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Anaconda on Caviness
$ vpkg_versions anaconda Available versions in package (* = default version): [/opt/shared/valet/2.1/etc/anaconda.vpkg_yaml] anaconda Open Enterprise Python * 5.2.0:python2 Anaconda Python2 5.2.0:python3 Anaconda Python3
Virtual Environment
If you are going to follow the instructions for creating an Anaconda virtual environment on Caviness consider using a slight modification to the documentation provided by each software package and use VALET to load the proper version of Anaconda for Python 2 or Python3 and also specify a path in your home directory not in the system path for Anaconda.
See the example below which creates a virtual Anaconda environment based on Python3 for FEniCS called fenicsproject
in the traine
home directory and installs all the fenics packages and mshr. Once the environment is created, then a simple test is done on a compute node via the devel
partition to verify the new fenicsproject
Anaconda environment is working properly.
[traine@login00 ~]$ vpkg_devrequire anaconda/5.2.0:python3 Adding package `anaconda/5.2.0:python3` to your environment [traine@login00 ~]$ conda create -p ~/fenicsproject -c conda-forge fenics fenics-dijitso fenics-dolfin fenics-ffc fenics-fiat fenics-libdolfin fenics-ufl mshr Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.5.11 latest version: 4.8.1 Please update conda by running $ conda update -n base -c defaults conda ## Package Plan ## environment location: /home/1201/fenicsproject added / updated specs: - fenics - fenics-dijitso - fenics-dolfin - fenics-ffc - fenics-fiat - fenics-libdolfin - fenics-ufl - mshr The following NEW packages will be INSTALLED: ... ... ... Proceed ([y]/n)? y Preparing transaction: done Verifying transaction: done Executing transaction: done ... ... ... # # To activate this environment, use: # > source activate /home/1201/fenicsproject # # To deactivate an active environment, use: # > source deactivate # [traine@login00 ~]$ workgroup -g it_css [(it_css:traine)@login00 ~]$ salloc --partition=devel salloc: Pending job allocation 5434421 salloc: job 5434421 queued and waiting for resources salloc: job 5434421 has been allocated resources salloc: Granted job allocation 5434421 salloc: Waiting for resource configuration salloc: Nodes r00n56 are ready for job [traine@r00n56 ~]$ source activate ~/fenicsproject (/home/1201/fenicsproject) [traine@r00n56 ~]$ python -c "import mshr" (/home/1201/fenicsproject) [traine@r00n56 ~]$ source deactivate [traine@r00n56 ~]$ exit exit salloc: Relinquishing job allocation 5434421 [(it_css:traine)@login00 ~]$
Using Anaconda's version of Python virtualenv to build PyQt5 by hand serves as a recipe for this specific installation, but can perhaps help others in solving similar installation dilemmas.