Python bash wrappers

dpython.sh

#!/bin/bash
# Add a timestamp to the python's output.
# Example:
# dpython -c "[print(i) for i in range(5)]"
# [2019-01-20 14:19:39]  0
# [2019-01-20 14:19:39]  1
# [2019-01-20 14:19:39]  2
# [2019-01-20 14:19:39]  3
# [2019-01-20 14:19:39]  4
# Setup:
# mkdir ~/bin && cp ./dpython.sh ~/bin/dpython
# chmod u+x ~/bin/dpython
# shellrc="$HOME/.$(ps | grep `echo $$` | awk '{ print $4 }')rc"
# echo 'export PATH="$HOME/bin:$PATH"' >> $shellrc
# echo 'alias dpy=dpython' >> $shellrc


python "$@" | while read n; do
    echo "$(date '+[%Y-%m-%d %H:%M:%S] ') $n";
done

gpython.sh

#!/bin/bash
# Run a python interpreter with an available GPU.
# Example:
# gpython -c "import torch; torch.as_tensor([1,2,3], device='cuda')"
# Setup:
# mkdir ~/bin && cp ./gpython.sh ~/bin/gpython
# chmod u+x ~/bin/gpython
# shellrc="$HOME/.$(ps | grep `echo $$` | awk '{ print $4 }')rc"
# echo 'export PATH="$HOME/bin:$PATH"' >> $shellrc
# echo 'alias gpy=gpython' >> $shellrc

# Get list of gpus
gpus=$(nvidia-smi -L | grep -o "GPU .")
readarray -t gpus <<<"$gpus"

# Find an available GPU
for gpu in "${gpus[@]}"
do
    gpu="$(echo $gpu | cut -d' ' -f2)"
    gpu_no_processes=$(nvidia-smi -q --display=PIDS -i $gpu | grep "Processes.*: None")
    if [[ -n $gpu_no_processes ]]
    then
        assigned_gpu=$gpu
        break
    fi
done

# Run the interpreter if a GPU is available
if [[ -n $assigned_gpu ]]
then
    echo "Assigned GPU $assigned_gpu"
    export CUDA_VISIBLE_DEVICES=$assigned_gpu; python $@
else
    echo "No GPUs availables"
fi