Mailman 3 February 2023 - Typing-sig

Re: Typing Meetup
by S Pradeep Kumar 19 Sep '23

19 Sep '23

Updating the Typing Meetup date to Wednesday as there were some conflicts. Let me know if there are any major time conflicts. Date: *Wednesday, November 03, 2021.*Time: 10 am San Francisco time (UTC-7) / 5 pm London time (UTC) Duration: 1 hour Potential discussion topics: + Typing **kwargs using a TypedDict (Franek Magiera?, Pradeep) [1] + Remaining questions about Callable syntax (Steven) + Non-required Protocol fields (Sebastian Rittau?) [2] + Type support for sealed classes (Adrian Freund?) [3] + Safe, typed JSON validation + Type system documentation (Shannon?) If you're working on these or any other topics and would like to start a discussion at the meetup, reach out to me. If you have interesting topics you'd like to see discussed, share them too. Once we have topics, we can always start a discussion even if there's no proposer yet. We will probably have time for 3-4 topics in this session. On Fri, Oct 15, 2021 at 12:55 PM S Pradeep Kumar <gohanpra(a)gmail.com> wrote: >>> >>>> Hello all, >>>> >>>> We plan to hold a virtual Typing Meetup to discuss key typing-related >>>> issues in real-time. The idea is that we can make progress on important or >>>> controversial discussions, get early feedback on in-progress PEPs, and >>>> gauge interest in new proposals. >>>> >>>> A virtual meetup will be more accessible to people in other timezones >>>> than Bay Area in-person meetups. It should also help consolidate >>>> discussions that are often spread out across mailing lists or Github repos. >>>> The tentative plan is to have a monthly meetup, but we can change that as >>>> needed. >>>> >>>> Date: Monday, November 01, 2021. >>>> Time: 10 am San Francisco time (UTC-7) / 5 pm London time (UTC) >>>> Duration: 1 hour >>>> >>>> Time and date are flexible. I'll share the zoom link and agenda the >>>> week before. I'll also record the meetup and share afterwards. >>>> >>>> If you're interested in presenting a new proposal or your work on some >>>> existing proposal, please respond here. We can shoot for 15 minutes per >>>> presentation. I know there are quite a few interesting threads on >>>> typing-sig that haven't seen much activity in a while :) >>>> -- >>>> S Pradeep Kumar >>>> _______________________________________________ >>>> Typing-sig mailing list -- typing-sig(a)python.org >>>> To unsubscribe send an email to typing-sig-leave(a)python.org >>>> https://mail.python.org/mailman3/lists/typing-sig.python.org/ >>>> Member address: guido(a)python.org >>> >>> Links: [1] Typing **kwargs using TypedDict: https://mail.python.org/archives/list/typing-sig@python.org/thread/IUCXT2IQ… [2] Non-required Protocol fields: https://mail.python.org/archives/list/typing-sig@python.org/thread/P6FCGRJU… [3] Sealed classes: https://mail.python.org/archives/list/typing-sig@python.org/thread/QSCT2N4R… -- S Pradeep Kumar

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Type narrowing for TypeGuard in the negative case
by Eric Traut 04 Aug '23

04 Aug '23

Since the introduction of PEP 647 (User-defined Type Guards), we've received a steady stream of input from users saying that they don't like the limitation that type narrowing is applied only in the positive case and is not applied in the negative case. In general, type narrowing is not safe to perform if a user-defined type guard returns False, so I've stood by the original decision not to provide type narrowing in the negative case, but there are cases where such narrowing is safe and desirable. Here's a recent thread where this was discussed in some detail: https://github.com/python/typing/issues/996#issuecomment-1002716830 In this discussion, Ilya Kamen proposed a solution. The proposal is to extend the existing `TypeGuard` to support an optional second type argument. If present, the second argument indicates the narrowed type in the negative type narrowing situation. Here's a simple (admittedly contrived) example: ```python def is_str(val: str | int) -> TypeGuard[str, int]: return isinstance(val, str) def func(val: str | int): if is_str(val): reveal_type(val) # str else: reveal_type(val) # int ``` I've implemented this proposal in the latest published version of pyright (1.1.202) so folks can experiment with it and see if they like it. If there's general consensus that it's the right approach, I can file an amendment for the existing PEP 647 to include this functionality. It was trivial to add to pyright, so I'm optimistic that it would likewise be easy to add to the other type checkers. Another common request for PEP 647 is the desire for an "assert" form of TypeGuard — a way to indicate that a function performs runtime validation of a type, raising an exception if the type is incorrect. It occurred to me that this two-argument form of `TypeGuard` could also be used to handle this use case. The second argument would be specified as a `NoReturn`. I've provisionally implemented this in pyright as well (although it's not in the currently-published version — you'll need to wait until 1.1.203 is published). Here's what this would look like: ```python def validate_sequence(val: Sequence[_T | None]) -> TypeGuard[Sequence[_T], NoReturn]: """Verifies that the sequence contains no None values""" if len([x for x in val if x is not None]) > 0: raise Exception() return True def func(val: Sequence[int | None]): validate_sequence(val) reveal_type(val) # Sequence[int] ``` I'm interested in input on these proposals. -Eric -- Eric Traut Contributor to Pyright & Pylance Microsoft

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Any way to express that a dict is expected to have a key(s) but don't care about other keys?
by Brett Cannon 20 Jun '23

20 Jun '23

Looking at TypedDict it seems that it does not like the idea of superfluous keys existing in a dict. In my case I have a REST call returning JSON for an error and all I'm guaranteed is to get an "error" key. But there may be extra keys that provide more details about the specific error. Unfortunately I don't know the exhaustive list of keys so I can't use a TypedDict with `totality == False` to try to be complete. I can't think of any way to somehow say "require/expect this one key, but other keys are OK". Am I missing anything that would let me do this?

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Runtime Access to Type Parameters
by Saul Shanabrook 07 Jun '23

07 Jun '23

I would like to propose being able to access, at runtime, the type parameters in classmethods and in constructors. I wrote up a draft PEP on this to capture the thinking here: https://github.com/saulshanabrook/peps/blob/master/pep-9999.md It seems easier to add them to classmethods, so even that addition alone would be very welcome! It could be added to Guido's existing draft PR for pep 585, by making a small change in the getattr function (https://github.com/python/cpython/pull/18239/files#diff-a34ae826f869897e56e…), to first do a `__getattribute__` and check if the result is a descriptor (has a `__get__` attribute), and if so passing the generic class itself in as the class, instead of the origin class. I wrote up a little example of that in the PEP. To make it available in the constructor, I proposed adding a global function `get_parameters` to `typing` which returns the parameters in the constructor. I also provide a little mock implementation of that. Note that work is only for custom classes which inherit from `typing.Generic` not for any built in collections.

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Extending published stubs
by Irv Lustig 26 Apr '23

26 Apr '23

I'm the leader of the pandas-stubs project. In pandas, users can extend the library by creating their own accessor via `(a)pd.api.extensions.register_dataframe_accessor` (see https://pandas.pydata.org/docs/reference/api/pandas.api.extensions.register…). So for a `DataFrame`, if you do `(a)pd.api.extensions.register_dataframe_accessor("xyz")`, you now have `DataFrame.xyz` returning the class you annotated. Now suppose you want to create a stub for your new accessor, that would extend the existing pandas-stubs. AFAIK, there isn't a way to do something like this in a stub: ``` from pandas import DataFrame @typing.extend class DataFrame: def xyz(self) -> MyXyzClass: ... ``` The idea here is that there is a class (in this case, `DataFrame`) that already has stubs, and you want to add a method to it. Has this idea been discussed anywhere?

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Support Algebraic Data Types with @sealed
by John Hagen 20 Mar '23

20 Mar '23

The original (superseded) PEP 622 proposed adding a @sealed decorator so that users could define algebraic data types (ADTs) that static type checkers could verify are `match`ed exhaustively: - https://peps.python.org/pep-0622/#sealed-classes-as-algebraic-data-types There is a somewhat fairly-upvoted question about ADTs in Python, indicating interest in this area: - https://stackoverflow.com/questions/16258553 @sealed would be very valuable towards making ADT usage within Python more type-safe. Is there any historical discussion about why @sealed was dropped from the final pattern matching PEP? What would be the next steps needed to push this forward? Would writing a new PEP be the next step?

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PyCon 2023 Typing Summit: Interest form
by S Pradeep Kumar 16 Mar '23

16 Mar '23

Hello all, PyCon 2023 is just a few months out. Jelle and I are looking forward to organizing the Typing Summit this year. We plan to be in-person in Salt Lake City, as we did last year. We have confirmed the Typing Summit with PyCon and will announce the exact date soon (tentatively a day before the main conference talks). We will try to record the event for those who cannot make it. For those who haven't attended before, the Typing Summit is a 3-4 hour event with a series of presentations and group discussions related to type checking. You can find the 2022 summit here: https://youtu.be/BNTkWQfqP_c If you are interested in attending, please fill out this form: https://forms.gle/yv1WnDoAVscg21vW8. This way, we can get a sense of the expected number of attendees and the topics you want to hear about. In a few weeks, we will send out another mail to typing-sig calling for presenters. Let us know if you have any questions. Best, Jelle Zijlstra Pradeep Kumar Srinivasan

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Opened and changed typing issues week 2023-W08
by Typing Bot 27 Feb '23

27 Feb '23

The following is an overview of all issues and pull requests in the typing repository on GitHub with the label 'topic: feature' that were opened or updated last week, excluding closed issues. --------------------------------------------------- The following issues and pull requests were updated last week: #256 Possible to distinguish between Sequence[str]/Iterable[str] and str? opened by @jtatum https://github.com/python/typing/issues/256 #1160 Allow `float("inf")` and `float("-inf")` in literals opened by @antonagestam https://github.com/python/typing/issues/1160 #1273 Type lookup table for generics opened by @jonathanslenders https://github.com/python/typing/issues/1273 --------------------------------------------------- All issues and pull requests with the label 'topic: feature' can be viewed under the following URL: https://github.com/python/typing/issues?q=label%3A%22topic%3A+feature%22

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Is it possible to annotate decorators that work on both functions and methods?
by Neil Girdhar 26 Feb '23

26 Feb '23

It appears to be impossible to perfectly annotation a decorator that works on both functions or methods. And also, it's particularly hard to implement the __get__ method. I propose adding typing.PositionalSubstitute to resolve this. Consider: from typing import Callable, Generic, Protocol, TypeVar, overload, Any from typing_extensions import ParamSpec, Self, Concatenate V_co = TypeVar("V_co", covariant=True) U = TypeVar("U", contravariant=True) P = ParamSpec("P") class Wrapped(Protocol, Generic[P, V_co]): def __call__(self, /, *args: P.args, **kwargs: P.kwargs) -> V_co: ... class MethodWrapped(Protocol, Generic[U, P, V_co]): def __get__(self, instance: Any, owner: Any = None) -> Wrapped[P, V_co]: ... @overload def jit(f: Callable[Concatenate[U, P], V_co]) -> MethodWrapped[U, P, V_co]: # type: ignore pass @overload def jit(f: Callable[P, V_co]) -> Wrapped[P, V_co]: # pyright: ignore pass def jit(f: Callable[..., Any]) -> Any: pass class X: @jit def f(self, x: int) -> None: pass @jit def g(x: int, y: float) -> None: pass x = X() x.f(3) x.f(x=3) g(3, 4.2) g(x=3, y=4.2) # Fails! reveal_type(x.f) reveal_type(g.__call__) We can't seem to deal with the method case alongside the function case. Here's the proposed solution: class Wrapped(Protocol, Generic[P, V_co]): def __call__(self, *args: P.args, **kwargs: P.kwargs) -> V_co: ... def __get__(self, instance: U, owner: Any = None ) -> Wrapped[PositionalSubstitute[P, U], V_co]: ... # Much easier! def jit(f: Callable[P, V_co]) -> Wrapped[P, V_co]: # pyright: ignore pass # No overloads! The idea is that PositionalSubstitute takes a ParamSpec argument and returns it less that ParamSpec's first positional parameter. It verifies that this removed parameter matches its second argument. This could be generalized to substitute with tuples (or ParamSpec.args), or generalized to support multiple applications (taking a tuple argument as its second argument).

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Should we add a contains_only type guard to the collection mixin?
by Neil Girdhar 26 Feb '23

26 Feb '23

As type guards become more popular, this one may become extremely common: ``` _T = TypeVar("_T") class Collection: def contains_only(self, type_: Type[_T]) -> TypeGuard[Collection[_T]]: return all(isinstance(x, type_) for x in self) # usage: usernames = settings_dict['usernames'] assert isinstance(usernames, list) assert usernames.contains_only(str) # Ensure it contains only strings. assert_type(usernames, list[str]) # Should pass, but see note. ``` Would it make sense to add it to the `Collection` mixin so that it's available on all collections? Maybe `is_collection_of` would be a better name? The final check may not be easy to get working without an extra ``` assert isinstance(usernames, list) ``` in today's Pyright/MyPy. Or maybe it would be better to have this work on a `GenericAlias` of a collection? Like ```python assert list[str].typeguard(usernames) ``` The benefit of this being that generic class `G[C]` could use `C.typeguard(vaue)` in its code without knowing what `C` is. E.g. ``` class SupportsTypeguard(Protocol): @classmethod # this needs to be available on the generic alias, though def typeguard(cls) -> TypeGuard[Self]: ... C = TypeVar(C, bound=SupportsTypeguard) class G(Generic[C]): def f(self, ...) -> C: # generate a return value of unknown type assert C.typeguard(value) # Works if C is int, or list[str], or whatever else implements this interface. return value

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