HPCaVe provides Anaconda distributions of Python 2.7 and 3.5. In each of these, you will find few predefined environnements regrouping the most used softwares, which can be used as they are, or cloned in your home directory (30Go) to customize them as needed.

More information are available on the User Guide of the Conda documentation, as well as a reminder of the most useful commands in the Conda cheatsheet (PDF).

Working with Anaconda

Loading a predefined conda environment

Before using the conda tools and environments, you must first load the appropriate module, chosen with module avail:

> module avail
--------------------------------------- /opt/dev/Modules/Anaconda ---------------------------------------
conda2/lua-torch       conda2/R-3.4           conda3/simflow-cfd-py3
conda2/paraview-5.2    conda2/simflow-cfd

> module load conda3/simflow-cfd-py3

Once the appropriate Conda module is load (using module load + environnent name) , you can gain access to the available Conda environments with the command conda-env list:

> conda-env list
# conda environments:
Python-3.6_base          /opt/dev/Langs/Conda3/envs/Python-3.6_base
biologie                 /opt/dev/Langs/Conda3/envs/biologie
lua-torch-py3            /opt/dev/Langs/Conda3/envs/lua-torch-py3
maths                    /opt/dev/Langs/Conda3/envs/maths
simflow-cfd-py3          /opt/dev/Langs/Conda3/envs/simflow-cfd-py3
root                  *  /opt/dev/Langs/Conda3

To activate your environment  use the  source activate command. Then if you want to check the available packages use the  conda list command. For instance:

>source activate maths
(maths) user@mesu1:~> conda list
# packages in environment at /opt/dev/Langs/Conda3/envs/maths:
alabaster 0.7.9 py35_0 conda-forge
aragorn 1.2.36 1 bioconda
argcomplete 1.8.2 py35_0 conda-forge
argparse 1.4.0 py35_0 bioconda
args 0.1.0 py35_0 conda-forge
argutils 0.3.2 py35_0 bioconda
aria2 1.23.0 0 bioconda
astalavista 3.2 0 bioconda
astroid 1.4.8 py35_0 conda-forge
astropy 1.3 np111py35_0 conda-forge

Creating your own conda environment

If the default environment provided by HPCaVe does not suit you, the possibilty of initializing a new Conda environment from scratch, specifying the installation directory and the packages you want is feasible. You can use conda commands as user without root priviledge. For instance:

> conda create -p /path/to/your/new/env numpy boost alabaster vtk
Fetching package metadata ...........

The following NEW packages will be INSTALLED:

    alabaster:       0.7.10-py27he5a193a_0
    boost:           1.65.1-py27_4        
    bzip2:           1.0.6-h6d464ef_2     
    ca-certificates: 2017.08.26-h1d4fec5_0
    certifi:         2018.1.18-py27_0     

To activate or  deactivate a newly created Conda environment, use the commands source activate and source deactivate:

> source activate /path/to/your/new/env
(newEnv) user@mesu1:~> source deactivate /path/to/your/new/env

Clone an existing conda environment

You can also clone one of the predefined conda environments (available through conda-env list) if most of the tools you wish to use are already present in it, then add new packages as necessary with the conda install command for instance:

> conda create -p /path/to/your/new/env --clone bio
> source activate /path/to/your/new/env
(yourNewEnv) > conda install vtk