## Summary
Thread visitors through the rest of `apply_type_mapping`: callable and
protocol types.
## Test Plan
Added mdtest that previously stack overflowed.
## Summary
We have the ability to defer type inference of some parts of
definitions, so as to allow us to create a type that may need to be
recursively referenced in those other parts of the definition.
We also have the ability to do type inference in a context where all
name resolution should be deferred (that is, names should be looked up
from all-reachable-definitions rather than from the location of use.)
This is used for all annotations in stubs, or if `from __future__ import
annotations` is active.
Previous to this PR, these two concepts were linked: deferred-inference
always implied deferred-name-resolution, though we also supported
deferred-name-resolution without deferred-inference, via
`DeferredExpressionState`.
For the upcoming `typing.TypeAlias` support, I will defer inference of
the entire RHS of the alias (so as to support cycles), but that doesn't
imply deferred name resolution; at runtime, the RHS of a name annotated
as `typing.TypeAlias` is executed eagerly.
So this PR fully de-couples the two concepts, instead explicitly setting
the `DeferredExpressionState` in those cases where we should defer name
resolution.
It also fixes a long-standing related bug, where we were deferring name
resolution of all names in class bases, if any of the class bases
contained a stringified annotation.
## Test Plan
Added test that failed before this PR.
Reverts astral-sh/ruff#20156. As @sharkdp noted in his post-merge
review, there were several issues with that PR that I didn't spot before
merging — but I'm out for four days now, and would rather not leave
things in an inconsistent state for that long. I'll revisit this on
Wednesday.
## Summary
This error is about assigning to attributes rather than reading
attributes, so I think `invalid-assignment` makes more sense than
`invalid-attribute-access`
## Test Plan
existing mdtests updated
## Summary
Now that we have `Type::TypeAlias`, which can wrap a union, and the
possibility of unions including non-unpacked type aliases (which is
necessary to support recursive type aliases), we can no longer assume in
`UnionType::normalized_impl` that normalizing each element of an
existing union will result in a set of elements that we can order and
then place raw into `UnionType` to create a normalized union. It's now
possible for those elements to themselves include union types (unpacked
from an alias). So instead, we need to feed those elements into the full
`UnionBuilder` (with alias-unpacking turned on) to flatten/normalize
them, and then order them.
## Test Plan
Added mdtest.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
This PR fixes various TODOs around overload call when a variadic
argument is used.
The reason this bug existed is because the specialization wouldn't
account for unpacking the type of the variadic argument.
This is fixed by expanding `MatchedArgument` to contain the type of that
argument _only_ when it is a variadic argument. The reason is that
there's a split for when the argument type is inferred -- the
non-variadic arguments are inferred using `infer_argument_types` _after_
parameter matching while the variadic argument type is inferred _during_
the parameter matching. And, the `MatchedArgument` is populated _during_
parameter matching which means the unpacking would need to happen during
parameter matching.
This split seems a bit inconsistent but I don't want to spend a lot of
time on trying to merge them such that all argument type inference
happens in a single place. I might look into it while adding support for
`**kwargs`.
## Test Plan
Update existing tests by resolving the todos.
The ecosystem changes looks correct to me except for the `slice` call
but it seems that it's unrelated to this PR as we infer `slice[Any, Any,
Any]` for a `slice(1, 2, 3)` call on `main` as well
([playground](https://play.ty.dev/9eacce00-c7d5-4dd5-a932-4265cb2bb4f6)).
## Summary
Decrease the maximum number of literals in a union before we collapse to
the supertype. The better fix for this will be
https://github.com/astral-sh/ty/issues/957, but it is very tempting to
solve this for now by simply decreasing the limit by one, to get below
the salsa limit of 200.
closes https://github.com/astral-sh/ty/issues/660
## Test Plan
Added a regression test that would previously lead to a "too many cycle
iterations" panic.
## Summary
With this PR, we stop performing boundness analysis for implicit
instance attributes:
```py
class C:
def __init__(self):
if False:
self.x = 1
C().x # would previously show an error, with this PR we pretend the attribute exists
```
This PR is potentially just a temporary measure until we find a better
fix. But I have already invested a lot of time trying to find the root
cause of https://github.com/astral-sh/ty/issues/758 (and [this
example](https://github.com/astral-sh/ty/issues/758#issuecomment-3206108262),
which I'm not entirely sure is related) and I still don't understand
what is going on. This PR fixes the performance problems in both of
these problems (in a rather crude way).
The impact of the proposed change on the ecosystem is small, and the
three new diagnostics are arguably true positives (previously hidden
because we considered the code unreachable, based on e.g. `assert`ions
that depended on implicit instance attributes). So this seems like a
reasonable fix for now.
Note that we still support cases like these:
```py
class D:
if False: # or any other expression that statically evaluates to `False`
x: int = 1
D().x # still an error
class E:
if False: # or any other expression that statically evaluates to `False`
def f(self):
self.x = 1
E().x # still an error
```
closes https://github.com/astral-sh/ty/issues/758
## Test Plan
Updated tests, benchmark results
## Summary
closes https://github.com/astral-sh/ty/issues/692
If the expression (or any child expressions) is not definitely bound the
reachability constraint evaluation is determined as ambiguous.
This fixes the infinite cycles panic in the following code:
```py
from typing import Literal
class Toggle:
def __init__(self: "Toggle"):
if not self.x:
self.x: Literal[True] = True
```
Credit of this solution is for David.
## Test Plan
- Added a test case with too many cycle iterations panic.
- Previous tests.
---------
Co-authored-by: David Peter <mail@david-peter.de>
Part of #994. This adds a new field to the Specialization struct to
record when we're dealing with the top or bottom materialization of an
invariant generic. It also implements subtyping and assignability for
these objects.
Next planned steps after this is done are to implement other operations
on top/bottom materializations; probably attribute access is an
important one.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
There are some situations that we have a confusing diagnostics due to
identical class names.
## Class with same name from different modules
```python
import pandas
import polars
df: pandas.DataFrame = polars.DataFrame()
```
This yields the following error:
**Actual:**
error: [invalid-assignment] "Object of type `DataFrame` is not
assignable to `DataFrame`"
**Expected**:
error: [invalid-assignment] "Object of type `polars.DataFrame` is not
assignable to `pandas.DataFrame`"
## Nested classes
```python
from enum import Enum
class A:
class B(Enum):
ACTIVE = "active"
INACTIVE = "inactive"
class C:
class B(Enum):
ACTIVE = "active"
INACTIVE = "inactive"
```
**Actual**:
error: [invalid-assignment] "Object of type `Literal[B.ACTIVE]` is not
assignable to `B`"
**Expected**:
error: [invalid-assignment] "Object of type
`Literal[my_module.C.B.ACTIVE]` is not assignable to `my_module.A.B`"
## Solution
In this MR we added an heuristics to detect when to use a fully
qualified name:
- There is an invalid assignment and;
- They are two different classes and;
- They have the same name
The fully qualified name always includes:
- module name
- nested classes name
- actual class name
There was no `QualifiedDisplay` so I had to implement it from scratch.
I'm very new to the codebase, so I might have done things inefficiently,
so I appreciate feedback.
Should we pre-compute the fully qualified name or do it on demand?
## Not implemented
### Function-local classes
Should we approach this in a different PR?
**Example**:
```python
# t.py
from __future__ import annotations
def function() -> A:
class A:
pass
return A()
class A:
pass
a: A = function()
```
#### mypy
```console
t.py:8: error: Incompatible return value type (got "t.A@5", expected "t.A") [return-value]
```
From my testing the 5 in `A@5` comes from the like number.
#### ty
```console
error[invalid-return-type]: Return type does not match returned value
--> t.py:4:19
|
4 | def function() -> A:
| - Expected `A` because of return type
5 | class A:
6 | pass
7 |
8 | return A()
| ^^^ expected `A`, found `A`
|
info: rule `invalid-return-type` is enabled by default
```
Fixes https://github.com/astral-sh/ty/issues/848
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Properly preserve type qualifiers when accessing attributes on unions
and intersections. This is a prerequisite for
https://github.com/astral-sh/ruff/pull/19579.
Also fix a completely wrong implementation of
`map_with_boundness_and_qualifiers`. It now closely follows
`map_with_boundness` (just above).
## Test Plan
I thought about it, but didn't find any easy way to test this. This only
affected `Type::member`. Things like validation of attribute writes
(where type qualifiers like `ClassVar` and `Final` are important) were
already handling things correctly.
## Summary
Add a subtly different test case for recursive PEP 695 type aliases,
which does require that we relax our union simplification, so we don't
eagerly unpack aliases from user-provided union annotations.
## Test Plan
Added mdtest.
## Summary
This has been here for awhile (since our initial PEP 695 type alias
support) but isn't really correct. The right-hand-side of a PEP 695 type
alias is a distinct scope, and we don't mark it as an "eager" nested
scope, so it automatically gets "deferred" resolution of names from
outer scopes (just like a nested function). Thus it's
redundant/unnecessary for us to use `DeferredExpressionState::Deferred`
for resolving that RHS expression -- that's for deferring resolution of
individual names within a scope. Using it here causes us to wrongly
ignore applicable outer-scope narrowing.
## Test Plan
Added mdtest that failed before this PR (the second snippet -- the first
snippet always passed.)
## Summary
Implement validation for `TypedDict` constructor calls and dictionary
literal assignments, including support for `total=False` and proper
field management.
Also add support for `Required` and `NotRequired` type qualifiers in
`TypedDict` classes, along with proper inheritance behavior and the
`total=` parameter.
Support both constructor calls and dict literal syntax
part of https://github.com/astral-sh/ty/issues/154
### Basic Required Field Validation
```py
class Person(TypedDict):
name: str
age: int | None
# Error: Missing required field 'name' in TypedDict `Person` constructor
incomplete = Person(age=25)
# Error: Invalid argument to key "name" with declared type `str` on TypedDict `Person`
wrong_type = Person(name=123, age=25)
# Error: Invalid key access on TypedDict `Person`: Unknown key "extra"
extra_field = Person(name="Bob", age=25, extra=True)
```
<img width="773" height="191" alt="Screenshot 2025-08-07 at 17 59 22"
src="https://github.com/user-attachments/assets/79076d98-e85f-4495-93d6-a731aa72a5c9"
/>
### Support for `total=False`
```py
class OptionalPerson(TypedDict, total=False):
name: str
age: int | None
# All valid - all fields are optional with total=False
charlie = OptionalPerson()
david = OptionalPerson(name="David")
emily = OptionalPerson(age=30)
frank = OptionalPerson(name="Frank", age=25)
# But type validation and extra fields still apply
invalid_type = OptionalPerson(name=123) # Error: Invalid argument type
invalid_extra = OptionalPerson(extra=True) # Error: Invalid key access
```
### Dictionary Literal Validation
```py
# Type checking works for both constructors and dict literals
person: Person = {"name": "Alice", "age": 30}
reveal_type(person["name"]) # revealed: str
reveal_type(person["age"]) # revealed: int | None
# Error: Invalid key access on TypedDict `Person`: Unknown key "non_existing"
reveal_type(person["non_existing"]) # revealed: Unknown
```
### `Required`, `NotRequired`, `total`
```python
from typing import TypedDict
from typing_extensions import Required, NotRequired
class PartialUser(TypedDict, total=False):
name: Required[str] # Required despite total=False
age: int # Optional due to total=False
email: NotRequired[str] # Explicitly optional (redundant)
class User(TypedDict):
name: Required[str] # Explicitly required (redundant)
age: int # Required due to total=True
bio: NotRequired[str] # Optional despite total=True
# Valid constructions
partial = PartialUser(name="Alice") # name required, age optional
full = User(name="Bob", age=25) # name and age required, bio optional
# Inheritance maintains original field requirements
class Employee(PartialUser):
department: str # Required (new field)
# name: still Required (inherited)
# age: still optional (inherited)
emp = Employee(name="Charlie", department="Engineering") # ✅
Employee(department="Engineering") # ❌
e: Employee = {"age": 1} # ❌
```
<img width="898" height="683" alt="Screenshot 2025-08-11 at 22 02 57"
src="https://github.com/user-attachments/assets/4c1b18cd-cb2e-493a-a948-51589d121738"
/>
## Implementation
The implementation reuses existing validation logic done in
https://github.com/astral-sh/ruff/pull/19782
### ℹ️ Why I did NOT synthesize an `__init__` for `TypedDict`:
`TypedDict` inherits `dict.__init__(self, *args, **kwargs)` that accepts
all arguments.
The type resolution system finds this inherited signature **before**
looking for synthesized members.
So `own_synthesized_member()` is never called because a signature
already exists.
To force synthesis, you'd have to override Python’s inheritance
mechanism, which would break compatibility with the existing ecosystem.
This is why I went with ad-hoc validation. IMO it's the only viable
approach that respects Python’s
inheritance semantics while providing the required validation.
### Refacto of `Field`
**Before:**
```rust
struct Field<'db> {
declared_ty: Type<'db>,
default_ty: Option<Type<'db>>, // NamedTuple and dataclass only
init_only: bool, // dataclass only
init: bool, // dataclass only
is_required: Option<bool>, // TypedDict only
}
```
**After:**
```rust
struct Field<'db> {
declared_ty: Type<'db>,
kind: FieldKind<'db>,
}
enum FieldKind<'db> {
NamedTuple { default_ty: Option<Type<'db>> },
Dataclass { default_ty: Option<Type<'db>>, init_only: bool, init: bool },
TypedDict { is_required: bool },
}
```
## Test Plan
Updated Markdown tests
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
This PR limits the argument type expansion size for an overload call
evaluation to 512.
The limit chosen is arbitrary but I've taken the 256 limit from Pyright
into account and bumped it x2 to start with.
Initially, I actually started out by trying to refactor the entire
argument type expansion to be lazy. Currently, expanding a single
argument at any position eagerly creates the combination (argument
lists) and returns that (`Vec<CallArguments>`) but I thought we could
make it lazier by converting the return type of `expand` from
`Iterator<Item = Vec<CallArguments>>` to `Iterator<Item = Iterator<Item
= CallArguments>>` but that's proving to be difficult to implement
mainly because we **need** to maintain the previous expansion to
generate the next expansion which is the main reason to use
`std::iter::successors` in the first place.
Another approach would be to eagerly expand all the argument types and
then use the `combinations` from `itertools` to generate the
combinations but we would need to find the "boundary" between arguments
lists produced from expanding argument at position 1 and position 2
because that's important for the algorithm.
Closes: https://github.com/astral-sh/ty/issues/868
## Test Plan
Add test case to demonstrate the limit along with the diagnostic
snapshot stating that the limit has been reached.
Part of astral-sh/ty#994
## Summary
Add new special forms to `ty_extensions`, `Top[T]` and `Bottom[T]`.
Remove `ty_extensions.top_materialization` and
`ty_extensions.bottom_materialization`.
## Test Plan
Converted the existing `materialization.md` mdtest to the new syntax.
Added some tests for invalid use of the new special form.
## Summary
Previously we held off from doing this because we weren't sure that it
was worth the added complexity cost. But our code has changed in the
months since we made that initial decision, and I think the structure of
the code is such that it no longer really leads to much added complexity
to add precise inference when unpacking a string literal or a bytes
literal.
The improved inference we gain from this has real benefits to users (see
the mypy_primer report), and this PR doesn't appear to have a
performance impact.
## Test plan
mdtests
"Why would you do this? This looks like you just replaced `bool` with an
overly complex trait"
Yes that's correct!
This should be a no-op refactoring. It replaces all of the logic in our
assignability, subtyping, equivalence, and disjointness methods to work
over an arbitrary `Constraints` trait instead of only working on `bool`.
The methods that `Constraints` provides looks very much like what we get
from `bool`. But soon we will add a new impl of this trait, and some new
methods, that let us express "fuzzy" constraints that aren't always true
or false. (In particular, a constraint will express the upper and lower
bounds of the allowed specializations of a typevar.)
Even once we have that, most of the operations that we perform on
constraint sets will be the usual boolean operations, just on sets.
(`false` becomes empty/never; `true` becomes universe/always; `or`
becomes union; `and` becomes intersection; `not` becomes negation.) So
it's helpful to have this separate PR to refactor how we invoke those
operations without introducing the new functionality yet.
Note that we also have translations of `Option::is_some_and` and
`is_none_or`, and of `Iterator::any` and `all`, and that the `and`,
`or`, `when_any`, and `when_all` methods are meant to short-circuit,
just like the corresponding boolean operations. For constraint sets,
that depends on being able to implement the `is_always` and `is_never`
trait methods.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Part of: https://github.com/astral-sh/ty/issues/868
This PR adds a heuristic to avoid argument type expansion if it's going
to eventually lead to no matching overload.
This is done by checking whether the non-expandable argument types are
assignable to the corresponding annotated parameter type. If one of them
is not assignable to all of the remaining overloads, then argument type
expansion isn't going to help.
## Test Plan
Add mdtest that would otherwise take a long time because of the number
of arguments that it would need to expand (30).
This commit corrects the type checker's behavior when handling
`dataclass_transform` decorators that don't explicitly specify
`field_specifiers`. According to [PEP 681 (Data Class
Transforms)](https://peps.python.org/pep-0681/#dataclass-transform-parameters),
when `field_specifiers` is not provided, it defaults to an empty tuple,
meaning no field specifiers are supported and
`dataclasses.field`/`dataclasses.Field` calls should be ignored.
Fixes https://github.com/astral-sh/ty/issues/980
## Summary
Closes: https://github.com/astral-sh/ty/issues/669
(This turned out to be simpler that I thought :))
## Test Plan
Update existing test cases.
### Ecosystem report
Most of them are basically because ty has now started inferring more
precise types for the return type to an overloaded call and a lot of the
types are defined using type aliases, here's some examples:
<details><summary>Details</summary>
<p>
> attrs (https://github.com/python-attrs/attrs)
> + tests/test_make.py:146:14: error[unresolved-attribute] Type
`Literal[42]` has no attribute `default`
> - Found 555 diagnostics
> + Found 556 diagnostics
This is accurate now that we infer the type as `Literal[42]` instead of
`Unknown` (Pyright infers it as `int`)
> optuna (https://github.com/optuna/optuna)
> + optuna/_gp/search_space.py:181:53: error[invalid-argument-type]
Argument to function `_round_one_normalized_param` is incorrect:
Expected `tuple[int | float, int | float]`, found `tuple[Unknown |
ndarray[Unknown, <class 'float'>], Unknown | ndarray[Unknown, <class
'float'>]]`
> + optuna/_gp/search_space.py:181:83: error[invalid-argument-type]
Argument to function `_round_one_normalized_param` is incorrect:
Expected `int | float`, found `Unknown | ndarray[Unknown, <class
'float'>]`
> + tests/gp_tests/test_search_space.py:109:13:
error[invalid-argument-type] Argument to function
`_unnormalize_one_param` is incorrect: Expected `tuple[int | float, int
| float]`, found `Unknown | ndarray[Unknown, <class 'float'>]`
> + tests/gp_tests/test_search_space.py:110:13:
error[invalid-argument-type] Argument to function
`_unnormalize_one_param` is incorrect: Expected `int | float`, found
`Unknown | ndarray[Unknown, <class 'float'>]`
> - Found 559 diagnostics
> + Found 563 diagnostics
Same as above where ty is now inferring a more precise type like
`Unknown | ndarray[tuple[int, int], <class 'float'>]` instead of just
`Unknown` as before
> jinja (https://github.com/pallets/jinja)
> + src/jinja2/bccache.py:298:39: error[invalid-argument-type] Argument
to bound method `write_bytecode` is incorrect: Expected `IO[bytes]`,
found `_TemporaryFileWrapper[str]`
> - Found 186 diagnostics
> + Found 187 diagnostics
This requires support for type aliases to match the correct overload.
> hydra-zen (https://github.com/mit-ll-responsible-ai/hydra-zen)
> + src/hydra_zen/wrapper/_implementations.py:945:16:
error[invalid-return-type] Return type does not match returned value:
expected `DataClass_ | type[@Todo(type[T] for protocols)] | ListConfig |
DictConfig`, found `@Todo(unsupported type[X] special form) | (((...) ->
Any) & dict[Unknown, Unknown]) | (DataClass_ & dict[Unknown, Unknown]) |
dict[Any, Any] | (ListConfig & dict[Unknown, Unknown]) | (DictConfig &
dict[Unknown, Unknown]) | (((...) -> Any) & list[Unknown]) | (DataClass_
& list[Unknown]) | list[Any] | (ListConfig & list[Unknown]) |
(DictConfig & list[Unknown])`
> + tests/annotations/behaviors.py:60:28: error[call-non-callable]
Object of type `Path` is not callable
> + tests/annotations/behaviors.py:64:21: error[call-non-callable]
Object of type `Path` is not callable
> + tests/annotations/declarations.py:167:17: error[call-non-callable]
Object of type `Path` is not callable
> + tests/annotations/declarations.py:524:17:
error[unresolved-attribute] Type `<class 'int'>` has no attribute
`_target_`
> - Found 561 diagnostics
> + Found 566 diagnostics
Same as above, this requires support for type aliases to match the
correct overload.
> paasta (https://github.com/yelp/paasta)
> + paasta_tools/utils.py:4188:19: warning[redundant-cast] Value is
already of type `list[str]`
> - Found 888 diagnostics
> + Found 889 diagnostics
This is correct.
> colour (https://github.com/colour-science/colour)
> + colour/plotting/diagrams.py:448:13: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/diagrams.py:462:13: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/models.py:419:13: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/temperature.py:230:9: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/temperature.py:474:13: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/temperature.py:495:17: error[invalid-argument-type]
Argument to bound method `__init__` is incorrect: Expected
`Sequence[@Todo(Support for `typing.TypeAlias`)]`, found
`ndarray[tuple[int, int, int], dtype[Unknown]]`
> + colour/plotting/temperature.py:513:13: error[invalid-argument-type]
Argument to bound method `text` is incorrect: Expected `int | float`,
found `ndarray[@Todo(Support for `typing.TypeAlias`), dtype[Unknown]]`
> + colour/plotting/temperature.py:514:13: error[invalid-argument-type]
Argument to bound method `text` is incorrect: Expected `int | float`,
found `ndarray[@Todo(Support for `typing.TypeAlias`), dtype[Unknown]]`
> - Found 480 diagnostics
> + Found 488 diagnostics
Most of them are correct except for the last two diagnostics which I'm
not sure
what's happening, it's trying to index into an `np.ndarray` type (which
is
inferred correctly) but I think it might be picking up an incorrect
overload
for the `__getitem__` method.
Scipy's diagnostics also requires support for type alises to pick the
correct overload.
</p>
</details>
In implementing partial stubs I had observed that this continue in the
namespace package code seemed erroneous since the same continue for
partial stubs didn't work. Unfortunately I wasn't confident enough to
push on that hunch. Fortunately I remembered that hunch to make this an
easy fix.
The issue with the continue is that it bails out of the current
search-path without testing any .py files. This breaks when for example
`google` and `google-stubs`/`types-google` are both in the same
site-packages dir -- failing to find a module in `types-google` has us
completely skip over `google`!
Fixes https://github.com/astral-sh/ty/issues/520
fix https://github.com/astral-sh/ty/issues/1047
## Summary
This PR fixes how `KW_ONLY` is applied in dataclasses. Previously, the
sentinel leaked into subclasses and incorrectly marked their fields as
keyword-only; now it only affects fields declared in the same class.
```py
from dataclasses import dataclass, KW_ONLY
@dataclass
class D:
x: int
_: KW_ONLY
y: str
@dataclass
class E(D):
z: bytes
# This should work: x=1 (positional), z=b"foo" (positional), y="foo" (keyword-only)
E(1, b"foo", y="foo")
reveal_type(E.__init__) # revealed: (self: E, x: int, z: bytes, *, y: str) -> None
```
<!-- What's the purpose of the change? What does it do, and why? -->
## Test Plan
<!-- How was it tested? -->
mdtests
## Summary
Fixes https://github.com/astral-sh/ty/issues/1046
We special-case iteration of certain types because they may have a more
detailed tuple-spec. Now that type aliases are a distinct type variant,
we need to handle them as well.
I don't love that `Type::TypeAlias` means we have to remember to add a
case for it basically anywhere we are special-casing a certain kind of
type, but at the moment I don't have a better plan. It's another
argument for avoiding fallback cases in `Type` matches, which we usually
prefer; I've updated this match statement to be comprehensive.
## Test Plan
Added mdtest.
`Type::TypeVar` now distinguishes whether the typevar in question is
inferable or not.
A typevar is _not inferable_ inside the body of the generic class or
function that binds it:
```py
def f[T](t: T) -> T:
return t
```
The infered type of `t` in the function body is `TypeVar(T,
NotInferable)`. This represents how e.g. assignability checks need to be
valid for all possible specializations of the typevar. Most of the
existing assignability/etc logic only applies to non-inferable typevars.
Outside of the function body, the typevar is _inferable_:
```py
f(4)
```
Here, the parameter type of `f` is `TypeVar(T, Inferable)`. This
represents how e.g. assignability doesn't need to hold for _all_
specializations; instead, we need to find the constraints under which
this specific assignability check holds.
This is in support of starting to perform specialization inference _as
part of_ performing the assignability check at the call site.
In the [[POPL2015][]] paper, this concept is called _monomorphic_ /
_polymorphic_, but I thought _non-inferable_ / _inferable_ would be
clearer for us.
Depends on #19784
[POPL2015]: https://doi.org/10.1145/2676726.2676991
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR adds a new lint, `invalid-await`, for all sorts of reasons why
an object may not be `await`able, as discussed in astral-sh/ty#919.
Precisely, `__await__` is guarded against being missing, possibly
unbound, or improperly defined (expects additional arguments or doesn't
return an iterator).
Of course, diagnostics need to be fine-tuned. If `__await__` cannot be
called with no extra arguments, it indicates an error (or a quirk?) in
the method signature, not at the call site. Without any doubt, such an
object is not `Awaitable`, but I feel like talking about arguments for
an *implicit* call is a bit leaky.
I didn't reference any actual diagnostic messages in the lint
definition, because I want to hear feedback first.
Also, there's no mention of the actual required method signature for
`__await__` anywhere in the docs. The only reference I had is the
`typing` stub. I basically ended up linking `[Awaitable]` to ["must
implement
`__await__`"](https://docs.python.org/3/library/collections.abc.html#collections.abc.Awaitable),
which is insufficient on its own.
## Test Plan
The following code was tested:
```python
import asyncio
import typing
class Awaitable:
def __await__(self) -> typing.Generator[typing.Any, None, int]:
yield None
return 5
class NoDunderMethod:
pass
class InvalidAwaitArgs:
def __await__(self, value: int) -> int:
return value
class InvalidAwaitReturn:
def __await__(self) -> int:
return 5
class InvalidAwaitReturnImplicit:
def __await__(self):
pass
async def main() -> None:
result = await Awaitable() # valid
result = await NoDunderMethod() # `__await__` is missing
result = await InvalidAwaitReturn() # `__await__` returns `int`, which is not a valid iterator
result = await InvalidAwaitArgs() # `__await__` expects additional arguments and cannot be called implicitly
result = await InvalidAwaitReturnImplicit() # `__await__` returns `Unknown`, which is not a valid iterator
asyncio.run(main())
```
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
For PEP 695 generic functions and classes, there is an extra "type
params scope" (a child of the outer scope, and wrapping the body scope)
in which the type parameters are defined; class bases and function
parameter/return annotations are resolved in that type-params scope.
This PR fixes some longstanding bugs in how we resolve name loads from
inside these PEP 695 type parameter scopes, and also defers type
inference of PEP 695 typevar bounds/constraints/default, so we can
handle cycles without panicking.
We were previously treating these type-param scopes as lazy nested
scopes, which is wrong. In fact they are eager nested scopes; the class
`C` here inherits `int`, not `str`, and previously we got that wrong:
```py
Base = int
class C[T](Base): ...
Base = str
```
But certain syntactic positions within type param scopes (typevar
bounds/constraints/defaults) are lazy at runtime, and we should use
deferred name resolution for them. This also means they can have cycles;
in order to handle that without panicking in type inference, we need to
actually defer their type inference until after we have constructed the
`TypeVarInstance`.
PEP 695 does specify that typevar bounds and constraints cannot be
generic, and that typevar defaults can only reference prior typevars,
not later ones. This reduces the scope of (valid from the type-system
perspective) cycles somewhat, although cycles are still possible (e.g.
`class C[T: list[C]]`). And this is a type-system-only restriction; from
the runtime perspective an "invalid" case like `class C[T: T]` actually
works fine.
I debated whether to implement the PEP 695 restrictions as a way to
avoid some cycles up-front, but I ended up deciding against that; I'd
rather model the runtime name-resolution semantics accurately, and
implement the PEP 695 restrictions as a separate diagnostic on top.
(This PR doesn't yet implement those diagnostics, thus some `# TODO:
error` in the added tests.)
Introducing the possibility of cyclic typevars made typevar display
potentially stack overflow. For now I've handled this by simply removing
typevar details (bounds/constraints/default) from typevar display. This
impacts display of two kinds of types. If you `reveal_type(T)` on an
unbound `T` you now get just `typing.TypeVar` instead of
`typing.TypeVar("T", ...)` where `...` is the bound/constraints/default.
This matches pyright and mypy; pyrefly uses `type[TypeVar[T]]` which
seems a bit confusing, but does include the name. (We could easily
include the name without cycle issues, if there's a syntax we like for
that.)
It also means that displaying a generic function type like `def f[T:
int](x: T) -> T: ...` now displays as `f[T](x: T) -> T` instead of `f[T:
int](x: T) -> T`. This matches pyright and pyrefly; mypy does include
bound/constraints/defaults of typevars in function/callable type
display. If we wanted to add this, we would either need to thread a
visitor through all the type display code, or add a `decycle` type
transformation that replaced recursive reoccurrence of a type with a
marker.
## Test Plan
Added mdtests and modified existing tests to improve their correctness.
After this PR, there's only a single remaining py-fuzzer seed in the
0-500 range that panics! (Before this PR, there were 10; the fuzzer
likes to generate cyclic PEP 695 syntax.)
## Ecosystem report
It's all just the changes to `TypeVar` display.
## Summary
A [passing
comment](https://github.com/astral-sh/ruff/pull/19711#issuecomment-3169312014)
led me to explore why we didn't report a class attribute as possibly
unbound if it was a method and defined in two different conditional
branches.
I found that the reason was because of our handling of "conflicting
declarations" in `place_from_declarations`. It returned a `Result` which
would be `Err` in case of conflicting declarations.
But we only actually care about conflicting declarations when we are
actually doing type inference on that scope and might emit a diagnostic
about it. And in all cases (including that one), we want to otherwise
proceed with the union of the declared types, as if there was no
conflict.
In several cases we were failing to handle the union of declared types
in the same way as a normal declared type if there was a declared-types
conflict. The `Result` return type made this mistake really easy to
make, as we'd match on e.g. `Ok(Place::Type(...))` and do one thing,
then match on `Err(...)` and do another, even though really both of
those cases should be handled the same.
This PR refactors `place_from_declarations` to instead return a struct
which always represents the declared type we should use in the same way,
as well as carrying the conflicting declared types, if any. This struct
has a method to allow us to explicitly ignore the declared-types
conflict (which is what we want in most cases), as well as a method to
get the declared type and the conflict information, in the case where we
want to emit a diagnostic on the conflict.
## Test Plan
Existing CI; added a test showing that we now understand a
multiply-conditionally-defined method as possibly-unbound.
This does trigger issues on a couple new fuzzer seeds, but the issues
are just new instances of an already-known (and rarely occurring)
problem which I already plan to address in a future PR, so I think it's
OK to land as-is.
I happened to build this initially on top of
https://github.com/astral-sh/ruff/pull/19711, which adds invalid-await
diagnostics, so I also updated some invalid-syntax tests to not await on
an invalid type, since the purpose of those tests is to check the
syntactic location of the `await`, not the validity of the awaited type.
## Summary
Support recursive type aliases by adding a `Type::TypeAlias` type
variant, which allows referring to a type alias directly as a type
without eagerly unpacking it to its value.
We still unpack type aliases when they are added to intersections and
unions, so that we can simplify the intersection/union appropriately
based on the unpacked value of the type alias.
This introduces new possible recursive types, and so also requires
expanding our usage of recursion-detecting visitors in Type methods. The
use of these visitors is still not fully comprehensive in this PR, and
will require further expansion to support recursion in more kinds of
types (I already have further work on this locally), but I think it may
be better to do this incrementally in multiple PRs.
## Test Plan
Added some recursive type-alias tests and made them pass.
fix https://github.com/astral-sh/ty/issues/943
## Summary
Add module-level `__getattr__` support for ty's type checker, fixing
issue https://github.com/astral-sh/ty/issues/943.
Module-level `__getattr__` functions ([PEP
562](https://peps.python.org/pep-0562/)) are now respected when
resolving dynamic attributes, matching the behavior of mypy and pyright.
## Implementation
Thanks @sharkdp for the guidance in
https://github.com/astral-sh/ty/issues/943#issuecomment-3157566579
- Adds module-specific `__getattr__` resolution in
`ModuleLiteral.static_member()`
- Maintains proper attribute precedence: explicit attributes >
submodules > `__getattr__`
## Test Plan
- New mdtest covering basic functionality, type annotations, attribute
precedence, and edge cases
(run ```cargo nextest run -p ty_python_semantic
mdtest__import_module_getattr```)
- All new tests pass, verifying `__getattr__` is called correctly and
returns proper types
- Existing test suite passes, ensuring no regressions introduced
## 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
Validates writes to `TypedDict` keys, for example:
```py
class Person(TypedDict):
name: str
age: int | None
def f(person: Person):
person["naem"] = "Alice" # error: [invalid-key]
person["age"] = "42" # error: [invalid-assignment]
```
The new specialized `invalid-assignment` diagnostic looks like this:
<img width="1160" height="279" alt="image"
src="https://github.com/user-attachments/assets/51259455-3501-4829-a84e-df26ff90bd89"
/>
## Ecosystem analysis
As far as I can tell, all true positives!
There are some extremely long diagnostic messages. We should truncate
our display of overload sets somehow.
## Test Plan
New Markdown tests
This fixes our logic for binding a legacy typevar with its binding
context. (To recap, a legacy typevar starts out "unbound" when it is
first created, and each time it's used in a generic class or function,
we "bind" it with the corresponding `Definition`.)
We treat `typing.Self` the same as a legacy typevar, and so we apply
this binding logic to it too. Before, we were using the enclosing class
as its binding context. But that's not correct — it's the method where
`typing.Self` is used that binds the typevar. (Each invocation of the
method will find a new specialization of `Self` based on the specific
instance type containing the invoked method.)
This required plumbing through some additional state to the
`in_type_expression` method.
This also revealed that we weren't handling `Self`-typed instance
attributes correctly (but were coincidentally not getting the expected
false positive diagnostics).
## Summary
Disallow `typing.TypedDict` in type expressions.
Related reference: https://github.com/python/mypy/issues/11030
## Test Plan
New Markdown tests, checked ecosystem and conformance test impact.
## 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 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.
David Peter
Carl Meyer
Alex Waygood
Eric Jolibois
Dhruv Manilawala
Shaygan Hooshyari
Jelle Zijlstra
Leandro Braga
Renkai Ge
Dylan
github-actions[bot]
Douglas Creager
Aria Desires
Eric Mark Martin
Matthew Mckee
Shunsuke Shibayama
Andrii Turov
justin
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Jack O'Connor
Simon Lamon