Pylint alerts corrections as part of an intervention experiment

[evidencebp]

Pylint alerts are correlated with tendency to bugs and harder maintenance.
I'd like to conduct a software engineering experiment regarding the benefit of Pylint alerts removal.
The experiment is described here.

In the experiments, Pylint is used with some specific alerts, files are selected for intervention and control.
After the interventions are done, one can wait and examine the results.

Your repository is expected to benefit from the interventions.
I'm asking for your approval for conducting an intervention in your repository.

See examples of interventions in stanford-oval/storm, gabfl/vault, and coreruleset/coreruleset.

You can see the planed interventions
The plan is to do 17 interventions in 13 files
The interventions will be of the following types:
superfluous-parens: 2
too-many-branches: 7
try-except-raise: 1
unnecessary-pass: 1
too-many-statements: 2
simplifiable-if-statement: 1
broad-exception-caught: 2
too-many-lines: 1

May I do the interventions?

[aliciaaevans]

I'll bring this to the attention of the @bioconda/core team and get back to you.

[evidencebp]

Thanks!

[bgruening]

+1 from me.

[evidencebp]

Thanks, @bgruening !

[evidencebp]

Please see the PR

[evidencebp]

There are some alerts that I'll be happy to get your advices about.

broad-exception-caught
bioconda_utils\lint_init_.py
The function lint_one catches Exception in line 614. The tried code is res = self.check_instances[check].run(recipe, fix) I did not figure out which exceptions are expected. The handing logs the exception. The method lint calls in line 557 msgs = self.lint_one(recipe_name, fix=fix) leading to the same confusion.

too-many-lines
bioconda_utils\githubhandler.py
The file has over 1,300 lines of code, making it hard to read and understand. The class contains some different classes so it is natural to split the classes into dedicated files. Are you ok with splitting the file? Are dedicated files per class the proper solution?

try-except-raise
bioconda_utils\aiopipe.py
Function process catches asyncio.CancelledError and immediately raises it.In principle, it can just be removed but doing that here will make it handled by the Exception section below. It is not logged like other exceptions in the function.Is it intended?