How to install / use Conda on Google Colab

In this article we will see how to install and use the conda package manager on Google Colab !

Conda is an open source system that allows you to manage independent environments and install libraries / packages.

It is an ideal tool to create specific environments for development, testing or even production as it allows you to create “sandbox” spaces.

So, when doing Machine Learning, it can be interesting to use Conda and create free and independent environments.

As we are Google Colab adepts which allows us to code Python on the Cloud, we will see how to use Conda on this platform.

Google Colab

Is conda already installed?

First of all, I recommend that you to check that conda is not already installed.

To do this, we check the version of conda ! Obviously if it is not installed, the code will return an error :

!conda --version

You should have : /bin/bash: conda: command not found

Install conda

To install conda, a library has been created specifically for Google Colab, conda-colab, and fortunately for us it is very easy to use !

You just have to install it with the pip command, then install conda with the condacolab.install() function.

!pip install -q condacolab
import condacolab
condacolab.install()

Once the installation is complete, the kernel should have rebooted itself and you’ll get :

Conda has been installed. To ensure it, we may display the version of Conda :

!conda --version

The code should return something like : conda 4.9.2.

You can also look at the location of the conda folder you just installed with this command :

!which conda

That’s it ! You can now use conda on Google Colab as you wish!

Be careful though, every time you quit or reset the runtime environment you will have to install conda again.

That’s why I advise you to always have this piece of code at hand :

!conda --version
#If !conda --version returns no results, install conda with :
#!pip install -q condacolab
#import condacolab
#condacolab.install()

Other tips are waiting for you in this section, feel free to have a look 😉

Photo by Thomas Evans on Unsplash

Tom Keldenich
Tom Keldenich

Data Engineer & passionate about Artificial Intelligence !

Founder of the website Inside Machine Learning

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