## Summary
This PR fixes a few inaccuracies in attribute access on `TypedDict`s. It
also changes the return type of `type(person)` to `type[dict[str,
object]]` if `person: Person` is an inhabitant of a `TypedDict`
`Person`. We still use `type[Person]` as the *meta type* of Person,
however (see reasoning
[here](https://github.com/astral-sh/ruff/pull/19733#discussion_r2253297926)).
## Test Plan
Updated Markdown tests.
## Summary
This PR adds a new `Type::TypedDict` variant. Before this PR, we treated
`TypedDict`-based types as dynamic Todo-types, and I originally planned
to make this change a no-op. And we do in fact still treat that new
variant similar to a dynamic type when it comes to type properties such
as assignability and subtyping. But then I somehow tricked myself into
implementing some of the things correctly, so here we are. The two main
behavioral changes are: (1) we now also detect generic `TypedDict`s,
which removes a few false positives in the ecosystem, and (2) we now
support *attribute* access (not key-based indexing!) on these types,
i.e. we infer proper types for something like
`MyTypedDict.__required_keys__`. Nothing exciting yet, but gets the
infrastructure into place.
Note that with this PR, the type of (the type) `MyTypedDict` itself is
still represented as a `Type::ClassLiteral` or `Type::GenericAlias` (in
case `MyTypedDict` is generic). Only inhabitants of `MyTypedDict`
(instances of `dict` at runtime) are represented by `Type::TypedDict`.
We may want to revisit this decision in the future, if this turns out to
be too error-prone. Right now, we need to use `.is_typed_dict(db)` in
all the right places to distinguish between actual (generic) classes and
`TypedDict`s. But so far, it seemed unnecessary to add additional `Type`
variants for these as well.
part of https://github.com/astral-sh/ty/issues/154
## Ecosystem impact
The new diagnostics on `cloud-init` look like true positives to me.
## Test Plan
Updated and new Markdown tests
## Summary
This is a follow-up to #19321.
Narrowing constraints introduced in a class scope were not applied even
when they can be applied in lazy nested scopes. This PR fixes so that
they are now applied.
Conversely, there were cases where narrowing constraints were being
applied in places where they should not, so it is also fixed.
## Test Plan
Some TODOs in `narrow/conditionals/nested.md` are now work correctly.
## Summary
This is a follow-up to #19321.
If we try to access a class variable before it is defined, the variable
is looked up in the global scope, rather than in any enclosing scopes.
Closes https://github.com/astral-sh/ty/issues/875.
## Test Plan
New tests in `narrow/conditionals/nested.md`.
## Summary
Support `as` patterns in reachability analysis:
```py
from typing import assert_never
def f(subject: str | int):
match subject:
case int() as x:
pass
case str():
pass
case _:
assert_never(subject) # would previously emit an error
```
Note that we still don't support inferring correct types for the bound
name (`x`).
Closes https://github.com/astral-sh/ty/issues/928
## Test Plan
New Markdown tests
## Summary
This PR reduces the virality of some of the `Todo` types in
`infer_tuple_type_expression`. Rather than inferring `Todo`, we instead
infer `tuple[Todo, ...]`. This reflects the fact that whatever the
contents of the slice in a `tuple[]` type expression, we would always
infer some kind of tuple type as the result of the type expression. Any
tuple type should be assignable to `tuple[Todo, ...]`, so this shouldn't
introduce any new false positives; this can be seen in the ecosystem
report.
As a result of the change, we are now able to enforce in the signature
of `Type::infer_tuple_type_expression` that it returns an
`Option<TupleType<'db>>`, which is more strongly typed and expresses
clearly the invariant that a tuple type expression should always be
inferred as a `tuple` type. To enable this, it was necessary to refactor
several `TupleType` constructors in `tuple.rs` so that they return
`Option<TupleType>` rather than `Type`; this means that callers of these
constructor functions are now free to either propagate the
`Option<TupleType<'db>>` or convert it to a `Type<'db>`.
## Test Plan
Mdtests updated.
This is subtle, and the root cause became more apparent with #19604,
since we now have many more cases of superclasses and subclasses using
different typevars. The issue is easiest to see in the following:
```py
class C[T]:
def __init__(self, t: T) -> None: ...
class D[U](C[T]):
pass
reveal_type(C(1)) # revealed: C[int]
reveal_type(D(1)) # should be: D[int]
```
When instantiating a generic class, the `__init__` method inherits the
generic context of that class. This lets our call binding machinery
infer a specialization for that context.
Prior to this PR, the instantiation of `C` worked just fine. Its
`__init__` method would inherit the `[T]` generic context, and we would
infer `{T = int}` as the specialization based on the argument
parameters.
It didn't work for `D`. The issue is that the `__init__` method was
inheriting the generic context of the class where `__init__` was defined
(here, `C` and `[T]`). At the call site, we would then infer `{T = int}`
as the specialization — but that wouldn't help us specialize `D[U]`,
since `D` does not have `T` in its generic context!
Instead, the `__init__` method should inherit the generic context of the
class that we are performing the lookup on (here, `D` and `[U]`). That
lets us correctly infer `{U = int}` as the specialization, which we can
successfully apply to `D[U]`.
(Note that `__init__` refers to `C`'s typevars in its signature, but
that's okay; our member lookup logic already applies the `T = U`
specialization when returning a member of `C` while performing a lookup
on `D`, transforming its signature from `(Self, T) -> None` to `(Self,
U) -> None`.)
Closes https://github.com/astral-sh/ty/issues/588
This PR introduces a few related changes:
- We now keep track of each time a legacy typevar is bound in a
different generic context (e.g. class, function), and internally create
a new `TypeVarInstance` for each usage. This means the rest of the code
can now assume that salsa-equivalent `TypeVarInstance`s refer to the
same typevar, even taking into account that legacy typevars can be used
more than once.
- We also go ahead and track the binding context of PEP 695 typevars.
That's _much_ easier to track since we have the binding context right
there during type inference.
- With that in place, we can now include the name of the binding context
when rendering typevars (e.g. `T@f` instead of `T`)
## Summary
Adds an initial set of tests based on the highest-priority items in
https://github.com/astral-sh/ty/issues/154. This is certainly not yet
exhaustive (required/non-required, `total`, and other things are
missing), but will be useful to measure progress on this feature.
## Test Plan
Checked intended behavior against runtime and other type checkers.
## Summary
Adds validation to subscript assignment expressions.
```py
class Foo: ...
class Bar:
__setattr__ = None
class Baz:
def __setitem__(self, index: str, value: int) -> None:
pass
# We now emit a diagnostic on these statements
Foo()[1] = 2
Bar()[1] = 2
Baz()[1] = 2
```
Also improves error messages on invalid `__getitem__` expressions
## Test Plan
Update mdtests and add more to `subscript/instance.md`
---------
Co-authored-by: David Peter <sharkdp@users.noreply.github.com>
Co-authored-by: David Peter <mail@david-peter.de>
Summary
--
Fixes#19640. I'm not sure these are the exact fixes we really want, but
I
reproduced the issue in a 32-bit Docker container and tracked down the
causes,
so I figured I'd open a PR.
As I commented on the issue, the `goto_references` test depends on the
iteration
order of the files in an `FxHashSet` in `Indexed`. In this case, we can
just
sort the output in test code.
Similarly, the tuple case depended on the order of overloads inserted in
an
`FxHashMap`. `FxIndexMap` seemed like a convenient drop-in replacement,
but I
don't know if that will have other detrimental effects. I did have to
change the
assertion for the tuple test, but I think it should now be stable across
architectures.
Test Plan
--
Running the tests in the aforementioned Docker container
## Summary
This PR improves our generics solver such that we are able to solve the
`TypeVar` in this snippet to `int | str` (the union of the elements in
the heterogeneous tuple) by upcasting the heterogeneous tuple to its
pure-homogeneous-tuple supertype:
```py
def f[T](x: tuple[T, ...]) -> T:
return x[0]
def g(x: tuple[int, str]):
reveal_type(f(x))
```
## Test Plan
Mdtests. Some TODOs remain in the mdtest regarding solving `TypeVar`s
for mixed tuples, but I think this PR on its own is a significant step
forward for our generics solver when it comes to tuple types.
---------
Co-authored-by: Douglas Creager <dcreager@dcreager.net>
## Summary
Add support for `async for` loops and async iterables.
part of https://github.com/astral-sh/ty/issues/151
## Ecosystem impact
```diff
- boostedblob/listing.py:445:54: warning[unused-ignore-comment] Unused blanket `type: ignore` directive
```
This is correct. We now find a true positive in the `# type: ignore`'d
code.
All of the other ecosystem hits are of the type
```diff
trio (https://github.com/python-trio/trio)
+ src/trio/_core/_tests/test_guest_mode.py:532:24: error[not-iterable] Object of type `MemorySendChannel[int] | MemoryReceiveChannel[int]` may not be iterable
```
The message is correct, because only `MemoryReceiveChannel` has an
`__aiter__` method, but `MemorySendChannel` does not. What's not correct
is our inferred type here. It should be `MemoryReceiveChannel[int]`, not
the union of the two. This is due to missing unpacking support for tuple
subclasses, which @AlexWaygood is working on. I don't think this should
block merging this PR, because those wrong types are already there,
without this PR.
## Test Plan
New Markdown tests and snapshot tests for diagnostics.
## Summary
- Add support for the return types of `async` functions
- Add type inference for `await` expressions
- Add support for `async with` / async context managers
- Add support for `yield from` expressions
This PR is generally lacking proper error handling in some cases (e.g.
illegal `__await__` attributes). I'm planning to work on this in a
follow-up.
part of https://github.com/astral-sh/ty/issues/151
closes https://github.com/astral-sh/ty/issues/736
## Ecosystem
There are a lot of true positives on `prefect` which look similar to:
```diff
prefect (https://github.com/PrefectHQ/prefect)
+ src/integrations/prefect-aws/tests/workers/test_ecs_worker.py:406:12: error[unresolved-attribute] Type `str` has no attribute `status_code`
```
This is due to a wrong return type annotation
[here](e926b8c4c1/src/integrations/prefect-aws/tests/workers/test_ecs_worker.py (L355-L391)).
```diff
mitmproxy (https://github.com/mitmproxy/mitmproxy)
+ test/mitmproxy/addons/test_clientplayback.py:18:1: error[invalid-argument-type] Argument to function `asynccontextmanager` is incorrect: Expected `(...) -> AsyncIterator[Unknown]`, found `def tcp_server(handle_conn, **server_args) -> Unknown | tuple[str, int]`
```
[This](a4d794c59a/test/mitmproxy/addons/test_clientplayback.py (L18-L19))
is a true positive. That function should return
`AsyncIterator[Address]`, not `Address`.
I looked through almost all of the other new diagnostics and they all
look like known problems or true positives.
## Typing conformance
The typing conformance diff looks good.
## Test Plan
New Markdown tests
The diagram is written in the Dot language, which can
be converted to SVG (or any other image) by GraphViz.
I thought it was a good idea to write this down in
preparation for adding routines that list modules.
Code reuse is likely to be difficult and I wanted to
be sure I understood how it worked.
I mostly just did this because the long string literals were annoying
me. And these can make rustfmt give up on formatting.
I also re-flowed some long comment lines while I was here.
Douglas Creager
Alex Waygood
David Peter
Shunsuke Shibayama
Matthew Mckee
Brent Westbrook
Ibraheem Ahmed
Andrew Gallant