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  1. Interactive Shell: IPython provides a more powerful and user-friendly shell for executing Python code interactively. It supports features like tab-completion, multiline editing, and history management.
  2. Rich Media Support: You can display images, videos, HTML, and other media types directly within the IPython shell, making it useful for creating interactive presentations or data visualizations.
  3. Magic Commands: IPython includes “magic commands” that start with % or %%, which provide shortcuts for common tasks and operations. For example, %run to run Python scripts, %load to load code from external files, and %%timeit to measure code execution time.
  4. Interactive Help: You can access documentation and help for Python objects and modules by using the ? symbol or the help() function. This makes it easier to understand and use Python libraries.
  5. History and Logging: IPython keeps a history of your previous commands, which you can access and re-run. It also allows you to log your session’s input and output for reproducibility.
  6. Parallel Computing: IPython supports parallel and distributed computing, making it suitable for scientific and data-intensive tasks that require parallelism.
  7. Jupyter Integration: IPython is tightly integrated with Jupyter notebooks. Jupyter notebooks provide a web-based interface for interactive computing, and they use IPython as their default kernel.

To use IPython, you typically install it as part of the Jupyter ecosystem or separately as a standalone package. You can start an IPython session by running the ipython command in your terminal, or within a Jupyter notebook by selecting the IPython kernel.

Here’s a simple example of running IPython:

pythonCopy code$ ipython
Python 3.8.10 (default, May  3 2021, 08:55:58)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.22.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: x = 5

In [2]: y = 10

In [3]: x + y
Out[3]: 15

In [4]: import math

In [5]: math.sqrt(25)
Out[5]: 5.0

In [6]: exit()

This is just a brief overview of IPython’s capabilities. It is a valuable tool for data scientists, researchers, and anyone who wants to work with Python interactively

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