GCEでpyenv&poetry&jupyterの環境構築

Most of pyenv installation part is based on this article, install pyenv and poetry on GCE instance.

Create debian instance on us-central1-a with instance name example-instance.

gcloud compute ssh --zone us-central1-a example-instance

Install dependencies

sudo apt install -y build-essential libssl-dev  libsqlite3-dev libbz2-dev libgdbm-dev libncurses5-dev libncursesw5-dev libreadline-dev zlib1g-dev libffi-dev liblzma-dev

In addition to the original article, I added liblzma-dev to install pyenv.
See pyenv wiki.

Install curl and git

sudo apt install -y curl git

Install pyenv

curl -L https://github.com/pyenv/pyenv-installer/raw/master/bin/pyenv-installer | bash

Add shell configuration

echo 'export PATH="$HOME/.pyenv/bin:$PATH"' >> ~/.bashrc
echo 'eval "$(pyenv init -)"' >> ~/.bashrc
echo 'eval "$(pyenv virtualenv-init -)"' >> ~/.bashrc
source ~/.bashrc

Install python 3.10.13 (the latest version of python 3.10) and set it as global.

pyenv install 3.10.13
pyenv global 3.10.13

Install poetry

curl -sSL https://install.python-poetry.org | python3 -
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc

Create workspace directory and initialize jupyter project.

mkdir workspace
cd workspace
poetry new deep-learning-project
poetry add --group dev jupyterlab

Run jupyter lab

nohup poetry run jupyter-lab --no-browser &
cat nohup.out

Copy the url with token.
http://localhost:8888/lab?token=xxxxxxxx

Add ssh pub key to GCE instance.
Set up ssh tunneling

ssh -i ~/.ssh/id_rsa -N -f -L 8888:localhost:8888 <external ip address>

Now, you can access jupyter lab from your local machine.