Running jupyter on a cluster

jupyter-server

#!/usr/bin/env bash
#### PBS preamble

#PBS -N jupyter-server
#PBS -o /path/to/software/logs/jupyter-server.${PBS_JOBID%%.*}.out

#PBS -j oe
#PBS -m n

#PBS -l mem=128GB
#PBS -l vmem=128GB
#PBS -l nodes=1:ppn=1

#### PBS preamble

#### SLURM preamble

#SBATCH --job-name=jupyter-server
#SBATCH --output=/path/to/software/logs/jupyter-server.${SLURM_JOBID%%.*}.out

#SBATCH --mem=128000
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1

#SBATCH --export=NONE #ALL

#### SLURM preamble

# change dirs to home directory
# TODO: if you want to access your /projects/ dir, change this to
#   `cd /projects/$USER/`
# or symlink your projects to your
# home directory
cd


# load up your conda environment
# TODO: change this to suit your needs/load your own python/conda and change envs.
# I do it through using a user-defined modulefile:
module use -a /path/to/software/modules
module load conda

# get nodes IP address
# TODO: If you aren't me, change this port number please!!
IPADDR=$(hostname -i)
if [[ -z "${PORT}" ]]; then
  PORT=8899
fi

# TODO: before launching, *please* make sure you have already run 
#     jupyter notebook --generate-config
#     jupyter notebook password
# in order to password protect your notebook server. Otherwise, anyone who stumbles upon your server
# will have write permissions as if they are you

# launch notebooks
jupyter notebook \
    --no-browser \
    --ip=${IPADDR} \
    --port=${PORT}