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Software Information
Environments
One of the most powerful characteristic of CONDA is the use of virtual environments to set-up your project software needs. Each of them is independent, so the management of different versions of the same software can be done in a straight forward way.
Custom environments can be easily created by the user himself. Those custom environments are installed in /scratch/<user>/.conda/env/<env_name> by default.
Useful commands
| Command | Description |
|---|---|
conda env list | List available environments. |
conda activate env_name | Activate the environment env_name. |
conda list | List installed packages in the active conda environment. |
conda create -n my_env | Create an environment called my_env. The custom creation path is /scratch/<user>/.conda/envs/my_env. |
conda install package | Install the package in the active conda environment. |
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#!/bin/bash
#SBATCH -J conda_example
#SBATCH -e conda_example.err
#SBATCH -o conda_example.out
#SBATCH -p std
#SBATCH -n 1
#SBATCH -t 0-02:00
module load apps/conda/current
##
# Modify the input and output files
INPUT_FILE=example.py
OUTPUT_FILE=example.log
cp -r ${SLURM_SUBMIT_DIR}/${INPUT_FILE} ${SCRATCH}
cd ${SCRATCH}
# Modify the environment name
conda activate environment_name
srun python ${INPUT_FILE} > ${OUTPUT_FILE}
cp ./${OUTPUT_FILE} ${SLURM_SUBMIT_DIR} |
Sbatch options:
The options shown in the example are detailed below. For more information and a more comprehensive list of available options, see the sbatch command page.
- -J: Name for the job's allocation.
- -e: Name of the sterr redirection filename.
- -o: Name of the stdout redirection filename.
- -p: Name of the partition (queue) where the job will be submited.
-n: Number of tasks.
- -c: Number of cores per task.
- -t: Set the job's time limit. If the job don't finish before the time runs out, it will be killed.