3 Great Additions for your Jupyter Notebooks

I also use this to create basic snippets for my deep learning notebooks and NLP based notebooks.


Execution TimeWe have used %time as well as decorator based timer functions to measure time for our functions.

You can also use this excellent extension to do that.

Plus it looks great.

Just select the ExecutionTime extension from the NBextensions list and you will have an execution result at the bottom of the cell after every cell execution as well as the time when the cell was executed.

Other ExtensionsNBExtensions has a lot of extensions.

Some other extensions from NBExtensions I like and you might want to look at:Limit Output: Ever had your notebook hang since you printed a lot of text in your notebook.

This extension limits the number of characters that can be printed below a code cell2to3Convertor: Having problems with your old python2 notebooks.

Tired of changing the print statements.

This one is a good one.

Live Markdown Preview: Some of us like writing our blogs using Markdown in a jupyter notebook.

Sometimes it can be hectic as you make errors in writing.

Now you can see Live-preview of the rendered output of markdown cells while editing their source.

ConclusionI love how there is a package for everything with Python.

And that holds good with the Jupyter notebook too.

The jupyter_contrib_nbextensions package works great out of the box.

It has made my life a lot easier when it comes to checking execution times, scrolling through the notebook, and repetitive tasks.

There are many other extensions this package does provide.

Do take a look at them and try to see which ones you find useful.

Also, if you want to learn more about Python 3, I would like to call out an excellent course on Learn Intermediate level Python from the University of Michigan.

Do check it out.

I am going to be writing more of such posts in the future too.

Let me know what you think about the series.

Follow me up at Medium or Subscribe to my blog to be informed about them.

As always, I welcome feedback and constructive criticism and can be reached on Twitter @mlwhiz.


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