I have grown to believe that python is not appropriate for any organization where multiple teams will work in the same codebase / repo. The system is prone to disorder and should be in the same category as perl for similar reasons.
Programming is a team sport and static types is just too useful and the bolted on typing is insufficient. We are burning, literally, millions of dollars in salaries to make python work at our org. It has been the same now at the four shops I've been a staff/principal level. Dynamic languages lend towards less maintainable code because the compiler offloads work to your squishy human working memory.
I tend to agree, the flexibility that non-statically typed languages (i.e. Python) offer on smaller-scale projects (very) quickly diverges to chaos on larger-scale. With scale, rules and rigidity provide structure, without they provide verbosity and bureaucratic obstacles. Unfortunately “scale” is a gradient, not discrete, so there’s no “right answer” - hence the waste you experience. Ultimately, waste is in the eye of the beholder… “One person’s waste is another’s GDP.”
mypy helps, but I generally agree. Similar thing on the node side.. Typescript is great but it's still a lot harder to scale an application. It can be done in dynamic languages obviously (PHP: Slack, Typescript: VSCode) but IMO it's harder.
Despite having a big Django/DRF and FastAPI footprint, our backends in-development are using C#/aspnet.
Programming is a team sport and static types is just too useful and the bolted on typing is insufficient. We are burning, literally, millions of dollars in salaries to make python work at our org. It has been the same now at the four shops I've been a staff/principal level. Dynamic languages lend towards less maintainable code because the compiler offloads work to your squishy human working memory.