Python bundles

Bundle names

  • The bundle names reflect the content, like Python packages, and its version, but also which Python version, compilers and libraries that are compatible with it.

Danger

  • Make sure to use bundles that are compatible with each-other and with needed Python version.

  • Otherwise it is better to create isolated environments with Conda or virtual environments, see Isolated environments in Python.

Principles with example: matplotlib

  • Decide what you need!

    1. Start new project with newest toolchain

    2. Go for version you have used before (reproduce)

    3. Exact versions of many packages may need an isolated environment.

  • Load one or several bundles, python is loaded on the fly!

  • Check versions

ml spider matplotlib

This is a very good way to find packages that are not in a bundle with the same name. For instance, pandas and numpy are parts of the SciPy-bundle

or

ml avail matplotlib
  • Load prerequisites, if needed, and then

ml matplotlib/<version>

or

ml matplotlib/<version>
  • Start Python session in a console with

python
  • Load a needed library, like

import matplotlib