shell and environment variables like PATH). Filesystem navigation, via a magic%cd command, along with a persistent bookmark system (using%bookmark) for fast access to frequently visited directories.

A lightweight persistence framework via the%store command, which allows you to save arbitrary Python variables. These get restored when you run the%store -r command.

Automatic indentation (optional) of code as you type (through the readline library). Macro system for quickly re-executing multiple lines of previous input with a single name via the%macro command. Macros can be stored persistently via%store and edited via%edit. Session logging (you can then later use these logs as code in your programs). Logs can optionally timestamp all input, and also store session output (marked as comments, so the log remains valid Python source code).

Session restoring: logs can be replayed to restore a previous session to the state where you left it. Verbose and colored exception traceback printouts. Easier to parse visually, and in verbose mode they produce a lot of useful debugging information (basically a terminal version of the cgitb module). Auto-parentheses via the%autocall command: callable objects can be executed without parentheses: sin 3 is automatically converted to sin(3). Auto-quoting: using, or; as the first character forces auto-quoting of the rest of the line:,myfunction a b becomes automatically myfunction('a','b'), while;myfunction a b becomes myfunction('a b').

Extensible input syntax. You can define filters that pre-process user input to simplify input in special situations.

This allows for example pasting multi-line code fragments which start with. Such as those from other python sessions or the standard Python documentation. It uses a configuration file which allows permanent setting of all command-line options, module loading, code and file execution. The system allows recursive file inclusion, so you can have a base file with defaults and layers which load other customizations for particular projects. Embeddable. You can call IPython as a python shell inside your own python programs. This can be used both for debugging code or for providing interactive abilities to your programs with knowledge about the local namespaces (very useful in debugging and data analysis situations).

Easy debugger access. You can set IPython to call up an enhanced version of the Python debugger (pdb) every time there is an uncaught exception. This drops you inside the code which triggered the exception with all the data live and it is possible to navigate the stack to rapidly isolate the source of a bug. The%run magic command (with the -d option) can run any script under pdb’s control, automatically setting initial breakpoints for you. This version of pdb has IPython-specific improvements, including tab-completion and traceback coloring support.

For even easier debugger access, try%debug after seeing an exception. Profiler support. You can run single statements (similar to profile.run) or complete programs under the profiler’s control. While this is possible with standard cProfile or profile modules, IPython wraps this functionality with magic commands (see%prun and%run -p) convenient for rapid interactive work.

Simple timing information. You can use the%timeit command to get the execution time of a Python statement or expression. This machinery is intelligent enough to do more repetitions for commands that finish very quickly in order to get a better estimate of their running time. Decoupled two-process model IPython has abstracted and extended the notion of a traditional Read-Evaluate-Print Loop (REPL) environment by decoupling the evaluation into its own process. We call this process a kernel: it receives execution instructions from clients and communicates the results back to them. This decoupling allows us to have several clients connected to the same kernel, and even allows clients and kernels to live on different machines.

With the exclusion of the traditional single process terminal-based IPython (what you start if you run ipython without any subcommands), all other IPython machinery uses this two-process model. This includes ipython console, ipython qtconsole, and ipython notebook. As an example, this means that when you start ipython qtconsole, you’re really starting two processes, a kernel and a Qt-based client can send commands to and receive results from that kernel. If there is already a kernel running that you want to connect to, you can pass the -existing flag which will skip initiating a new kernel and connect to the most recent kernel, instead. To connect to a specific kernel once you have several kernels running, use the%connectinfo magic to get the unique connection file, which will be something like -existing kernel-19732.json but with different numbers which correspond to the Process ID of the kernel. You can read more about using,. There is also a which documents the protocol for communication between kernels and clients.

Interactive parallel computing Increasingly, parallel computer hardware, such as multicore CPUs, clusters and supercomputers, is becoming ubiquitous. Over the last several years, we have developed an architecture within IPython that allows such hardware to be used quickly and easily from Python. Moreover, this architecture is designed to support interactive and collaborative parallel computing. The main features of this system are:.

Quickly parallelize Python code from an interactive Python/IPython session. A flexible and dynamic process model that be deployed on anything from multicore workstations to supercomputers.

An architecture that supports many different styles of parallelism, from message passing to task farming. And all of these styles can be handled interactively. Both blocking and fully asynchronous interfaces. High level APIs that enable many things to be parallelized in a few lines of code.

Zss-656 Copy-paste From Clipboard To Zss Not Working For Mac Cosmetics

Write parallel code that will run unchanged on everything from multicore workstations to supercomputers. Full integration with Message Passing libraries (MPI). Capabilities based security model with full encryption of network connections.

Share live parallel jobs with other users securely. We call this collaborative parallel computing. Dynamically load balanced task farming system. Robust error handling. Python exceptions raised in parallel execution are gathered and presented to the top-level code. For more information, see our of using IPython for parallel computing.

IPython 4.1 IPython 4.1.2 (March, 2016) fixes installation issues with some versions of setuptools. Released February, 2016. IPython 4.1 contains mostly bug fixes, though there are a few improvements. IPython debugger (IPdb) now supports the number of context lines for the where (and w) commands. The context keyword is also available in various APIs.

See PR. YouTube video will now show thumbnail when exported to a media that do not support video. Add warning when running ipython when subcommand is deprecated. Jupyter should now be used. Code in%pinfo (also known as??) are now highlighter.%aimport now support module completion. ipdb output is now colored!. Add ability to transpose columns for completion: Many many docs improvements and bug fixes, you can see the.

Best free pdf editor for mac. IPython 4.0 Released August, 2015 IPython 4.0 is the first major release after the Big Split. IPython no longer contains the notebook, qtconsole, etc.

Which have moved to. IPython subprojects, such as and have moved to their own repos as well. The following subpackages are deprecated:. IPython.kernel (now jupyterclient and ipykernel). IPython.consoleapp (now jupyterclient.consoleapp).

IPython.nbformat (now nbformat). IPython.nbconvert (now nbconvert). IPython.html (now notebook). IPython.parallel (now ipyparallel). IPython.utils.traitlets (now traitlets).

IPython.config (now traitlets.config). IPython.qt (now qtconsole). IPython.terminal.console (now jupyterconsole) and a few other utilities.

Shims for the deprecated subpackages have been added, so existing code should continue to work with a warning about the new home. There are few changes to the code beyond the reorganization and some bugfixes. IPython highlights:. Public APIs for discovering IPython paths is moved from to. The old function locations continue to work with deprecation warnings.

Code raising DeprecationWarning entered by the user in an interactive session will now display the warning by default. The -deep-reload flag and the corresponding options to inject dreload or reload into the interactive namespace have been deprecated, and will be removed in future versions. You should now explicitly import reload from IPython.lib.deepreload to use it. IPython 3.2 IPython 3.2 contains important security fixes. Users are strongly encouraged to upgrade immediately. Highlights:. Address cross-site scripting vulnerabilities CVE-2015-4706, CVE-2015-4707.

A security improvement that set the secure attribute to login cookie to prevent them to be sent over http. Revert the face color of matplotlib axes in the inline backend to not be transparent. Enable mathjax safe mode by default. Fix XSS vulnerability in JSON error messages. Various widget-related fixes See for details. IPython 3.1 Released April 3, 2015 The first 3.x bugfix release, with 33 contributors and 344 commits.

This primarily includes bugfixes to notebook layout and focus problems. Highlights:. Various focus jumping and scrolling fixes in the notebook. Various message ordering and widget fixes in the notebook.

Images in markdown and output are confined to the notebook width. An.unconfined CSS class is added to disable this behavior per-image. The resize handle on output images is removed. Improved ordering of tooltip content for Python functions, putting the signature at the top. Fix UnicodeErrors when displaying some objects with unicode reprs on Python 2. Set the kernel’s working directory to the notebook directory when running nbconvert -execute, so that behavior matches the live notebook. Allow setting custom SSL options for the tornado server with NotebookApp.ssloptions, and protect against POODLE with default settings by disabling SSLv3.

Fix memory leak in the IPython.parallel Controller on Python 3. See for details. Release 3.0 Released February 27, 2015 This is a really big release. Over 150 contributors, and almost 6000 commits in a bit under a year. Support for languages other than Python is greatly improved, notebook UI has been significantly redesigned, and a lot of improvement has happened in the experimental interactive widgets. The message protocol and document format have both been updated, while maintaining better compatibility with previous versions than prior updates. The notebook webapp now enables editing of any text file, and even a web-based terminal (on Unix platforms).

3.x will be the last monolithic release of IPython, as the next release cycle will see the growing project split into its Python-specific and language-agnostic components. Language-agnostic projects (notebook, qtconsole, etc.) will move under the umbrella of the new Project Jupyter name, while Python-specific projects (interactive Python shell, Python kernel, IPython.parallel) will remain under IPython, and be split into a few smaller packages. To reflect this, IPython is in a bit of a transition state. The logo on the notebook is now the Jupyter logo. When installing kernels system-wide, they go in a jupyter directory.

We are going to do our best to ease this transition for users and developers. Big changes are ahead. In 1 :% load -n mymodule.somefunction. DirectView objects have a new usecloudpickle method, which works like view.usedill, but causes the cloudpickle module from PiCloud’s library to be used rather than dill or the builtin pickle module. Added a.ipynb exporter to nbconvert. It can be used by passing -to notebook as a commandline argument to nbconvert. New nbconvert preprocessor called ClearOutputPreprocessor.

This clears the output from IPython notebooks. New preprocessor for nbconvert that executes all the code cells in a notebook. To run a notebook and save its output in a new notebook.

Ipython nbconvert InputNotebook -ExecutePreprocessor.enabled=True -to notebook -output Executed. Consecutive stream (stdout/stderr) output is merged into a single output in the notebook document.

Previously, all output messages were preserved as separate output fields in the JSON. Now, the same merge is applied to the stored output as the displayed output, improving document load time for notebooks with many small outputs. NotebookApp.webappsettings is deprecated and replaced with the more informatively named NotebookApp.tornadosettings. Using prints warnings if there is atleast a 4x difference in timings between the slowest and fastest runs, since this might meant that the multiple runs are not independent of one another. It’s now possible to provide mechanisms to integrate IPython with other event loops, in addition to the ones we already support. This lets you run GUI code in IPython with an interactive prompt, and to embed the IPython kernel in GUI applications. See for details.

As part of this, the direct enable. and disable. functions for various GUIs in have been deprecated in favour of. A ScrollManager was added to the notebook. The ScrollManager controls how the notebook document is scrolled using keyboard. Users can inherit from the ScrollManager or TargetScrollManager to customize how their notebook scrolls. The default ScrollManager is the SlideScrollManager, which tries to scroll to the nearest slide or sub-slide cell.

The function interactmanual has been added which behaves similarly to interact, but adds a button to explicitly run the interacted-with function, rather than doing it automatically for every change of the parameter widgets. This should be useful for long-running functions. The%cython magic is now part of the Cython module. Use%loadext Cython with a version of Cython = 0.21 to have access to the magic now. The Notebook application now offers integrated terminals on Unix platforms, intended for when it is used on a remote server. To enable these, install the terminado Python package.

The Notebook application can now edit any plain text files, via a full-page CodeMirror instance. Setting the default highlighting language for nbconvert with the config option NbConvertBase.defaultlanguage is deprecated. Nbconvert now respects metadata stored in the. IPython can now be configured systemwide, with files in /etc/ipython or /usr/local/etc/ipython on Unix systems, or%PROGRAMDATA% ipython on Windows. Added support for configurable user-supplied HTML templates for the notebook.

Paths to directories containing template files can be specified via NotebookApp.extratemplatepaths. User-supplied template directories searched first by the notebook, making it possible to replace existing templates with your own files. For example, to replace the notebook’s built-in error.html with your own, create a directory like /home/mytemplates and put your override template at /home/mytemplates/error.html. To start the notebook with your custom error page enabled, you would run.

Backwards incompatible changes. The has been updated from version 4 to version 5.

Adapters are included, so IPython frontends can still talk to kernels that implement protocol version 4. The notebook format has been updated from version 3 to version 4. Read-only support for v4 notebooks has been backported to IPython 2.4. Notable changes:. heading cells are removed in favor or markdown headings. notebook outputs and output messages are more consistent with each other. use IPython.nbformat.read and write to read and write notebook files instead of the deprecated IPython.nbformat.current APIs.

You can downgrade a notebook to v3 via nbconvert. Content Security Policy The Content Security Policy is a web standard for adding a layer of security to detect and mitigate certain classes of attacks, including Cross Site Scripting (XSS) and data injection attacks.

This was introduced into the notebook to ensure that the IPython Notebook and its APIs (by default) can only be embedded in an iframe on the same origin. Override headers'Content-Security-Policy' within your notebook configuration to extend for alternate domains and security settings. Issues closed in 3.1 GitHub stats for 2015/02/27 - 2015/04/03 (since 3.0) These lists are automatically generated, and may be incomplete or contain duplicates. We closed 46 issues and merged 133 pull requests.

The full list can be seen. The following 33 authors contributed 344 commits:. Abe Guerra. Adal Chiriliuc. Benjamin Ragan-Kelley.

Brian Drawert. Fernando Perez. Gareth Elston. Gert-Ludwig Ingold. Giuseppe Venturini. Jakob Gager.

Jan Schulz. Jason Grout. Jessica B. Hamrick. Jonathan Frederic. Justin Tyberg. Lorena Pantano.

mashenjun. Mathieu. Matthias Bussonnier. Morten Enemark Lund. Naveen Nathan. Nicholas Bollweg.

onesandzeroes. Patrick Snape. Peter Parente.

RickWinter. Robert Smith.

Ryan Nelson. Scott Sanderson. Sylvain Corlay. Thomas Kluyver. tmtabor. Wieland Hoffmann.

Yuval Langer. Upgrading Notebooks.

The first thing you’ll notice when upgrading an IPython 2.0 widget notebook to IPython 3.0 is the “Notebook converted” dialog. All of the widgets distributed with IPython have been renamed. The “Widget” suffix was removed from the end of the class name. ButtonWidget is now Button.

ContainerWidget was renamed to Box. PopupWidget was removed from IPython. If you use the PopupWidget, try using a Box widget instead. If your notebook can’t live without the popup functionality, subclass the Box widget (both in Python and JS) and use JQuery UI’s draggable and resizable methods to mimic the behavior. addclass and removeclass were removed. More often than not a new attribute exists on the widget that allows you to achieve the same explicitly.

The Button widget now has a buttonstyle attribute which you can set to ‘primary’, ‘success’, ‘info’, ‘warning’, ‘danger’, or ‘’ instead of using addclass to add the bootstrap class. VBox and HBox classes (flexible Box subclasses) were added that allow you to avoid using addclass and removeclass to make flexible box model layouts. As a last resort, if you can’t find a built in attribute for the class you want to use, a new domclasses list trait was added, which combines addclass and removeclass into one stateful list. setcss and getcss were removed in favor of explicit style attributes - visible, width, height, padding, margin, color, backgroundcolor, bordercolor, borderwidth, borderradius, borderstyle, fontstyle, fontweight, fontsize, and fontfamily are a few. If you can’t find a trait to see the css attribute you need, you can, in order of preference, (A) subclass to create your own custom widget, (B) use CSS and the domclasses trait to set domclasses, or (C) use the css dictionary to set CSS styling like setcss and getcss.

For selection widgets, such as Dropdown, the values argument has been renamed to options. Javascript. If you are distributing your widget and decide to use the deferred loading technique (preferred), you can remove all references to the WidgetManager and the register model/view calls (see the Python section below for more information). In 2.0 require.js was used incorrectly, that has been fixed and now loading works more like Python’s import. Requiring widgets/js/widget doesn’t import the WidgetManager class, instead it imports a dictionary that exposes the classes within that module. Python Generally, custom widget Python code can remain unchanged.

If you distribute your custom widget, you may be using display and Javascript to publish the widget’s Javascript to the front-end. That is no longer the recommended way of distributing widget Javascript. Instead have the user install the Javascript to his/her nbextension directory or their profile’s static directory. Then use the new viewmodule and modelmodule traitlets in combination with viewname and modelname to instruct require.js on how to load the widget’s Javascript. The Javascript is then loaded when the widget is used for the first time. Asynchronous In the IPython 2.x series the only way to register custom widget views and models was to use the registry in the widget manager.

Unfortunately, using this method made distributing and running custom widgets difficult. The widget maintainer had to either use the rich display framework to push the widget’s Javascript to the notebook or instruct the users to install the Javascript by hand in a custom profile. With the first method, the maintainer would have to be careful about when the Javascript was pushed to the front-end. If the Javascript was pushed on Python widget import, the widgets wouldn’t work after page refresh. This is because refreshing the page does not restart the kernel, and the Python import statement only runs once in a given kernel instance (unless you reload the Python modules, which isn’t straight forward).

This meant the maintainer would have to have a separate pushjs method that the user would have to call after importing the widget’s Python code. Our solution was to add support for loading widget views and models using require.js paths. Thus the comm and widget frameworks now support lazy loading. To do so, everything had to be converted to asynchronous code. HTML5 promises are used to accomplish that (, ).

Smaller Changes. Latex math is supported in widget descriptions. Widgets can be display more than once within a single container widget (, ). FloatRangeSlider and IntRangeSlider were added.

“Widget” was removed from the ends of all of the widget class names. ContainerWidget was renamed to Box.

HBox and VBox widgets were added. add class and remove class were removed in favor of a domclasses list. get css and set css were removed in favor of explicit traits for widget styling. jslink and jsdlink were added (, ). An Output widget was added, which allows you to print and display within widgets. PopupWidget was removed. A visual cue was added for widgets with ‘dead’ comms.

A SelectMultiple widget was added (a Select widget that allows multiple things to be selected at once). A class was added to help manage children views.

A warning was added that shows on widget import because it’s expected that the API will change again by IPython 4.0. This warning can be supressed (, ). Comm and Widget PR Index Here is a chronological list of PRs affecting the widget and comm frameworks for IPython 3.0.

Note that later PRs may revert changes made in earlier PRs:. Add placeholder attribute to text widgets. Add latex support in widget labels,. Allow widgets to display more than once within container widgets. use require.js,. Range widgets. Interact ondemand option.

Allow text input on slider widgets. support binary buffers in comm messages.

Embrace the flexible box model in the widgets. Widget trait serialization. Make Container widgets take children as the first positional argument. once-displayed.

Validate slider value, when limits change. Unregistering comms in Comm Manager. Add EventfulList and EventfulDict trait types. Remove add/removeclass and set/getcss. avoid unregistering widget model twice.

Widget property lock should compare json states, not python states. Strip the IPYMODEL prefix from widget IDs before referencing them. “event” is not defined error in Firefox. Javascript link. Bulk update of widget attributes. Creating a widget registry on the Python side. Allow widget views to be loaded from require modules.

Fix Issue #6530. Make comm manager (mostly) independent of InteractiveShell. Add semantic classes to top-level containers for single widgets. Selection Widgets: forcing ‘value’ to be in ‘values’. Allow widgets to be constructed from Javascript.

Output widget. Minor change in widgets.less to fix alignment issue. Make Selection widgets respect values order.

Widget persistence API. Add promises to the widget framework. SelectMultiple widget. Tooltip on toggle button. Allow empty text box.while typing. for numeric widgets.

Ignore failure of widget MathJax typesetting. Refactor the dodiff and manual child view lists into a separate ViewList object. Add warning to widget namespace import. lazy load widgets. Fix padding of widgets. Persist widgets across page refresh.

Make the widget experimental error a real python warning. Make the widget error message shorter and more understandable. Make the widget warning brief and easy to filter. Add visual cue for widgets with dead comms.

Widget values as positional arguments. Remove the popup widget. document and validate link, dlink. Document interact 5637.

Update some broken examples of using widgets. Use Output widget with Interact.

don’t send empty executeresult messages. Validation on the python side.

only show prompt overlay if there’s a prompt. Allow predictate to be used for comparison in selection widgets. Fix widget view persistence.

Revert “Use Output widget with Interact”. Release 2.0.0 April, 2014 IPython 2.0 requires Python ≥ 2.7.2 or ≥ 3.3.0.

It does not support Python 3.0, 3.1, 3.2, 2.5, or 2.6. Changes to hidden namespace on startup Previously, all names declared in code run at startup (startup files, ipython -i script.py, etc.) were added to the hidden namespace, which hides the names from tools like%whos. There are two changes to this behavior:. Scripts run on the command-line ipython -i script.py``now behave the same as if they were passed to ``%run, so their variables are never hidden. A boolean config flag InteractiveShellApp.hideinitialns has been added to optionally disable the hidden behavior altogether.

The default behavior is unchanged. DisplayFormatter changes There was no official way to query or remove callbacks in the Formatter API. To remedy this, the following methods are added to BaseFormatter:. lookup(instance) - return appropriate callback or a given object. lookupbytype(typeorstr) - return appropriate callback for a given type or 'mod.name' type string.

pop(typeorstr) - remove a type (by type or string). Pass a second argument to avoid KeyError (like dict). All of the above methods raise a KeyError if no match is found.

And the following methods are changed:. fortype(typeorstr) - behaves the same as before, only adding support for 'mod.name' type strings in addition to plain types. This removes the need for fortypebyname, but it remains for backward compatibility. Formatters can now raise NotImplementedError in addition to returning None to indicate that they cannot format a given object.