pants VS pyupgrade

> C/C++'s header system with conditional inclusion

Wouldn't it be more accurate to say something like "older build systems"? I don't think any of the things you listed are "modern". Which isn't a criticism of their legacy! They have been very useful for a long time, and that's to be applauded. But they have huge problems, which is a big part of why newer systems have been created.

FWIW, I have been using pants[0] (v2) for a little under a year. We chose it after also evaluating it and bazel (but not nix, for better or worse). I think it's really really great! Also painful in some ways (as is inevitably the case with any software). And of course it's nearly impossible to entirely stomp out "genrules" use cases. But it's much easier to get much closer to true hermeticity, and I'm a big fan of that.

0: https://www.pantsbuild.org/

Does pants/bazel can help me?

Hyper-large tech companies managing hyper-large monorepos using Bazel (google), buck (Facebook), please (thought machine), pants (Twitter, Foursquare & Square) enjoy them but also have a lot of resources devoted to running and maintaining it.

Yeah there's definitely some alternatives out there. Pants is another one that has a lot of traction.

You should look into pex, or it’s parent build system pants. A PEX (Python EXecutable) file can package up all your code including dependencies and run on another machine of similar OS with just an available compatible interpreter.

We don't have the CD yet, but I think what I put in place counts as simple CI (even if incomplete)? Every push & PR trigger an azure pipeline, which runs pants. This install the dependencies from the lockfile, run some linters, uses DVC to pull the data necessary for tests, and run unit tests (mypy check is deactivated until I solve a weird error). Basically the same script runs on laptops cross-platform (one of us uses Max, one Ubuntu with GPU, one Ubuntu with CPU, the scripts runs on every platform). The only difference with CI is the installation of Pants and the gestion of Cache (needs to be downloaded in CI so it takes ~3min in CI versus 20 seconds on my laptop).

This has also been recently integrated in pants.

https://github.com/pantsbuild/pants/issues/13393

pyupgrade and flynt are examples of tools that modify your code base from earlier python versions into the newest python syntax, rewriting all string formats into f-strings and similar things.

pyupgrade - A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.

He made yesqa and pyupgrade (among others), and also works on flake8. His main job is for https://sentry.io/.

That's a decade to make a 30 second change. Add something like https://github.com/asottile/pyupgrade to your pre-commit hooks and you won't even need 25 of those seconds.

There is also pyupgrade: https://github.com/asottile/pyupgrade

pyupgrade is a useful tool that can help you find some of these things.

and last a little plug or two -- because I do this all for free and despite millions benefiting I receive zero proportional benefit from the maintenance work I put in -- consider sponsoring or maybe check out pre-commit.ci which would have automatically fixed this problem for you a year and a half ago

Running https://github.com/adamchainz/django-upgrade with https://github.com/asottile/pyupgrade recursively will give an idea about how much work is there on Django side. Still, there may have dependency on third party libraries (both django+python). Another thing to consider is which role Django performing here, serving APIs or html views. As good test coverage is already there, you are on lucky side.

Such goodness here and even points to an interesting project I’d never heard of for automated “de-deprecation”

https://github.com/asottile/pyupgrade

I do would like to recommend pyupgrade. Just pip install as expected and then run pyupgrade --py310-plus to drag your code kicking and screaming into $CURRENT_YEAR. Or at least into whatever version you're using :)