Seitenhistorie

A note on Anaconda/Miniconda

Dear users,

we know that many of you would like to install or are using Anaconda/Miniconda already to manage their Python packages. No one can prevent you from doing so, and in some cases this is justified. We know its ease of use is very appealing, however, we strongly recommend against using it. The reasons for this are the following:

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We do provide Python installations and various packages (i.e. scipy, numpy, pandas, matplotlib etc.) based on the intel or gcc compiler, which are optimized to perform very well on the cluster. If you need to install Python packages yourself, we will explain how to do so in this article. If you run into problems you can always contact support at hpc@uni-muenster.de. There are some occasions, where anything other than conda fails but we would like to try every other option before going this route.

Thank you.

Installing additional Python packages

You may want to install Python libraries that are not provided by the default  installation or any other module. These can be installed directly to your home directory without any admin privileges using the following procedure.  Note that some packages might need external libraries. Requirements can usually be found in the package documentation. These libraries have to be loaded before by using the module load command.

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Installing additional Perl modules

1. Load the base Perl module from the intel or foss toolchain

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