Mastering Google Colab: Tips and Tricks

Introduction

Google colab is a free Jupyter notebook environment provided by Google. It offers a great way to write and run code, and it comes with many powerful features. In this blog post, we will explore some of the magic commands and tips that can help you to be more productive in Colab.

Magic command

Magic commands are special commands that start with a percent sign % or two percent signs %% and are used to perform various operations. Here are some useful magic commands in Colab:

%paste # when code notebook formatting
%run <file.py> # == !python <file.py>
%timeit L = [n ** 2 for n in range(1000)] # single line code
%time 
%%timeit # multi line code

Shell commands

You can also use shell commands in Colab by prefixing them with an exclamation mark !. Here are some of the most common ones:

!ls
!pwd
%cd == cd # !cd not working
%cat, %cp, %env, %ls, %man, %mkdir, %more, %mv, %pwd, %rm, and %rmdir

Run and debug

Colab makes it easy to run and debug your code. Here are some of the commands you can use:

%run <file.py> # == !python <file.py>
%debug # up, down, quit

Useful setup

To make your Colab experience even better, here are some tips for setting up your environment:

Editor

Go to Menu > Tools > Settings and adjust the following settings:

Editor font size: 12, space: 4, do not check Automatically trigger code completions to use Tab completion/ suggest: ctrl + space
Github: connect to github

Change python env

Run on GPU:

To run your code on a GPU, go to Menu > Runtime > change runtime type > GPU (limited resource in terms of time).

Switch python version

Open a new or existing notebook in Colab.
Click on Runtime in the menu bar, then click on Change runtime type.
In the Runtime type dropdown, select Python as the runtime type.
In the Python version dropdown, select the version of Python you want to use. Colab currently supports Python 2.7, 3.6, 3.7, and 3.8.
Click on Save to apply the changes.
Conclusion

These tips and tricks will help you to be more productive in Colab and get the most out of this great tool. Happy coding!

References

https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb#scrollTo=j7L3GiLYp1hV

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