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This example is about installing and using one Python package in an a Mamba 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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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.edu
interactive -p htc -c 4 -t 30
module load mamba/latest
module load cuda-12.4.1-gcc-12.1.0
If the package is for running codes on GPUs, a compatible
cuda
module is also needed.Now we are ready to create env and install packages. It can be done in seperated separated commands, but the fastest way is to do it in a single command, here is how:
Create an environment:
Code Block mamba create -n myENV -c conda-forge python=3 source activate myENV
Install Multiqc using the command found in step 1
Code Block mamba install -c bioconda multiqc
Combine commands from a, b, c into the fastest single command:
Code Block mamba create -n myENV -c conda-forge -c bioconda python=3 multiqc
And answer Y to the promoted question, if everything looks fine
Wait till the installation finish
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As explained in Python Package Installation Method Comparison , 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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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
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Almost all of the Python packages can be found on anaconda.org, and mamba is always preferred. |
The example Here we take a python package called q2-greengenes2
as an example. The commands to have a package it installed via pip
to a mamba env are:
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