## 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 validation to subscript assignment expressions.
```py
class Foo: ...
class Bar:
__setattr__ = None
class Baz:
def __setitem__(self, index: str, value: int) -> None:
pass
# We now emit a diagnostic on these statements
Foo()[1] = 2
Bar()[1] = 2
Baz()[1] = 2
```
Also improves error messages on invalid `__getitem__` expressions
## Test Plan
Update mdtests and add more to `subscript/instance.md`
---------
Co-authored-by: David Peter <sharkdp@users.noreply.github.com>
Co-authored-by: David Peter <mail@david-peter.de>
Summary
--
Fixes#19640. I'm not sure these are the exact fixes we really want, but
I
reproduced the issue in a 32-bit Docker container and tracked down the
causes,
so I figured I'd open a PR.
As I commented on the issue, the `goto_references` test depends on the
iteration
order of the files in an `FxHashSet` in `Indexed`. In this case, we can
just
sort the output in test code.
Similarly, the tuple case depended on the order of overloads inserted in
an
`FxHashMap`. `FxIndexMap` seemed like a convenient drop-in replacement,
but I
don't know if that will have other detrimental effects. I did have to
change the
assertion for the tuple test, but I think it should now be stable across
architectures.
Test Plan
--
Running the tests in the aforementioned Docker container
## Summary
This PR improves our generics solver such that we are able to solve the
`TypeVar` in this snippet to `int | str` (the union of the elements in
the heterogeneous tuple) by upcasting the heterogeneous tuple to its
pure-homogeneous-tuple supertype:
```py
def f[T](x: tuple[T, ...]) -> T:
return x[0]
def g(x: tuple[int, str]):
reveal_type(f(x))
```
## Test Plan
Mdtests. Some TODOs remain in the mdtest regarding solving `TypeVar`s
for mixed tuples, but I think this PR on its own is a significant step
forward for our generics solver when it comes to tuple types.
---------
Co-authored-by: Douglas Creager <dcreager@dcreager.net>
## Summary
Add support for `async for` loops and async iterables.
part of https://github.com/astral-sh/ty/issues/151
## Ecosystem impact
```diff
- boostedblob/listing.py:445:54: warning[unused-ignore-comment] Unused blanket `type: ignore` directive
```
This is correct. We now find a true positive in the `# type: ignore`'d
code.
All of the other ecosystem hits are of the type
```diff
trio (https://github.com/python-trio/trio)
+ src/trio/_core/_tests/test_guest_mode.py:532:24: error[not-iterable] Object of type `MemorySendChannel[int] | MemoryReceiveChannel[int]` may not be iterable
```
The message is correct, because only `MemoryReceiveChannel` has an
`__aiter__` method, but `MemorySendChannel` does not. What's not correct
is our inferred type here. It should be `MemoryReceiveChannel[int]`, not
the union of the two. This is due to missing unpacking support for tuple
subclasses, which @AlexWaygood is working on. I don't think this should
block merging this PR, because those wrong types are already there,
without this PR.
## Test Plan
New Markdown tests and snapshot tests for diagnostics.
## Summary
- Add support for the return types of `async` functions
- Add type inference for `await` expressions
- Add support for `async with` / async context managers
- Add support for `yield from` expressions
This PR is generally lacking proper error handling in some cases (e.g.
illegal `__await__` attributes). I'm planning to work on this in a
follow-up.
part of https://github.com/astral-sh/ty/issues/151
closes https://github.com/astral-sh/ty/issues/736
## Ecosystem
There are a lot of true positives on `prefect` which look similar to:
```diff
prefect (https://github.com/PrefectHQ/prefect)
+ src/integrations/prefect-aws/tests/workers/test_ecs_worker.py:406:12: error[unresolved-attribute] Type `str` has no attribute `status_code`
```
This is due to a wrong return type annotation
[here](e926b8c4c1/src/integrations/prefect-aws/tests/workers/test_ecs_worker.py (L355-L391)).
```diff
mitmproxy (https://github.com/mitmproxy/mitmproxy)
+ test/mitmproxy/addons/test_clientplayback.py:18:1: error[invalid-argument-type] Argument to function `asynccontextmanager` is incorrect: Expected `(...) -> AsyncIterator[Unknown]`, found `def tcp_server(handle_conn, **server_args) -> Unknown | tuple[str, int]`
```
[This](a4d794c59a/test/mitmproxy/addons/test_clientplayback.py (L18-L19))
is a true positive. That function should return
`AsyncIterator[Address]`, not `Address`.
I looked through almost all of the other new diagnostics and they all
look like known problems or true positives.
## Typing conformance
The typing conformance diff looks good.
## Test Plan
New Markdown tests
The diagram is written in the Dot language, which can
be converted to SVG (or any other image) by GraphViz.
I thought it was a good idea to write this down in
preparation for adding routines that list modules.
Code reuse is likely to be difficult and I wanted to
be sure I understood how it worked.
I mostly just did this because the long string literals were annoying
me. And these can make rustfmt give up on formatting.
I also re-flowed some long comment lines while I was here.
I'm not sure if this used to be used elsewhere, but it no longer is.
And it looks like an internal-only helper function, so just un-export
it.
And note that `ModuleNameIngredient` is also un-exported, so this
function isn't really usable outside of its defining module anyway.
This eliminates the panic reported in
https://github.com/astral-sh/ty/issues/909, though it doesn't address
the underlying cause, which is that we aren't yet checking the types of
the fields of a protocol when checking whether a class implements the
protocol. And in particular, if a class explictly opts out of iteration
via
```py
class NotIterable:
__iter__ = None
```
we currently treat that as "having an `__iter__`" member, and therefore
implementing `Iterable`.
Note that the assumption that was in the comment before is still
correct: call binding will have already checked that the argument
satisfies `Iterable`, and so it shouldn't be an error to iterate over
said argument. But arguably, the new logic in this PR is a better way to
discharge that assumption — instead of panicking if we happen to be
wrong, fall back on an unknown iteration result.
As of [this cpython PR](https://github.com/python/cpython/pull/135996),
it is not allowed to concatenate t-strings with non-t-strings,
implicitly or explicitly. Expressions such as `"foo" t"{bar}"` are now
syntax errors.
This PR updates some AST nodes and parsing to reflect this change.
The structural change is that `TStringPart` is no longer needed, since,
as in the case of `BytesStringLiteral`, the only possibilities are that
we have a single `TString` or a vector of such (representing an implicit
concatenation of t-strings). This removes a level of nesting from many
AST expressions (which is what all the snapshot changes reflect), and
simplifies some logic in the implementation of visitors, for example.
The other change of note is in the parser. When we meet an implicit
concatenation of string-like literals, we now count the number of
t-string literals. If these do not exhaust the total number of
implicitly concatenated pieces, then we emit a syntax error. To recover
from this syntax error, we encode any t-string pieces as _invalid_
string literals (which means we flag them as invalid, record their
range, and record the value as `""`). Note that if at least one of the
pieces is an f-string we prefer to parse the entire string as an
f-string; otherwise we parse it as a string.
This logic is exactly the same as how we currently treat
`BytesStringLiteral` parsing and error recovery - and carries with it
the same pros and cons.
Finally, note that I have not implemented any changes in the
implementation of the formatter. As far as I can tell, none are needed.
I did change a few of the fixtures so that we are always concatenating
t-strings with t-strings.
We now correctly exclude legacy typevars from enclosing scopes when
constructing the generic context for a generic function.
more detail:
A function is generic if it refers to legacy typevars in its signature:
```py
from typing import TypeVar
T = TypeVar("T")
def f(t: T) -> T:
return t
```
Generic functions are allowed to appear inside of other generic
contexts. When they do, they can refer to the typevars of those
enclosing generic contexts, and that should not rebind the typevar:
```py
from typing import TypeVar, Generic
T = TypeVar("T")
U = TypeVar("U")
class C(Generic[T]):
@staticmethod
def method(t: T, u: U) -> None: ...
# revealed: def method(t: int, u: U) -> None
reveal_type(C[int].method)
```
This substitution was already being performed correctly, but we were
also still including the enclosing legacy typevars in the method's own
generic context, which can be seen via `ty_extensions.generic_context`
(which has been updated to work on generic functions and methods):
```py
from ty_extensions import generic_context
# before: tuple[T, U]
# after: tuple[U]
reveal_type(generic_context(C[int].method))
```
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
We currently infer a `@Todo` type whenever we access an attribute on an
intersection type with negative components. This can happen very
naturally. Consequently, this `@Todo` type is rather pervasive and hides
a lot of true positives that ty could otherwise detect:
```py
class Foo:
attr: int = 1
def _(f: Foo | None):
if f:
reveal_type(f) # Foo & ~AlwaysFalsy
reveal_type(f.attr) # now: int, previously: @Todo
```
The changeset here proposes to handle member access on these
intersection types by simply ignoring all negative contributions. This
is not always ideal: a negative contribution like `~<Protocol with
members 'attr'>` could be a hint that `.attr` should not be accessible
on the full intersection type. The behavior can certainly be improved in
the future, but this seems like a reasonable initial step to get rid of
this unnecessary `@Todo` type.
## Ecosystem analysis
There are quite a few changes here. I spot-checked them and found one
bug where attribute access on pure negation types (`~P == object & ~P`)
would not allow attributes on `object` to be accessed. After that was
fixed, I only see true positives and known problems. The fact that a lot
of `unused-ignore-comment` diagnostics go away are also evidence for the
fact that this touches a sensitive area, where static analysis clashes
with dynamically adding attributes to objects:
```py
… # type: ignore # Runtime attribute access
```
## Test Plan
Updated tests.
## Summary
Add basic support for `dataclasses.field`:
* remove fields with `init=False` from the signature of the synthesized
`__init__` method
* infer correct default value types from `default` or `default_factory`
arguments
```py
from dataclasses import dataclass, field
def default_roles() -> list[str]:
return ["user"]
@dataclass
class Member:
name: str
roles: list[str] = field(default_factory=default_roles)
tag: str | None = field(default=None, init=False)
# revealed: (self: Member, name: str, roles: list[str] = list[str]) -> None
reveal_type(Member.__init__)
```
Support for `kw_only` has **not** been added.
part of https://github.com/astral-sh/ty/issues/111
## Test Plan
New Markdown tests
Co-authored-by: David Peter <sharkdp@users.noreply.github.com>
Co-authored-by: Carl Meyer <carl@oddbird.net>
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
I saw that this creates a lot of false positives in the ecosystem, and
it seemed to be relatively easy to add basic support for this.
Some preliminary work on this was done by @InSyncWithFoo — thank you.
part of https://github.com/astral-sh/ty/issues/111
## Ecosystem analysis
The results look good.
## Test Plan
New Markdown tests
---------
Co-authored-by: InSync <insyncwithfoo@gmail.com>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
This PR updates our iterator protocol machinery to return a tuple spec
describing the elements that are returned, instead of a type. That
allows us to track heterogeneous iterators more precisely, and
consolidates the logic in unpacking and splatting, which are the two
places where we can take advantage of that more precise information.
(Other iterator consumers, like `for` loops, have to collapse the
iterated elements down to a single type regardless, and we provide a new
helper method on `TupleSpec` to perform that summarization.)
## Summary
Implements proper reachability analysis and — in effect — exhaustiveness
checking for `match` statements. This allows us to check the following
code without any errors (leads to *"can implicitly return `None`"* on
`main`):
```py
from enum import Enum, auto
class Color(Enum):
RED = auto()
GREEN = auto()
BLUE = auto()
def hex(color: Color) -> str:
match color:
case Color.RED:
return "#ff0000"
case Color.GREEN:
return "#00ff00"
case Color.BLUE:
return "#0000ff"
```
Note that code like this already worked fine if there was a
`assert_never(color)` statement in a catch-all case, because we would
then consider that `assert_never` call terminal. But now this also works
without the wildcard case. Adding a member to the enum would still lead
to an error here, if that case would not be handled in `hex`.
What needed to happen to support this is a new way of evaluating match
pattern constraints. Previously, we would simply compare the type of the
subject expression against the patterns. For the last case here, the
subject type would still be `Color` and the value type would be
`Literal[Color.BLUE]`, so we would infer an ambiguous truthiness.
Now, before we compare the subject type against the pattern, we first
generate a union type that corresponds to the set of all values that
would have *definitely been matched* by previous patterns. Then, we
build a "narrowed" subject type by computing `subject_type &
~already_matched_type`, and compare *that* against the pattern type. For
the example here, `already_matched_type = Literal[Color.RED] |
Literal[Color.GREEN]`, and so we have a narrowed subject type of `Color
& ~(Literal[Color.RED] | Literal[Color.GREEN]) = Literal[Color.BLUE]`,
which allows us to infer a reachability of `AlwaysTrue`.
<details>
<summary>A note on negated reachability constraints</summary>
It might seem that we now perform duplicate work, because we also record
*negated* reachability constraints. But that is still important for
cases like the following (and possibly also for more realistic
scenarios):
```py
from typing import Literal
def _(x: int | str):
match x:
case None:
pass # never reachable
case _:
y = 1
y
```
</details>
closes https://github.com/astral-sh/ty/issues/99
## Test Plan
* I verified that this solves all examples from the linked ticket (the
first example needs a PEP 695 type alias, because we don't support
legacy type aliases yet)
* Verified that the ecosystem changes are all because of removed false
positives
* Updated tests
