## 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
## Summary
Follow up from https://github.com/astral-sh/ruff/pull/21411. Again,
there are more things that could be improved here (like the diagnostics
for `lists`, or extending what we have for `dict` to `OrderedDict` etc),
but that will have to be postponed.
## Summary
Extends literal promotion to apply to any generic method, as opposed to
only generic class constructors. This PR also improves our literal
promotion heuristics to only promote literals in non-covariant position
in the return type, and avoid promotion if the literal is present in
non-covariant position in any argument type.
Resolves https://github.com/astral-sh/ty/issues/1357.
## 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
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
## 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.
## Summary
Adds proper type narrowing and reachability analysis for matching on
non-inferable type variables bound to enums. For example:
```py
from enum import Enum
class Answer(Enum):
NO = 0
YES = 1
def is_yes(self) -> bool: # no error here!
match self:
case Answer.YES:
return True
case Answer.NO:
return False
```
closes https://github.com/astral-sh/ty/issues/1404
## Test Plan
Added regression tests
## Summary
- Type checkers (and type-checker authors) think in terms of types, but
I think most Python users think in terms of values. Rather than saying
that a _type_ `X` "has no attribute `foo`" (which I think sounds strange
to many users), say that "an object of type `X` has no attribute `foo`"
- Special-case certain types so that the diagnostic messages read more
like normal English: rather than saying "Type `<class 'Foo'>` has no
attribute `bar`" or "Object of type `<class 'Foo'>` has no attribute
`bar`", just say "Class `Foo` has no attribute `bar`"
## Test Plan
Mdtests and snapshots updated
## Summary
Use the declared type of variables as type context for the RHS of assignment expressions, e.g.,
```py
x: list[int | str]
x = [1]
reveal_type(x) # revealed: list[int | str]
```
## Summary
Resolves https://github.com/astral-sh/ty/issues/1349.
Fix match statement value patterns to use equality comparison semantics
instead of incorrectly narrowing to literal types directly. Value
patterns use equality for matching, and equality can be overridden, so
we can't always narrow to the matched literal.
## Test Plan
Updated match.md with corrected expected types and an additional example
with explanation
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
Quoting from the newly added comment:
Module-level globals can be mutated externally. A `MY_CONSTANT = 1`
global might be changed to `"some string"` from code outside of the
module that we're looking at, and so from a gradual-guarantee
perspective, it makes sense to infer a type of `Literal[1] | Unknown`
for global symbols. This allows the code that does the mutation to type
check correctly, and for code that uses the global, it accurately
reflects the lack of knowledge about the type.
External modifications (or modifications through `global` statements)
that would require a wider type are relatively rare. From a practical
perspective, we can therefore achieve a better user experience by
trusting the inferred type. Users who need the external mutation to work
can always annotate the global with the wider type. And everyone else
benefits from more precise type inference.
I initially implemented this by applying literal promotion to the type
of the unannotated module globals (as suggested in
https://github.com/astral-sh/ty/issues/1069), but the ecosystem impact
showed a lot of problems (https://github.com/astral-sh/ruff/pull/20643).
I fixed/patched some of these problems, but this PR seems like a good
first step, and it seems sensible to apply the literal promotion change
in a second step that can be evaluated separately.
closes https://github.com/astral-sh/ty/issues/1069
## Ecosystem impact
This seems like an (unexpectedly large) net positive with 650 fewer
diagnostics overall.. even though this change will certainly catch more
true positives.
* There are 666 removed `type-assertion-failure` diagnostics, where we
were previously used the correct type already, but removing the
`Unknown` now leads to an "exact" match.
* 1464 of the 1805 total new diagnostics are `unresolved-attribute`
errors, most (1365) of which were previously
`possibly-missing-attribute` errors. So they could also be counted as
"changed" diagnostics.
* For code that uses constants like
```py
IS_PYTHON_AT_LEAST_3_10 = sys.version_info >= (3, 10)
```
where we would have previously inferred a type of `Literal[True/False] |
Unknown`, removing the `Unknown` now allows us to do reachability
analysis on branches that use these constants, and so we get a lot of
favorable ecosystem changes because of that.
* There is code like the following, where we previously emitted
`conflicting-argument-forms` diagnostics on calls to the aliased
`assert_type`, because its type was `Unknown | def …` (and the call to
`Unknown` "used" the type form argument in a non type-form way):
```py
if sys.version_info >= (3, 11):
import typing
assert_type = typing.assert_type
else:
import typing_extensions
assert_type = typing_extensions.assert_type
```
* ~100 new `invalid-argument-type` false positives, due to missing
`**kwargs` support (https://github.com/astral-sh/ty/issues/247)
## Typing conformance
```diff
+protocols_modules.py:25:1: error[invalid-assignment] Object of type `<module '_protocols_modules1'>` is not assignable to `Options1`
```
This diagnostic should apparently not be there, but it looks like we
also fail other tests in that file, so it seems to be a limitation that
was previously hidden by `Unknown` somehow.
## Test Plan
Updated tests and relatively thorough ecosystem analysis.
## Summary
Modify the (external) signature of instance methods such that the first
parameter uses `Self` unless it is explicitly annotated. This allows us
to correctly type-check more code, and allows us to infer correct return
types for many functions that return `Self`. For example:
```py
from pathlib import Path
from datetime import datetime, timedelta
reveal_type(Path(".config") / ".ty") # now Path, previously Unknown
def _(dt: datetime, delta: timedelta):
reveal_type(dt - delta) # now datetime, previously Unknown
```
part of https://github.com/astral-sh/ty/issues/159
## Performance
I ran benchmarks locally on `attrs`, `freqtrade` and `colour`, the
projects with the largest regressions on CodSpeed. I see much smaller
effects locally, but can definitely reproduce the regression on `attrs`.
From looking at the profiling results (on Codspeed), it seems that we
simply do more type inference work, which seems plausible, given that we
now understand much more return types (of many stdlib functions). In
particular, whenever a function uses an implicit `self` and returns
`Self` (without mentioning `Self` anywhere else in its signature), we
will now infer the correct type, whereas we would previously return
`Unknown`. This also means that we need to invoke the generics solver in
more cases. Comparing half a million lines of log output on attrs, I can
see that we do 5% more "work" (number of lines in the log), and have a
lot more `apply_specialization` events (7108 vs 4304). On freqtrade, I
see similar numbers for `apply_specialization` (11360 vs 5138 calls).
Given these results, I'm not sure if it's generally worth doing more
performance work, especially since none of the code modifications
themselves seem to be likely candidates for regressions.
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./ty_main check /home/shark/ecosystem/attrs` | 92.6 ± 3.6 | 85.9 |
102.6 | 1.00 |
| `./ty_self check /home/shark/ecosystem/attrs` | 101.7 ± 3.5 | 96.9 |
113.8 | 1.10 ± 0.06 |
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./ty_main check /home/shark/ecosystem/freqtrade` | 599.0 ± 20.2 |
568.2 | 627.5 | 1.00 |
| `./ty_self check /home/shark/ecosystem/freqtrade` | 607.9 ± 11.5 |
594.9 | 626.4 | 1.01 ± 0.04 |
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./ty_main check /home/shark/ecosystem/colour` | 423.9 ± 17.9 | 394.6
| 447.4 | 1.00 |
| `./ty_self check /home/shark/ecosystem/colour` | 426.9 ± 24.9 | 373.8
| 456.6 | 1.01 ± 0.07 |
## Test Plan
New Markdown tests
## Ecosystem report
* apprise: ~300 new diagnostics related to problematic stubs in apprise
😩
* attrs: a new true positive, since [this
function](4e2c89c823/tests/test_make.py (L2135))
is missing a `@staticmethod`?
* Some legitimate true positives
* sympy: lots of new `invalid-operator` false positives in [matrix
multiplication](cf9f4b6805/sympy/matrices/matrixbase.py (L3267-L3269))
due to our limited understanding of [generic `Callable[[Callable[[T1,
T2], T3]], Callable[[T1, T2], T3]]` "identity"
types](cf9f4b6805/sympy/core/decorators.py (L83-L84))
of decorators. This is not related to type-of-self.
## Typing conformance results
The changes are all correct, except for
```diff
+generics_self_usage.py:50:5: error[invalid-assignment] Object of type `def foo(self) -> int` is not assignable to `(typing.Self, /) -> int`
```
which is related to an assignability problem involving type variables on
both sides:
```py
class CallableAttribute:
def foo(self) -> int:
return 0
bar: Callable[[Self], int] = foo # <- we currently error on this assignment
```
---------
Co-authored-by: Shaygan Hooshyari <sh.hooshyari@gmail.com>
### Summary
This PR includes two changes, both of which are necessary to resolve
https://github.com/astral-sh/ty/issues/1196:
* For a generic class `C[T]`, we previously used `C[Unknown]` as the
upper bound of the `Self` type variable. There were two problems with
this. For one, when `Self` appeared in contravariant position, we would
materialize its upper bound to `Bottom[C[Unknown]]` (which might
simplify to `C[Never]` if `C` is covariant in `T`) when accessing
methods on `Top[C[Unknown]]`. This would result in `invalid-argument`
errors on the `self` parameter. Also, using an upper bound of
`C[Unknown]` would mean that inside methods, references to `T` would be
treated as `Unknown`. This could lead to false negatives. To fix this,
we now use `C[T]` (with a "nested" typevar) as the upper bound for
`Self` on `C[T]`.
* In order to make this work, we needed to allow assignability/subtyping
of inferable typevars to other types, since we now check assignability
of e.g. `C[int]` to `C[T]` (when checking assignability to the upper
bound of `Self`) when calling an instance-method on `C[int]` whose
`self` parameter is annotated as `self: Self` (or implicitly `Self`,
following https://github.com/astral-sh/ruff/pull/18007).
closes https://github.com/astral-sh/ty/issues/1196
closes https://github.com/astral-sh/ty/issues/1208
### Test Plan
Regression tests for both issues.
## Summary
Part of https://github.com/astral-sh/ty/issues/168. Infer more precise types for collection literals (currently, only `list` and `set`). For example,
```py
x = [1, 2, 3] # revealed: list[Unknown | int]
y: list[int] = [1, 2, 3] # revealed: list[int]
```
This could easily be extended to `dict` literals, but I am intentionally limiting scope for now.
## Summary
This is a follow-up to https://github.com/astral-sh/ruff/pull/19321.
Now lazy snapshots are updated to take into account new bindings on
every symbol reassignment.
```python
def outer(x: A | None):
if x is None:
x = A()
reveal_type(x) # revealed: A
def inner() -> None:
# lazy snapshot: {x: A}
reveal_type(x) # revealed: A
inner()
def outer() -> None:
x = None
x = 1
def inner() -> None:
# lazy snapshot: {x: Literal[1]} -> {x: Literal[1, 2]}
reveal_type(x) # revealed: Literal[1, 2]
inner()
x = 2
```
Closesastral-sh/ty#559.
## Test Plan
Some TODOs in `public_types.md` now work properly.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Closesastral-sh/ty#456. Part of astral-sh/ty#994.
After all the foundational work, this is only a small change, but let's
see if it exposes any unresolved issues.
## Summary
Reported in:
https://github.com/astral-sh/ruff/pull/19795#issuecomment-3161981945
If a root expression is reassigned, narrowing on the member should be
invalidated, but there was an oversight in the current implementation.
This PR fixes that, and also removes some unnecessary handling.
## Test Plan
New tests cases in `narrow/conditionals/nested.md`.
## Summary
This PR improves the `is_safe_mutable_class` function in `infer.rs` in
several ways:
- It uses `KnownClass::to_instance()` for all "safe mutable classes".
Previously, we were using `SpecialFormType::instance_fallback()` for
some variants -- I'm not totally sure why. Switching to
`KnownClass::to_instance()` for all "safe mutable classes" fixes a
number of TODOs in the `assignment.md` mdtest suite
- Rather than eagerly calling `.to_instance(db)` on all "safe mutable
classes" every time `is_safe_mutable_class` is called, we now only call
it lazily on each element, allowing us to short-circuit more
effectively.
- I removed the entry entirely for `TypedDict` from the list of "safe
mutable classes", as it's not correct.
`SpecialFormType::TypedDict.instance_fallback(db)` just returns an
instance type representing "any instance of `typing._SpecialForm`",
which I don't think was the intent of this code. No tests fail as a
result of removing this entry, as we already check separately whether an
object is an inhabitant of a `TypedDict` type (and consider that object
safe-mutable if so!).
## Test Plan
mdtests updated
## Summary
This PR adds type inference for key-based access on `TypedDict`s and a
new diagnostic for invalid subscript accesses:
```py
class Person(TypedDict):
name: str
age: int | None
alice = Person(name="Alice", age=25)
reveal_type(alice["name"]) # revealed: str
reveal_type(alice["age"]) # revealed: int | None
alice["naem"] # Unknown key "naem" - did you mean "name"?
```
## Test Plan
Updated 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`.
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 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
We currently infer a `@Todo` type whenever we access an attribute on an
intersection type with negative components. This can happen very
naturally. Consequently, this `@Todo` type is rather pervasive and hides
a lot of true positives that ty could otherwise detect:
```py
class Foo:
attr: int = 1
def _(f: Foo | None):
if f:
reveal_type(f) # Foo & ~AlwaysFalsy
reveal_type(f.attr) # now: int, previously: @Todo
```
The changeset here proposes to handle member access on these
intersection types by simply ignoring all negative contributions. This
is not always ideal: a negative contribution like `~<Protocol with
members 'attr'>` could be a hint that `.attr` should not be accessible
on the full intersection type. The behavior can certainly be improved in
the future, but this seems like a reasonable initial step to get rid of
this unnecessary `@Todo` type.
## Ecosystem analysis
There are quite a few changes here. I spot-checked them and found one
bug where attribute access on pure negation types (`~P == object & ~P`)
would not allow attributes on `object` to be accessed. After that was
fixed, I only see true positives and known problems. The fact that a lot
of `unused-ignore-comment` diagnostics go away are also evidence for the
fact that this touches a sensitive area, where static analysis clashes
with dynamically adding attributes to objects:
```py
… # type: ignore # Runtime attribute access
```
## Test Plan
Updated tests.
Co-authored-by: David Peter <sharkdp@users.noreply.github.com>
Co-authored-by: Carl Meyer <carl@oddbird.net>
Co-authored-by: Micha Reiser <micha@reiser.io>
This PR updates our call binding logic to handle splatted arguments.
Complicating matters is that we have separated call bind analysis into
two phases: parameter matching and type checking. Parameter matching
looks at the arity of the function signature and call site, and assigns
arguments to parameters. Importantly, we don't yet know the type of each
argument! This is needed so that we can decide whether to infer the type
of each argument as a type form or value form, depending on the
requirements of the parameter that the argument was matched to.
This is an issue when splatting an argument, since we need to know how
many elements the splatted argument contains to know how many positional
parameters to match it against. And to know how many elements the
splatted argument has, we need to know its type.
To get around this, we now make the assumption that splatted arguments
can only be used with value-form parameters. (If you end up splatting an
argument into a type-form parameter, we will silently pass in its
value-form type instead.) That allows us to preemptively infer the
(value-form) type of any splatted argument, so that we have its arity
available during parameter matching. We defer inference of non-splatted
arguments until after parameter matching has finished, as before.
We reuse a lot of the new tuple machinery to make this happen — in
particular resizing the tuple spec representing the number of arguments
passed in with the tuple length representing the number of parameters
the splat was matched with.
This work also shows that we might need to change how we are performing
argument expansion during overload resolution. At the moment, when we
expand parameters, we assume that each argument will still be matched to
the same parameters as before, and only retry the type-checking phase.
With splatted arguments, this is no longer the case, since the inferred
arity of each union element might be different than the arity of the
union as a whole, which can affect how many parameters the splatted
argument is matched to. See the regression test case in
`mdtest/call/function.md` for more details.
## Summary
Implement expansion of enums into unions of enum literals (and the
reverse operation). For the enum below, this allows us to understand
that `Color = Literal[Color.RED, Color.GREEN, Color.BLUE]`, or that
`Color & ~Literal[Color.RED] = Literal[Color.GREEN, Color.BLUE]`. This
helps in exhaustiveness checking, which is why we see some removed
`assert_never` false positives. And since exhaustiveness checking also
helps with understanding terminal control flow, we also see a few
removed `invalid-return-type` and `possibly-unresolved-reference` false
positives. This PR also adds expansion of enums in overload resolution
and type narrowing constructs.
```py
from enum import Enum
from typing_extensions import Literal, assert_never
from ty_extensions import Intersection, Not, static_assert, is_equivalent_to
class Color(Enum):
RED = 1
GREEN = 2
BLUE = 3
type Red = Literal[Color.RED]
type Green = Literal[Color.GREEN]
type Blue = Literal[Color.BLUE]
static_assert(is_equivalent_to(Red | Green | Blue, Color))
static_assert(is_equivalent_to(Intersection[Color, Not[Red]], Green | Blue))
def color_name(color: Color) -> str: # no error here (we detect that this can not implicitly return None)
if color is Color.RED:
return "Red"
elif color is Color.GREEN:
return "Green"
elif color is Color.BLUE:
return "Blue"
else:
assert_never(color) # no error here
```
## Performance
I avoided an initial regression here for large enums, but the
`UnionBuilder` and `IntersectionBuilder` parts can certainly still be
optimized. We might want to use the same technique that we also use for
unions of other literals. I didn't see any problems in our benchmarks so
far, so this is not included yet.
## Test Plan
Many new Markdown tests
David Peter
Ibraheem Ahmed
Alex Waygood
Shunsuke Shibayama
Eric Mark Martin
Renkai Ge
Jelle Zijlstra
Samuel Rigaud
Jack O'Connor
Douglas Creager
Matthew Mckee