Imagine that we are working on a generic project called
project-name then the
setup is as follows
conda create --name project-name python=3.7 conda activate project-name pip install poetry poetry config virtualenvs.create false poetry install --no-root ipython kernel install --name "project-name" --user
This initialises a
conda environment with a name and the correct python version,
poetry using pip, and then installs and manages your packages through
poetry, finally it installs a jupyter kernel with the same name.
project-name to the name of your repo and you’re all set!