## Summary
If you manage to create an `typing.GenericAlias` instance without us
knowing how that was created, then we don't know what to do with this in
a type annotation. So it's better to be explicit and show an error
instead of failing silently with a `@Todo` type.
## Test Plan
* New Markdown tests
* Zero ecosystem impact
## Summary
We had tests for this already, but they used generic classes that were
bivariant in their type parameter, and so this case wasn't captured.
closes https://github.com/astral-sh/ty/issues/1702
## Test Plan
Updated Markdown tests
## Summary
These projects from `mypy_primer` were missing from both `good.txt` and
`bad.txt` for some reason. I thought about writing a script that would
verify that `good.txt` + `bad.txt` = `mypy_primer.projects`, but that's
not completely trivial since there are projects like `cpython` only
appear once in `good.txt`. Given that we can hopefully soon get rid of
both of these files (and always run on all projects), it's probably not
worth the effort. We are usually notified of all `mypy_primer` changes.
## Test Plan
CI on this PR
## Summary
The exact behavior around what's allowed vs. disallowed was partly
detected through trial and error in the runtime.
I was a little confused by [this
comment](https://github.com/python/cpython/pull/129352) that says
"`NamedTuple` subclasses cannot be inherited from" because in practice
that doesn't appear to error at runtime.
Closes [#1683](https://github.com/astral-sh/ty/issues/1683).
## Summary
This is another small refactor for
https://github.com/astral-sh/ruff/pull/21445 that splits the single
`paramspec.md` into `generics/legacy/paramspec.md` and
`generics/pep695/paramspec.md`.
## Test Plan
Make sure that all mdtests pass.
## Summary
Add support for generic PEP 613 type aliases and generic implicit type
aliases:
```py
from typing import TypeVar
T = TypeVar("T")
ListOrSet = list[T] | set[T]
def _(xs: ListOrSet[int]):
reveal_type(xs) # list[int] | set[int]
```
closes https://github.com/astral-sh/ty/issues/1643
closes https://github.com/astral-sh/ty/issues/1629
closes https://github.com/astral-sh/ty/issues/1596
closes https://github.com/astral-sh/ty/issues/573
closes https://github.com/astral-sh/ty/issues/221
## Typing conformance
```diff
-aliases_explicit.py:52:5: error[type-assertion-failure] Type `list[int]` does not match asserted type `@Todo(specialized generic alias in type expression)`
-aliases_explicit.py:53:5: error[type-assertion-failure] Type `tuple[str, ...] | list[str]` does not match asserted type `@Todo(Generic specialization of types.UnionType)`
-aliases_explicit.py:54:5: error[type-assertion-failure] Type `tuple[int, int, int, str]` does not match asserted type `@Todo(specialized generic alias in type expression)`
-aliases_explicit.py:56:5: error[type-assertion-failure] Type `(int, str, /) -> str` does not match asserted type `@Todo(Generic specialization of typing.Callable)`
-aliases_explicit.py:59:5: error[type-assertion-failure] Type `int | str | None | list[list[int]]` does not match asserted type `int | str | None | list[@Todo(specialized generic alias in type expression)]`
```
New true negatives ✔️
```diff
+aliases_explicit.py:41:36: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
-aliases_explicit.py:57:5: error[type-assertion-failure] Type `(int, str, str, /) -> None` does not match asserted type `@Todo(Generic specialization of typing.Callable)`
+aliases_explicit.py:57:5: error[type-assertion-failure] Type `(int, str, str, /) -> None` does not match asserted type `(...) -> Unknown`
```
These require `ParamSpec`
```diff
+aliases_explicit.py:67:24: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+aliases_explicit.py:68:24: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+aliases_explicit.py:69:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_explicit.py:70:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_explicit.py:71:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_explicit.py:102:20: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
```
New true positives ✔️
```diff
-aliases_implicit.py:63:5: error[type-assertion-failure] Type `list[int]` does not match asserted type `@Todo(specialized generic alias in type expression)`
-aliases_implicit.py:64:5: error[type-assertion-failure] Type `tuple[str, ...] | list[str]` does not match asserted type `@Todo(Generic specialization of types.UnionType)`
-aliases_implicit.py:65:5: error[type-assertion-failure] Type `tuple[int, int, int, str]` does not match asserted type `@Todo(specialized generic alias in type expression)`
-aliases_implicit.py:67:5: error[type-assertion-failure] Type `(int, str, /) -> str` does not match asserted type `@Todo(Generic specialization of typing.Callable)`
-aliases_implicit.py:70:5: error[type-assertion-failure] Type `int | str | None | list[list[int]]` does not match asserted type `int | str | None | list[@Todo(specialized generic alias in type expression)]`
-aliases_implicit.py:71:5: error[type-assertion-failure] Type `list[bool]` does not match asserted type `@Todo(specialized generic alias in type expression)`
```
New true negatives ✔️
```diff
+aliases_implicit.py:54:36: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
-aliases_implicit.py:68:5: error[type-assertion-failure] Type `(int, str, str, /) -> None` does not match asserted type `@Todo(Generic specialization of typing.Callable)`
+aliases_implicit.py:68:5: error[type-assertion-failure] Type `(int, str, str, /) -> None` does not match asserted type `(...) -> Unknown`
```
These require `ParamSpec`
```diff
+aliases_implicit.py:76:24: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+aliases_implicit.py:77:24: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+aliases_implicit.py:78:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_implicit.py:79:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_implicit.py:80:29: error[invalid-type-arguments] Too many type arguments: expected 1, got 2
+aliases_implicit.py:81:25: error[invalid-type-arguments] Type `str` is not assignable to upper bound `int | float` of type variable `TFloat@GoodTypeAlias12`
+aliases_implicit.py:135:20: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
```
New true positives ✔️
```diff
+callables_annotation.py:172:19: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+callables_annotation.py:175:19: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+callables_annotation.py:188:25: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
+callables_annotation.py:189:25: error[invalid-type-arguments] Too many type arguments: expected 0, got 1
```
These require `ParamSpec` and `Concatenate`.
```diff
-generics_defaults_specialization.py:26:5: error[type-assertion-failure] Type `SomethingWithNoDefaults[int, str]` does not match asserted type `SomethingWithNoDefaults[int, typing.TypeVar]`
+generics_defaults_specialization.py:26:5: error[type-assertion-failure] Type `SomethingWithNoDefaults[int, str]` does not match asserted type `SomethingWithNoDefaults[int, DefaultStrT]`
```
Favorable diagnostic change ✔️
```diff
-generics_defaults_specialization.py:27:5: error[type-assertion-failure] Type `SomethingWithNoDefaults[int, bool]` does not match asserted type `@Todo(specialized generic alias in type expression)`
```
New true negative ✔️
```diff
-generics_defaults_specialization.py:30:1: error[non-subscriptable] Cannot subscript object of type `<class 'SomethingWithNoDefaults[int, typing.TypeVar]'>` with no `__class_getitem__` method
+generics_defaults_specialization.py:30:15: error[invalid-type-arguments] Too many type arguments: expected between 0 and 1, got 2
```
Correct new diagnostic ✔️
```diff
-generics_variance.py:175:25: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:175:35: error[non-subscriptable] Cannot subscript object of type `<class 'Co[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:179:29: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:179:39: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:183:21: error[non-subscriptable] Cannot subscript object of type `<class 'Co[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:183:27: error[non-subscriptable] Cannot subscript object of type `<class 'Co[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:187:25: error[non-subscriptable] Cannot subscript object of type `<class 'Co[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:187:31: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:191:33: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:191:43: error[non-subscriptable] Cannot subscript object of type `<class 'Co[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:191:49: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:196:5: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:196:15: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
-generics_variance.py:196:25: error[non-subscriptable] Cannot subscript object of type `<class 'Contra[typing.TypeVar]'>` with no `__class_getitem__` method
```
One of these should apparently be an error, but not of this kind, so
this is good ✔️
```diff
-specialtypes_type.py:152:16: error[invalid-type-form] `typing.TypeVar` is not a generic class
-specialtypes_type.py:156:16: error[invalid-type-form] `typing.TypeVar` is not a generic class
```
Good, those were false positives. ✔️
I skipped the analysis for everything involving `TypeVarTuple`.
## Ecosystem impact
**[Full report with detailed
diff](https://david-generic-implicit-alias.ecosystem-663.pages.dev/diff)**
Previous iterations of this PR showed all kinds of problems. In it's
current state, I do not see any large systematic problems, but it is
hard to tell with 5k diagnostic changes.
## Performance
* There is a huge 4x regression in `colour-science/colour`, related to
[this large
file](https://github.com/colour-science/colour/blob/develop/colour/io/luts/tests/test_lut.py)
with [many assignments of hard-coded arrays (lists of lists) to
`np.NDArray`
types](83e754c8b6/colour/io/luts/tests/test_lut.py (L701-L781))
that we now understand. We now take ~2 seconds to check this file, so
definitely not great, but maybe acceptable for now.
## Test Plan
Updated and new Markdown tests
## Summary
This is a bugfix for subtyping of `type[Any]` / `type[T]` and protocols.
## Test Plan
Regression test that will only be really meaningful once
https://github.com/astral-sh/ruff/pull/21553 lands.
## Summary
Previously if an explicit specialization failed (e.g. wrong number of
type arguments or violates an upper bound) we just inferred `Unknown`
for the entire type. This actually caused us to panic on an a case of a
recursive upper bound with invalid specialization; the upper bound would
oscillate indefinitely in fixpoint iteration between `Unknown` and the
given specialization. This could be fixed with a cycle recovery
function, but in this case there's a simpler fix: if we infer
`C[Unknown]` instead of `Unknown` for an invalid attempt to specialize
`C`, that allows fixpoint iteration to quickly converge, as well as
giving a more precise type inference.
Other type checkers actually just go with the attempted specialization
even if it's invalid. So if `C` has a type parameter with upper bound
`int`, and you say `C[str]`, they'll emit a diagnostic but just go with
`C[str]`. Even weirder, if `C` has a single type parameter and you say
`C[str, bytes]`, they'll just go with `C[str]` as the type. I'm not
convinced by this approach; it seems odd to have specializations
floating around that explicitly violate the declared upper bound, or in
the latter case aren't even the specialization the annotation requested.
I prefer `C[Unknown]` for this case.
Fixing this revealed an issue with `collections.namedtuple`, which
returns `type[tuple[Any, ...]]`. Due to
https://github.com/astral-sh/ty/issues/1649 we consider that to be an
invalid specialization. So previously we returned `Unknown`; after this
PR it would be `type[tuple[Unknown]]`, leading to more false positives
from our lack of functional namedtuple support. To avoid that I added an
explicit Todo type for functional namedtuples for now.
## Test Plan
Added and updated mdtests.
The conformance suite changes have to do with `ParamSpec`, so no
meaningful signal there.
The ecosystem changes appear to be the expected effects of having more
precise type information (including occurrences of known issues such as
https://github.com/astral-sh/ty/issues/1495 ). Most effects are just
changes to types in diagnostics.
## Summary
This PR updates the explicit specialization logic to avoid using the
call machinery.
Previously, the logic would use the call machinery by converting the
list of type variables into a `Binding` with a single `Signature` where
all the type variables are positional-only parameters with bounds and
constraints as the annotated type and the default type as the default
parameter value. This has the advantage that it doesn't need to
implement any specific logic but the disadvantages are subpar diagnostic
messages as it would use the ones specific to a function call. But, an
important disadvantage is that the kind of type variable is lost in this
translation which becomes important in #21445 where a `ParamSpec` can
specialize into a list of types which is provided using list literal.
For example,
```py
class Foo[T, **P]: ...
Foo[int, [int, str]]
```
This PR converts the logic to use a simple loop using `zip_longest` as
all type variables and their corresponding type argument maps on a 1-1
basis. They cannot be specified using keyword argument either e.g.,
`dict[_VT=str, _KT=int]` is invalid.
This PR also makes an initial attempt to improve the diagnostic message
to specifically target the specialization part by using words like "type
argument" instead of just "argument" and including information like the
type variable, bounds, and constraints. Further improvements can be made
by highlighting the type variable definition or the bounds / constraints
as a sub-diagnostic but I'm going to leave that as a follow-up.
## Test Plan
Update messages in existing test cases.
## Summary
Derived from #17371Fixesastral-sh/ty#256
Fixes https://github.com/astral-sh/ty/issues/1415
Fixes https://github.com/astral-sh/ty/issues/1433
Fixes https://github.com/astral-sh/ty/issues/1524
Properly handles any kind of recursive inference and prevents panics.
---
Let me explain techniques for converging fixed-point iterations during
recursive type inference.
There are two types of type inference that naively don't converge
(causing salsa to panic): divergent type inference and oscillating type
inference.
### Divergent type inference
Divergent type inference occurs when eagerly expanding a recursive type.
A typical example is this:
```python
class C:
def f(self, other: "C"):
self.x = (other.x, 1)
reveal_type(C().x) # revealed: Unknown | tuple[Unknown | tuple[Unknown | tuple[..., Literal[1]], Literal[1]], Literal[1]]
```
To solve this problem, we have already introduced `Divergent` types
(https://github.com/astral-sh/ruff/pull/20312). `Divergent` types are
treated as a kind of dynamic type [^1].
```python
Unknown | tuple[Unknown | tuple[Unknown | tuple[..., Literal[1]], Literal[1]], Literal[1]]
=> Unknown | tuple[Divergent, Literal[1]]
```
When a query function that returns a type enters a cycle, it sets
`Divergent` as the cycle initial value (instead of `Never`). Then, in
the cycle recovery function, it reduces the nesting of types containing
`Divergent` to converge.
```python
0th: Divergent
1st: Unknown | tuple[Divergent, Literal[1]]
2nd: Unknown | tuple[Unknown | tuple[Divergent, Literal[1]], Literal[1]]
=> Unknown | tuple[Divergent, Literal[1]]
```
Each cycle recovery function for each query should operate only on the
`Divergent` type originating from that query.
For this reason, while `Divergent` appears the same as `Any` to the
user, it internally carries some information: the location where the
cycle occurred. Previously, we roughly identified this by having the
scope where the cycle occurred, but with the update to salsa, functions
that create cycle initial values can now receive a `salsa::Id`
(https://github.com/salsa-rs/salsa/pull/1012). This is an opaque ID that
uniquely identifies the cycle head (the query that is the starting point
for the fixed-point iteration). `Divergent` now has this `salsa::Id`.
### Oscillating type inference
Now, another thing to consider is oscillating type inference.
Oscillating type inference arises from the fact that monotonicity is
broken. Monotonicity here means that for a query function, if it enters
a cycle, the calculation must start from a "bottom value" and progress
towards the final result with each cycle. Monotonicity breaks down in
type systems that have features like overloading and overriding.
```python
class Base:
def flip(self) -> "Sub":
return Sub()
class Sub(Base):
def flip(self) -> "Base":
return Base()
class C:
def __init__(self, x: Sub):
self.x = x
def replace_with(self, other: "C"):
self.x = other.x.flip()
reveal_type(C(Sub()).x)
```
Naive fixed-point iteration results in `Divergent -> Sub -> Base -> Sub
-> ...`, which oscillates forever without diverging or converging. To
address this, the salsa API has been modified so that the cycle recovery
function receives the value of the previous cycle
(https://github.com/salsa-rs/salsa/pull/1012).
The cycle recovery function returns the union type of the current cycle
and the previous cycle. In the above example, the result type for each
cycle is `Divergent -> Sub -> Base (= Sub | Base) -> Base`, which
converges.
The final result of oscillating type inference does not contain
`Divergent` because `Divergent` that appears in a union type can be
removed, as is clear from the expansion. This simplification is
performed at the same time as nesting reduction.
```
T | Divergent = T | (T | (T | ...)) = T
```
[^1]: In theory, it may be possible to strictly treat types containing
`Divergent` types as recursive types, but we probably shouldn't go that
deep yet. (AFAIK, there are no PEPs that specify how to handle
implicitly recursive types that aren't named by type aliases)
## Performance analysis
A happy side effect of this PR is that we've observed widespread
performance improvements!
This is likely due to the removal of the `ITERATIONS_BEFORE_FALLBACK`
and max-specialization depth trick
(https://github.com/astral-sh/ty/issues/1433,
https://github.com/astral-sh/ty/issues/1415), which means we reach a
fixed point much sooner.
## Ecosystem analysis
The changes look good overall.
You may notice changes in the converged values for recursive types,
this is because the way recursive types are normalized has been changed.
Previously, types containing `Divergent` types were normalized by
replacing them with the `Divergent` type itself, but in this PR, types
with a nesting level of 2 or more that contain `Divergent` types are
normalized by replacing them with a type with a nesting level of 1. This
means that information about the non-divergent parts of recursive types
is no longer lost.
```python
# previous
tuple[tuple[Divergent, int], int] => Divergent
# now
tuple[tuple[Divergent, int], int] => tuple[Divergent, int]
```
The false positive error introduced in this PR occurs in class
definitions with self-referential base classes, such as the one below.
```python
from typing_extensions import Generic, TypeVar
T = TypeVar("T")
U = TypeVar("U")
class Base2(Generic[T, U]): ...
# TODO: no error
# error: [unsupported-base] "Unsupported class base with type `<class 'Base2[Sub2, U@Sub2]'> | <class 'Base2[Sub2[Unknown], U@Sub2]'>`"
class Sub2(Base2["Sub2", U]): ...
```
This is due to the lack of support for unions of MROs, or because cyclic
legacy generic types are not inferred as generic types early in the
query cycle.
## Test Plan
All samples listed in astral-sh/ty#256 are tested and passed without any
panic!
## Acknowledgments
Thanks to @MichaReiser for working on bug fixes and improvements to
salsa for this PR. @carljm also contributed early on to the discussion
of the query convergence mechanism proposed in this PR.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
We now use the type context for a lot of things, so re-inferring without
type context actually makes diagnostics more confusing (in most cases).
## Summary
This PR adds a code action to remove unused ignore comments.
This PR also includes some infrastructure boilerplate to set up code
actions in the editor:
* Extend `snapshot-diagnostics` to render fixes
* Render fixes when using `--output-format=full`
* Hook up edits and the code action request in the LSP
* Add the `Unnecessary` tag to `unused-ignore-comment` diagnostics
* Group multiple unused codes into a single diagnostic
The same fix can be used on the CLI once we add `ty fix`
Note: `unused-ignore-comment` is currently disabled by default.
https://github.com/user-attachments/assets/f9e21087-3513-4156-85d7-a90b1a7a3489
## Summary
Building on https://github.com/astral-sh/ruff/pull/21436.
There's nothing conceptually more complicated about this, it just
requires its own set of tests and its own subdiagnostic hint.
I also uncovered another inconsistency between mypy/pyright/pyrefly,
which is fun. In this case, I suggest we go with pyright's behaviour.
## Test Plan
mdtests/snapshots
## Summary
For something like this:
```py
from typing import Callable
def my_lossy_decorator(fn: Callable[..., int]) -> Callable[..., int]:
return fn
class MyClass:
@my_lossy_decorator
def method(self) -> int:
return 42
```
we will currently infer the type of `MyClass.method` as a function-like
`Callable`, but we will infer the type of `MyClass().method` as a
`Callable` that is _not_ function-like. That's because a `CallableType`
currently "forgets" whether it was function-like or not during the
`bound_self` transformation:
a57e291311/crates/ty_python_semantic/src/types.rs (L10985-L10987)
This seems incorrect, and it's quite different to what we do when
binding the `self` parameter of `FunctionLiteral` types: `BoundMethod`
types are all seen as subtypes of function-like `Callable` supertypes --
here's `BoundMethodType::into_callable_type`:
a57e291311/crates/ty_python_semantic/src/types.rs (L10844-L10860)
The bug here is also causing lots of false positives in the ecosystem
report on https://github.com/astral-sh/ruff/pull/21611: a decorated
method on a subclass is currently not seen as validly overriding an
undecorated method with the same signature on a superclass, because the
undecorated superclass method is seen as function-like after binding
`self` whereas the decorated subclass method is not.
Fixing the bug required adding a new API in `protocol_class.rs`, because
it turns out that for our purposes in protocol subtyping/assignability,
we really do want a callable type to forget its function-like-ness when
binding `self`.
I initially tried out this change without changing anything in
`protocol_class.rs`. However, it resulted in many ecosystem false
positives and new false positives on the typing conformance test suite.
This is because it would mean that no protocol with a `__call__` method
would ever be seen as a subtype of a `Callable` type, since the
`__call__` method on the protocol would be seen as being function-like
whereas the `Callable` type would not be seen as function-like.
## Test Plan
Added an mdtest that fails on `main`
Before, we would collapse any constraint of the form `Never ≤ T ≤
object` down to the "always true" constraint set. This is correct in
terms of BDD semantics, but loses information, since "not constraining a
typevar at all" is different than "constraining a typevar to take on any
type". Once we get to specialization inference, we should fall back on
the typevar's default for the former, but not for the latter.
This is much easier to support now that we have a sequent map, since we
need to treat `¬(Never ≤ T ≤ object)` as being impossible, and prune it
when we walk through BDD paths, just like we do for other impossible
combinations.
This patch updates our protocol assignability checks to substitute for
any occurrences of `typing.Self` in method signatures, replacing it with
the class being checked for assignability against the protocol.
This requires a new helper method on signatures, `apply_self`, which
substitutes occurrences of `typing.Self` _without_ binding the `self`
parameter.
We also update the `try_upcast_to_callable` method. Before, it would
return a `Type`, since certain types upcast to a _union_ of callables,
not to a single callable. However, even in that case, we know that every
element of the union is a callable. We now return a vector of
`CallableType`. (Actually a smallvec to handle the most common case of a
single callable; and wrapped in a new type so that we can provide helper
methods.) If there is more than one element in the result, it represents
a union of callables. This lets callers get at the `CallableType`
instances in a more type-safe way. (This makes it easier for our
protocol checking code to call the new `apply_self` helper.) We also
provide an `into_type` method so that callers that really do want a
`Type` can get the original result easily.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Fixes https://github.com/astral-sh/ty/issues/1620. #20909 added hints if
you do something like this and your Python version is set to 3.10 or
lower:
```py
import typing
typing.LiteralString
```
And we also have hints if you try to do something like this and your
Python version is set too low:
```py
from stdlib_module import new_submodule
```
But we don't currently have any subdiagnostic hint if you do something
like _this_ and your Python version is set too low:
```py
from typing import LiteralString
```
This PR adds that hint!
## Test Plan
snapshots
---------
Co-authored-by: Aria Desires <aria.desires@gmail.com>
## Summary
This PR adds a failing mdtest for the panic in
https://github.com/astral-sh/ty/issues/1587. The added snippet currently
panics with this query stacktrace:
```
error[panic]: Panicked at /Users/alexw/.cargo/git/checkouts/salsa-e6f3bb7c2a062968/17bc55d/src/function/execute.rs:321:21 when checking `/Users/alexw/dev/ruff/foo.py`: `ClassLiteral < 'db >::explicit_bases_(Id(4c09)): execute: too many cycle iterations`
info: This indicates a bug in ty.
info: If you could open an issue at https://github.com/astral-sh/ty/issues/new?title=%5Bpanic%5D, we'd be very appreciative!
info: Platform: macos aarch64
info: Version: ruff/0.14.5+105 (d24c891a4 2025-11-22)
info: Args: ["target/debug/ty", "check", "foo.py", "--python-version=3.14"]
info: run with `RUST_BACKTRACE=1` environment variable to show the full backtrace information
info: query stacktrace:
0: cached_protocol_interface(Id(6805))
at crates/ty_python_semantic/src/types/protocol_class.rs:795
1: is_equivalent_to_object_inner(Id(8003))
at crates/ty_python_semantic/src/types/instance.rs:667
2: infer_deferred_types(Id(1406))
at crates/ty_python_semantic/src/types/infer.rs:140
cycle heads: infer_definition_types(Id(140b)) -> iteration = 200, TypeVarInstance < 'db >::lazy_bound_(Id(5802)) -> iteration = 200
3: TypeVarInstance < 'db >::lazy_bound_(Id(5803))
at crates/ty_python_semantic/src/types.rs:8827
4: infer_definition_types(Id(140c))
at crates/ty_python_semantic/src/types/infer.rs:94
5: infer_deferred_types(Id(1405))
at crates/ty_python_semantic/src/types/infer.rs:140
6: TypeVarInstance < 'db >::lazy_bound_(Id(5802))
at crates/ty_python_semantic/src/types.rs:8827
7: infer_definition_types(Id(140b))
at crates/ty_python_semantic/src/types/infer.rs:94
8: infer_scope_types(Id(1000))
at crates/ty_python_semantic/src/types/infer.rs:70
9: check_file_impl(Id(c00))
at crates/ty_project/src/lib.rs:535
```
It's not totally clear to me how to fix this or to what extent it might
be a bug in our `Protocol` internals rather than a bug in our `TypeVar`
internals. (It's sort of interesting that we're trying to evaluate the
upper bound of any `TypeVar`s here!) @carljm suggested that it would be
a good idea to add a failing mdtest in the meantime to document the
panic, which I agree with.
## Test Plan
I verified that we panic on this snippet, and that the test fails if I
remove the `expect-panic` assertion or if I change the asserted error
message.
I experimented with ways of minimizing the snippet further, but I think
any further minimization takes the snippet further away from something a
user would actually be likely to write -- so I think is probably
counterproductive. The failing test added in this PR isn't unreasonable
code at the end of the day; I've seen Python like it in the wild.
These were added to try to make it clearer that assignability checks
will eventually return more detailed answers than true or false.
However, the constraint set display rendering is still more brittle than
I'd like it to be, and it's more trouble than it's worth to keep them
updated with semantically identically but textually different edits. The
`static_assert`s are sufficient to check correctness, and we can always
add `reveal_type` when needed for further debugging.
Refs https://github.com/astral-sh/ty/issues/544
## Summary
Takes a more incremental approach to PEP 613 type alias support (vs
https://github.com/astral-sh/ruff/pull/20107). Instead of eagerly
inferring the RHS of a PEP 613 type alias as a type expression, infer it
as a value expression, just like we do for implicit type aliases, taking
advantage of the same support for e.g. unions and other type special
forms.
The main reason I'm following this path instead of the one in
https://github.com/astral-sh/ruff/pull/20107 is that we've realized that
people do sometimes use PEP 613 type aliases as values, not just as
types (because they are just a normal runtime assignment, unlike PEP 695
type aliases which create an opaque `TypeAliasType`).
This PR doesn't yet provide full support for recursive type aliases
(they don't panic, but they just fall back to `Unknown` at the recursion
point). This is future work.
## Test Plan
Added mdtests.
Many new ecosystem diagnostics, mostly because we
understand new types in lots of places.
Conformance suite changes are correct.
Performance regression is due to understanding lots of new
types; nothing we do in this PR is inherently expensive.
## Summary
Eagerly evaluate the elements of a PEP 604 union in value position (e.g.
`IntOrStr = int | str`) as type expressions and store the result (the
corresponding `Type::Union` if all elements are valid type expressions,
or the first encountered `InvalidTypeExpressionError`) on the
`UnionTypeInstance`, such that the `Type::Union(…)` does not need to be
recomputed every time the implicit type alias is used in a type
annotation.
This might lead to performance improvements for large unions, but is
also necessary for correctness, because the elements of the union might
refer to type variables that need to be looked up in the scope of the
type alias, not at the usage site.
## Test Plan
New Markdown tests
#21414 added the ability to create a specialization from a constraint
set. It handled mutually constrained typevars just fine, e.g. given `T ≤
int ∧ U = T` we can infer `T = int, U = int`.
But it didn't handle _nested_ constraints correctly, e.g. `T ≤ int ∧ U =
list[T]`. Now we do! This requires doing a fixed-point "apply the
specialization to itself" step to propagate the assignments of any
nested typevars, and then a cycle detection check to make sure we don't
have an infinite expansion in the specialization.
This gets at an interesting nuance in our constraint set structure that
@sharkdp has asked about before. Constraint sets are BDDs, and each
internal node represents an _individual constraint_, of the form `lower
≤ T ≤ upper`. `lower` and `upper` are allowed to be other typevars, but
only if they appear "later" in the arbitary ordering that we establish
over typevars. The main purpose of this is to avoid infinite expansion
for mutually constrained typevars.
However, that restriction doesn't help us here, because only applies
when `lower` and `upper` _are_ typevars, not when they _contain_
typevars. That distinction is important, since it means the restriction
does not affect our expressiveness: we can always rewrite `Never ≤ T ≤
U` (a constraint on `T`) into `T ≤ U ≤ object` (a constraint on `U`).
The same is not true of `Never ≤ T ≤ list[U]` — there is no "inverse" of
`list` that we could apply to both sides to transform this into a
constraint on a bare `U`.
Alex Waygood
David Peter
Carl Meyer
Shunsuke Shibayama
Charlie Marsh
Micha Reiser
Dhruv Manilawala
Ibraheem Ahmed
Jack O'Connor
Douglas Creager
Aria Desires