OHW22 Python tutorial environment changes

[abkfenris]

Please comment with any Python packages that are need for OHW22 tutorials here. We are looking to get all of these at least a week before the main event starts, so we aren't changing anything for the undergrads!

Users can create their own conda environments for projects, so those packages do not need to be installed into the base environment (which will help keep it smaller and faster).

Please use a checkbox for each package so we can track what has been added, ex:

- [ ] some-awesome-package, link to documentation if the conda package isn't obvious to someone who doesn't use it

The current Python environment is defined in https://github.com/oceanhackweek/jupyter-image/blob/main/py-base/environment.yml

[emiliom]

For Python env:

• [x] fsspec (https://anaconda.org/conda-forge/fsspec). Though, other packages (eg, echopype) probably already install it as a dependency (the same is true for other packages currently listed, such as numpy and s3fs); better to be explicit?

On a different note, git and nb_conda_kernels are listed twice in the Python env file. Twice the goodness?

[abkfenris]

Fsspec has been explictly added, but I should make sure some of the IAAS libraries are included.

• [x] s3fs
• [x] gcsfs
• [ ] abfs

[gmanuch]

We need tensorflow for the undergraduate program tutorial on Friday, Aug 12.

https://www.tensorflow.org/install

We will also be using tensorflow for projects and it's a pain to install, so I'd say it is necessary to pre-install it beforehand instead of asking for each user to do it on their own.

You can install the CPU version of tensorflow if the GPU version is too much of a trouble to install.

[abkfenris]

• [x] gh cli tool https://github.com/conda-forge/gh-feedstock

[abkfenris]

@gmanuch Conda makes it easy to install either version of Tensorflow, but as we don't have GPUs, and the GPU accelerated version easily doubled the size of the build, I installed tensorflow-cpu.

If you truly have projects and tutorials that would benefit from GPU accelleration, it would probably be worth making a Conda environment that participants can install locally to use.

[emiliom]

This request is not Python specific. Maybe it belongs in both Python and R.

• [x] nano

There's interest here (NW satellite) in having nano available. We mention nano in https://oceanhackweek.github.io/resources/prep/git.html#terminal-command-line-text-editor, but of course, if need be we can edit that text to remove mention of nano ... and replace it with notepad, maybe :roll_eyes:

[abkfenris]

Nano is in https://github.com/oceanhackweek/jupyter-image/pull/58