IPython is a command shell for computing in multiple programming languages. IPython was developed for python language by Fernando Perez in 2001 as a well-equipped python interpreter that offers shell syntax, introspections, tab completion, and history. Compared to standard Python, IPython gives more advanced features, which are:
- It provides an interactive python shell.
- This acts like the central kernel of the Jupiter notebook.
- As mentioned above, introspection is the ability to look after the features of an object during runtime.
- This highlights syntax.
- This stores interaction history.
- Tab completion of keywords and function names.
- There will also be access to the python debugger.
Learning the IPython does not require any knowledge of Python. We can execute the commands similar to the standard Python Prompt. Ipython can do much more than the standard Python Prompt.
IPython shell is all the same as a python command line. Still, the IPython shell is cleverer and acts in favor of the programmer. For example, if you type a multi-line program in Python and want to repeat that, you have to scroll from the top and search for it. Still, in ipython, you can scroll back through the whole code, and it is easy to navigate the line to line and change that block.
It is recommended that Installing the Anaconda or Canopy Python distributions before installing IPython can provide Python IPython, including all of its dependencies. Also, Open-Source Packages of Data Science and Scientific Computing.
If Python is already installed in your system, use the following command to install the IPython
“pip install Ipython”
if you are a new user, you have to install Anaconda before and then install IPython. To install Anaconda by clicking on the download given below, and then use the further command
Through this link, you can install Anaconda to your system.
We can update the IPython to sync with the current version using the following commands.
Conda update Conda
Conda update ipython
Difference between ipython and Python
Python and ipython might sound the same, but in use, they are different. Python is a computer programming language that was created in the 1980s. Web developers mostly use this, and many scientists use python libraries like scipy, NumPy, pandas, and matplotlib. And Python is an object-oriented language.
Coming to IPython is a command line terminal used for Python, developed in 2001. It is so intelligent, which makes scientific computing more accessible and feasible cause it offers REPL(Read-Eval-Print loop), so this ipython acts like an interface to python language.
In short, Python is a programming language, and IPython is the interface where you run the python functions with more advanced options.
The debugger in Python is interactive to the user, so as you write the code; it keeps showing errors other than different debuggers; if you use the IPython debugger it will always alert when your code gets an uncaught exception.
IPython called magic commands, offers some significant enhancements. These magic commands are used to solve problems in data analysis using Python. Magic commands help embed the wrong syntax.
There are two types of magic commands: Line magics and cell magics.
Line magics are similar to command line calls. These commands are written with ‘%’ starting, and the next comes to the argument normally without any parenthesis. These line magics are used as expressions to return the value assigned to a variable.
Some built-in line magics are:
- %autocall [mode]
Cell magics operate on multiple lines below the call. These have “%%” before the argument. Through these, we can make modifications to arbitrary inputs.
Benefits of ipython
- It’s a robust interactive shell
- It is a kernel for jupyter
- Flexible, embedded interpreters to load into your codes.
- Easy to access high usage tools for computing parallelly
Finally, in this article, we have covered the basics of the IPython shell, its installation in various ways and basic commands, its features, its benefits, and how this differs from Python. Covering all these gives you a basic idea of the IPython shell. And the usage of IPython in your python projects.