I work on a project that uses type hints but not mypy. To be fair, we used to use mypy, but there was just too much code that it couldn't check (sqlalchemy models, schematics models, some custom models, essentially lots of different data-modelling types!) Maybe it's improved since then, but it just wasn't mature enough at the time.
However, type annotations still make the code so much easier to work with, because they serve as documentation and are understood by the IDE. When I hit "." I actually get correct autocompletion because of the type annotations. When I want to know what a function returns I don't need to dig through multiple levels of function calls.
The article seems to be suggesting that because the type annotations might be wrong that they are worthless, which seems like a ridiculous argument. Any documentation can be wrong, but clearly having documentation that is 99% accurate is better than not having it at all.
I've found that it's pretty easy to slowly enable mypy checking. You can mark modules with "type:ignore" to make mypy ignore them. Then, you can move to marking individual statements with "type:ignore". Finally, you can start marking modules with "mypy: disallow-any-generics" at the top. That requires that functions are annotated with types.
In a large code base, our team has found type annotations and mypy to be quite helpful. If you are writing a quick-and-dirty script, forget about wasting time with type annotations. However, for long-lived and important code, it seems to be worth adding the types.
Another thing I noticed, if your type annotations are hard to write, e.g. lots "Union", "Optional" or deeply nested type expressions, it's probably a sign that your code is poorly designed. Think about what types you actually want to consume and return. Define new containers using dataclasses or attrs to keep the types simple, if required.
Right - I mean we had mypy passing across the whole project, but it just wasn't detecting any issues because so many of our types had to be ignored because mypy didn't understand that the runtime type of a Column field in SQLAlchemy is not Column, and things like that.
Rather than maintain all of the mypy stubs for no benefit, we decided to just scrap mypy.
> You can mark modules with "type:ignore" to make mypy ignore them.
If I added MyPy to the CI/CD checks, some coworkers would flood the code with these to not have to think about their typing. Too bad that some libraries like SQLAlchemy make this mandatory sometimes. I'd like the option to ignore these "type:ignore", but the type system is too immature and has to be overridden sometimes.
Touché. I guess a common pattern I find myself doing for Union types is having if statements checking if something is of a type using reflection. When checking if it is none, it is more elegant.
There are still a lot of libraries without hints, so mypy has to be told to ignore them in the setup.cfg file. Last I checked, sqlalchemy still isn't so good with mypy. So we have it ignored. But mypy is still great overall.
However, type annotations still make the code so much easier to work with, because they serve as documentation and are understood by the IDE. When I hit "." I actually get correct autocompletion because of the type annotations. When I want to know what a function returns I don't need to dig through multiple levels of function calls.
The article seems to be suggesting that because the type annotations might be wrong that they are worthless, which seems like a ridiculous argument. Any documentation can be wrong, but clearly having documentation that is 99% accurate is better than not having it at all.