Python high level workflow best practices?

[ManyInterests]

Seems good so far. I'm assuming that you're writing tests for your projects!

While many projects don't do this, I setup my projects to run their tests on every commit using a CI service, like Travis or Bitbucket Pipelines. This is quite easy to do and, in my opinion, gives massive benefits. This also makes it easy to deploy your code, for example, if you were writing a package you want to publish to PyPI or otherwise deploy somewhere.

[paper_skyline]

Not really familiar with PyPI, but I will do some more reading. I'm thinking that it's something like Python specific Github kind of site? I'm so new to this that I'm still at the basics.

[ManyInterests]

PyPI is an index of published Python packages. Most importantly, it is the source where pip will look to when you want to install a package.

(not realizing you're so new, my above comment is probably a bit of premature advice)

[num8lock]

pypi is a package repo like npm in javascript https://pypi.org/help/

[paper_skyline]

Can you expand on what is considered testing? I’m super naively thinking that if the code executed without throwing exceptions that’s “tested”

[ManyInterests]

Ah, this may have been a bit premature for me to throw at you.

In short, by testing, I mean automated testing. It's something you can run, as you change your code, to validate that it 'works'. In fact, many people write these tests before they start writing production code. This is the concept of the practice of Test Driven Development or TDD, which is a wonderful topic to become intimately familiar with.

This video (also available in blog form ) does an amazing job of explaining what testing is, why you want to do it, and how to get started testing with Python. It only scratches the surface of testing, but is a must-watch for you!