Installing Python packages on BinAC

This tutorial describes how to install Python packages in your $HOME directory on BinAC via Miniconda, which can be used to create reproducible runtime environments. Miniconda can manage packets, dependencies and environments for every language, not just Python.

First of all, Miniconda has to be installed in $HOME and the working environment has to be configured.

We install Miniconda by downloading and running the installer from their website.

Sollen neben Python-Paketen auch Conda-Pakete installiert werden, muss noch zusätzlich der bioconda conda-channel hinzugefügt werden (relevant für Bioinformatiker).

If you want to install Conda packages alongside Python packages you have to add the bioconda channel as well (mostly relevant for bioinformatics).

Ein Beispiel der neuen Umgebung 'test' mit einer frischen Python 3.5 Installation:

In order install packages using Conda, a new environment has to be created first. This will install a new Python installation with some basic packets in the specified directory.

The environment has been created in $HOME but it has to be activated before installing new packages. This basically configures the current shell to use the Python executables of that specific environment.

Using which we can confirm that the correct executable is being used.

Installing new packages via pip install is very easy. Conda is making sure that all files get put into the correct directory once the environment has been activated. For example, installing a specific Numpy version works like this:

You can check the Numpy version and it's installation directory in a Python shell.

Existing Conda environments can be listed using

and a specific environment can be fully removed using

As mentionded, Conda can do a lot more than managing Python packets. Learn more in Conda's User guide.