On Thu, 25 Nov 2021 at 21:45, Christopher Barker <pythonchb@gmail.com> wrote:
> The issue is that, intended or not, typing is making it's way into Python culture. As an instructor of beginning python users, I am unsure at this point when to introduce type annotations.
>
> What is their role? Up to today, I have treated them as an advanced feature, useful for "complex codebases". But there are any number of examples springing up on the internet, to the point where many students now think they are "best practice", if not actually required.

Agreed this is somewhat OT, but I also think the messaging around
annotations needs to be reviewed. I suspect that students will also
not clearly understand the fact that annotations aren't checked at
runtime. And IMO this is particularly difficult to get across in the
case of non-typechecker uses of annotations.

The following, for example, is extremely non-intuitive to me:

>>> from dataclasses import dataclass
>>>
>>> @dataclass
... class A:
...   n: int
...
>>> a = A("didn't expect this!")
>>> a
A(n="didn't expect this!")

Even though the "typing is optional" message is well-understood, my
instincts still lead me to expect that declaring the type of n will
result in a runtime type-check, in the constructor at least. (If I
check the code with mypy, it does raise an error, so that's good.
Although the more I think about it, given that I believe dataclasses
use eval "under the hood", the less I understand *how* it manages to
do that without special-case knowledge of the dataclass decorator...)

I'd like to see a clearer statement from "somewhere" about how APIs
should use annotations at runtime, such that Python users have a much
clearer intuition about APIs like the dataclass one, and library
designers can build their APIs based on a clear "common understanding"
of what to expect when annotations are used.