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Information

Purpose: Statistics and Plotting
Latest version: 4.6.4
Licence: Open Source - BSD ext-link
Website: https://conda.io/en/latest/ ext-link

Conda is an open source package management system and environment management system that quickly installs, runs and updates packages and their dependencies. It, also, easily creates, saves, loads and switches between environments. It was created for Python programs, but it can package and distribute software for any language (Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++, FORTRAN...).



Useful commands

conda env list

conda list

conda activate




Environments

Since the 3.x is newer, this should be your default choice.

Switching or moving between environments is called activating the environment.

By default there are some basic environments installed in the system:

  • Machine learning / Deep learning:
    • TensorFlow
    • Pytorch
    • Keras (Neural networks)
    • Sklearn
  • Modelling optimitzation
    • Pyomo
  • Statistics & computing
    • Dask
    • Pandas
    • Theano


With Conda, you can create, export, remove, and update your own custom environments that have different versions of Python and/or packages installed in them. Theses custom environments are installed in ~/.conda/env/<env_name> by default. Switching or moving between environments is called activating the environment.



SLURM Submit script example

This script example has been generated using the Job Script Generator.

conda_example.slm
#!/bin/bash
#SBATCH -J conda_example
#SBATCH -e conda_example.err
#SBATCH -o conda_example.out
#SBATCH -p std
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --mem=2000MB

module load apps/conda/3

INPUT_DIR=${SLURM_SUBMIT_DIR}
OUTPUT_DIR=${SLURM_SUBMIT_DIR}

cd $SCRATCH
cp -r $INPUT_DIR/* $SCRATCH

conda activate environment_name
python example.py

cp ./* $OUTPUT_DIR



Sbatch options:

  • -J: Specify a name for the job allocation. The default is the name of the batch script.
  • -e: Specify a name for the error output file.
  • -o: Specify a name for the output file.
  • -p: Specify the name of the partition (queue) where the job will be submitted. The default is std.
  • --nodes: Number of nodes requested for allocation.
  • --ntasks: Number of processes requested for allocation.
  • --mem, --mem-per-cpu: Memory allocated per node/core respectively. If it is not specified SLURM associates:
    • 3998MB per requested core in std and gpu nodes.
    • 24180MB per requested core in mem nodes.



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