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This example is about installing and using one Python package in an environment. |
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The “conda install” on the above page gives the installation commands:
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The conda part in the red circle needs to be changed to mamba, and the bioconda part in the blue box is the channel name of this multiqc package. Channel is similar to the name of an online folder, that mamba can find and download the correct package. This is important for the next step.
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As explained in Python Package Installation Method Comparison , if a package is not found on anaconda.org, but found on pypi.org , pip can be used inside a mamba env. This is the only correct way to use pip on the ASU supercomputers at the moment, is to use it inside an activated mamba env.
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Almost all of the Python packages can be found on anaconda.org, and mamba is always preferred. |
Here is an example of such a special package called q2-greengenes2:
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The commands to have this package installed There are some packages can only be found on pypi.org but not anaconda.org, then the only option to install them is via pip, inside an activated mamba env. Notably that the current official installation guide for both tensorflow and pytorch prefers pip, but the conda-forge channel still supports them, and our public tensorflow/pytorch environments were built via mamba.
The example commands to have a package installed via pip to a mamba env are:
Connect to the VPN
Open a command line interface on Sol by navigating to sol.asu.edu on your browser and
selecting the "Sol Shell Access" option from the "System" menu option. Or by SSHing into
Sol using the commandssh <asurite>@sol.asu.eduinteractive -p htc -c 4 -t 30module load mamba/latestsource activate myENV(or create a new on using themamba createcommand)pip install q2-greengenes2
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