IPython: Difference between revisions

| screenshot alt = Screenshot of IPython 6.x on Mac OS, showing the computation of a fourrierfourier transform using numpy.

| developer = Brian E. Granger, Min Ragan-Kelley, Paul Ivanov, Thomas Kluyver, Matthias Bussonnier

* Interactive shells (terminal and [[Qt (frameworksoftware)|Qt]]-based).

IPython is based on an architecture that provides parallel and distributed computing. IPython enables parallel applications to be developed, executed, debugged and monitored interactively, hence the I (Interactive) in IPython<!-- The 'I' in IPython refers to an 'interactive' command window that helps users to run code, access variables, call up data analysis packages and view plots, while the Python refers to the popular programming language that the notebook is based on. see, http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261 -->.<ref>{{cite journal|last1=Helen|first1=Shen|title=Interactive notebooks: Sharing the code|journal=Nature|date=2014|volume=515|issue=7525|pages=151–152|doi=10.1038/515151a|pmid=25373681|bibcode=2014Natur.515..151S|doi-access=free}}</ref> This architecture abstracts out parallelism, enabling IPython to support many different styles of parallelism<ref>{{cite web|title=Using IPython for Parallel computing - IPython docs|url=https://ipython.org/ipython-doc/stable/parallel/parallel_intro.html}}</ref> including:

With the release of IPython 4.0, the parallel computing capabilities were made optional and released under the [https://pypi.org/project/ipyparallel/ ipyparallel] python package. And most of the capabilities of ipyparallel are now covered by more mature libraries like [[Dask (software)|Dask]].

IPython frequently draws from SciPy stack<ref name="scipystack">{{cite web|url=http://www.scipy.org/install.html|title=SciPy Stack}}</ref> libraries like [[NumPy]] and [[SciPy]], often installed alongside one of many Scientific Python distributions.<ref name="scipystack" /> IPython provides integration with some libraries of the [[SciPy]] stack, notably [[matplotlib]], producing inline graphs when in used with the [[Jupyter]] notebook. Python libraries can implement IPython specific hooks to customize rich object display. [[SymPy]] for example implements rendering of mathematical expressions as rendered [[LaTeX]] when used within IPython context, and [[Pandas (software)|Pandas]] dataframe use an HTML representation.<ref>{{Cite web|url=http://docs.sympy.org/1.1/tutorial/printing.html#setting-up-pretty-printing|title=Printing — SymPy 1.1 documentation|website=docs.sympy.org|access-date=2018-04-11}}</ref>

IPython allows non-blocking interaction with [[Tkinter]], [[PyGTK]], [[PyQt]]/[[PySide]] and [[wxPython]] (the standard Python shell only allows interaction with Tkinter). IPython can interactively manage parallel [[Computer cluster|computing clusters]] using asynchronous status callbacks and/or [[Message Passing Interface|MPI]]. IPython can also be used as a system shell replacement.<ref name="McKinney">{{cite book|chapter-url=http://shop.oreilly.com/product/0636920023784.do|last=McKinney|first=Wes|title=Python for Data Analysis|chapter=Chapter 3|year=2012|isbn=978-1-449-31979-3}}</ref> Its default behavior is largely similar to [[Unix shell]]s, but it allows customization and the flexibility of executing code in a live Python environment. Using IPython as a shell replacement is less common and it is now recommended to use Xonsh which provide most of the IPython feature with better shell integrations.

IPython 5.x (Long Time Support) series will beis the last version of IPython to support Python 2. The IPython project pledged to not support Python 2 beyond 2020<ref>{{Cite news|url=https://blog.jupyter.org/release-of-ipython-5-0-8ce60b8d2e8e|title=Release of IPython 5.0 – Jupyter Blog|date=2016-07-08|work=Jupyter Blog|access-date=2018-04-11}}</ref> by being one of the first projects to join the [http://python3statement.org/ Python 3 Statement], the 6.x series is only compatible with Python 3 and above. It is still possible though to run an IPython kernel and a Jupyter Notebook server on different Python versions allowing userusers to still access Python 2 on newer version of Jupyter.

{{Main|Project Jupyter}}

In 2014, IPython creator [[Fernando Pérez (software developer)|Fernando Pérez]] announced a spin-off project from IPython called [[Project Jupyter]].<ref>{{cite web|url=https://speakerdeck.com/fperez/project-jupyter|title=Project Jupyter // Speaker Deck}}</ref> IPython continued to exist as a Python shell and kernel for Jupyter, but the [[Notebook interface|notebook]] interface and other language-agnostic parts of IPython were moved under the Jupyter name.<ref>{{cite web|url=https://github.com/ipython/ipython|title=The Notebook, Qt console and a number of other pieces are now parts of Jupyter|website=[[GitHub]] |date=17 October 2021}}</ref><ref>{{cite web|url=https://blog.jupyter.org/the-big-split-9d7b88a031a7|title=The Big Split™|date=28 August 2017}}</ref> Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are [[Julia (programming language)|Julia]], [[Python (programming language)|Python]], and [[R (programming language)|R]].<ref>{{Cite web|url=https://github.com/jupyter/design/wiki/Jupyter-Logo|title=Jupyter Logo · jupyter/Design Wiki|website=[[GitHub]] }}</ref>

Jupyter [[Notebook interface|Notebook]] (formerly IPython NotebooksNotebook) is a [[Rich Internet applicationApplication|web-based interactive]] computational environment for creating, executing, and visualizing Jupyter notebooks. It is similar to the notebook interface of other programs such as [[Maple (software)|Maple]], [[Wolfram Mathematica|Mathematica]], and [[SageMath]], a computational interface style that originated with Mathematica in the 1980s.<ref name="Somers2018">{{Cite news|url=https://www.theatlantic.com/science/archive/2018/04/the-scientific-paper-is-obsolete/556676/|title=The Scientific Paper Is Obsolete|last=Somers|first=James|work=The Atlantic|access-date=2018-04-10|language=en-US}}</ref> It supports execution environments (aka kernels) in dozens of languages. By default Jupyter Notebook ships with the IPython kernel, but there are over 100 Jupyter kernels as of May 2018.

IPython has been mentioned in the popular computing press and other popular media,<ref name="press2">{{cite web|title=Introducing IPython|date=12 September 2005|last=Koziol|first=Conrad|publisher=NewsForge|url=http://archive09.linux.com/feature/47635|access-date=14 June 2012|archive-date=7 June 2012|archive-url=https://web.archive.org/web/20120607065802/http://archive09.linux.com/feature/47635|url-status=dead}}</ref><ref name=Somers2018/> and it has a presence at scientific conferences.<ref name="press1">{{cite web|url=https://ipython.org/presentation.html|title=IPython Presentations}}</ref> For scientific and engineering work, it is often presented as a companion tool to [[matplotlib]].<ref name="cise">{{cite journal |last1=Pérez |first1=Fernando |last2=Granger |first2=Brian E. |title=IPython: A System for Interactive Scientific Computing |journal=Computing in Science & Engineering |volume=9 |pages=21–29 |number=3 |year=2007 |url=http://fperez.org/papers/ipython07_pe-gr_cise.pdf |url-status=dead |archive-url= https://web.archive.org/web/20100602042637/http://fperez.org/papers/ipython07_pe-gr_cise.pdf |archive-date= 2 June 2010 |access-date= 30 July 2015|doi=10.1109/MCSE.2007.53 |bibcode=2007CSE.....9c..21P |s2cid=16637923 }}</ref>

Beginning 1 January 2013, the [[Alfred P. Sloan Foundation]] announced that it would support IPython development for two years.<ref>{{cite web|url=http://mail.scipy.org/pipermail/ipython-dev/2012-December/010799.html|title=Announcement in scipy mailing list|access-date=12 December 2012|archive-date=5 March 2016|archive-url=https://web.archive.org/web/20160305020306/https://mail.scipy.org/pipermail/ipython-dev/2012-December/010799.html|url-status=dead}}</ref>

In January 2014, it won the [[Jolt Awards|Jolt Productivity Award]]<ref>{{cite web|url=http://www.drdobbs.com/joltawards/jolt-awards-coding-tools/240165725?pgno=5|title=Jolt Productivity Award write-up in Dr. Dobb's}}</ref> from [[Dr. Dobb's]] in the category of coding tools. In July 2015, the project won a funding of $6 million from Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation and Leona M. and Harry B. Helmsley Charitable Trust.<ref>{{Cite news|url = https://www.moore.org/newsroom/press-releases/2015/07/07/$6m-for-uc-berkeley-and-cal-poly-to-expand-and-enhance-open-source-software-for-scientific-computing-and-data-science|title = $6M for UC Berkeley and Cal Poly to expand and enhance open-source software for scientific computing and data science|last = |first = |date = |work = |access-date = 13 August 2015|via = }}</ref>

{{Reflist|20em}}

[[Category:PythonNotebook development toolsinterface]]