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 in IPython. This architecture abstracts out parallelism, enabling IPython to support many different styles of parallelism including:
With the release of IPython 4.0, the parallel computing capabilities were made optional and released under the python package. IPython frequently draws from 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 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.
Other features
IPython allows non-blocking interaction with Tkinter, PyGTK, PyQt/PySide and wxPython. IPython can interactively manage parallel computing clusters using asynchronous status callbacks and/or MPI. IPython can also be used as a system shell replacement. Its default behavior is largely similar to Unix shells, 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.
End of Python 2 support
IPython 5.x series will be the last version of IPython to support Python 2. The IPython project pledged to not support Python 2 beyond 2020 by being one of the first projects to join the , 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 user to still access Python 2 on newer version of Jupyter.
In 2014, Fernando Pérez announced a spin-off project from IPython called Project Jupyter. 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. Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. Jupyter 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. It supports execution environments in dozens of languages. By default Jupyter Notebook ships with the IPython kernel but there are over 100 Jupyter kernels as of May 2018.
In the media
IPython has been mentioned in the popular computing press and other popular media, and it has a presence at scientific conferences. For scientific and engineering work, it is often presented as a companion tool to matplotlib.
