My experience with Python can be summed up as: it's tempting to start something with it, since it has such low (initial) friction and hey, "this is just a small throwaway project anyway". Months or years later, it's a beast, hard to understand or refactor, full of holes and pitfalls, and Python's terrible tooling doesn't help either. And I never learn the lesson!
What tooling are you missing?
The linter is ok, and an occasional lifesaver (but it shouldn't even be needed! It requires extra work to catch problems that other languages catch "for free"). And it shouldn't be a separate tool. It's also cumbersome to use, silence what is not needed (way too noisy) and fine-tune it. Inline comments to enable/disable it for specific warnings look ugly, too. Python devs tend to suppress whatever bothers them instead of fixing it because it's not in their culture.
The type hinting checking is terrible. It's getting better, but it still misses obvious things and requires too much hand-holding. In my experience, average Python devs don't use it because they don't understand it, or don't find the ROI worthwhile. And because it's optional, they can just pretend it doesn't exist (or complain if you make it mandatory).
The mess that is dependency management has been discussed multiple times. In Python's defense, it's in "good" company with other messes from different languages. But Python's case seems particularly horrifying.
In general, with tooling, Python lives in a special hell where every blog and article will tell you "it's awful because you're doing it wrong, you should instead [use|avoid] pip, pyenv, pipenv, poetry, , , ".