## Summary
Infer the first argument `type` inside `Annotated[type, …]` as a type
expression. This allows us to support stringified annotations inside
`Annotated`.
## Ecosystem
* The removed diagnostic on `prefect` shows that we now understand the
`State.data` type annotation in
`src/prefect/client/schemas/objects.py:230`, which uses a stringified
annotation in `Annoated`. The other diagnostics are downstream changes
that result from this, it seems to be a commonly used data type.
* `artigraph` does something like `Annotated[cast(Any,
field_info.annotation), *field_info.metadata]` which I'm not sure we
need to allow? It's unfortunate since this is probably supported at
runtime, but it seems reasonable that they need to add a `# type:
ignore` for that.
* `pydantic` uses something like `Annotated[(self.annotation,
*self.metadata)]` but adds a `# type: ignore`
## Test Plan
New Markdown test
## Summary
Typeshed has a (fake) `__getattr__` method on `types.ModuleType` with a
return type of `Any`. We ignore this method when accessing attributes on
module *literals*, but with this PR, we respect this method when dealing
with `ModuleType` itself. That is, we allow arbitrary attribute accesses
on instances of `types.ModuleType`. This is useful because dynamic
import mechanisms such as `importlib.import_module` use `ModuleType` as
a return type.
closes https://github.com/astral-sh/ty/issues/1346
## Ecosystem
Massive reduction in diagnostics. The few new diagnostics are true
positives.
## Test Plan
Added regression test.
## Summary
Add synthetic members to completions on dataclasses and dataclass
instances.
Also, while we're at it, add support for `__weakref__` and
`__match_args__`.
closes https://github.com/astral-sh/ty/issues/1542
## Test Plan
New Markdown tests
## Summary
Support various legacy `typing` special forms (`List`, `Dict`, …) in
implicit type aliases.
## Ecosystem impact
A lot of true positives (e.g. on `alerta`)!
## Test Plan
New Markdown tests
## Summary
Support `type[…]` in implicit type aliases, for example:
```py
SubclassOfInt = type[int]
reveal_type(SubclassOfInt) # GenericAlias
def _(subclass_of_int: SubclassOfInt):
reveal_type(subclass_of_int) # type[int]
```
part of https://github.com/astral-sh/ty/issues/221
## Typing conformance
```diff
-specialtypes_type.py:138:5: error[type-assertion-failure] Argument does not have asserted type `type[Any]`
-specialtypes_type.py:140:5: error[type-assertion-failure] Argument does not have asserted type `type[Any]`
```
Two new tests passing ✔️
```diff
-specialtypes_type.py:146:1: error[unresolved-attribute] Object of type `GenericAlias` has no attribute `unknown`
```
An `TA4.unknown` attribute on a PEP 613 alias (`TA4: TypeAlias =
type[Any]`) is being accessed, and the conformance suite expects this to
be an error. Since we currently use the inferred type for these type
aliases (and possibly in the future as well), we treat this as a direct
access of the attribute on `type[Any]`, which falls back to an access on
`Any` itself, which succeeds. 🔴
```
+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
```
New errors because we don't handle `T = TypeVar("T"); MyType = type[T];
MyType[T]` yet. Support for this is being tracked in
https://github.com/astral-sh/ty/issues/221🔴
## Ecosystem impact
Looks mostly good, a few known problems.
## Test Plan
New Markdown tests
## Summary
Further improve subscript assignment diagnostics, especially for
`dict`s:
```py
config: dict[str, int] = {}
config["retries"] = "three"
```
<img width="1276" height="274" alt="image"
src="https://github.com/user-attachments/assets/9762c733-8d1c-4a57-8c8a-99825071dc7d"
/>
I have many more ideas, but this looks like a reasonable first step.
Thank you @AlexWaygood for some of the suggestions here.
## Test Plan
Update tests
## Summary
We synthesize a (potentially large) set of `__setitem__` overloads for
every item in a `TypedDict`. Previously, validation of subscript
assignments on `TypedDict`s relied on actually calling `__setitem__`
with the provided key and value types, which implied that we needed to
do the full overload call evaluation for this large set of overloads.
This PR improves the performance of subscript assignment checks on
`TypedDict`s by validating the assignment directly instead of calling
`__setitem__`.
This PR also adds better handling for assignments to subscripts on union
and intersection types (but does not attempt to make it perfect). It
achieves this by distributing the check over unions and intersections,
instead of calling `__setitem__` on the union/intersection directly. We
already do something similar when validating *attribute* assignments.
## Ecosystem impact
* A lot of diagnostics change their rule type, and/or split into
multiple diagnostics. The new version is more verbose, but easier to
understand, in my opinion
* Almost all of the invalid-key diagnostics come from pydantic, and they
should all go away (including many more) when we implement
https://github.com/astral-sh/ty/issues/1479
* Everything else looks correct to me. There may be some new diagnostics
due to the fact that we now check intersections.
## Test Plan
New Markdown tests.
## Summary
cf. https://github.com/astral-sh/ruff/pull/20962
In the following code, `foo` in the comprehension was not reported as
unresolved:
```python
# error: [unresolved-reference] "Name `foo` used when not defined"
foo
foo = [
# no error!
# revealed: Divergent
reveal_type(x) for _ in () for x in [foo]
]
baz = [
# error: [unresolved-reference] "Name `baz` used when not defined"
# revealed: Unknown
reveal_type(x) for _ in () for x in [baz]
]
```
In fact, this is a more serious bug than it looks: for `foo`,
[`explicit_global_symbol` is
called](6cc3393ccd/crates/ty_python_semantic/src/types/infer/builder.rs (L8052)),
causing a symbol that should actually be `Undefined` to be reported as
being of type `Divergent`.
This PR fixes this bug. As a result, the code in
`mdtest/regression/pr_20962_comprehension_panics.md` no longer panics.
## Test Plan
`corpus\cyclic_symbol_in_comprehension.py` is added.
New tests are added in `mdtest/comprehensions/basic.md`.
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Add (snapshot) tests for subscript assignment diagnostics. This is
mainly intended to establish a baseline before I hope to improve some of
these messages.
## Summary
Add support for `typing.Union` in implicit type aliases / in value
position.
## Typing conformance tests
Two new tests are passing
## Ecosystem impact
* The 2k new `invalid-key` diagnostics on pydantic are caused by
https://github.com/astral-sh/ty/issues/1479#issuecomment-3513854645.
* Everything else I've checked is either a known limitation (often
related to type narrowing, because union types are often narrowed down
to a subset of options), or a true positive.
## Test Plan
New Markdown tests
## Summary
Fix https://github.com/astral-sh/ty/issues/664
This PR adds support for storing attributes in comprehension scopes (any
eager scope.)
For example in the following code we infer type of `z` correctly:
```py
class C:
def __init__(self):
[None for self.z in range(1)]
reveal_type(C().z) # previously [unresolved-attribute] but now shows Unknown | int
```
The fix works by adjusting the following logics:
To identify if an attriute is an assignment to self or cls we need to
check the scope is a method. To allow comprehension scopes here we skip
any eager scope in the check.
Also at this stage the code checks if self or the first method argument
is shadowed by another binding that eager scope to prevent this:
```py
class D:
g: int
class C:
def __init__(self):
[[None for self.g in range(1)] for self in [D()]]
reveal_type(C().g) # [unresolved-attribute]
```
When determining scopes that attributes might be defined after
collecting all the methods of the class the code also returns any
decendant scope that is eager and only has eager parents until the
method scope.
When checking reachability of a attribute definition if the attribute is
defined in an eager scope we use the reachability of the first non eager
scope which must be a method. This allows attributes to be marked as
reachable and be seen.
There are also which I didn't add support for:
```py
class C:
def __init__(self):
def f():
[None for self.z in range(1)]
f()
reveal_type(C().z) # [unresolved-attribute]
```
In the above example we will not even return the comprehension scope as
an attribute scope because there is a non eager scope (`f` function)
between the comprehension and the `__init__` method
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Fixes https://github.com/astral-sh/ty/issues/1409
This PR allows `Final` instance attributes to be initialized in
`__init__` methods, as mandated by the Python typing specification (PEP
591). Previously, ty incorrectly prevented this initialization, causing
false positive errors.
The fix checks if we're inside an `__init__` method before rejecting
Final attribute assignments, allowing assignments during
instance initialization while still preventing reassignment elsewhere.
## Test Plan
- Added new test coverage in `final.md` for the reported issue with
`Self` annotations
- Updated existing tests that were incorrectly expecting errors
- All 278 mdtest tests pass
- Manually tested with real-world code examples
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Fixes https://github.com/astral-sh/ty/issues/1487
This one is a true extension of non-standard semantics, and is therefore
a certified Hot Take we might conclude is simply a Bad Take (let's see
what ecosystem tests say...).
By resolving `.` and the LHS of the from import during semantic
indexing, we can check if the LHS is a submodule of `.`, and handle
`from whatever.thispackage.x.y import z` exactly like we do `from .x.y
import z`.
Fixes https://github.com/astral-sh/ty/issues/1484
This manifested as an error when inferring the type of a PEP-695 generic
class via its constructor parameters:
```py
class D[T, U]:
@overload
def __init__(self: "D[str, U]", u: U) -> None: ...
@overload
def __init__(self, t: T, u: U) -> None: ...
def __init__(self, *args) -> None: ...
# revealed: D[Unknown, str]
# SHOULD BE: D[str, str]
reveal_type(D("string"))
```
This manifested because `D` is inferred to be bivariant in both `T` and
`U`. We weren't seeing this in the equivalent example for legacy
typevars, since those default to invariant. (This issue also showed up
for _covariant_ typevars, so this issue was not limited to bivariance.)
The underlying cause was because of a heuristic that we have in our
current constraint solver, which attempts to handle situations like
this:
```py
def f[T](t: T | None): ...
f(None)
```
Here, the `None` argument matches the non-typevar union element, so this
argument should not add any constraints on what `T` can specialize to.
Our previous heuristic would check for this by seeing if the argument
type is a subtype of the parameter annotation as a whole — even if it
isn't a union! That would cause us to erroneously ignore the `self`
parameter in our constructor call, since bivariant classes are
equivalent to each other, regardless of their specializations.
The quick fix is to move this heuristic "down a level", so that we only
apply it when the parameter annotation is a union. This heuristic should
go away completely 🤞 with the new constraint solver.
This loses any ability to have "per-function" implicit submodule
imports, to avoid the "ok but now we need per-scope imports" and "ok but
this should actually introduce a global that only exists during this
function" problems. A simple and clean implementation with no weird
corners.
Fixes https://github.com/astral-sh/ty/issues/1482
This rips out the previous implementation in favour of a new
implementation with 3 rules:
- **froms are locals**: a `from..import` can only define locals, it does
not have global
side-effects. Specifically any submodule attribute `a` that's implicitly
introduced by either
`from .a import b` or `from . import a as b` (in an `__init__.py(i)`) is
a local and not a
global. If you do such an import at the top of a file you won't notice
this. However if you do
such an import in a function, that means it will only be function-scoped
(so you'll need to do
it in every function that wants to access it, making your code less
sensitive to execution
order).
- **first from first serve**: only the *first* `from..import` in an
`__init__.py(i)` that imports a
particular direct submodule of the current package introduces that
submodule as a local.
Subsequent imports of the submodule will not introduce that local. This
reflects the fact that
in actual python only the first import of a submodule (in the entire
execution of the program)
introduces it as an attribute of the package. By "first" we mean "the
first time in this scope
(or any parent scope)". This pairs well with the fact that we are
specifically introducing a
local (as long as you don't accidentally shadow or overwrite the local).
- **dot re-exports**: `from . import a` in an `__init__.pyi` is
considered a re-export of `a`
(equivalent to `from . import a as a`). This is required to properly
handle many stubs in the
wild. Currently it must be *exactly* `from . import ...`.
This implementation is intentionally limited/conservative (notably,
often requiring a from import to be relative). I'm going to file a ton
of followups for improvements so that their impact can be evaluated
separately.
Fixes https://github.com/astral-sh/ty/issues/133
## Summary
Detect usages of implicit `self` in property getters, which allows us to
treat their signature as being generic.
closes https://github.com/astral-sh/ty/issues/1502
## Typing conformance
Two new type assertions that are succeeding.
## Ecosystem results
Mostly look good. There are a few new false positives related to a bug
with constrained typevars that is unrelated to the work here. I reported
this as https://github.com/astral-sh/ty/issues/1503.
## Test Plan
Added regression tests.
## Summary
Add support for `Optional` and `Annotated` in implicit type aliases
part of https://github.com/astral-sh/ty/issues/221
## Typing conformance changes
New expected diagnostics.
## Ecosystem
A lot of true positives, some known limitations unrelated to this PR.
## Test Plan
New Markdown tests
## Summary
This PR adds extra validation for `isinstance()` and `issubclass()`
calls that use `UnionType` instances for their second argument.
According to typeshed's annotations, any `UnionType` is accepted for the
second argument, but this isn't true at runtime: at runtime, all
elements in the `UnionType` must either be class objects or be `None` in
order for the `isinstance()` or `issubclass()` call to reliably succeed:
```pycon
% uvx python3.14
Python 3.14.0 (main, Oct 10 2025, 12:54:13) [Clang 20.1.4 ] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from typing import LiteralString
>>> import types
>>> type(LiteralString | int) is types.UnionType
True
>>> isinstance(42, LiteralString | int)
Traceback (most recent call last):
File "<python-input-5>", line 1, in <module>
isinstance(42, LiteralString | int)
~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/alexw/Library/Application Support/uv/python/cpython-3.14.0-macos-aarch64-none/lib/python3.14/typing.py", line 559, in __instancecheck__
raise TypeError(f"{self} cannot be used with isinstance()")
TypeError: typing.LiteralString cannot be used with isinstance()
```
## Test Plan
Added mdtests/snapshots
When checking whether a constraint set is satisfied, if a typevar has a
non-fully-static upper bound or constraint, we are free to choose any
materialization that makes the check succeed.
In non-inferable positions, we have to show that the constraint set is
satisfied for all valid specializations, so it's best to choose the most
restrictive materialization, since that minimizes the set of valid
specializations that have to pass.
In inferable positions, we only have to show that the constraint set is
satisfied for _some_ valid specializations, so it's best to choose the
most permissive materialization, since that maximizes our chances of
finding a specialization that passes.
## Summary
Add support for `Literal` types in implicit type aliases.
part of https://github.com/astral-sh/ty/issues/221
## Ecosystem analysis
This looks good to me, true positives and known problems.
## Test Plan
New Markdown tests.
## Summary
This PR adds support for understanding the legacy definition and PEP 695
definition for `ParamSpec`.
This is still very initial and doesn't really implement any of the
semantics.
Part of https://github.com/astral-sh/ty/issues/157
## Test Plan
Add mdtest cases.
## Ecosystem analysis
Most of the diagnostics in `starlette` are due to the fact that ty now
understands `ParamSpec` is not a `Todo` type, so the assignability check
fails. The code looks something like:
```py
class _MiddlewareFactory(Protocol[P]):
def __call__(self, app: ASGIApp, /, *args: P.args, **kwargs: P.kwargs) -> ASGIApp: ... # pragma: no cover
class Middleware:
def __init__(
self,
cls: _MiddlewareFactory[P],
*args: P.args,
**kwargs: P.kwargs,
) -> None:
self.cls = cls
self.args = args
self.kwargs = kwargs
# ty complains that `ServerErrorMiddleware` is not assignable to `_MiddlewareFactory[P]`
Middleware(ServerErrorMiddleware, handler=error_handler, debug=debug)
```
There are multiple diagnostics where there's an attribute access on the
`Wrapped` object of `functools` which Pyright also raises:
```py
from functools import wraps
def my_decorator(f):
@wraps(f)
def wrapper(*args, **kwds):
return f(*args, **kwds)
# Pyright: Cannot access attribute "__signature__" for class "_Wrapped[..., Unknown, ..., Unknown]"
Attribute "__signature__" is unknown [reportAttributeAccessIssue]
# ty: Object of type `_Wrapped[Unknown, Unknown, Unknown, Unknown]` has no attribute `__signature__` [unresolved-attribute]
wrapper.__signature__
return wrapper
```
There are additional diagnostics that is due to the assignability checks
failing because ty now infers the `ParamSpec` instead of using the
`Todo` type which would always succeed. This results in a few
`no-matching-overload` diagnostics because the assignability checks
fail.
There are a few diagnostics related to
https://github.com/astral-sh/ty/issues/491 where there's a variable
which is either a bound method or a variable that's annotated with
`Callable` that doesn't contain the instance as the first parameter.
Another set of (valid) diagnostics are where the code hasn't provided
all the type variables. ty is now raising diagnostics for these because
we include `ParamSpec` type variable in the signature. For example,
`staticmethod[Any]` which contains two type variables.
This PR carries over some of the `has_relation_to` logic for comparing a
typevar with itself. A typevar will specialize to the same type if it's
mentioned multiple times, so it is always assignable to and a subtype of
itself. (Note that typevars can only specialize to fully static types.)
This is also true when the typevar appears in a union on the right-hand
side, or in an intersection on the left-hand side. Similarly, a typevar
is always disjoint from its negation, so when a negated typevar appears
on the left-hand side, the constraint set is never satisfiable.
(Eventually this will allow us to remove the corresponding clauses from
`has_relation_to`, but that can't happen until more of #20093 lands.)
## Summary
Splitting this one out from https://github.com/astral-sh/ruff/pull/21210. This is also something that should be made obselete by the new constraint solver, but is easy enough to fix now.
## Summary
Allow values of type `None` in type expressions. The [typing
spec](https://typing.python.org/en/latest/spec/annotations.html#type-and-annotation-expressions)
could be more explicit on whether this is actually allowed or not, but
it seems relatively harmless and does help in some use cases like:
```py
try:
from module import MyClass
except ImportError:
MyClass = None # ty: ignore
def f(m: MyClass):
pass
```
## Test Plan
Updated tests, ecosystem check.
## Summary
A lot of the bidirectional inference work relies on `dict` not being
assignable to `TypedDict`, so I think it makes sense to add this before
fully implementing https://github.com/astral-sh/ty/issues/1387.
## Summary
Add support for implicit type aliases that use PEP 604 unions:
```py
IntOrStr = int | str
reveal_type(IntOrStr) # UnionType
def _(int_or_str: IntOrStr):
reveal_type(int_or_str) # int | str
```
## Typing conformance
The changes are either removed false positives, or new diagnostics due
to known limitations unrelated to this PR.
## Ecosystem impact
Spot checked, a mix of true positives and known limitations.
## Test Plan
New Markdown tests.
Fixes https://github.com/astral-sh/ty/issues/1053
## Summary
Other type checkers prioritize a submodule over a package `__getattr__`
in `from mod import sub`, even though the runtime precedence is the
other direction. In effect, this is making an implicit assumption that a
module `__getattr__` will not handle (that is, will raise
`AttributeError`) for names that are also actual submodules, rather than
shadowing them. In practice this seems like a realistic assumption in
the ecosystem? Or at least the ecosystem has adapted to it, and we need
to adapt this precedence also, for ecosystem compatibility.
The implementation is a bit ugly, precisely because it departs from the
runtime semantics, and our implementation is oriented toward modeling
runtime semantics accurately. That is, `__getattr__` is modeled within
the member-lookup code, so it's hard to split "member lookup result from
module `__getattr__`" apart from other member lookup results. I did this
via a synthetic `TypeQualifier::FROM_MODULE_GETATTR` that we attach to a
type resulting from a member lookup, which isn't beautiful but it works
well and doesn't introduce inefficiency (e.g. redundant member lookups).
## Test Plan
Updated mdtests.
Also added a related mdtest formalizing our support for a module
`__getattr__` that is explicitly annotated to accept a limited set of
names. In principle this could be an alternative (more explicit) way to
handle the precedence problem without departing from runtime semantics,
if the ecosystem would adopt it.
### Ecosystem analysis
Lots of removed diagnostics which are an improvement because we now
infer the expected submodule.
Added diagnostics are mostly unrelated issues surfaced now because we
previously had an earlier attribute error resulting in `Unknown`; now we
correctly resolve the module so that earlier attribute error goes away,
we get an actual type instead of `Unknown`, and that triggers a new
error.
In scipy and sklearn, the module `__getattr__` which we were respecting
previously is un-annotated so returned a forgiving `Unknown`; now we
correctly see the actual module, which reveals some cases of
https://github.com/astral-sh/ty/issues/133 that were previously hidden
(`scipy/optimize/__init__.py` [imports `from
._tnc`](eff82ca575/scipy/optimize/__init__.py (L429)).)
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Fixes https://github.com/astral-sh/ty/issues/1368
## Summary
Add support for patterns like this, where a type alias to a literal type
(or union of literal types) is used to subscript `typing.Literal`:
```py
type MyAlias = Literal[1]
def _(x: Literal[MyAlias]): ...
```
This shows up in the ecosystem report for PEP 613 type alias support.
One interesting case is an alias to `bool` or an enum type. `bool` is an
equivalent type to `Literal[True, False]`, which is a union of literal
types. Similarly an enum type `E` is also equivalent to a union of its
member literal types. Since (for explicit type aliases) we infer the RHS
directly as a type expression, this makes it difficult for us to
distinguish between `bool` and `Literal[True, False]`, so we allow
either one to (or an alias to either one) to appear inside `Literal`,
where other type checkers allow only the latter.
I think for implicit type aliases it may be simpler to support only
types derived from actually subscripting `typing.Literal`, though, so I
didn't make a TODO-comment commitment here.
## Test Plan
Added mdtests, including TODO-filled tests for PEP 613 and implicit type
aliases.
### Conformance suite
All changes here are positive -- we now emit errors on lines that should
be errors. This is a side effect of the new implementation, not the
primary purpose of this PR, but it's still a positive change.
### Ecosystem
Eliminates one ecosystem false positive, where a PEP 695 type alias for
a union of literal types is used to subscript `typing.Literal`.
## Summary
Adds type inference for list/dict/set comprehensions, including
bidirectional inference:
```py
reveal_type({k: v for k, v in [("a", 1), ("b", 2)]}) # dict[Unknown | str, Unknown | int]
squares: list[int | None] = [x for x in range(10)]
reveal_type(squares) # list[int | None]
```
## Ecosystem impact
I did spot check the changes and most of them seem like known
limitations or true positives. Without proper bidirectional inference,
we saw a lot of false positives.
## Test Plan
New Markdown tests
