iPython

File:IpythonArchitecture.png

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.{{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}} This architecture abstracts out parallelism, enabling IPython to support many different styles of parallelism{{cite web|title=Using IPython for Parallel computing - IPython docs|url=https://ipython.org/ipython-doc/stable/parallel/parallel_intro.html}} including:

• Single program, multiple data (SPMD) parallelism
• Multiple program, multiple data (MPMD) parallelism
• Message passing using MPI
• Task parallelism
• Data parallelism
• Combinations of these approaches
• Custom user defined approaches

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.

IPython frequently draws from SciPy stack{{cite web|url=http://www.scipy.org/install.html|title=SciPy Stack}} libraries like NumPy and SciPy, often installed alongside one of many Scientific Python distributions. IPython provides integration with some libraries of the SciPy stack, notably matplotlib, producing inline graphs when 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 dataframe use an HTML representation.{{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}}

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 computing clusters using asynchronous status callbacks and/or MPI. IPython can also be used as a system shell replacement.{{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}} Its default behavior is largely similar to Unix shells, but it allows customization and the flexibility of executing code in a live Python environment.

IPython 5.x (Long Time Support) series is the last version of IPython to support Python 2. The IPython project pledged to not support Python 2 beyond 2020{{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}} 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 users to still access Python 2 on newer version of Jupyter.

{{Main|Project Jupyter}}

{{Third-party|section|date=October 2016}}

File:IPython-notebook.png

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

Jupyter Notebook (formerly IPython Notebook) is a 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, Mathematica, and SageMath, a computational interface style that originated with Mathematica in the 1980s.{{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}} 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,{{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}} and it has a presence at scientific conferences.{{cite web|url=https://ipython.org/presentation.html|title=IPython Presentations}} For scientific and engineering work, it is often presented as a companion tool to matplotlib.{{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 }}

Beginning 1 January 2013, the Alfred P. Sloan Foundation announced that it would support IPython development for two years.{{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}}

On 23 March 2013, Fernando Perez was awarded the Free Software Foundation Advancement of Free Software award for IPython.

In August 2013, Microsoft made a donation of $100,000 to sponsor IPython's continued development.{{cite web|url=https://ipython.org/microsoft-donation-2013.html|title=IPython Announcement}}

In January 2014, it won the Jolt Productivity Award{{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}} 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.{{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|access-date = 13 August 2015}}

In May 2018, it was awarded the 2017 ACM Software System Award.{{cite web|url=https://awards.acm.org/software-system|title=Recent Software System Award News}} It is the largest team to have won the award.{{cite news|url = https://blog.jupyter.org/jupyter-receives-the-acm-software-system-award-d433b0dfe3a2|title=Jupyter receives the ACM Software System Award}}

{{Portal|Free and open-source software|Computer programming}}

• Python (programming language)
• Electronic lab notebook
• SageMath
• Project Jupyter

{{Reflist}}

• {{Official website}}
• [https://github.com/ipython/ipython/blob/01bd59ec7c184171df0cb0d933c5672e8c20b67e/IPython/core/magics/pylab.py#L37-L100 Inline graphs]
• [https://jupyter.org/ Project Jupyter]

Category:Command shells

Category:Free mathematics software

Category:Free software programmed in Python

Category:Notebook interface

Category:Python (programming language) development tools

Category:Software using the BSD license