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Adding missing Python libraries to Pythion in SD Desktop

By default, SD Desktop virtual machines have Python 2.7.5 (python) and Python 3.10.12 (python3) or Python 3.9.16 (python3.9) installed. As Python 2 is mostly outdated, we recommend that you use Python3 whenever possible and also this tutorial focuses on that version only.

The Python 3 in SD Desktop includes a wide selection of commonly used libraries like pandas, numpy and scipy but as there is huge amount of python libraries available, you quite often would like to use a library that is not available in SD Desktop.

In normal computers, the problem can be easily solved by adding the missing library using pip install command. However, as SD Desktop virtual machines don't have internet connection, you can't run pip install command in the way they are normally used.

If you plan to use a complex python environment in SD Desktop, the best solution is to build an Apptainer container that includes all the Python libraries you need, and import that container to SD Desktop.

However, if you would need to add just few missing libraries to the Python 3.9 in SD Desktop, you could create a Python virtual environment to add the missing libraries. This tutorial demonstrates how you can import and install missing Python libraries to SD desktop. As an example we use SciKit-Optimize library.

1. Building an installation file for SD Desktop

The first thing to do is to build a pip installation package file for the library you want to use. This you must do outside SD Desktop, in a machine that has internet access and python and pip commands installed (if possible, use Python version that matches with the Python version in SD Desktop).

In this machine, create a new directory, use pip download to download the installation files and then package this directory for transportation. In the case of user asund in a Linux or Mac, SciKit-Optimize library could be packaged with commands:

mkdir scikit-optimize
pip download scikit-optimize -d "/home/asund/scikit-optimize"
tar cvfz scikit-optimize.tgz scikit-optimize

Next you should upload the installation package (scikit-optimize.tgz) to one of your data buckets in SD Connect.

2. Installing the library

After uploading the installation package to SD Connect, you will do rest of the installation steps in your SD Desktop environment.

  1. Open terminal session and create a Python virtual environment with command (this needs to be done only once):

    python3 -m venv $HOME/my-python

  2. Activate your Python virtual environment and add the location of default python libraries to PYTHONPATH environment variable: (this you must do each time you start a new terminal session)

    source $HOME/my-python/bin/activate
export PYTHONPATH=/usr/local/lib/python3.9/site-packages

  3. Open or refresh your DataGateway connection and copy scikit-optiomize.tgz to your local disk.

  4. Uncompress the package

    tar zxvf scikit-optimize.tgz

  5. Move to the new directory:

    cd scikit-optimize

  6. Install the package:

    pip install scikit_optimize-0.9.0-py2.py3-none -any-whl -f ./ --no-index --no-deps

Now python (pointing to $HOME/my-python/bin/python) should contain scikit_optimize library.