## Summary
Discussion with @ibraheemdev clarified that
https://github.com/astral-sh/ruff/pull/21168 was incorrect. In a case of
failed inference of a dict literal as a `TypedDict`, we should store the
context-less inferred type of the dict literal as the type of the dict
literal expression itself; the fallback to declared type should happen
at the level of the overall assignment definition.
The reason the latter isn't working yet is because currently we
(wrongly) consider a homogeneous dict type as assignable to a
`TypedDict`, so we don't actually consider the assignment itself as
failed. So the "bug" I observed (and tried to fix) will naturally be
fixed by implementing TypedDict assignability rules.
Rollback https://github.com/astral-sh/ruff/pull/21168 except for the
tests, and modify the tests to include TODOs as needed.
## Test Plan
Updated mdtests.
The parser currently uses single quotes to wrap tokens. This is
inconsistent with the rest of ruff/ty, which use backticks.
For example, see the inconsistent diagnostics produced in this simple
example: https://play.ty.dev/0a9d6eab-6599-4a1d-8e40-032091f7f50f
Consistently wrapping tokens in backticks produces uniform diagnostics.
Following the style decision of #723, in #2889 some quotes were already
switched into backticks.
This is also in line with Rust's guide on diagnostics
(https://rustc-dev-guide.rust-lang.org/diagnostics.html#diagnostic-structure):
> When code or an identifier must appear in a message or label, it
should be surrounded with backticks
## Summary
In general, when we have an invalid assignment (inferred assigned type
is not assignable to declared type), we fall back to inferring the
declared type, since the declared type is a more explicit declaration of
the programmer's intent. This also maintains the invariant that our
inferred type for a name is always assignable to the declared type for
that same name. For example:
```py
x: str = 1
reveal_type(x) # revealed: str
```
We weren't following this pattern for dictionary literals inferred (via
type context) as a typed dictionary; if the literal was not valid for
the annotated TypedDict type, we would just fall back to the normal
inferred type of the dict literal, effectively ignoring the annotation,
and resulting in inferred type not assignable to declared type.
## Test Plan
Added mdtest assertions.
## Summary
The solver is currently order-dependent, and will choose a supertype
over the exact type if it appears earlier in the list of constraints. We
could be smarter and try to choose the most precise subtype, but I
imagine this is something the new constraint solver will fix anyways,
and this fixes the issue showing up on
https://github.com/astral-sh/ruff/pull/21070.
This PR adds a new `satisfied_by_all_typevar` method, which implements
one of the final steps of actually using these dang constraint sets.
Constraint sets exist to help us check assignability and subtyping of
types in the presence of typevars. We construct a constraint set
describing the conditions under which assignability holds between the
two types. Then we check whether that constraint set is satisfied for
the valid specializations of the relevant typevars (which is this new
method).
We also add a new `ty_extensions.ConstraintSet` method so that we can
test this method's behavior in mdtests, before hooking it up to the rest
of the specialization inference machinery.
## Summary
We currently perform a subtyping check instead of the intended subclass
check (and the subtyping check is confusingly named `is_subclass_of`).
This showed up in https://github.com/astral-sh/ruff/pull/21070.
## Summary
Before this PR, we would emit diagnostics like "Invalid key access" for
a TypedDict literal with invalid key, which doesn't make sense since
there's no "access" in that case. This PR just adjusts the wording to be
more general, and adjusts the documentation of the lint rule too.
I noticed this in the playground and thought it would be a quick fix. As
usual, it turned out to be a bit more subtle than I expected, but for
now I chose to punt on the complexity. We may ultimately want to have
different rules for invalid subscript vs invalid TypedDict literal,
because an invalid key in a TypedDict literal is low severity: it's a
typo detector, but not actually a type error. But then there's another
wrinkle there: if the TypedDict is `closed=True`, then it _is_ a type
error. So would we want to separate the open and closed cases into
separate rules, too? I decided to leave this as a question for future.
If we wanted to use separate rules, or use specific wording for each
case instead of the generalized wording I chose here, that would also
involve a bit of extra work to distinguish the cases, since we use a
generic set of functions for reporting these errors.
## Test Plan
Added and updated mdtests.
This is a second take at the implicit imports approach, allowing `from .
import submodule` in an `__init__.pyi` to create the
`mypackage.submodule` attribute everyhere.
This implementation operates inside of the
available_submodule_attributes subsystem instead of as a re-export rule.
The upside of this is we are no longer purely syntactic, and absolute
from imports that happen to target submodules work (an intentional
discussed deviation from pyright which demands a relative from import).
Also we don't re-export functions or classes.
The downside(?) of this is star imports no longer see these attributes
(this may be either good or bad. I believe it's not a huge lift to make
it work with star imports but it's some non-trivial reworking).
I've also intentionally made `import mypackage.submodule` not trigger
this rule although it's trivial to change that.
I've tried to cover as many relevant cases as possible for discussion in
the new test file I've added (there are some random overlaps with
existing tests but trying to add them piecemeal felt confusing and
weird, so I just made a dedicated file for this extension to the rules).
Fixes https://github.com/astral-sh/ty/issues/133
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## Summary
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## Test Plan
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## Summary
Fixes https://github.com/astral-sh/ty/issues/1427
This PR fixes a regression introduced in alpha.24 where non-dataclass
children of generic dataclasses lost generic type parameter information
during `__init__` synthesis.
The issue occurred because when looking up inherited members in the MRO,
the child class's `inherited_generic_context` was correctly passed down,
but `own_synthesized_member()` (which synthesizes dataclass `__init__`
methods) didn't accept this parameter. It only used
`self.inherited_generic_context(db)`, which returned the parent's
context instead of the child's.
The fix threads the child's generic context through to the synthesis
logic, allowing proper generic type inference for inherited dataclass
constructors.
## Test Plan
- Added regression test for non-dataclass inheriting from generic
dataclass
- Verified the exact repro case from the issue now works
- All 277 mdtest tests passing
- Clippy clean
- Manually verified with Python runtime, mypy, and pyright - all accept
this code pattern
## Verification
Tested against multiple type checkers:
- ✅ Python runtime: Code works correctly
- ✅ mypy: No issues found
- ✅ pyright: 0 errors, 0 warnings
- ✅ ty alpha.23: Worked (before regression)
- ❌ ty alpha.24: Regression
- ✅ ty with this fix: Works correctly
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: David Peter <mail@david-peter.de>
It's possible for a constraint to mention two typevars. For instance, in
the body of
```py
def f[S: int, T: S](): ...
```
the baseline constraint set would be `(T ≤ S) ∧ (S ≤ int)`. That is, `S`
must specialize to some subtype of `int`, and `T` must specialize to a
subtype of the type that `S` specializes to.
This PR updates the new "constraint implication" relationship from
#21010 to work on these kinds of constraint sets. For instance, in the
example above, we should be able to see that `T ≤ int` must always hold:
```py
def f[S, T]():
constraints = ConstraintSet.range(Never, S, int) & ConstraintSet.range(Never, T, S)
static_assert(constraints.implies_subtype_of(T, int)) # now succeeds!
```
This did not require major changes to the implementation of
`implies_subtype_of`. That method already relies on how our `simplify`
and `domain` methods expand a constraint set to include the transitive
closure of the constraints that it mentions, and to mark certain
combinations of constraints as impossible. Previously, that transitive
closure logic only looked at pairs of constraints that constrain the
same typevar. (For instance, to notice that `(T ≤ bool) ∧ ¬(T ≤ int)` is
impossible.)
Now we also look at pairs of constraints that constraint different
typevars, if one of the constraints is bound by the other — that is,
pairs of the form `T ≤ S` and `S ≤ something`, or `S ≤ T` and `something
≤ S`. In those cases, transitivity lets us add a new derived constraint
that `T ≤ something` or `something ≤ T`, respectively. Having done that,
our existing `implies_subtype_of` logic finds and takes into account
that derived constraint.
## Summary
We weren't correctly modeling it as a `staticmethod` in all cases,
leading us to incorrectly infer that the `cls` argument would be bound
if it was accessed on an instance (rather than the class object).
## Test Plan
Added mdtests that fail on `main`. The primer output also looks good!
## Summary
Adds proper type narrowing and reachability analysis for matching on
non-inferable type variables bound to enums. For example:
```py
from enum import Enum
class Answer(Enum):
NO = 0
YES = 1
def is_yes(self) -> bool: # no error here!
match self:
case Answer.YES:
return True
case Answer.NO:
return False
```
closes https://github.com/astral-sh/ty/issues/1404
## Test Plan
Added regression tests
## Summary
We previously didn't understand `range` and wrote these custom
`IntIterable`/`IntIterator` classes for tests. We can now remove them
and make the tests shorter in some places.
## Summary
Infer a type of unannotated `self` parameters in decorated methods /
properties.
closes https://github.com/astral-sh/ty/issues/1448
## Test Plan
Existing tests, some new tests.
This PR updates the mdtests that test how our generics solver interacts
with our new constraint set implementation. Because the rendering of a
constraint set can get long, this standardizes on putting the `revealed`
assertion on a separate line. We also add a `static_assert` test for
each constraint set to verify that they are all coerced into simple
`bool`s correctly.
This is a pure reformatting (not even a refactoring!) that changes no
behavior. I've pulled it out of #20093 to reduce the amount of effort
that will be required to review that PR.
We have several functions in `ty_extensions` for testing our constraint
set implementation. This PR refactors those functions so that they are
all methods of the `ConstraintSet` class, rather than being standalone
top-level functions. 🎩 to @sharkdp for pointing out that
`KnownBoundMethod` gives us what we need to implement that!
This PR adds the new **_constraint implication_** relationship between
types, aka `is_subtype_of_given`, which tests whether one type is a
subtype of another _assuming that the constraints in a particular
constraint set hold_.
For concrete types, constraint implication is exactly the same as
subtyping. (A concrete type is any fully static type that is not a
typevar. It can _contain_ a typevar, though — `list[T]` is considered
concrete.)
The interesting case is typevars. The other typing relationships (TODO:
will) all "punt" on the question when considering a typevar, by
translating the desired relationship into a constraint set. At some
point, though, we need to resolve a constraint set; at that point, we
can no longer punt on the question. Unlike with concrete types, the
answer will depend on the constraint set that we are considering.
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
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This PR implements semantic syntax error where alternative patterns bind
different names
## Test Plan
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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]
```
