Jupyterlab docker container

Update ./jupyterlab/environment.yml with your dependencies

Update the ports in docker-compose.yml

Build and run the container:

docker compose up jupyterlab

Choose the conda env kernel (not IPython) in your notebooks.

Before training and pickling a model:

• Rebuild the jupyterlab container to get the most recent python modules:

  docker compose up --build --no-start binaries docker compose up --build --no-start forge docker compose up --build jupyterlab

• Get the versions of numpy, pandas, scikit-learn (and any other serialized dependencies) from inside the notebook:

  !pip list

• Pin the versions found in ./jupyterlab/environment.yml so that pickled objects can be deserialized correctly later.

  • numpy=1.23.1
  • pandas=1.4.3
  • scikit-learn==1.1.2