I’m very happy Rhys Mainwaring released a ROS Melodic software stack for their Curio rover, a sibling of my Sawppy rover. It looks good, so I’ve abandoned my own ROS Melodic project, but not before writing down some notes. Part 1 dealt with ROS itself, many of which Rhys covered nicely. This post about Python Style is part 2, something I had hoped to do for the sake of my own learning and I’ll revisit on my next Python project. (Which may or may not be a robotic project.)

The original motivation was to get more proficient at writing Python code that conforms to recommended best practices. It’s not something I can yet do instinctively, so every time I tackle a new Python project I have to keep PEP8 open in a browser window for reference. And the items not explicitly covered by PEP8 are probably covered by another style guide like Google’s Python style guide.

But the rules are useless without enforcement. While it’s perfectly acceptable for a personal project to stop with “looks good to me” I wanted to practice going a step further with static code analysis tools called “linter“s. For PEP8 rules, the canonical linter is Flake8 which is a Python source code analysis tool packaged with a set of default rules for enforcing PEP8. But as mentioned earlier, PEP8 doesn’t cover everything, so Flake8 has option for additional modules for enforcing even more style rules. While browsing these packages, I was amused to find the wemake Python style guide which called itself “the strictest and most opinionated python linter ever.”

I installed wemake packages so that I can make Python code in my abandoned ROS Melodic project compliant with wemake. While I can’t say I was thrilled by all of the rules (it did get quite tedious!) I can confirm it does result in very consistent code. I’m glad I’ve given it a try, and I’m still undecided if I’m going to commit to wemake for future Python projects. No matter the final decision, I’ll definitely keep running at least plain flake8.

But while consistent code structure is useful for ease of maintenance, during the initial prototyping and algorithm design it’s nice to have something with more flexibility and immediate feedback. And I’ve only just discovered Jupyter notebooks for that purpose.