>I honestly can’t think of anybody in my career who’s been comfortable with dynamic languages that had a desire to move to static. It’s such an impediment to the entire programming style that it doesn’t naturally happen.
I'm someone who would be described as a pythonist. I learned CS in python, had a quick foray into Java (which I'm not particularly fond of), and then have done the vast majority of my coding, both personal and professional, in python. I'm a huge proponent of type hinting.
Reasons for this:
- It's not really an impediment. Quality code should already have APIs notated with argument and return types. Converting docstrings to mypy is easy.
- It's optional. You have some weird super dynamic magic nonsense. Cool, annotations are optional. Don't include them on your metaclass-generating decorator function. Being able to opt out of the safety guarantees easily is really really useful for those cases where you do want to abuse dynamism.
- Its super useful. I catch bugs faster now. I write less buggy code. Refactoring is much, much easier (mypy highlights the lines where I'm now doing bad attribute accesses etc.). Some of these things can be provided by a good ide, but I'm often not in an IDE, and this way I can run it as a pre-commit hook.
Agreed that for sysadmin work its maybe not as helpful. For math and ML, I think it is. There are issues that make numpy/tensorflow really difficult to typecheck internally, but there's active work on that front as far as I know.
I'm someone who would be described as a pythonist. I learned CS in python, had a quick foray into Java (which I'm not particularly fond of), and then have done the vast majority of my coding, both personal and professional, in python. I'm a huge proponent of type hinting.
Reasons for this:
- It's not really an impediment. Quality code should already have APIs notated with argument and return types. Converting docstrings to mypy is easy.
- It's optional. You have some weird super dynamic magic nonsense. Cool, annotations are optional. Don't include them on your metaclass-generating decorator function. Being able to opt out of the safety guarantees easily is really really useful for those cases where you do want to abuse dynamism.
- Its super useful. I catch bugs faster now. I write less buggy code. Refactoring is much, much easier (mypy highlights the lines where I'm now doing bad attribute accesses etc.). Some of these things can be provided by a good ide, but I'm often not in an IDE, and this way I can run it as a pre-commit hook.
Agreed that for sysadmin work its maybe not as helpful. For math and ML, I think it is. There are issues that make numpy/tensorflow really difficult to typecheck internally, but there's active work on that front as far as I know.