additional-information.md

Additional Information

Dockerfile Best Practices

Additional Kernels

To install a new kernel that can be selected within a jupyter notebook, you can look into creating a second conda environment and use nb_conda_kernels to add it in.

Keep your images small

Concatentate RUN steps into a single RUN block

# Creates a separate image layer for every RUN block
RUN apt-get -y update
RUN apt-get install -y python

# Single RUN block results in a smaller image
RUN apt-get -y update && \
    apt-get install -y python

If you've converted all your RUN statements and find that your container is still prohibitively large, try breaking your container into a multi-stage build or have multiple containers for different purposes.

Use Mamba instead of Conda when Conda is slow

Sometimes you may need to install a conda package. If you include a statement like below:

RUN conda install <package> -y

and you find that it an in-ordinate amount of time to install, you can try using mamba. It works faster.

If that still doesn't work, you can try to manually install your software

Remove unused files and software

If you need to reduce the size of your image, try removing files and/or software you may not need. You can also try starting from our smallest image ucsd-ets/datahub-base-notebook as your starting point An overview of standard Datahub/DSMLP containers maintained by UCSD EdTech Services