Distribute docs build over number of CPUs.

[cosenal]

Description

An attempt to speed up docs build (related to #2083, but not the same as that's about RTD).
It looks like the bottleneck is the notebook execution. MyST-NB is parallel-friendly, hence this attempt.

Some data points from testing this on my local machine (Apple M2 Pro):

Build	time make docs-clean
Serial	962.92s user 424.57s system 193% cpu 11:57.48 total
Parallel	1052.97s user 250.09s system 443% cpu 4:53.88 total

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License

• I license this contribution under the terms of the GNU GPL, version 3 and grant Unitary Fund the right to provide additional permissions as described in section 7 of the GNU GPL, version 3.

Before opening the PR, please ensure you have completed the following where appropriate.

N/A - [ ] I added unit tests for new code.
N/A - [ ] I used type hints in function signatures.
N/A - [ ] I used Google-style docstrings for functions.
N/A - [ ] I updated the documentation where relevant.

• Added myself / the copyright holder to the AUTHORS file

[github-actions]

Hello @cosenal, thank you for submitting a PR to Mitiq! We will respond as soon as possible, and if you have any questions in the meantime, you can ask us on the Unitary Fund Discord.

[nathanshammah]

Nice! It's failing here, not sure why.

[cosenal]

@nathanshammah Yes, I cancelled the workflow, because I saw it failing on the docs build, which I am investigating. I am leaving it as a Draft PR until the build is fixed.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.72%. Comparing base (c0688d8) to head (8b5530d).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #2235   +/-   ##
=======================================
  Coverage   98.72%   98.72%           
=======================================
  Files          92       92           
  Lines        4161     4161           
=======================================
  Hits         4108     4108           
  Misses         53       53           

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[nathanshammah]

Is this blocked by the PyData Sphinx theme action?

[cosenal]

@nathanshammah indeed – I have just dropped a comment there

[cosenal]

Since v0.15.4, the Sphinx theme enabled parallel write. The next blocking factor is Jupyter-cache not supporting parallel execution, see executablebooks/jupyter-cache#37 and sphinx-doc/sphinx#12481.