On Thu, 25 Nov 2021 at 21:45, Christopher Barker <python...@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.
Paul
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