Conda for managing environments

If you have installed the Anaconda distribution, or you have tried conda by using a Miniconda installation, you can also take advantage of the conda command to run virtual environments as an alternative to virtualenv. Let's see how to use conda for that in practice. We can check what environments we have available like this:

>$ conda info -e

This command will report to you what environments you can use on your system based on conda. Most likely, your only environment will be root, pointing to your Anaconda distribution folder.

As an example, we can create an environment based on Python Version 3.6, having all the necessary Anaconda-packaged libraries installed. This makes sense, for instance, when installing a particular set of packages for a data science project. In order to create such an environment, just perform the following:

$> conda create -n python36 python=3.6 anaconda

The preceding command asks for a particular Python version, 3.6, and requires the installation of all packages that are available on the Anaconda distribution (the argument anaconda). It names the environment as python36 using the argument -n. The complete installation should take a while, given a large number of packages in the Anaconda installation. After having completed all of the installations, you can activate the environment:

$> activate python36

If you need to install additional packages to your environment when activated, you just use the following:

$> conda install -n python36 <package-name1> <package-name2>

That is, you make the list of the required packages follow the name of your environment. Naturally, you can also use pip install, as you would do in a virtualenv environment.

You can also use a file instead of listing all the packages by name yourself. You can create a list in an environment using the list argument and pipe the output to a file:

$> conda list -e > requirements.txt

Then, in your target environment, you can install the entire list by using the following:

$> conda install --file requirements.txt

You can even create an environment, based on a requirements list:

$> conda create -n python36 python=3.6 --file requirements.txt

Finally, after having used the environment, to close the session, you simply use the following command:

$> deactivate

Contrary to virtualenv, there is a specialized argument in order to completely remove an environment from your system:

$> conda remove -n python36 --all