That PR title might be a bit inscrutable.
Consider the two constraints `T ≤ bool` and `T ≤ int`. Since `bool ≤
int`, by transitivity `T ≤ bool` implies `T ≤ int`. (Every type that is
a subtype of `bool` is necessarily also a subtype of `int`.) That means
that `T ≤ bool ∧ T ≰ int` is an impossible combination of constraints,
and is therefore not a valid input to any BDD. We say that that
assignment is not in the _domain_ of the BDD.
The implication `T ≤ bool → T ≤ int` can be rewritten as `T ≰ bool ∨ T ≤
int`. (That's the definition of implication.) If we construct that
constraint set in an mdtest, we should get a constraint set that is
always satisfiable. Previously, that constraint set would correctly
_display_ as `always`, but a `static_assert` on it would fail.
The underlying cause is that our `is_always_satisfied` method would only
test if the BDD was the `AlwaysTrue` terminal node. `T ≰ bool ∨ T ≤ int`
does not simplify that far, because we purposefully keep around those
constraints in the BDD structure so that it's easier to compare against
other BDDs that reference those constraints.
To fix this, we need a more nuanced definition of "always satisfied".
Instead of evaluating to `true` for _every_ input, we only need it to
evaluate to `true` for every _valid_ input — that is, every input in its
domain.
## Summary
Infer a type of `Self` for unannotated `self` parameters in methods of
classes.
part of https://github.com/astral-sh/ty/issues/159
closes https://github.com/astral-sh/ty/issues/1081
## Conformance tests changes
```diff
+enums_member_values.py:85:9: error[invalid-assignment] Object of type `int` is not assignable to attribute `_value_` of type `str`
```
A true positive ✔️
```diff
-generics_self_advanced.py:35:9: error[type-assertion-failure] Argument does not have asserted type `Self@method2`
-generics_self_basic.py:14:9: error[type-assertion-failure] Argument does not have asserted type `Self@set_scale
```
Two false positives going away ✔️
```diff
+generics_syntax_infer_variance.py:82:9: error[invalid-assignment] Cannot assign to final attribute `x` on type `Self@__init__`
```
This looks like a true positive to me, even if it's not marked with `#
E` ✔️
```diff
+protocols_explicit.py:56:9: error[invalid-assignment] Object of type `tuple[int, int, str]` is not assignable to attribute `rgb` of type `tuple[int, int, int]`
```
True positive ✔️
```
+protocols_explicit.py:85:9: error[invalid-attribute-access] Cannot assign to ClassVar `cm1` from an instance of type `Self@__init__`
```
This looks like a true positive to me, even if it's not marked with `#
E`. But this is consistent with our understanding of `ClassVar`, I
think. ✔️
```py
+qualifiers_final_annotation.py:52:9: error[invalid-assignment] Cannot assign to final attribute `ID4` on type `Self@__init__`
+qualifiers_final_annotation.py:65:9: error[invalid-assignment] Cannot assign to final attribute `ID7` on type `Self@method1`
```
New true positives ✔️
```py
+qualifiers_final_annotation.py:52:9: error[invalid-assignment] Cannot assign to final attribute `ID4` on type `Self@__init__`
+qualifiers_final_annotation.py:57:13: error[invalid-assignment] Cannot assign to final attribute `ID6` on type `Self@__init__`
+qualifiers_final_annotation.py:59:13: error[invalid-assignment] Cannot assign to final attribute `ID6` on type `Self@__init__`
```
This is a new false positive, but that's a pre-existing issue on main
(if you annotate with `Self`):
https://play.ty.dev/3ee1c56d-7e13-43bb-811a-7a81e236e6ab❌ => reported
as https://github.com/astral-sh/ty/issues/1409
## Ecosystem
* There are 5931 new `unresolved-attribute` and 3292 new
`possibly-missing-attribute` attribute errors, way too many to look at
all of them. I randomly sampled 15 of these errors and found:
* 13 instances where there was simply no such attribute that we could
plausibly see. Sometimes [I didn't find it
anywhere](8644d886c6/openlibrary/plugins/openlibrary/tests/test_listapi.py (L33)).
Sometimes it was set externally on the object. Sometimes there was some
[`setattr` dynamicness going
on](a49f6b927d/setuptools/wheel.py (L88-L94)).
I would consider all of them to be true positives.
* 1 instance where [attribute was set on `obj` in
`__new__`](9e87b44fd4/sympy/tensor/array/array_comprehension.py (L45C1-L45C36)),
which we don't support yet
* 1 instance [where the attribute was defined via `__slots__`
](e250ec0fc8/lib/spack/spack/vendor/pyrsistent/_pdeque.py (L48C5-L48C14))
* I see 44 instances [of the false positive
above](https://github.com/astral-sh/ty/issues/1409) with `Final`
instance attributes being set in `__init__`. I don't think this should
block this PR.
## Test Plan
New Markdown tests.
---------
Co-authored-by: Shaygan Hooshyari <sh.hooshyari@gmail.com>
This PR adds another useful simplification when rendering constraint
sets: `T = int` instead of `T = int ∧ T ≠ str`. (The "smaller"
constraint `T = int` implies the "larger" constraint `T ≠ str`.
Constraint set clauses are intersections, and if one constraint in a
clause implies another, we can throw away the "larger" constraint.)
While we're here, we also normalize the bounds of a constraint, so that
we equate e.g. `T ≤ int | str` with `T ≤ str | int`, and change the
ordering of BDD variables so that all constraints with the same typevar
are ordered adjacent to each other.
Lastly, we also add a new `display_graph` helper method that prints out
the full graph structure of a BDD.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Fall back to `C[Divergent]` if we are trying to specialize `C[T]` with a
type that itself already contains deeply nested specialized generic
classes. This is a way to prevent infinite recursion for cases like
`self.x = [self.x]` where type inference for the implicit instance
attribute would not converge.
closes https://github.com/astral-sh/ty/issues/1383
closes https://github.com/astral-sh/ty/issues/837
## Test Plan
Regression tests.
## Summary
We currently panic in the seemingly rare case where the type of a
default value of a parameter depends on the callable itself:
```py
class C:
def f(self: C):
self.x = lambda a=self.x: a
```
Types of default values are only used for display reasons, and it's
unclear if we even want to track them (or if we should rather track the
actual value). So it didn't seem to me that we should spend a lot of
effort (and runtime) trying to achieve a theoretically correct type here
(which would be infinite).
Instead, we simply replace *nested* default types with `Unknown`, i.e.
only if the type of the default value is a callable itself.
closes https://github.com/astral-sh/ty/issues/1402
## Test Plan
Regression tests
## Summary
Only run the "pull types" test after performing the "actual" mdtest. We
observed that the order matters. There is currently one mdtest which
panics when checked in the CLI or the playground. With this change, it
also panics in the mdtest suite.
reopens https://github.com/astral-sh/ty/issues/837?
## 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.
