7 Advantages of Using Google Colab for Python

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Python in Plain English

3 min readJun 4, 2020

Python scripts are a very useful and can both be a great replacement and a great addition to using spreadsheets.

Thanks to Python it’s possible to make calculations over 100000 rows of cells without breaking your spreadsheet
Thanks to Python, it’s possible to include new cutting-edge machine learning techniques for analyzing data and text.
Thanks to Python, spending lots of time to gather data and execute repetitive analyses is a thing of the past.

While Python is a great tool, there are some disadvantages on running Python scripts locally, especially if you want to share your code. Different Python configurations (versions, modules) can make or break your code. Versioning, local machine performance and user experience for non-technical persons are other problems.

But Google Colab is coming to the rescue. It offers you following advantages:

1) Sharing

You can share your Google Colab notebooks very easily. Thanks to Google Colab everyone with a Google account can just copy the notebook on his own Google Drive account. No need to install any modules to run any code, modules come preinstalled within Google Colab.

2) Versioning

You can save your notebook to Github with just one simple click on a button. No need to write “git add git commit git push git pull” codes in your command client (this is if you did use versioning already)!

3) Code snippets

Google Colab has a great collection of snippets you can just plug in on your code.

E.g. if you want to write data to a Google Sheet automatically, there’s a snippet for it in the Google Library

Just copy the snippet in your notebook and get started.

4) Forms for non-technical users

Not only programmers have to analyze data and Python can be useful for almost everyone in an office job. The problem is non-technical people are scared to death of making even the tiniest change to the code. But Google Colab has the solution for that. Just insert
the comment #@param {type:”string”} and you turn any variable field in a easy-to-use form input field. Your non-technical user needs to change form fields and Google Colab will automatically update the code. You can find more info on https://colab.research.google.com/notebooks/forms.ipynb

5) Performance

Use the computing power of the Google servers instead of your own machine. Running python scripts requires often a lot of computing power and can take time. By running scripts in the cloud, you don’t need to worry. Your local machine performance won’t drop while executing your Python scripts.