## 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
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## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
This PR implements semantic syntax error where alternative patterns bind
different names
## Test Plan
<!-- How was it tested? -->
I have written inline tests as directed in #17412
---------
Signed-off-by: 11happy <soni5happy@gmail.com>
Co-authored-by: Brent Westbrook <brentrwestbrook@gmail.com>
## Summary
Derived from #20900
Implement `VarianceInferable` for `KnownInstanceType` (especially for
`KnownInstanceType::TypeAliasType`).
The variance of a type alias matches its value type. In normal usage,
type aliases are expanded to value types, so the variance of a type
alias can be obtained without implementing this. However, for example,
if we want to display the variance when hovering over a type alias, we
need to be able to obtain the variance of the type alias itself (cf.
#20900).
## Test Plan
I couldn't come up with a way to test this in mdtest, so I'm testing it
in a test submodule at the end of `types.rs`.
I also added a test to `mdtest/generics/pep695/variance.md`, but it
passes without the changes in this PR.
## Summary
Support `dataclass_transform` when used on a (base) class.
## Typing conformance
* The changes in `dataclasses_transform_class.py` look good, just a few
mistakes due to missing `alias` support.
* I didn't look closely at the changes in
`dataclasses_transform_converter.py` since we don't support `converter`
yet.
## Ecosystem impact
The impact looks huge, but it's concentrated on a single project (ibis).
Their setup looks more or less like this:
* the real `Annotatable`:
d7083c2c96/ibis/common/grounds.py (L100-L101)
* the real `DataType`:
d7083c2c96/ibis/expr/datatypes/core.py (L161-L179)
* the real `Array`:
d7083c2c96/ibis/expr/datatypes/core.py (L1003-L1006)
```py
from typing import dataclass_transform
@dataclass_transform()
class Annotatable:
pass
class DataType(Annotatable):
nullable: bool = True
class Array[T](DataType):
value_type: T
```
They expect something like `Array([1, 2])` to work, but ty, pyright,
mypy, and pyrefly would all expect there to be a first argument for the
`nullable` field on `DataType`. I don't really understand on what
grounds they expect the `nullable` field to be excluded from the
signature, but this seems to be the main reason for the new diagnostics
here. Not sure if related, but it looks like their typing setup is not
really complete
(https://github.com/ibis-project/ibis/issues/6844#issuecomment-1868274770,
this thread also mentions `dataclass_transform`).
## Test Plan
Update pre-existing tests.
Detect legacy namespace packages and treat them like namespace packages
when looking them up as the *parent* of the module we're interested in.
In all other cases treat them like a regular package.
(This PR is coauthored by @MichaReiser in a shared coding session)
Fixes https://github.com/astral-sh/ty/issues/838
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
Prefer the declared type for collection literals, e.g.,
```py
x: list[Any] = [1, "2", (3,)]
reveal_type(x) # list[Any]
```
This solves a large part of https://github.com/astral-sh/ty/issues/136
for invariant generics, where respecting the declared type is a lot more
important. It also means that annotated dict literals with `dict[_,
Any]` is a way out of https://github.com/astral-sh/ty/issues/1248.
## 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
Ignore the type context when specializing a generic call if it leads to
an unnecessarily wide return type. For example, [the example mentioned
here](https://github.com/astral-sh/ruff/pull/20796#issuecomment-3403319536)
works as expected after this change:
```py
def id[T](x: T) -> T:
return x
def _(i: int):
x: int | None = id(i)
y: int | None = i
reveal_type(x) # revealed: int
reveal_type(y) # revealed: int
```
I also added extended our usage of `filter_disjoint_elements` to tuple
and typed-dict inference, which resolves
https://github.com/astral-sh/ty/issues/1266.
## Summary
Add support for the `field_specifiers` parameter on
`dataclass_transform` decorator calls.
closes https://github.com/astral-sh/ty/issues/1068
## Conformance test results
All true positives ✔️
## Ecosystem analysis
* `trio`: this is the kind of change that I would expect from this PR.
The code makes use of a dataclass `Outcome` with a `_unwrapped: bool =
attr.ib(default=False, eq=False, init=False)` field that is excluded
from the `__init__` signature, so we now see a bunch of
constructor-call-related errors going away.
* `home-assistant/core`: They have a `domain: str = attr.ib(init=False,
repr=False)` field and then use
```py
@domain.default
def _domain_default(self) -> str:
# …
```
This accesses the `default` attribute on `dataclasses.Field[…]` with a
type of `default: _T | Literal[_MISSING_TYPE.MISSING]`, so we get those
"Object of type `_MISSING_TYPE` is not callable" errors. I don't really
understand how that is supposed to work. Even if `_MISSING_TYPE` would
be absent from that union, what does this try to call? pyright also
issues an error and it doesn't seem to work at runtime? So this looks
like a true positive?
* `attrs`: Similar here. There are some new diagnostics on code that
tries to access `.validator` on a field. This *does* work at runtime,
but I'm not sure how that is supposed to type-check (without a [custom
plugin](2c6c395935/mypy/plugins/attrs.py (L575-L602))).
pyright errors on this as well.
* A handful of new false positives because we don't support `alias` yet
## Test Plan
Updated tests.
Summary
--
This PR unifies the two different ways Ruff and ty construct syntax
errors. Ruff has been storing the primary message in the diagnostic
itself, while ty attached the message to the primary annotation:
```
> ruff check try.py
invalid-syntax: name capture `x` makes remaining patterns unreachable
--> try.py:2:10
|
1 | match 42:
2 | case x: ...
| ^
3 | case y: ...
|
Found 1 error.
> uvx ty check try.py
WARN ty is pre-release software and not ready for production use. Expect to encounter bugs, missing features, and fatal errors.
Checking ------------------------------------------------------------ 1/1 files
error[invalid-syntax]
--> try.py:2:10
|
1 | match 42:
2 | case x: ...
| ^ name capture `x` makes remaining patterns unreachable
3 | case y: ...
|
Found 1 diagnostic
```
I think there are benefits to both approaches, and I do like ty's
version, but I feel like we should pick one (and it might help with
#20901 eventually). I slightly prefer Ruff's version, so I went with
that. Hopefully this isn't too controversial, but I'm happy to close
this if it is.
Note that this shouldn't change any other diagnostic formats in ty
because
[`Diagnostic::primary_message`](98d27c4128/crates/ruff_db/src/diagnostic/mod.rs (L177))
was already falling back to the primary annotation message if the
diagnostic message was empty. As a result, I think this change will
partially resolve the FIXME therein.
Test Plan
--
Existing tests with updated snapshots
This is the ultra-minimal implementation of
* https://github.com/astral-sh/ty/issues/296
that was previously discussed as a good starting point. In particular we
don't actually bother trying to figure out the exact python versions,
but we still mention "hey btw for No Reason At All... you're on python
3.10" when you try to access something that has a definition rooted in
the stdlib that we believe exists sometimes.
This is a drive-by improvement that I stumbled backwards into while
looking into
* https://github.com/astral-sh/ty/issues/296
I was writing some simple tests for "thing not in old version of stdlib"
diagnostics and checked what was added in 3.14, and saw
`compression.zstd` and to my surprise discovered that `import
compression.zstd` and `from compression import zstd` had completely
different quality diagnostics.
This is because `compression` and `compression.zstd` were *both*
introduced in 3.14, and so per VERSIONS policy only an entry for
`compression` was added, and so we don't actually have any definite info
on `compression.zstd` and give up on producing a diagnostic. However the
`from compression import zstd` form fails on looking up `compression`
and we *do* have an exact match for that, so it gets a better
diagnostic!
(aside: I have now learned about the VERSIONS format and I *really* wish
they would just enumerate all the submodules but, oh well!)
The fix is, when handling an import failure, if we fail to find an exact
match *we requery with the parent module*. In cases like
`compression.zstd` this lets us at least identify that, hey, not even
`compression` exists, and luckily that fixes the whole issue. In cases
where the parent module and submodule were introduced at different times
then we may discover that the parent module is in-range and that's fine,
we don't produce the richer stdlib diagnostic.
## Summary
`dataclasses.field` and field-specifier functions of commonly used
libraries like `pydantic`, `attrs`, and `SQLAlchemy` all return the
default type for the field (or `Any`) instead of an actual `Field`
instance, even if this is not what happens at runtime. Let's make use of
this fact and assume that *all* field specifiers return the type of the
default value of the field.
For standard dataclasses, this leads to more or less the same outcome
(see test diff for details), but this change is important for 3rd party
dataclass-transformers.
## Test Plan
Tested the consequences of this change on the field-specifiers branch as
well.
## 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
If a function is decorated with a decorator that returns a union of
`Callable`s, also treat it as a union of function-like `Callable`s.
Labeling as `internal`, since the previous change has not been released
yet.
## Test Plan
New regression test.
Generic classes are not allowed to bind or reference a typevar from an
enclosing scope:
```py
def f[T](x: T, y: T) -> None:
class Ok[S]: ...
# error: [invalid-generic-class]
class Bad1[T]: ...
# error: [invalid-generic-class]
class Bad2(Iterable[T]): ...
class C[T]:
class Ok1[S]: ...
# error: [invalid-generic-class]
class Bad1[T]: ...
# error: [invalid-generic-class]
class Bad2(Iterable[T]): ...
```
It does not matter if the class uses PEP 695 or legacy syntax. It does
not matter if the enclosing scope is a generic class or function. The
generic class cannot even _reference_ an enclosing typevar in its base
class list.
This PR adds diagnostics for these cases.
In addition, the PR adds better fallback behavior for generic classes
that violate this rule: any enclosing typevars are not included in the
class's generic context. (That ensures that we don't inadvertently try
to infer specializations for those typevars in places where we
shouldn't.) The `dulwich` ecosystem project has [examples of
this](d912eaaffd/dulwich/config.py (L251))
that were causing new false positives on #20677.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Treat `Callable`s as bound-method descriptors if `Callable` is the
return type of a decorator that is applied to a function definition. See
the [rendered version of the new test
file](https://github.com/astral-sh/ruff/blob/david/callables-as-descriptors/crates/ty_python_semantic/resources/mdtest/call/callables_as_descriptors.md)
for the full description of this new heuristic.
I could imagine that we want to treat `Callable`s as bound-method
descriptors in other cases as well, but this seems like a step in the
right direction. I am planning to add other "use cases" from
https://github.com/astral-sh/ty/issues/491 to this test suite.
partially addresses https://github.com/astral-sh/ty/issues/491
closes https://github.com/astral-sh/ty/issues/1333
## Ecosystem impact
All positive
* 2961 removed `unsupported-operator` diagnostics on `sympy`, which was
one of the main motivations for implementing this change
* 37 removed `missing-argument` diagnostics, and no added call-error
diagnostics, which is an indicator that this heuristic shouldn't cause
many false positives
* A few removed `possibly-missing-attribute` diagnostics when accessing
attributes like `__name__` on decorated functions. The two added
`unused-ignore-comment` diagnostics are also cases of this.
* One new `invalid-assignment` diagnostic on `dd-trace-py`, which looks
suspicious, but only because our `invalid-assignment` diagnostics are
not great. This is actually a "Implicit shadowing of function"
diagnostic that hides behind the `invalid-assignment` diagnostic,
because a module-global function is being patched through a
`module.func` attribute assignment.
## Test Plan
New Markdown tests.
## Summary
When accessing an (instance) attribute on a given class, we were
previously traversing its MRO, and building a union of types (if the
attribute was available on multiple classes in the MRO) until we found a
*definitely bound* symbol. The idea was that possibly unbound symbols in
a subclass might only partially shadow the underlying base class
attribute.
This behavior was problematic for two reasons:
* if the attribute was definitely bound on a class (e.g. `self.x =
None`), we would have stopped iterating, even if there might be a `x:
str | None` declaration in a base class (the bug reported in
https://github.com/astral-sh/ty/issues/1067).
* if the attribute originated from an implicit instance attribute
assignment (e.g. `self.x = 1` in method `Sub.foo`), we might stop
looking and miss another implicit instance attribute assignment in a
base class method (e.g. `self.x = 2` in method `Base.bar`).
With this fix, we still iterate the MRO of the class, but we only stop
iterating if we find a *definitely declared* symbol. In this case, we
only return the declared attribute type. Otherwise, we keep building a
union of inferred attribute types.
The implementation here seemed to be the easiest fix for
https://github.com/astral-sh/ty/issues/1067 that also kept the ecosystem
impact low (the changes that I see all look correct). However, as the
Markdown tests show, there are other things to fix in this area. For
example, we should do a similar thing for *class attributes*. This is
more involved, though (affects many different areas and probably
involves a change to our descriptor protocol implementation), so I'd
like to postpone this to a follow-up.
closes https://github.com/astral-sh/ty/issues/1067
## Test Plan
Updated Markdown tests, including a regression test for
https://github.com/astral-sh/ty/issues/1067.
## Summary
Implements bidirectional type inference using function return type
annotations.
This PR was originally proposed to solve astral-sh/ty#1167, but this
does not fully resolve it on its own.
Additionally, I believe we need to allow dataclasses to generate their
own `__new__` methods, [use constructor return types for
inference](5844c0103d/crates/ty_python_semantic/src/types.rs (L5326-L5328)),
and a mechanism to discard type narrowing like `& ~AlwaysFalsy` if
necessary (at a more general level than this PR).
## Test Plan
`mdtest/bidirectional.md` is added.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Ibraheem Ahmed <ibraheem@ibraheem.ca>
## Summary
Adds a set of basic new tests corresponding to open points in
https://github.com/astral-sh/ty/issues/1327, to document the state of
support for `dataclass_transform`.
## Summary
Type annotations are deferred by default starting with Python 3.14. No
`from __future__ import annotations` import is necessary.
## Test Plan
New Markdown test
## Summary
Simplify and fix the implementation of
`ty_extensions.CallableTypeOf[..]`.
closes https://github.com/astral-sh/ty/issues/1331
## Test Plan
Added regression test.
## Summary
This allows us to handle self-referential bounds/constraints/defaults
without panicking.
Handles more cases from https://github.com/astral-sh/ty/issues/256
This also changes the way we infer the types of legacy TypeVars. Rather
than understanding a constructor call to `typing[_extension].TypeVar`
inside of any (arbitrarily nested) expression, and having to use a
special `assigned_to` field of the semantic index to try to best-effort
figure out what name the typevar was assigned to, we instead understand
the creation of a legacy `TypeVar` only in the supported syntactic
position (RHS of a simple un-annotated assignment with one target). In
any other position, we just infer it as creating an opaque instance of
`typing.TypeVar`. (This behavior matches all other type checkers.)
So we now special-case TypeVar creation in `TypeInferenceBuilder`, as a
special case of an assignment definition, rather than deeper inside call
binding. This does mean we re-implement slightly more of
argument-parsing, but in practice this is minimal and easy to handle
correctly.
This is easier to implement if we also make the RHS of a simple (no
unpacking) one-target assignment statement no longer a standalone
expression. Which is fine to do, because simple one-target assignments
don't need to infer the RHS more than once. This is a bonus performance
(0-3% across various projects) and significant memory-usage win, since
most assignment statements are simple one-target assignment statements,
meaning we now create many fewer standalone-expression salsa
ingredients.
This change does mean that inference of manually-constructed
`TypeAliasType` instances can no longer find its Definition in
`assigned_to`, which regresses go-to-definition for these aliases. In a
future PR, `TypeAliasType` will receive the same treatment that
`TypeVar` did in this PR (moving its special-case inference into
`TypeInferenceBuilder` and supporting it only in the correct syntactic
position, and lazily inferring its value type to support recursion),
which will also fix the go-to-definition regression. (I decided a
temporary edge-case regression is better in this case than doubling the
size of this PR.)
This PR also tightens up and fixes various aspects of the validation of
`TypeVar` creation, as seen in the tests.
We still (for now) treat all typevars as instances of `typing.TypeVar`,
even if they were created using `typing_extensions.TypeVar`. This means
we'll wrongly error on e.g. `T.__default__` on Python 3.11, even if `T`
is a `typing_extensions.TypeVar` instance at runtime. We share this
wrong behavior with both mypy and pyrefly. It will be easier to fix
after we pull in https://github.com/python/typeshed/pull/14840.
There are some issues that showed up here with typevar identity and
`MarkTypeVarsInferable`; the fix here (using the new `original` field
and `is_identical_to` methods on `BoundTypeVarInstance` and
`TypeVarInstance`) is a bit kludgy, but it can go away when we eliminate
`MarkTypeVarsInferable`.
## Test Plan
Added and updated mdtests.
### Conformance suite impact
The impact here is all positive:
* We now correctly error on a legacy TypeVar with exactly one constraint
type given.
* We now correctly error on a legacy TypeVar with both an upper bound
and constraints specified.
### Ecosystem impact
Basically none; in the setuptools case we just issue slightly different
errors on an invalid TypeVar definition, due to the modified validation
code.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Avoid literal promotion when a literal type annotation is provided, e.g.,
```py
x: list[Literal[1]] = [1]
```
Resolves https://github.com/astral-sh/ty/issues/1198. This does not fix
issue https://github.com/astral-sh/ty/issues/1284, but it does make it
more relevant because after this change, it is possible to directly
instantiate a generic type with a literal specialization.
## Summary
Respect parameters such as `frozen_default` for metaclass-based
`@dataclass_transformer` models.
Related to: https://github.com/astral-sh/ty/issues/1260
## Typing conformance changes
Those are all correct (new true positives)
## Test Plan
New Markdown tests
## Summary
- Add support for eq, kw_only, and frozen parameter overrides in
@dataclass_transform
- Previously only order parameter override was supported
- Update test documentation to reflect fixed behavior
- Resolves issue where kw_only_default and frozen_default could not be
overridden
closes https://github.com/astral-sh/ty/issues/1260
## Test Plan
New Markdown tests
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
Even disambiguating classes using their fully qualified names is not
enough for some diagnostics. We've seen real-world examples in the
ecosystem (and https://github.com/astral-sh/ruff/pull/20368 introduces
some more!) where two types can be different, but can still have the
same fully qualified name. In these cases, our disambiguation machinery
needs to print the file path and line number of the class in order to
disambiguate classes with similar names in our diagnostics.
Helps with https://github.com/astral-sh/ty/issues/1306
## Test Plan
Mdtests
## Summary
This adds a couple of new test cases related to
https://github.com/astral-sh/ty/issues/1067 and beyond that. For now,
they are just documenting the current (problematic) behavior. Since the
topic has some subtleties, I'd like to merge this prior to the actual
bugfix(es) in order to evaluate the changes in an easier way.
