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fuchsia / third_party / github.com / python / mypy / refs/tags/v1.4.0 / . / mypy / types.py
blob: 5fbdd385826c3ffd2e0cdb18e42a6dba8a8c2ef4 [file] [log] [blame]
"""Classes for representing mypy types."""
from __future__ import annotations
import sys
from abc import abstractmethod
from typing import (
TYPE_CHECKING,
Any,
ClassVar,
Dict,
Iterable,
NamedTuple,
NewType,
Sequence,
TypeVar,
Union,
cast,
)
from typing_extensions import Final, Self, TypeAlias as _TypeAlias, TypeGuard, overload
import mypy.nodes
from mypy.bogus_type import Bogus
from mypy.nodes import (
ARG_POS,
ARG_STAR,
ARG_STAR2,
INVARIANT,
ArgKind,
FakeInfo,
FuncDef,
SymbolNode,
)
from mypy.options import Options
from mypy.state import state
from mypy.util import IdMapper
T = TypeVar("T")
JsonDict: _TypeAlias = Dict[str, Any]
# The set of all valid expressions that can currently be contained
# inside of a Literal[...].
#
# Literals can contain bytes and enum-values: we special-case both of these
# and store the value as a string. We rely on the fallback type that's also
# stored with the Literal to determine how a string is being used.
#
# TODO: confirm that we're happy with representing enums (and the
# other types) in the manner described above.
#
# Note: if we change the set of types included below, we must also
# make sure to audit the following methods:
#
# 1. types.LiteralType's serialize and deserialize methods: this method
# needs to make sure it can convert the below types into JSON and back.
#
# 2. types.LiteralType's 'alue_repr` method: this method is ultimately used
# by TypeStrVisitor's visit_literal_type to generate a reasonable
# repr-able output.
#
# 3. server.astdiff.SnapshotTypeVisitor's visit_literal_type_method: this
# method assumes that the following types supports equality checks and
# hashability.
#
# Note: Although "Literal[None]" is a valid type, we internally always convert
# such a type directly into "None". So, "None" is not a valid parameter of
# LiteralType and is omitted from this list.
#
# Note: Float values are only used internally. They are not accepted within
# Literal[...].
LiteralValue: _TypeAlias = Union[int, str, bool, float]
# If we only import type_visitor in the middle of the file, mypy
# breaks, and if we do it at the top, it breaks at runtime because of
# import cycle issues, so we do it at the top while typechecking and
# then again in the middle at runtime.
# We should be able to remove this once we are switched to the new
# semantic analyzer!
if TYPE_CHECKING:
from mypy.type_visitor import (
SyntheticTypeVisitor as SyntheticTypeVisitor,
TypeVisitor as TypeVisitor,
)
TYPED_NAMEDTUPLE_NAMES: Final = ("typing.NamedTuple", "typing_extensions.NamedTuple")
# Supported names of TypedDict type constructors.
TPDICT_NAMES: Final = (
"typing.TypedDict",
"typing_extensions.TypedDict",
"mypy_extensions.TypedDict",
)
# Supported fallback instance type names for TypedDict types.
TPDICT_FB_NAMES: Final = (
"typing._TypedDict",
"typing_extensions._TypedDict",
"mypy_extensions._TypedDict",
)
# Supported names of Protocol base class.
PROTOCOL_NAMES: Final = ("typing.Protocol", "typing_extensions.Protocol")
# Supported TypeAlias names.
TYPE_ALIAS_NAMES: Final = ("typing.TypeAlias", "typing_extensions.TypeAlias")
# Supported Final type names.
FINAL_TYPE_NAMES: Final = ("typing.Final", "typing_extensions.Final")
# Supported @final decorator names.
FINAL_DECORATOR_NAMES: Final = ("typing.final", "typing_extensions.final")
# Supported Literal type names.
LITERAL_TYPE_NAMES: Final = ("typing.Literal", "typing_extensions.Literal")
# Supported Annotated type names.
ANNOTATED_TYPE_NAMES: Final = ("typing.Annotated", "typing_extensions.Annotated")
# We use this constant in various places when checking `tuple` subtyping:
TUPLE_LIKE_INSTANCE_NAMES: Final = (
"builtins.tuple",
"typing.Iterable",
"typing.Container",
"typing.Sequence",
"typing.Reversible",
)
REVEAL_TYPE_NAMES: Final = (
"builtins.reveal_type",
"typing.reveal_type",
"typing_extensions.reveal_type",
)
ASSERT_TYPE_NAMES: Final = ("typing.assert_type", "typing_extensions.assert_type")
OVERLOAD_NAMES: Final = ("typing.overload", "typing_extensions.overload")
# Attributes that can optionally be defined in the body of a subclass of
# enum.Enum but are removed from the class __dict__ by EnumMeta.
ENUM_REMOVED_PROPS: Final = ("_ignore_", "_order_", "__order__")
NEVER_NAMES: Final = (
"typing.NoReturn",
"typing_extensions.NoReturn",
"mypy_extensions.NoReturn",
"typing.Never",
"typing_extensions.Never",
)
# Mypyc fixed-width native int types (compatible with builtins.int)
MYPYC_NATIVE_INT_NAMES: Final = ("mypy_extensions.i64", "mypy_extensions.i32")
DATACLASS_TRANSFORM_NAMES: Final = (
"typing.dataclass_transform",
"typing_extensions.dataclass_transform",
)
# Supported @override decorator names.
OVERRIDE_DECORATOR_NAMES: Final = ("typing.override", "typing_extensions.override")
# A placeholder used for Bogus[...] parameters
_dummy: Final[Any] = object()
# A placeholder for int parameters
_dummy_int: Final = -999999
class TypeOfAny:
"""
This class describes different types of Any. Each 'Any' can be of only one type at a time.
"""
__slots__ = ()
# Was this Any type inferred without a type annotation?
unannotated: Final = 1
# Does this Any come from an explicit type annotation?
explicit: Final = 2
# Does this come from an unfollowed import? See --disallow-any-unimported option
from_unimported_type: Final = 3
# Does this Any type come from omitted generics?
from_omitted_generics: Final = 4
# Does this Any come from an error?
from_error: Final = 5
# Is this a type that can't be represented in mypy's type system? For instance, type of
# call to NewType(...). Even though these types aren't real Anys, we treat them as such.
# Also used for variables named '_'.
special_form: Final = 6
# Does this Any come from interaction with another Any?
from_another_any: Final = 7
# Does this Any come from an implementation limitation/bug?
implementation_artifact: Final = 8
# Does this Any come from use in the suggestion engine? This is
# used to ignore Anys inserted by the suggestion engine when
# generating constraints.
suggestion_engine: Final = 9
def deserialize_type(data: JsonDict | str) -> Type:
if isinstance(data, str):
return Instance.deserialize(data)
classname = data[".class"]
method = deserialize_map.get(classname)
if method is not None:
return method(data)
raise NotImplementedError(f"unexpected .class {classname}")
class Type(mypy.nodes.Context):
"""Abstract base class for all types."""
__slots__ = ("_can_be_true", "_can_be_false")
# 'can_be_true' and 'can_be_false' mean whether the value of the
# expression can be true or false in a boolean context. They are useful
# when inferring the type of logic expressions like `x and y`.
#
# For example:
# * the literal `False` can't be true while `True` can.
# * a value with type `bool` can be true or false.
# * `None` can't be true
# * ...
def __init__(self, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
# Value of these can be -1 (use the default, lazy init), 0 (false) or 1 (true)
self._can_be_true = -1
self._can_be_false = -1
@property
def can_be_true(self) -> bool:
if self._can_be_true == -1: # Lazy init helps mypyc
self._can_be_true = self.can_be_true_default()
return bool(self._can_be_true)
@can_be_true.setter
def can_be_true(self, v: bool) -> None:
self._can_be_true = v
@property
def can_be_false(self) -> bool:
if self._can_be_false == -1: # Lazy init helps mypyc
self._can_be_false = self.can_be_false_default()
return bool(self._can_be_false)
@can_be_false.setter
def can_be_false(self, v: bool) -> None:
self._can_be_false = v
def can_be_true_default(self) -> bool:
return True
def can_be_false_default(self) -> bool:
return True
def accept(self, visitor: TypeVisitor[T]) -> T:
raise RuntimeError("Not implemented")
def __repr__(self) -> str:
return self.accept(TypeStrVisitor(options=Options()))
def str_with_options(self, options: Options) -> str:
return self.accept(TypeStrVisitor(options=options))
def serialize(self) -> JsonDict | str:
raise NotImplementedError(f"Cannot serialize {self.__class__.__name__} instance")
@classmethod
def deserialize(cls, data: JsonDict) -> Type:
raise NotImplementedError(f"Cannot deserialize {cls.__name__} instance")
def is_singleton_type(self) -> bool:
return False
class TypeAliasType(Type):
"""A type alias to another type.
To support recursive type aliases we don't immediately expand a type alias
during semantic analysis, but create an instance of this type that records the target alias
definition node (mypy.nodes.TypeAlias) and type arguments (for generic aliases).
This is very similar to how TypeInfo vs Instance interact, where a recursive class-based
structure like
class Node:
value: int
children: List[Node]
can be represented in a tree-like manner.
"""
__slots__ = ("alias", "args", "type_ref")
def __init__(
self,
alias: mypy.nodes.TypeAlias | None,
args: list[Type],
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.alias = alias
self.args = args
self.type_ref: str | None = None
def _expand_once(self) -> Type:
"""Expand to the target type exactly once.
This doesn't do full expansion, i.e. the result can contain another
(or even this same) type alias. Use this internal helper only when really needed,
its public wrapper mypy.types.get_proper_type() is preferred.
"""
assert self.alias is not None
if self.alias.no_args:
# We know that no_args=True aliases like L = List must have an instance
# as their target.
assert isinstance(self.alias.target, Instance) # type: ignore[misc]
return self.alias.target.copy_modified(args=self.args)
if self.alias.tvar_tuple_index is None:
mapping = {v.id: s for (v, s) in zip(self.alias.alias_tvars, self.args)}
else:
prefix = self.alias.tvar_tuple_index
suffix = len(self.alias.alias_tvars) - self.alias.tvar_tuple_index - 1
start, middle, end = split_with_prefix_and_suffix(tuple(self.args), prefix, suffix)
tvar = self.alias.alias_tvars[prefix]
assert isinstance(tvar, TypeVarTupleType)
mapping = {tvar.id: TupleType(list(middle), tvar.tuple_fallback)}
for tvar, sub in zip(
self.alias.alias_tvars[:prefix] + self.alias.alias_tvars[prefix + 1 :], start + end
):
mapping[tvar.id] = sub
new_tp = self.alias.target.accept(InstantiateAliasVisitor(mapping))
new_tp.accept(LocationSetter(self.line, self.column))
new_tp.line = self.line
new_tp.column = self.column
return new_tp
def _partial_expansion(self, nothing_args: bool = False) -> tuple[ProperType, bool]:
# Private method mostly for debugging and testing.
unroller = UnrollAliasVisitor(set())
if nothing_args:
alias = self.copy_modified(args=[UninhabitedType()] * len(self.args))
else:
alias = self
unrolled = alias.accept(unroller)
assert isinstance(unrolled, ProperType)
return unrolled, unroller.recursed
def expand_all_if_possible(self, nothing_args: bool = False) -> ProperType | None:
"""Attempt a full expansion of the type alias (including nested aliases).
If the expansion is not possible, i.e. the alias is (mutually-)recursive,
return None. If nothing_args is True, replace all type arguments with an
UninhabitedType() (used to detect recursively defined aliases).
"""
unrolled, recursed = self._partial_expansion(nothing_args=nothing_args)
if recursed:
return None
return unrolled
@property
def is_recursive(self) -> bool:
"""Whether this type alias is recursive.
Note this doesn't check generic alias arguments, but only if this alias
*definition* is recursive. The property value thus can be cached on the
underlying TypeAlias node. If you want to include all nested types, use
has_recursive_types() function.
"""
assert self.alias is not None, "Unfixed type alias"
is_recursive = self.alias._is_recursive
if is_recursive is None:
is_recursive = self.expand_all_if_possible(nothing_args=True) is None
# We cache the value on the underlying TypeAlias node as an optimization,
# since the value is the same for all instances of the same alias.
self.alias._is_recursive = is_recursive
return is_recursive
def can_be_true_default(self) -> bool:
if self.alias is not None:
return self.alias.target.can_be_true
return super().can_be_true_default()
def can_be_false_default(self) -> bool:
if self.alias is not None:
return self.alias.target.can_be_false
return super().can_be_false_default()
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_type_alias_type(self)
def __hash__(self) -> int:
return hash((self.alias, tuple(self.args)))
def __eq__(self, other: object) -> bool:
# Note: never use this to determine subtype relationships, use is_subtype().
if not isinstance(other, TypeAliasType):
return NotImplemented
return self.alias == other.alias and self.args == other.args
def serialize(self) -> JsonDict:
assert self.alias is not None
data: JsonDict = {
".class": "TypeAliasType",
"type_ref": self.alias.fullname,
"args": [arg.serialize() for arg in self.args],
}
return data
@classmethod
def deserialize(cls, data: JsonDict) -> TypeAliasType:
assert data[".class"] == "TypeAliasType"
args: list[Type] = []
if "args" in data:
args_list = data["args"]
assert isinstance(args_list, list)
args = [deserialize_type(arg) for arg in args_list]
alias = TypeAliasType(None, args)
alias.type_ref = data["type_ref"]
return alias
def copy_modified(self, *, args: list[Type] | None = None) -> TypeAliasType:
return TypeAliasType(
self.alias, args if args is not None else self.args.copy(), self.line, self.column
)
class TypeGuardedType(Type):
"""Only used by find_isinstance_check() etc."""
__slots__ = ("type_guard",)
def __init__(self, type_guard: Type):
super().__init__(line=type_guard.line, column=type_guard.column)
self.type_guard = type_guard
def __repr__(self) -> str:
return f"TypeGuard({self.type_guard})"
class RequiredType(Type):
"""Required[T] or NotRequired[T]. Only usable at top-level of a TypedDict definition."""
def __init__(self, item: Type, *, required: bool) -> None:
super().__init__(line=item.line, column=item.column)
self.item = item
self.required = required
def __repr__(self) -> str:
if self.required:
return f"Required[{self.item}]"
else:
return f"NotRequired[{self.item}]"
def accept(self, visitor: TypeVisitor[T]) -> T:
return self.item.accept(visitor)
class ProperType(Type):
"""Not a type alias.
Every type except TypeAliasType must inherit from this type.
"""
__slots__ = ()
class TypeVarId:
# A type variable is uniquely identified by its raw id and meta level.
# For plain variables (type parameters of generic classes and
# functions) raw ids are allocated by semantic analysis, using
# positive ids 1, 2, ... for generic class parameters and negative
# ids -1, ... for generic function type arguments. A special value 0
# is reserved for Self type variable (autogenerated). This convention
# is only used to keep type variable ids distinct when allocating
# them; the type checker makes no distinction between class and
# function type variables.
# Metavariables are allocated unique ids starting from 1.
raw_id: int = 0
# Level of the variable in type inference. Currently either 0 for
# declared types, or 1 for type inference metavariables.
meta_level: int = 0
# Class variable used for allocating fresh ids for metavariables.
next_raw_id: ClassVar[int] = 1
# Fullname of class (or potentially function in the future) which
# declares this type variable (not the fullname of the TypeVar
# definition!), or ''
namespace: str
def __init__(self, raw_id: int, meta_level: int = 0, *, namespace: str = "") -> None:
self.raw_id = raw_id
self.meta_level = meta_level
self.namespace = namespace
@staticmethod
def new(meta_level: int) -> TypeVarId:
raw_id = TypeVarId.next_raw_id
TypeVarId.next_raw_id += 1
return TypeVarId(raw_id, meta_level)
def __repr__(self) -> str:
return self.raw_id.__repr__()
def __eq__(self, other: object) -> bool:
return (
isinstance(other, TypeVarId)
and self.raw_id == other.raw_id
and self.meta_level == other.meta_level
and self.namespace == other.namespace
)
def __ne__(self, other: object) -> bool:
return not (self == other)
def __hash__(self) -> int:
return hash((self.raw_id, self.meta_level, self.namespace))
def is_meta_var(self) -> bool:
return self.meta_level > 0
class TypeVarLikeType(ProperType):
__slots__ = ("name", "fullname", "id", "upper_bound", "default")
name: str # Name (may be qualified)
fullname: str # Fully qualified name
id: TypeVarId
upper_bound: Type
default: Type
def __init__(
self,
name: str,
fullname: str,
id: TypeVarId | int,
upper_bound: Type,
default: Type,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.name = name
self.fullname = fullname
if isinstance(id, int):
id = TypeVarId(id)
self.id = id
self.upper_bound = upper_bound
self.default = default
def serialize(self) -> JsonDict:
raise NotImplementedError
@classmethod
def deserialize(cls, data: JsonDict) -> TypeVarLikeType:
raise NotImplementedError
def copy_modified(self, *, id: TypeVarId, **kwargs: Any) -> Self:
raise NotImplementedError
@classmethod
def new_unification_variable(cls, old: Self) -> Self:
new_id = TypeVarId.new(meta_level=1)
return old.copy_modified(id=new_id)
def has_default(self) -> bool:
t = get_proper_type(self.default)
return not (isinstance(t, AnyType) and t.type_of_any == TypeOfAny.from_omitted_generics)
class TypeVarType(TypeVarLikeType):
"""Type that refers to a type variable."""
__slots__ = ("values", "variance")
values: list[Type] # Value restriction, empty list if no restriction
variance: int
def __init__(
self,
name: str,
fullname: str,
id: TypeVarId | int,
values: list[Type],
upper_bound: Type,
default: Type,
variance: int = INVARIANT,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(name, fullname, id, upper_bound, default, line, column)
assert values is not None, "No restrictions must be represented by empty list"
self.values = values
self.variance = variance
def copy_modified(
self,
*,
values: Bogus[list[Type]] = _dummy,
upper_bound: Bogus[Type] = _dummy,
default: Bogus[Type] = _dummy,
id: Bogus[TypeVarId | int] = _dummy,
line: int = _dummy_int,
column: int = _dummy_int,
**kwargs: Any,
) -> TypeVarType:
return TypeVarType(
name=self.name,
fullname=self.fullname,
id=self.id if id is _dummy else id,
values=self.values if values is _dummy else values,
upper_bound=self.upper_bound if upper_bound is _dummy else upper_bound,
default=self.default if default is _dummy else default,
variance=self.variance,
line=self.line if line == _dummy_int else line,
column=self.column if column == _dummy_int else column,
)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_type_var(self)
def __hash__(self) -> int:
return hash((self.id, self.upper_bound, tuple(self.values)))
def __eq__(self, other: object) -> bool:
if not isinstance(other, TypeVarType):
return NotImplemented
return (
self.id == other.id
and self.upper_bound == other.upper_bound
and self.values == other.values
)
def serialize(self) -> JsonDict:
assert not self.id.is_meta_var()
return {
".class": "TypeVarType",
"name": self.name,
"fullname": self.fullname,
"id": self.id.raw_id,
"namespace": self.id.namespace,
"values": [v.serialize() for v in self.values],
"upper_bound": self.upper_bound.serialize(),
"default": self.default.serialize(),
"variance": self.variance,
}
@classmethod
def deserialize(cls, data: JsonDict) -> TypeVarType:
assert data[".class"] == "TypeVarType"
return TypeVarType(
name=data["name"],
fullname=data["fullname"],
id=TypeVarId(data["id"], namespace=data["namespace"]),
values=[deserialize_type(v) for v in data["values"]],
upper_bound=deserialize_type(data["upper_bound"]),
default=deserialize_type(data["default"]),
variance=data["variance"],
)
class ParamSpecFlavor:
# Simple ParamSpec reference such as "P"
BARE: Final = 0
# P.args
ARGS: Final = 1
# P.kwargs
KWARGS: Final = 2
class ParamSpecType(TypeVarLikeType):
"""Type that refers to a ParamSpec.
A ParamSpec is a type variable that represents the parameter
types, names and kinds of a callable (i.e., the signature without
the return type).
This can be one of these forms
* P (ParamSpecFlavor.BARE)
* P.args (ParamSpecFlavor.ARGS)
* P.kwargs (ParamSpecFLavor.KWARGS)
The upper_bound is really used as a fallback type -- it's shared
with TypeVarType for simplicity. It can't be specified by the user
and the value is directly derived from the flavor (currently
always just 'object').
"""
__slots__ = ("flavor", "prefix")
flavor: int
prefix: Parameters
def __init__(
self,
name: str,
fullname: str,
id: TypeVarId | int,
flavor: int,
upper_bound: Type,
default: Type,
*,
line: int = -1,
column: int = -1,
prefix: Parameters | None = None,
) -> None:
super().__init__(name, fullname, id, upper_bound, default, line=line, column=column)
self.flavor = flavor
self.prefix = prefix or Parameters([], [], [])
def with_flavor(self, flavor: int) -> ParamSpecType:
return ParamSpecType(
self.name,
self.fullname,
self.id,
flavor,
upper_bound=self.upper_bound,
default=self.default,
prefix=self.prefix,
)
def copy_modified(
self,
*,
id: Bogus[TypeVarId | int] = _dummy,
flavor: int = _dummy_int,
prefix: Bogus[Parameters] = _dummy,
default: Bogus[Type] = _dummy,
**kwargs: Any,
) -> ParamSpecType:
return ParamSpecType(
self.name,
self.fullname,
id if id is not _dummy else self.id,
flavor if flavor != _dummy_int else self.flavor,
self.upper_bound,
default=default if default is not _dummy else self.default,
line=self.line,
column=self.column,
prefix=prefix if prefix is not _dummy else self.prefix,
)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_param_spec(self)
def name_with_suffix(self) -> str:
n = self.name
if self.flavor == ParamSpecFlavor.ARGS:
return f"{n}.args"
elif self.flavor == ParamSpecFlavor.KWARGS:
return f"{n}.kwargs"
return n
def __hash__(self) -> int:
return hash((self.id, self.flavor, self.prefix))
def __eq__(self, other: object) -> bool:
if not isinstance(other, ParamSpecType):
return NotImplemented
# Upper bound can be ignored, since it's determined by flavor.
return self.id == other.id and self.flavor == other.flavor and self.prefix == other.prefix
def serialize(self) -> JsonDict:
assert not self.id.is_meta_var()
return {
".class": "ParamSpecType",
"name": self.name,
"fullname": self.fullname,
"id": self.id.raw_id,
"flavor": self.flavor,
"upper_bound": self.upper_bound.serialize(),
"default": self.default.serialize(),
"prefix": self.prefix.serialize(),
}
@classmethod
def deserialize(cls, data: JsonDict) -> ParamSpecType:
assert data[".class"] == "ParamSpecType"
return ParamSpecType(
data["name"],
data["fullname"],
data["id"],
data["flavor"],
deserialize_type(data["upper_bound"]),
deserialize_type(data["default"]),
prefix=Parameters.deserialize(data["prefix"]),
)
class TypeVarTupleType(TypeVarLikeType):
"""Type that refers to a TypeVarTuple.
See PEP646 for more information.
"""
def __init__(
self,
name: str,
fullname: str,
id: TypeVarId | int,
upper_bound: Type,
tuple_fallback: Instance,
default: Type,
*,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(name, fullname, id, upper_bound, default, line=line, column=column)
self.tuple_fallback = tuple_fallback
def serialize(self) -> JsonDict:
assert not self.id.is_meta_var()
return {
".class": "TypeVarTupleType",
"name": self.name,
"fullname": self.fullname,
"id": self.id.raw_id,
"upper_bound": self.upper_bound.serialize(),
"tuple_fallback": self.tuple_fallback.serialize(),
"default": self.default.serialize(),
}
@classmethod
def deserialize(cls, data: JsonDict) -> TypeVarTupleType:
assert data[".class"] == "TypeVarTupleType"
return TypeVarTupleType(
data["name"],
data["fullname"],
data["id"],
deserialize_type(data["upper_bound"]),
Instance.deserialize(data["tuple_fallback"]),
deserialize_type(data["default"]),
)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_type_var_tuple(self)
def __hash__(self) -> int:
return hash(self.id)
def __eq__(self, other: object) -> bool:
if not isinstance(other, TypeVarTupleType):
return NotImplemented
return self.id == other.id
def copy_modified(
self,
*,
id: Bogus[TypeVarId | int] = _dummy,
upper_bound: Bogus[Type] = _dummy,
default: Bogus[Type] = _dummy,
**kwargs: Any,
) -> TypeVarTupleType:
return TypeVarTupleType(
self.name,
self.fullname,
self.id if id is _dummy else id,
self.upper_bound if upper_bound is _dummy else upper_bound,
self.tuple_fallback,
self.default if default is _dummy else default,
line=self.line,
column=self.column,
)
class UnboundType(ProperType):
"""Instance type that has not been bound during semantic analysis."""
__slots__ = (
"name",
"args",
"optional",
"empty_tuple_index",
"original_str_expr",
"original_str_fallback",
)
def __init__(
self,
name: str | None,
args: Sequence[Type] | None = None,
line: int = -1,
column: int = -1,
optional: bool = False,
empty_tuple_index: bool = False,
original_str_expr: str | None = None,
original_str_fallback: str | None = None,
) -> None:
super().__init__(line, column)
if not args:
args = []
assert name is not None
self.name = name
self.args = tuple(args)
# Should this type be wrapped in an Optional?
self.optional = optional
# Special case for X[()]
self.empty_tuple_index = empty_tuple_index
# If this UnboundType was originally defined as a str or bytes, keep track of
# the original contents of that string-like thing. This way, if this UnboundExpr
# ever shows up inside of a LiteralType, we can determine whether that
# Literal[...] is valid or not. E.g. Literal[foo] is most likely invalid
# (unless 'foo' is an alias for another literal or something) and
# Literal["foo"] most likely is.
#
# We keep track of the entire string instead of just using a boolean flag
# so we can distinguish between things like Literal["foo"] vs
# Literal[" foo "].
#
# We also keep track of what the original base fallback type was supposed to be
# so we don't have to try and recompute it later
self.original_str_expr = original_str_expr
self.original_str_fallback = original_str_fallback
def copy_modified(self, args: Bogus[Sequence[Type] | None] = _dummy) -> UnboundType:
if args is _dummy:
args = self.args
return UnboundType(
name=self.name,
args=args,
line=self.line,
column=self.column,
optional=self.optional,
empty_tuple_index=self.empty_tuple_index,
original_str_expr=self.original_str_expr,
original_str_fallback=self.original_str_fallback,
)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_unbound_type(self)
def __hash__(self) -> int:
return hash((self.name, self.optional, tuple(self.args), self.original_str_expr))
def __eq__(self, other: object) -> bool:
if not isinstance(other, UnboundType):
return NotImplemented
return (
self.name == other.name
and self.optional == other.optional
and self.args == other.args
and self.original_str_expr == other.original_str_expr
and self.original_str_fallback == other.original_str_fallback
)
def serialize(self) -> JsonDict:
return {
".class": "UnboundType",
"name": self.name,
"args": [a.serialize() for a in self.args],
"expr": self.original_str_expr,
"expr_fallback": self.original_str_fallback,
}
@classmethod
def deserialize(cls, data: JsonDict) -> UnboundType:
assert data[".class"] == "UnboundType"
return UnboundType(
data["name"],
[deserialize_type(a) for a in data["args"]],
original_str_expr=data["expr"],
original_str_fallback=data["expr_fallback"],
)
class CallableArgument(ProperType):
"""Represents a Arg(type, 'name') inside a Callable's type list.
Note that this is a synthetic type for helping parse ASTs, not a real type.
"""
__slots__ = ("typ", "name", "constructor")
typ: Type
name: str | None
constructor: str | None
def __init__(
self,
typ: Type,
name: str | None,
constructor: str | None,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.typ = typ
self.name = name
self.constructor = constructor
def accept(self, visitor: TypeVisitor[T]) -> T:
assert isinstance(visitor, SyntheticTypeVisitor)
ret: T = visitor.visit_callable_argument(self)
return ret
def serialize(self) -> JsonDict:
assert False, "Synthetic types don't serialize"
class TypeList(ProperType):
"""Information about argument types and names [...].
This is used for the arguments of a Callable type, i.e. for
[arg, ...] in Callable[[arg, ...], ret]. This is not a real type
but a syntactic AST construct. UnboundTypes can also have TypeList
types before they are processed into Callable types.
"""
__slots__ = ("items",)
items: list[Type]
def __init__(self, items: list[Type], line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
self.items = items
def accept(self, visitor: TypeVisitor[T]) -> T:
assert isinstance(visitor, SyntheticTypeVisitor)
ret: T = visitor.visit_type_list(self)
return ret
def serialize(self) -> JsonDict:
assert False, "Synthetic types don't serialize"
def __hash__(self) -> int:
return hash(tuple(self.items))
def __eq__(self, other: object) -> bool:
return isinstance(other, TypeList) and self.items == other.items
class UnpackType(ProperType):
"""Type operator Unpack from PEP646. Can be either with Unpack[]
or unpacking * syntax.
The inner type should be either a TypeVarTuple, a constant size
tuple, or a variable length tuple, or a union of one of those.
"""
__slots__ = ["type"]
def __init__(self, typ: Type, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
self.type = typ
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_unpack_type(self)
def serialize(self) -> JsonDict:
return {".class": "UnpackType", "type": self.type.serialize()}
@classmethod
def deserialize(cls, data: JsonDict) -> UnpackType:
assert data[".class"] == "UnpackType"
typ = data["type"]
return UnpackType(deserialize_type(typ))
def __hash__(self) -> int:
return hash(self.type)
def __eq__(self, other: object) -> bool:
return isinstance(other, UnpackType) and self.type == other.type
class AnyType(ProperType):
"""The type 'Any'."""
__slots__ = ("type_of_any", "source_any", "missing_import_name")
def __init__(
self,
type_of_any: int,
source_any: AnyType | None = None,
missing_import_name: str | None = None,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.type_of_any = type_of_any
# If this Any was created as a result of interacting with another 'Any', record the source
# and use it in reports.
self.source_any = source_any
if source_any and source_any.source_any:
self.source_any = source_any.source_any
if source_any is None:
self.missing_import_name = missing_import_name
else:
self.missing_import_name = source_any.missing_import_name
# Only unimported type anys and anys from other anys should have an import name
assert missing_import_name is None or type_of_any in (
TypeOfAny.from_unimported_type,
TypeOfAny.from_another_any,
)
# Only Anys that come from another Any can have source_any.
assert type_of_any != TypeOfAny.from_another_any or source_any is not None
# We should not have chains of Anys.
assert not self.source_any or self.source_any.type_of_any != TypeOfAny.from_another_any
@property
def is_from_error(self) -> bool:
return self.type_of_any == TypeOfAny.from_error
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_any(self)
def copy_modified(
self,
# Mark with Bogus because _dummy is just an object (with type Any)
type_of_any: int = _dummy_int,
original_any: Bogus[AnyType | None] = _dummy,
) -> AnyType:
if type_of_any == _dummy_int:
type_of_any = self.type_of_any
if original_any is _dummy:
original_any = self.source_any
return AnyType(
type_of_any=type_of_any,
source_any=original_any,
missing_import_name=self.missing_import_name,
line=self.line,
column=self.column,
)
def __hash__(self) -> int:
return hash(AnyType)
def __eq__(self, other: object) -> bool:
return isinstance(other, AnyType)
def serialize(self) -> JsonDict:
return {
".class": "AnyType",
"type_of_any": self.type_of_any,
"source_any": self.source_any.serialize() if self.source_any is not None else None,
"missing_import_name": self.missing_import_name,
}
@classmethod
def deserialize(cls, data: JsonDict) -> AnyType:
assert data[".class"] == "AnyType"
source = data["source_any"]
return AnyType(
data["type_of_any"],
AnyType.deserialize(source) if source is not None else None,
data["missing_import_name"],
)
class UninhabitedType(ProperType):
"""This type has no members.
This type is the bottom type.
With strict Optional checking, it is the only common subtype between all
other types, which allows `meet` to be well defined. Without strict
Optional checking, NoneType fills this role.
In general, for any type T:
join(UninhabitedType, T) = T
meet(UninhabitedType, T) = UninhabitedType
is_subtype(UninhabitedType, T) = True
"""
__slots__ = ("ambiguous", "is_noreturn")
is_noreturn: bool # Does this come from a NoReturn? Purely for error messages.
# It is important to track whether this is an actual NoReturn type, or just a result
# of ambiguous type inference, in the latter case we don't want to mark a branch as
# unreachable in binder.
ambiguous: bool # Is this a result of inference for a variable without constraints?
def __init__(self, is_noreturn: bool = False, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
self.is_noreturn = is_noreturn
self.ambiguous = False
def can_be_true_default(self) -> bool:
return False
def can_be_false_default(self) -> bool:
return False
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_uninhabited_type(self)
def __hash__(self) -> int:
return hash(UninhabitedType)
def __eq__(self, other: object) -> bool:
return isinstance(other, UninhabitedType)
def serialize(self) -> JsonDict:
return {".class": "UninhabitedType", "is_noreturn": self.is_noreturn}
@classmethod
def deserialize(cls, data: JsonDict) -> UninhabitedType:
assert data[".class"] == "UninhabitedType"
return UninhabitedType(is_noreturn=data["is_noreturn"])
class NoneType(ProperType):
"""The type of 'None'.
This type can be written by users as 'None'.
"""
__slots__ = ()
def __init__(self, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
def can_be_true_default(self) -> bool:
return False
def __hash__(self) -> int:
return hash(NoneType)
def __eq__(self, other: object) -> bool:
return isinstance(other, NoneType)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_none_type(self)
def serialize(self) -> JsonDict:
return {".class": "NoneType"}
@classmethod
def deserialize(cls, data: JsonDict) -> NoneType:
assert data[".class"] == "NoneType"
return NoneType()
def is_singleton_type(self) -> bool:
return True
# NoneType used to be called NoneTyp so to avoid needlessly breaking
# external plugins we keep that alias here.
NoneTyp = NoneType
class ErasedType(ProperType):
"""Placeholder for an erased type.
This is used during type inference. This has the special property that
it is ignored during type inference.
"""
__slots__ = ()
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_erased_type(self)
class DeletedType(ProperType):
"""Type of deleted variables.
These can be used as lvalues but not rvalues.
"""
__slots__ = ("source",)
source: str | None # May be None; name that generated this value
def __init__(self, source: str | None = None, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
self.source = source
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_deleted_type(self)
def serialize(self) -> JsonDict:
return {".class": "DeletedType", "source": self.source}
@classmethod
def deserialize(cls, data: JsonDict) -> DeletedType:
assert data[".class"] == "DeletedType"
return DeletedType(data["source"])
# Fake TypeInfo to be used as a placeholder during Instance de-serialization.
NOT_READY: Final = mypy.nodes.FakeInfo("De-serialization failure: TypeInfo not fixed")
class ExtraAttrs:
"""Summary of module attributes and types.
This is used for instances of types.ModuleType, because they can have different
attributes per instance, and for type narrowing with hasattr() checks.
"""
def __init__(
self,
attrs: dict[str, Type],
immutable: set[str] | None = None,
mod_name: str | None = None,
) -> None:
self.attrs = attrs
if immutable is None:
immutable = set()
self.immutable = immutable
self.mod_name = mod_name
def __hash__(self) -> int:
return hash((tuple(self.attrs.items()), tuple(sorted(self.immutable))))
def __eq__(self, other: object) -> bool:
if not isinstance(other, ExtraAttrs):
return NotImplemented
return self.attrs == other.attrs and self.immutable == other.immutable
def copy(self) -> ExtraAttrs:
return ExtraAttrs(self.attrs.copy(), self.immutable.copy(), self.mod_name)
def __repr__(self) -> str:
return f"ExtraAttrs({self.attrs!r}, {self.immutable!r}, {self.mod_name!r})"
class Instance(ProperType):
"""An instance type of form C[T1, ..., Tn].
The list of type variables may be empty.
Several types have fallbacks to `Instance`, because in Python everything is an object
and this concept is impossible to express without intersection types. We therefore use
fallbacks for all "non-special" (like UninhabitedType, ErasedType etc) types.
"""
__slots__ = ("type", "args", "invalid", "type_ref", "last_known_value", "_hash", "extra_attrs")
def __init__(
self,
typ: mypy.nodes.TypeInfo,
args: Sequence[Type],
line: int = -1,
column: int = -1,
*,
last_known_value: LiteralType | None = None,
extra_attrs: ExtraAttrs | None = None,
) -> None:
super().__init__(line, column)
self.type = typ
self.args = tuple(args)
self.type_ref: str | None = None
# True if recovered after incorrect number of type arguments error
self.invalid = False
# This field keeps track of the underlying Literal[...] value associated with
# this instance, if one is known.
#
# This field is set whenever possible within expressions, but is erased upon
# variable assignment (see erasetype.remove_instance_last_known_values) unless
# the variable is declared to be final.
#
# For example, consider the following program:
#
# a = 1
# b: Final[int] = 2
# c: Final = 3
# print(a + b + c + 4)
#
# The 'Instance' objects associated with the expressions '1', '2', '3', and '4' will
# have last_known_values of type Literal[1], Literal[2], Literal[3], and Literal[4]
# respectively. However, the Instance object assigned to 'a' and 'b' will have their
# last_known_value erased: variable 'a' is mutable; variable 'b' was declared to be
# specifically an int.
#
# Or more broadly, this field lets this Instance "remember" its original declaration
# when applicable. We want this behavior because we want implicit Final declarations
# to act pretty much identically with constants: we should be able to replace any
# places where we use some Final variable with the original value and get the same
# type-checking behavior. For example, we want this program:
#
# def expects_literal(x: Literal[3]) -> None: pass
# var: Final = 3
# expects_literal(var)
#
# ...to type-check in the exact same way as if we had written the program like this:
#
# def expects_literal(x: Literal[3]) -> None: pass
# expects_literal(3)
#
# In order to make this work (especially with literal types), we need var's type
# (an Instance) to remember the "original" value.
#
# Preserving this value within expressions is useful for similar reasons.
#
# Currently most of mypy will ignore this field and will continue to treat this type like
# a regular Instance. We end up using this field only when we are explicitly within a
# Literal context.
self.last_known_value = last_known_value
# Cached hash value
self._hash = -1
# Additional attributes defined per instance of this type. For example modules
# have different attributes per instance of types.ModuleType. This is intended
# to be "short-lived", we don't serialize it, and even don't store as variable type.
self.extra_attrs = extra_attrs
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_instance(self)
def __hash__(self) -> int:
if self._hash == -1:
self._hash = hash((self.type, self.args, self.last_known_value, self.extra_attrs))
return self._hash
def __eq__(self, other: object) -> bool:
if not isinstance(other, Instance):
return NotImplemented
return (
self.type == other.type
and self.args == other.args
and self.last_known_value == other.last_known_value
and self.extra_attrs == other.extra_attrs
)
def serialize(self) -> JsonDict | str:
assert self.type is not None
type_ref = self.type.fullname
if not self.args and not self.last_known_value:
return type_ref
data: JsonDict = {".class": "Instance"}
data["type_ref"] = type_ref
data["args"] = [arg.serialize() for arg in self.args]
if self.last_known_value is not None:
data["last_known_value"] = self.last_known_value.serialize()
return data
@classmethod
def deserialize(cls, data: JsonDict | str) -> Instance:
if isinstance(data, str):
inst = Instance(NOT_READY, [])
inst.type_ref = data
return inst
assert data[".class"] == "Instance"
args: list[Type] = []
if "args" in data:
args_list = data["args"]
assert isinstance(args_list, list)
args = [deserialize_type(arg) for arg in args_list]
inst = Instance(NOT_READY, args)
inst.type_ref = data["type_ref"] # Will be fixed up by fixup.py later.
if "last_known_value" in data:
inst.last_known_value = LiteralType.deserialize(data["last_known_value"])
return inst
def copy_modified(
self,
*,
args: Bogus[list[Type]] = _dummy,
last_known_value: Bogus[LiteralType | None] = _dummy,
) -> Instance:
new = Instance(
self.type,
args if args is not _dummy else self.args,
self.line,
self.column,
last_known_value=last_known_value
if last_known_value is not _dummy
else self.last_known_value,
)
# We intentionally don't copy the extra_attrs here, so they will be erased.
new.can_be_true = self.can_be_true
new.can_be_false = self.can_be_false
return new
def copy_with_extra_attr(self, name: str, typ: Type) -> Instance:
if self.extra_attrs:
existing_attrs = self.extra_attrs.copy()
else:
existing_attrs = ExtraAttrs({}, set(), None)
existing_attrs.attrs[name] = typ
new = self.copy_modified()
new.extra_attrs = existing_attrs
return new
def is_singleton_type(self) -> bool:
# TODO:
# Also make this return True if the type corresponds to NotImplemented?
return (
self.type.is_enum
and len(self.get_enum_values()) == 1
or self.type.fullname == "builtins.ellipsis"
)
def get_enum_values(self) -> list[str]:
"""Return the list of values for an Enum."""
return [
name for name, sym in self.type.names.items() if isinstance(sym.node, mypy.nodes.Var)
]
class FunctionLike(ProperType):
"""Abstract base class for function types."""
__slots__ = ("fallback",)
fallback: Instance
def __init__(self, line: int = -1, column: int = -1) -> None:
super().__init__(line, column)
self._can_be_false = False
@abstractmethod
def is_type_obj(self) -> bool:
pass
@abstractmethod
def type_object(self) -> mypy.nodes.TypeInfo:
pass
@property
@abstractmethod
def items(self) -> list[CallableType]:
pass
@abstractmethod
def with_name(self, name: str) -> FunctionLike:
pass
@abstractmethod
def get_name(self) -> str | None:
pass
class FormalArgument(NamedTuple):
name: str | None
pos: int | None
typ: Type
required: bool
# TODO: should this take bound typevars too? what would this take?
# ex: class Z(Generic[P, T]): ...; Z[[V], V]
# What does a typevar even mean in this context?
class Parameters(ProperType):
"""Type that represents the parameters to a function.
Used for ParamSpec analysis."""
__slots__ = (
"arg_types",
"arg_kinds",
"arg_names",
"min_args",
"is_ellipsis_args",
"variables",
)
def __init__(
self,
arg_types: Sequence[Type],
arg_kinds: list[ArgKind],
arg_names: Sequence[str | None],
*,
variables: Sequence[TypeVarLikeType] | None = None,
is_ellipsis_args: bool = False,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.arg_types = list(arg_types)
self.arg_kinds = arg_kinds
self.arg_names = list(arg_names)
assert len(arg_types) == len(arg_kinds) == len(arg_names)
self.min_args = arg_kinds.count(ARG_POS)
self.is_ellipsis_args = is_ellipsis_args
self.variables = variables or []
def copy_modified(
self,
arg_types: Bogus[Sequence[Type]] = _dummy,
arg_kinds: Bogus[list[ArgKind]] = _dummy,
arg_names: Bogus[Sequence[str | None]] = _dummy,
*,
variables: Bogus[Sequence[TypeVarLikeType]] = _dummy,
is_ellipsis_args: Bogus[bool] = _dummy,
) -> Parameters:
return Parameters(
arg_types=arg_types if arg_types is not _dummy else self.arg_types,
arg_kinds=arg_kinds if arg_kinds is not _dummy else self.arg_kinds,
arg_names=arg_names if arg_names is not _dummy else self.arg_names,
is_ellipsis_args=(
is_ellipsis_args if is_ellipsis_args is not _dummy else self.is_ellipsis_args
),
variables=variables if variables is not _dummy else self.variables,
)
# the following are copied from CallableType. Is there a way to decrease code duplication?
def var_arg(self) -> FormalArgument | None:
"""The formal argument for *args."""
for position, (type, kind) in enumerate(zip(self.arg_types, self.arg_kinds)):
if kind == ARG_STAR:
return FormalArgument(None, position, type, False)
return None
def kw_arg(self) -> FormalArgument | None:
"""The formal argument for **kwargs."""
for position, (type, kind) in enumerate(zip(self.arg_types, self.arg_kinds)):
if kind == ARG_STAR2:
return FormalArgument(None, position, type, False)
return None
def formal_arguments(self, include_star_args: bool = False) -> list[FormalArgument]:
"""Yields the formal arguments corresponding to this callable, ignoring *arg and **kwargs.
To handle *args and **kwargs, use the 'callable.var_args' and 'callable.kw_args' fields,
if they are not None.
If you really want to include star args in the yielded output, set the
'include_star_args' parameter to 'True'."""
args = []
done_with_positional = False
for i in range(len(self.arg_types)):
kind = self.arg_kinds[i]
if kind.is_named() or kind.is_star():
done_with_positional = True
if not include_star_args and kind.is_star():
continue
required = kind.is_required()
pos = None if done_with_positional else i
arg = FormalArgument(self.arg_names[i], pos, self.arg_types[i], required)
args.append(arg)
return args
def argument_by_name(self, name: str | None) -> FormalArgument | None:
if name is None:
return None
seen_star = False
for i, (arg_name, kind, typ) in enumerate(
zip(self.arg_names, self.arg_kinds, self.arg_types)
):
# No more positional arguments after these.
if kind.is_named() or kind.is_star():
seen_star = True
if kind.is_star():
continue
if arg_name == name:
position = None if seen_star else i
return FormalArgument(name, position, typ, kind.is_required())
return self.try_synthesizing_arg_from_kwarg(name)
def argument_by_position(self, position: int | None) -> FormalArgument | None:
if position is None:
return None
if position >= len(self.arg_names):
return self.try_synthesizing_arg_from_vararg(position)
name, kind, typ = (
self.arg_names[position],
self.arg_kinds[position],
self.arg_types[position],
)
if kind.is_positional():
return FormalArgument(name, position, typ, kind == ARG_POS)
else:
return self.try_synthesizing_arg_from_vararg(position)
def try_synthesizing_arg_from_kwarg(self, name: str | None) -> FormalArgument | None:
kw_arg = self.kw_arg()
if kw_arg is not None:
return FormalArgument(name, None, kw_arg.typ, False)
else:
return None
def try_synthesizing_arg_from_vararg(self, position: int | None) -> FormalArgument | None:
var_arg = self.var_arg()
if var_arg is not None:
return FormalArgument(None, position, var_arg.typ, False)
else:
return None
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_parameters(self)
def serialize(self) -> JsonDict:
return {
".class": "Parameters",
"arg_types": [t.serialize() for t in self.arg_types],
"arg_kinds": [int(x.value) for x in self.arg_kinds],
"arg_names": self.arg_names,
"variables": [tv.serialize() for tv in self.variables],
}
@classmethod
def deserialize(cls, data: JsonDict) -> Parameters:
assert data[".class"] == "Parameters"
return Parameters(
[deserialize_type(t) for t in data["arg_types"]],
[ArgKind(x) for x in data["arg_kinds"]],
data["arg_names"],
variables=[cast(TypeVarLikeType, deserialize_type(v)) for v in data["variables"]],
)
def __hash__(self) -> int:
return hash(
(
self.is_ellipsis_args,
tuple(self.arg_types),
tuple(self.arg_names),
tuple(self.arg_kinds),
)
)
def __eq__(self, other: object) -> bool:
if isinstance(other, (Parameters, CallableType)):
return (
self.arg_types == other.arg_types
and self.arg_names == other.arg_names
and self.arg_kinds == other.arg_kinds
and self.is_ellipsis_args == other.is_ellipsis_args
)
else:
return NotImplemented
CT = TypeVar("CT", bound="CallableType")
class CallableType(FunctionLike):
"""Type of a non-overloaded callable object (such as function)."""
__slots__ = (
"arg_types", # Types of function arguments
"arg_kinds", # ARG_ constants
"arg_names", # Argument names; None if not a keyword argument
"min_args", # Minimum number of arguments; derived from arg_kinds
"ret_type", # Return value type
"name", # Name (may be None; for error messages and plugins)
"definition", # For error messages. May be None.
"variables", # Type variables for a generic function
"is_ellipsis_args", # Is this Callable[..., t] (with literal '...')?
"is_classmethod_class", # Is this callable constructed for the benefit
# of a classmethod's 'cls' argument?
"implicit", # Was this type implicitly generated instead of explicitly
# specified by the user?
"special_sig", # Non-None for signatures that require special handling
# (currently only value is 'dict' for a signature similar to
# 'dict')
"from_type_type", # Was this callable generated by analyzing Type[...]
# instantiation?
"bound_args", # Bound type args, mostly unused but may be useful for
# tools that consume mypy ASTs
"def_extras", # Information about original definition we want to serialize.
# This is used for more detailed error messages.
"type_guard", # T, if -> TypeGuard[T] (ret_type is bool in this case).
"from_concatenate", # whether this callable is from a concatenate object
# (this is used for error messages)
"unpack_kwargs", # Was an Unpack[...] with **kwargs used to define this callable?
)
def __init__(
self,
# maybe this should be refactored to take a Parameters object
arg_types: Sequence[Type],
arg_kinds: list[ArgKind],
arg_names: Sequence[str | None],
ret_type: Type,
fallback: Instance,
name: str | None = None,
definition: SymbolNode | None = None,
variables: Sequence[TypeVarLikeType] | None = None,
line: int = -1,
column: int = -1,
is_ellipsis_args: bool = False,
implicit: bool = False,
special_sig: str | None = None,
from_type_type: bool = False,
bound_args: Sequence[Type | None] = (),
def_extras: dict[str, Any] | None = None,
type_guard: Type | None = None,
from_concatenate: bool = False,
unpack_kwargs: bool = False,
) -> None:
super().__init__(line, column)
assert len(arg_types) == len(arg_kinds) == len(arg_names)
if variables is None:
variables = []
self.arg_types = list(arg_types)
self.arg_kinds = arg_kinds
self.arg_names = list(arg_names)
self.min_args = arg_kinds.count(ARG_POS)
self.ret_type = ret_type
self.fallback = fallback
assert not name or "<bound method" not in name
self.name = name
self.definition = definition
self.variables = variables
self.is_ellipsis_args = is_ellipsis_args
self.implicit = implicit
self.special_sig = special_sig
self.from_type_type = from_type_type
self.from_concatenate = from_concatenate
if not bound_args:
bound_args = ()
self.bound_args = bound_args
if def_extras:
self.def_extras = def_extras
elif isinstance(definition, FuncDef):
# This information would be lost if we don't have definition
# after serialization, but it is useful in error messages.
# TODO: decide how to add more info here (file, line, column)
# without changing interface hash.
first_arg: str | None = None
if definition.arg_names and definition.info and not definition.is_static:
if getattr(definition, "arguments", None):
first_arg = definition.arguments[0].variable.name
else:
first_arg = definition.arg_names[0]
self.def_extras = {"first_arg": first_arg}
else:
self.def_extras = {}
self.type_guard = type_guard
self.unpack_kwargs = unpack_kwargs
def copy_modified(
self: CT,
arg_types: Bogus[Sequence[Type]] = _dummy,
arg_kinds: Bogus[list[ArgKind]] = _dummy,
arg_names: Bogus[Sequence[str | None]] = _dummy,
ret_type: Bogus[Type] = _dummy,
fallback: Bogus[Instance] = _dummy,
name: Bogus[str | None] = _dummy,
definition: Bogus[SymbolNode] = _dummy,
variables: Bogus[Sequence[TypeVarLikeType]] = _dummy,
line: int = _dummy_int,
column: int = _dummy_int,
is_ellipsis_args: Bogus[bool] = _dummy,
implicit: Bogus[bool] = _dummy,
special_sig: Bogus[str | None] = _dummy,
from_type_type: Bogus[bool] = _dummy,
bound_args: Bogus[list[Type | None]] = _dummy,
def_extras: Bogus[dict[str, Any]] = _dummy,
type_guard: Bogus[Type | None] = _dummy,
from_concatenate: Bogus[bool] = _dummy,
unpack_kwargs: Bogus[bool] = _dummy,
) -> CT:
modified = CallableType(
arg_types=arg_types if arg_types is not _dummy else self.arg_types,
arg_kinds=arg_kinds if arg_kinds is not _dummy else self.arg_kinds,
arg_names=arg_names if arg_names is not _dummy else self.arg_names,
ret_type=ret_type if ret_type is not _dummy else self.ret_type,
fallback=fallback if fallback is not _dummy else self.fallback,
name=name if name is not _dummy else self.name,
definition=definition if definition is not _dummy else self.definition,
variables=variables if variables is not _dummy else self.variables,
line=line if line != _dummy_int else self.line,
column=column if column != _dummy_int else self.column,
is_ellipsis_args=(
is_ellipsis_args if is_ellipsis_args is not _dummy else self.is_ellipsis_args
),
implicit=implicit if implicit is not _dummy else self.implicit,
special_sig=special_sig if special_sig is not _dummy else self.special_sig,
from_type_type=from_type_type if from_type_type is not _dummy else self.from_type_type,
bound_args=bound_args if bound_args is not _dummy else self.bound_args,
def_extras=def_extras if def_extras is not _dummy else dict(self.def_extras),
type_guard=type_guard if type_guard is not _dummy else self.type_guard,
from_concatenate=(
from_concatenate if from_concatenate is not _dummy else self.from_concatenate
),
unpack_kwargs=unpack_kwargs if unpack_kwargs is not _dummy else self.unpack_kwargs,
)
# Optimization: Only NewTypes are supported as subtypes since
# the class is effectively final, so we can use a cast safely.
return cast(CT, modified)
def var_arg(self) -> FormalArgument | None:
"""The formal argument for *args."""
for position, (type, kind) in enumerate(zip(self.arg_types, self.arg_kinds)):
if kind == ARG_STAR:
return FormalArgument(None, position, type, False)
return None
def kw_arg(self) -> FormalArgument | None:
"""The formal argument for **kwargs."""
for position, (type, kind) in enumerate(zip(self.arg_types, self.arg_kinds)):
if kind == ARG_STAR2:
return FormalArgument(None, position, type, False)
return None
@property
def is_var_arg(self) -> bool:
"""Does this callable have a *args argument?"""
return ARG_STAR in self.arg_kinds
@property
def is_kw_arg(self) -> bool:
"""Does this callable have a **kwargs argument?"""
return ARG_STAR2 in self.arg_kinds
def is_type_obj(self) -> bool:
return self.fallback.type.is_metaclass() and not isinstance(
get_proper_type(self.ret_type), UninhabitedType
)
def type_object(self) -> mypy.nodes.TypeInfo:
assert self.is_type_obj()
ret = get_proper_type(self.ret_type)
if isinstance(ret, TypeVarType):
ret = get_proper_type(ret.upper_bound)
if isinstance(ret, TupleType):
ret = ret.partial_fallback
if isinstance(ret, TypedDictType):
ret = ret.fallback
assert isinstance(ret, Instance)
return ret.type
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_callable_type(self)
def with_name(self, name: str) -> CallableType:
"""Return a copy of this type with the specified name."""
return self.copy_modified(ret_type=self.ret_type, name=name)
def get_name(self) -> str | None:
return self.name
def max_possible_positional_args(self) -> int:
"""Returns maximum number of positional arguments this method could possibly accept.
This takes into account *arg and **kwargs but excludes keyword-only args."""
if self.is_var_arg or self.is_kw_arg:
return sys.maxsize
return sum(kind.is_positional() for kind in self.arg_kinds)
def formal_arguments(self, include_star_args: bool = False) -> list[FormalArgument]:
"""Return a list of the formal arguments of this callable, ignoring *arg and **kwargs.
To handle *args and **kwargs, use the 'callable.var_args' and 'callable.kw_args' fields,
if they are not None.
If you really want to include star args in the yielded output, set the
'include_star_args' parameter to 'True'."""
args = []
done_with_positional = False
for i in range(len(self.arg_types)):
kind = self.arg_kinds[i]
if kind.is_named() or kind.is_star():
done_with_positional = True
if not include_star_args and kind.is_star():
continue
required = kind.is_required()
pos = None if done_with_positional else i
arg = FormalArgument(self.arg_names[i], pos, self.arg_types[i], required)
args.append(arg)
return args
def argument_by_name(self, name: str | None) -> FormalArgument | None:
if name is None:
return None
seen_star = False
for i, (arg_name, kind, typ) in enumerate(
zip(self.arg_names, self.arg_kinds, self.arg_types)
):
# No more positional arguments after these.
if kind.is_named() or kind.is_star():
seen_star = True
if kind.is_star():
continue
if arg_name == name:
position = None if seen_star else i
return FormalArgument(name, position, typ, kind.is_required())
return self.try_synthesizing_arg_from_kwarg(name)
def argument_by_position(self, position: int | None) -> FormalArgument | None:
if position is None:
return None
if position >= len(self.arg_names):
return self.try_synthesizing_arg_from_vararg(position)
name, kind, typ = (
self.arg_names[position],
self.arg_kinds[position],
self.arg_types[position],
)
if kind.is_positional():
return FormalArgument(name, position, typ, kind == ARG_POS)
else:
return self.try_synthesizing_arg_from_vararg(position)
def try_synthesizing_arg_from_kwarg(self, name: str | None) -> FormalArgument | None:
kw_arg = self.kw_arg()
if kw_arg is not None:
return FormalArgument(name, None, kw_arg.typ, False)
else:
return None
def try_synthesizing_arg_from_vararg(self, position: int | None) -> FormalArgument | None:
var_arg = self.var_arg()
if var_arg is not None:
return FormalArgument(None, position, var_arg.typ, False)
else:
return None
@property
def items(self) -> list[CallableType]:
return [self]
def is_generic(self) -> bool:
return bool(self.variables)
def type_var_ids(self) -> list[TypeVarId]:
a: list[TypeVarId] = []
for tv in self.variables:
a.append(tv.id)
return a
def param_spec(self) -> ParamSpecType | None:
"""Return ParamSpec if callable can be called with one.
A Callable accepting ParamSpec P args (*args, **kwargs) must have the
two final parameters like this: *args: P.args, **kwargs: P.kwargs.
"""
if len(self.arg_types) < 2:
return None
if self.arg_kinds[-2] != ARG_STAR or self.arg_kinds[-1] != ARG_STAR2:
return None
arg_type = self.arg_types[-2]
if not isinstance(arg_type, ParamSpecType):
return None
# sometimes paramspectypes are analyzed in from mysterious places,
# e.g. def f(prefix..., *args: P.args, **kwargs: P.kwargs) -> ...: ...
prefix = arg_type.prefix
if not prefix.arg_types:
# TODO: confirm that all arg kinds are positional
prefix = Parameters(self.arg_types[:-2], self.arg_kinds[:-2], self.arg_names[:-2])
return arg_type.copy_modified(flavor=ParamSpecFlavor.BARE, prefix=prefix)
def expand_param_spec(
self, c: CallableType | Parameters, no_prefix: bool = False
) -> CallableType:
variables = c.variables
if no_prefix:
return self.copy_modified(
arg_types=c.arg_types,
arg_kinds=c.arg_kinds,
arg_names=c.arg_names,
is_ellipsis_args=c.is_ellipsis_args,
variables=[*variables, *self.variables],
)
else:
return self.copy_modified(
arg_types=self.arg_types[:-2] + c.arg_types,
arg_kinds=self.arg_kinds[:-2] + c.arg_kinds,
arg_names=self.arg_names[:-2] + c.arg_names,
is_ellipsis_args=c.is_ellipsis_args,
variables=[*variables, *self.variables],
)
def with_unpacked_kwargs(self) -> NormalizedCallableType:
if not self.unpack_kwargs:
return cast(NormalizedCallableType, self)
last_type = get_proper_type(self.arg_types[-1])
assert isinstance(last_type, TypedDictType)
extra_kinds = [
ArgKind.ARG_NAMED if name in last_type.required_keys else ArgKind.ARG_NAMED_OPT
for name in last_type.items
]
new_arg_kinds = self.arg_kinds[:-1] + extra_kinds
new_arg_names = self.arg_names[:-1] + list(last_type.items)
new_arg_types = self.arg_types[:-1] + list(last_type.items.values())
return NormalizedCallableType(
self.copy_modified(
arg_kinds=new_arg_kinds,
arg_names=new_arg_names,
arg_types=new_arg_types,
unpack_kwargs=False,
)
)
def __hash__(self) -> int:
# self.is_type_obj() will fail if self.fallback.type is a FakeInfo
if isinstance(self.fallback.type, FakeInfo):
is_type_obj = 2
else:
is_type_obj = self.is_type_obj()
return hash(
(
self.ret_type,
is_type_obj,
self.is_ellipsis_args,
self.name,
tuple(self.arg_types),
tuple(self.arg_names),
tuple(self.arg_kinds),
self.fallback,
)
)
def __eq__(self, other: object) -> bool:
if isinstance(other, CallableType):
return (
self.ret_type == other.ret_type
and self.arg_types == other.arg_types
and self.arg_names == other.arg_names
and self.arg_kinds == other.arg_kinds
and self.name == other.name
and self.is_type_obj() == other.is_type_obj()
and self.is_ellipsis_args == other.is_ellipsis_args
and self.fallback == other.fallback
)
else:
return NotImplemented
def serialize(self) -> JsonDict:
# TODO: As an optimization, leave out everything related to
# generic functions for non-generic functions.
return {
".class": "CallableType",
"arg_types": [t.serialize() for t in self.arg_types],
"arg_kinds": [int(x.value) for x in self.arg_kinds],
"arg_names": self.arg_names,
"ret_type": self.ret_type.serialize(),
"fallback": self.fallback.serialize(),
"name": self.name,
# We don't serialize the definition (only used for error messages).
"variables": [v.serialize() for v in self.variables],
"is_ellipsis_args": self.is_ellipsis_args,
"implicit": self.implicit,
"bound_args": [(None if t is None else t.serialize()) for t in self.bound_args],
"def_extras": dict(self.def_extras),
"type_guard": self.type_guard.serialize() if self.type_guard is not None else None,
"from_concatenate": self.from_concatenate,
"unpack_kwargs": self.unpack_kwargs,
}
@classmethod
def deserialize(cls, data: JsonDict) -> CallableType:
assert data[".class"] == "CallableType"
# TODO: Set definition to the containing SymbolNode?
return CallableType(
[deserialize_type(t) for t in data["arg_types"]],
[ArgKind(x) for x in data["arg_kinds"]],
data["arg_names"],
deserialize_type(data["ret_type"]),
Instance.deserialize(data["fallback"]),
name=data["name"],
variables=[cast(TypeVarLikeType, deserialize_type(v)) for v in data["variables"]],
is_ellipsis_args=data["is_ellipsis_args"],
implicit=data["implicit"],
bound_args=[(None if t is None else deserialize_type(t)) for t in data["bound_args"]],
def_extras=data["def_extras"],
type_guard=(
deserialize_type(data["type_guard"]) if data["type_guard"] is not None else None
),
from_concatenate=data["from_concatenate"],
unpack_kwargs=data["unpack_kwargs"],
)
# This is a little safety net to prevent reckless special-casing of callables
# that can potentially break Unpack[...] with **kwargs.
# TODO: use this in more places in checkexpr.py etc?
NormalizedCallableType = NewType("NormalizedCallableType", CallableType)
class Overloaded(FunctionLike):
"""Overloaded function type T1, ... Tn, where each Ti is CallableType.
The variant to call is chosen based on static argument
types. Overloaded function types can only be defined in stub
files, and thus there is no explicit runtime dispatch
implementation.
"""
__slots__ = ("_items",)
_items: list[CallableType] # Must not be empty
def __init__(self, items: list[CallableType]) -> None:
super().__init__(items[0].line, items[0].column)
self._items = items
self.fallback = items[0].fallback
@property
def items(self) -> list[CallableType]:
return self._items
def name(self) -> str | None:
return self.get_name()
def is_type_obj(self) -> bool:
# All the items must have the same type object status, so it's
# sufficient to query only (any) one of them.
return self._items[0].is_type_obj()
def type_object(self) -> mypy.nodes.TypeInfo:
# All the items must have the same type object, so it's sufficient to
# query only (any) one of them.
return self._items[0].type_object()
def with_name(self, name: str) -> Overloaded:
ni: list[CallableType] = []
for it in self._items:
ni.append(it.with_name(name))
return Overloaded(ni)
def get_name(self) -> str | None:
return self._items[0].name
def with_unpacked_kwargs(self) -> Overloaded:
if any(i.unpack_kwargs for i in self.items):
return Overloaded([i.with_unpacked_kwargs() for i in self.items])
return self
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_overloaded(self)
def __hash__(self) -> int:
return hash(tuple(self.items))
def __eq__(self, other: object) -> bool:
if not isinstance(other, Overloaded):
return NotImplemented
return self.items == other.items
def serialize(self) -> JsonDict:
return {".class": "Overloaded", "items": [t.serialize() for t in self.items]}
@classmethod
def deserialize(cls, data: JsonDict) -> Overloaded:
assert data[".class"] == "Overloaded"
return Overloaded([CallableType.deserialize(t) for t in data["items"]])
class TupleType(ProperType):
"""The tuple type Tuple[T1, ..., Tn] (at least one type argument).
Instance variables:
items: Tuple item types
partial_fallback: The (imprecise) underlying instance type that is used
for non-tuple methods. This is generally builtins.tuple[Any, ...] for
regular tuples, but it's different for named tuples and classes with
a tuple base class. Use mypy.typeops.tuple_fallback to calculate the
precise fallback type derived from item types.
implicit: If True, derived from a tuple expression (t,....) instead of Tuple[t, ...]
"""
__slots__ = ("items", "partial_fallback", "implicit")
items: list[Type]
partial_fallback: Instance
implicit: bool
def __init__(
self,
items: list[Type],
fallback: Instance,
line: int = -1,
column: int = -1,
implicit: bool = False,
) -> None:
super().__init__(line, column)
self.partial_fallback = fallback
self.items = items
self.implicit = implicit
def can_be_true_default(self) -> bool:
if self.can_be_any_bool():
# Corner case: it is a `NamedTuple` with `__bool__` method defined.
# It can be anything: both `True` and `False`.
return True
return self.length() > 0
def can_be_false_default(self) -> bool:
if self.can_be_any_bool():
# Corner case: it is a `NamedTuple` with `__bool__` method defined.
# It can be anything: both `True` and `False`.
return True
return self.length() == 0
def can_be_any_bool(self) -> bool:
return bool(
self.partial_fallback.type
and self.partial_fallback.type.fullname != "builtins.tuple"
and self.partial_fallback.type.names.get("__bool__")
)
def length(self) -> int:
return len(self.items)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_tuple_type(self)
def __hash__(self) -> int:
return hash((tuple(self.items), self.partial_fallback))
def __eq__(self, other: object) -> bool:
if not isinstance(other, TupleType):
return NotImplemented
return self.items == other.items and self.partial_fallback == other.partial_fallback
def serialize(self) -> JsonDict:
return {
".class": "TupleType",
"items": [t.serialize() for t in self.items],
"partial_fallback": self.partial_fallback.serialize(),
"implicit": self.implicit,
}
@classmethod
def deserialize(cls, data: JsonDict) -> TupleType:
assert data[".class"] == "TupleType"
return TupleType(
[deserialize_type(t) for t in data["items"]],
Instance.deserialize(data["partial_fallback"]),
implicit=data["implicit"],
)
def copy_modified(
self, *, fallback: Instance | None = None, items: list[Type] | None = None
) -> TupleType:
if fallback is None:
fallback = self.partial_fallback
if items is None:
items = self.items
return TupleType(items, fallback, self.line, self.column)
def slice(self, begin: int | None, end: int | None, stride: int | None) -> TupleType:
return TupleType(
self.items[begin:end:stride],
self.partial_fallback,
self.line,
self.column,
self.implicit,
)
class TypedDictType(ProperType):
"""Type of TypedDict object {'k1': v1, ..., 'kn': vn}.
A TypedDict object is a dictionary with specific string (literal) keys. Each
key has a value with a distinct type that depends on the key. TypedDict objects
are normal dict objects at runtime.
A TypedDictType can be either named or anonymous. If it's anonymous, its
fallback will be typing_extensions._TypedDict (Instance). _TypedDict is a subclass
of Mapping[str, object] and defines all non-mapping dict methods that TypedDict
supports. Some dict methods are unsafe and not supported. _TypedDict isn't defined
at runtime.
If a TypedDict is named, its fallback will be an Instance of the named type
(ex: "Point") whose TypeInfo has a typeddict_type that is anonymous. This
is similar to how named tuples work.
TODO: The fallback structure is perhaps overly complicated.
"""
__slots__ = ("items", "required_keys", "fallback")
items: dict[str, Type] # item_name -> item_type
required_keys: set[str]
fallback: Instance
def __init__(
self,
items: dict[str, Type],
required_keys: set[str],
fallback: Instance,
line: int = -1,
column: int = -1,
) -> None:
super().__init__(line, column)
self.items = items
self.required_keys = required_keys
self.fallback = fallback
self.can_be_true = len(self.items) > 0
self.can_be_false = len(self.required_keys) == 0
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_typeddict_type(self)
def __hash__(self) -> int:
return hash((frozenset(self.items.items()), self.fallback, frozenset(self.required_keys)))
def __eq__(self, other: object) -> bool:
if not isinstance(other, TypedDictType):
return NotImplemented
return (
frozenset(self.items.keys()) == frozenset(other.items.keys())
and all(
left_item_type == right_item_type
for (_, left_item_type, right_item_type) in self.zip(other)
)
and self.fallback == other.fallback
and self.required_keys == other.required_keys
)
def serialize(self) -> JsonDict:
return {
".class": "TypedDictType",
"items": [[n, t.serialize()] for (n, t) in self.items.items()],
"required_keys": sorted(self.required_keys),
"fallback": self.fallback.serialize(),
}
@classmethod
def deserialize(cls, data: JsonDict) -> TypedDictType:
assert data[".class"] == "TypedDictType"
return TypedDictType(
{n: deserialize_type(t) for (n, t) in data["items"]},
set(data["required_keys"]),
Instance.deserialize(data["fallback"]),
)
@property
def is_final(self) -> bool:
return self.fallback.type.is_final
def is_anonymous(self) -> bool:
return self.fallback.type.fullname in TPDICT_FB_NAMES
def as_anonymous(self) -> TypedDictType:
if self.is_anonymous():
return self
assert self.fallback.type.typeddict_type is not None
return self.fallback.type.typeddict_type.as_anonymous()
def copy_modified(
self,
*,
fallback: Instance | None = None,
item_types: list[Type] | None = None,
required_keys: set[str] | None = None,
) -> TypedDictType:
if fallback is None:
fallback = self.fallback
if item_types is None:
items = self.items
else:
items = dict(zip(self.items, item_types))
if required_keys is None:
required_keys = self.required_keys
return TypedDictType(items, required_keys, fallback, self.line, self.column)
def create_anonymous_fallback(self) -> Instance:
anonymous = self.as_anonymous()
return anonymous.fallback
def names_are_wider_than(self, other: TypedDictType) -> bool:
return len(other.items.keys() - self.items.keys()) == 0
def zip(self, right: TypedDictType) -> Iterable[tuple[str, Type, Type]]:
left = self
for item_name, left_item_type in left.items.items():
right_item_type = right.items.get(item_name)
if right_item_type is not None:
yield (item_name, left_item_type, right_item_type)
def zipall(self, right: TypedDictType) -> Iterable[tuple[str, Type | None, Type | None]]:
left = self
for item_name, left_item_type in left.items.items():
right_item_type = right.items.get(item_name)
yield (item_name, left_item_type, right_item_type)
for item_name, right_item_type in right.items.items():
if item_name in left.items:
continue
yield (item_name, None, right_item_type)
class RawExpressionType(ProperType):
"""A synthetic type representing some arbitrary expression that does not cleanly
translate into a type.
This synthetic type is only used at the beginning stages of semantic analysis
and should be completely removing during the process for mapping UnboundTypes to
actual types: we either turn it into a LiteralType or an AnyType.
For example, suppose `Foo[1]` is initially represented as the following:
UnboundType(
name='Foo',
args=[
RawExpressionType(value=1, base_type_name='builtins.int'),
],
)
As we perform semantic analysis, this type will transform into one of two
possible forms.
If 'Foo' was an alias for 'Literal' all along, this type is transformed into:
LiteralType(value=1, fallback=int_instance_here)
Alternatively, if 'Foo' is an unrelated class, we report an error and instead
produce something like this:
Instance(type=typeinfo_for_foo, args=[AnyType(TypeOfAny.from_error))
If the "note" field is not None, the provided note will be reported alongside the
error at this point.
Note: if "literal_value" is None, that means this object is representing some
expression that cannot possibly be a parameter of Literal[...]. For example,
"Foo[3j]" would be represented as:
UnboundType(
name='Foo',
args=[
RawExpressionType(value=None, base_type_name='builtins.complex'),
],
)
"""
__slots__ = ("literal_value", "base_type_name", "note")
def __init__(
self,
literal_value: LiteralValue | None,
base_type_name: str,
line: int = -1,
column: int = -1,
note: str | None = None,
) -> None:
super().__init__(line, column)
self.literal_value = literal_value
self.base_type_name = base_type_name
self.note = note
def simple_name(self) -> str:
return self.base_type_name.replace("builtins.", "")
def accept(self, visitor: TypeVisitor[T]) -> T:
assert isinstance(visitor, SyntheticTypeVisitor)
ret: T = visitor.visit_raw_expression_type(self)
return ret
def serialize(self) -> JsonDict:
assert False, "Synthetic types don't serialize"
def __hash__(self) -> int:
return hash((self.literal_value, self.base_type_name))
def __eq__(self, other: object) -> bool:
if isinstance(other, RawExpressionType):
return (
self.base_type_name == other.base_type_name
and self.literal_value == other.literal_value
)
else:
return NotImplemented
class LiteralType(ProperType):
"""The type of a Literal instance. Literal[Value]
A Literal always consists of:
1. A native Python object corresponding to the contained inner value
2. A fallback for this Literal. The fallback also corresponds to the
parent type this Literal subtypes.
For example, 'Literal[42]' is represented as
'LiteralType(value=42, fallback=instance_of_int)'
As another example, `Literal[Color.RED]` (where Color is an enum) is
represented as `LiteralType(value="RED", fallback=instance_of_color)'.
"""
__slots__ = ("value", "fallback", "_hash")
def __init__(
self, value: LiteralValue, fallback: Instance, line: int = -1, column: int = -1
) -> None:
super().__init__(line, column)
self.value = value
self.fallback = fallback
self._hash = -1 # Cached hash value
def can_be_false_default(self) -> bool:
return not self.value
def can_be_true_default(self) -> bool:
return bool(self.value)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_literal_type(self)
def __hash__(self) -> int:
if self._hash == -1:
self._hash = hash((self.value, self.fallback))
return self._hash
def __eq__(self, other: object) -> bool:
if isinstance(other, LiteralType):
return self.fallback == other.fallback and self.value == other.value
else:
return NotImplemented
def is_enum_literal(self) -> bool:
return self.fallback.type.is_enum
def value_repr(self) -> str:
"""Returns the string representation of the underlying type.
This function is almost equivalent to running `repr(self.value)`,
except it includes some additional logic to correctly handle cases
where the value is a string, byte string, a unicode string, or an enum.
"""
raw = repr(self.value)
fallback_name = self.fallback.type.fullname
# If this is backed by an enum,
if self.is_enum_literal():
return f"{fallback_name}.{self.value}"
if fallback_name == "builtins.bytes":
# Note: 'builtins.bytes' only appears in Python 3, so we want to
# explicitly prefix with a "b"
return "b" + raw
else:
# 'builtins.str' could mean either depending on context, but either way
# we don't prefix: it's the "native" string. And of course, if value is
# some other type, we just return that string repr directly.
return raw
def serialize(self) -> JsonDict | str:
return {
".class": "LiteralType",
"value": self.value,
"fallback": self.fallback.serialize(),
}
@classmethod
def deserialize(cls, data: JsonDict) -> LiteralType:
assert data[".class"] == "LiteralType"
return LiteralType(value=data["value"], fallback=Instance.deserialize(data["fallback"]))
def is_singleton_type(self) -> bool:
return self.is_enum_literal() or isinstance(self.value, bool)
class UnionType(ProperType):
"""The union type Union[T1, ..., Tn] (at least one type argument)."""
__slots__ = ("items", "is_evaluated", "uses_pep604_syntax")
def __init__(
self,
items: Sequence[Type],
line: int = -1,
column: int = -1,
is_evaluated: bool = True,
uses_pep604_syntax: bool = False,
) -> None:
super().__init__(line, column)
# We must keep this false to avoid crashes during semantic analysis.
# TODO: maybe switch this to True during type-checking pass?
self.items = flatten_nested_unions(items, handle_type_alias_type=False)
# is_evaluated should be set to false for type comments and string literals
self.is_evaluated = is_evaluated
# uses_pep604_syntax is True if Union uses OR syntax (X | Y)
self.uses_pep604_syntax = uses_pep604_syntax
def can_be_true_default(self) -> bool:
return any(item.can_be_true for item in self.items)
def can_be_false_default(self) -> bool:
return any(item.can_be_false for item in self.items)
def __hash__(self) -> int:
return hash(frozenset(self.items))
def __eq__(self, other: object) -> bool:
if not isinstance(other, UnionType):
return NotImplemented
return frozenset(self.items) == frozenset(other.items)
@overload
@staticmethod
def make_union(items: Sequence[ProperType], line: int = -1, column: int = -1) -> ProperType:
...
@overload
@staticmethod
def make_union(items: Sequence[Type], line: int = -1, column: int = -1) -> Type:
...
@staticmethod
def make_union(items: Sequence[Type], line: int = -1, column: int = -1) -> Type:
if len(items) > 1:
return UnionType(items, line, column)
elif len(items) == 1:
return items[0]
else:
return UninhabitedType()
def length(self) -> int:
return len(self.items)
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_union_type(self)
def relevant_items(self) -> list[Type]:
"""Removes NoneTypes from Unions when strict Optional checking is off."""
if state.strict_optional:
return self.items
else:
return [i for i in self.items if not isinstance(get_proper_type(i), NoneType)]
def serialize(self) -> JsonDict:
return {".class": "UnionType", "items": [t.serialize() for t in self.items]}
@classmethod
def deserialize(cls, data: JsonDict) -> UnionType:
assert data[".class"] == "UnionType"
return UnionType([deserialize_type(t) for t in data["items"]])
class PartialType(ProperType):
"""Type such as List[?] where type arguments are unknown, or partial None type.
These are used for inferring types in multiphase initialization such as this:
x = [] # x gets a partial type List[?], as item type is unknown
x.append(1) # partial type gets replaced with normal type List[int]
Or with None:
x = None # x gets a partial type None
if c:
x = 1 # Infer actual type int for x
"""
__slots__ = ("type", "var", "value_type")
# None for the 'None' partial type; otherwise a generic class
type: mypy.nodes.TypeInfo | None
var: mypy.nodes.Var
# For partial defaultdict[K, V], the type V (K is unknown). If V is generic,
# the type argument is Any and will be replaced later.
value_type: Instance | None
def __init__(
self,
type: mypy.nodes.TypeInfo | None,
var: mypy.nodes.Var,
value_type: Instance | None = None,
) -> None:
super().__init__()
self.type = type
self.var = var
self.value_type = value_type
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_partial_type(self)
class EllipsisType(ProperType):
"""The type ... (ellipsis).
This is not a real type but a syntactic AST construct, used in Callable[..., T], for example.
A semantically analyzed type will never have ellipsis types.
"""
__slots__ = ()
def accept(self, visitor: TypeVisitor[T]) -> T:
assert isinstance(visitor, SyntheticTypeVisitor)
ret: T = visitor.visit_ellipsis_type(self)
return ret
def serialize(self) -> JsonDict:
assert False, "Synthetic types don't serialize"
class TypeType(ProperType):
"""For types like Type[User].
This annotates variables that are class objects, constrained by
the type argument. See PEP 484 for more details.
We may encounter expressions whose values are specific classes;
those are represented as callables (possibly overloaded)
corresponding to the class's constructor's signature and returning
an instance of that class. The difference with Type[C] is that
those callables always represent the exact class given as the
return type; Type[C] represents any class that's a subclass of C,
and C may also be a type variable or a union (or Any).
Many questions around subtype relationships between Type[C1] and
def(...) -> C2 are answered by looking at the subtype
relationships between C1 and C2, since Type[] is considered
covariant.
There's an unsolved problem with constructor signatures (also
unsolved in PEP 484): calling a variable whose type is Type[C]
assumes the constructor signature for C, even though a subclass of
C might completely change the constructor signature. For now we
just assume that users of Type[C] are careful not to do that (in
the future we might detect when they are violating that
assumption).
"""
__slots__ = ("item",)
# This can't be everything, but it can be a class reference,
# a generic class instance, a union, Any, a type variable...
item: ProperType
def __init__(
self,
item: Bogus[Instance | AnyType | TypeVarType | TupleType | NoneType | CallableType],
*,
line: int = -1,
column: int = -1,
) -> None:
"""To ensure Type[Union[A, B]] is always represented as Union[Type[A], Type[B]], item of
type UnionType must be handled through make_normalized static method.
"""
super().__init__(line, column)
self.item = item
@staticmethod
def make_normalized(item: Type, *, line: int = -1, column: int = -1) -> ProperType:
item = get_proper_type(item)
if isinstance(item, UnionType):
return UnionType.make_union(
[TypeType.make_normalized(union_item) for union_item in item.items],
line=line,
column=column,
)
return TypeType(item, line=line, column=column) # type: ignore[arg-type]
def accept(self, visitor: TypeVisitor[T]) -> T:
return visitor.visit_type_type(self)
def __hash__(self) -> int:
return hash(self.item)
def __eq__(self, other: object) -> bool:
if not isinstance(other, TypeType):
return NotImplemented
return self.item == other.item
def serialize(self) -> JsonDict:
return {".class": "TypeType", "item": self.item.serialize()}
@classmethod
def deserialize(cls, data: JsonDict) -> Type:
assert data[".class"] == "TypeType"
return TypeType.make_normalized(deserialize_type(data["item"]))
class PlaceholderType(ProperType):
"""Temporary, yet-unknown type during semantic analysis.
This is needed when there's a reference to a type before the real symbol
table entry of the target type is available (specifically, we use a
temporary PlaceholderNode symbol node). Consider this example:
class str(Sequence[str]): ...
We use a PlaceholderType for the 'str' in 'Sequence[str]' since we can't create
a TypeInfo for 'str' until all base classes have been resolved. We'll soon
perform another analysis iteration which replaces the base class with a complete
type without any placeholders. After semantic analysis, no placeholder types must
exist.
"""
__slots__ = ("fullname", "args")
def __init__(self, fullname: str | None, args: list[Type], line: int) -> None:
super().__init__(line)
self.fullname = fullname # Must be a valid full name of an actual node (or None).
self.args = args
def accept(self, visitor: TypeVisitor[T]) -> T:
assert isinstance(visitor, SyntheticTypeVisitor)
ret: T = visitor.visit_placeholder_type(self)
return ret
def __hash__(self) -> int:
return hash((self.fullname, tuple(self.args)))
def __eq__(self, other: object) -> bool:
if not isinstance(other, PlaceholderType):
return NotImplemented
return self.fullname == other.fullname and self.args == other.args
def serialize(self) -> str:
# We should never get here since all placeholders should be replaced
# during semantic analysis.
assert False, f"Internal error: unresolved placeholder type {self.fullname}"
@overload
def get_proper_type(typ: None) -> None:
...
@overload
def get_proper_type(typ: Type) -> ProperType:
...
def get_proper_type(typ: Type | None) -> ProperType | None:
"""Get the expansion of a type alias type.
If the type is already a proper type, this is a no-op. Use this function
wherever a decision is made on a call like e.g. 'if isinstance(typ, UnionType): ...',
because 'typ' in this case may be an alias to union. Note: if after making the decision
on the isinstance() call you pass on the original type (and not one of its components)
it is recommended to *always* pass on the unexpanded alias.
"""
if typ is None:
return None
if isinstance(typ, TypeGuardedType): # type: ignore[misc]
typ = typ.type_guard
while isinstance(typ, TypeAliasType):
typ = typ._expand_once()
# TODO: store the name of original type alias on this type, so we can show it in errors.
return cast(ProperType, typ)
@overload
def get_proper_types(types: list[Type] | tuple[Type, ...]) -> list[ProperType]: # type: ignore[misc]
...
@overload
def get_proper_types(
types: list[Type | None] | tuple[Type | None, ...]
) -> list[ProperType | None]:
...
def get_proper_types(
types: list[Type] | list[Type | None] | tuple[Type | None, ...]
) -> list[ProperType] | list[ProperType | None]:
if isinstance(types, list):
typelist = types
# Optimize for the common case so that we don't need to allocate anything
if not any(
isinstance(t, (TypeAliasType, TypeGuardedType)) for t in typelist # type: ignore[misc]
):
return cast("list[ProperType]", typelist)
return [get_proper_type(t) for t in typelist]
else:
return [get_proper_type(t) for t in types]
# We split off the type visitor base classes to another module
# to make it easier to gradually get modules working with mypyc.
# Import them here, after the types are defined.
# This is intended as a re-export also.
from mypy.type_visitor import ( # noqa: F811,F401
ALL_STRATEGY as ALL_STRATEGY,
ANY_STRATEGY as ANY_STRATEGY,
BoolTypeQuery as BoolTypeQuery,
SyntheticTypeVisitor as SyntheticTypeVisitor,
TypeQuery as TypeQuery,
TypeTranslator as TypeTranslator,
TypeVisitor as TypeVisitor,
)
from mypy.typetraverser import TypeTraverserVisitor
class TypeStrVisitor(SyntheticTypeVisitor[str]):
"""Visitor for pretty-printing types into strings.
This is mostly for debugging/testing.
Do not preserve original formatting.
Notes:
- Represent unbound types as Foo? or Foo?[...].
- Represent the NoneType type as None.
"""
def __init__(self, id_mapper: IdMapper | None = None, *, options: Options) -> None:
self.id_mapper = id_mapper
self.any_as_dots = False
self.options = options
def visit_unbound_type(self, t: UnboundType) -> str:
s = t.name + "?"
if t.args:
s += f"[{self.list_str(t.args)}]"
return s
def visit_type_list(self, t: TypeList) -> str:
return f"<TypeList {self.list_str(t.items)}>"
def visit_callable_argument(self, t: CallableArgument) -> str:
typ = t.typ.accept(self)
if t.name is None:
return f"{t.constructor}({typ})"
else:
return f"{t.constructor}({typ}, {t.name})"
def visit_any(self, t: AnyType) -> str:
if self.any_as_dots and t.type_of_any == TypeOfAny.special_form:
return "..."
return "Any"
def visit_none_type(self, t: NoneType) -> str:
return "None"
def visit_uninhabited_type(self, t: UninhabitedType) -> str:
return "<nothing>"
def visit_erased_type(self, t: ErasedType) -> str:
return "<Erased>"
def visit_deleted_type(self, t: DeletedType) -> str:
if t.source is None:
return "<Deleted>"
else:
return f"<Deleted '{t.source}'>"
def visit_instance(self, t: Instance) -> str:
if t.last_known_value and not t.args:
# Instances with a literal fallback should never be generic. If they are,
# something went wrong so we fall back to showing the full Instance repr.
s = f"{t.last_known_value.accept(self)}?"
else:
s = t.type.fullname or t.type.name or "<???>"
if t.args:
if t.type.fullname == "builtins.tuple":
assert len(t.args) == 1
s += f"[{self.list_str(t.args)}, ...]"
else:
s += f"[{self.list_str(t.args)}]"
if self.id_mapper:
s += f"<{self.id_mapper.id(t.type)}>"
return s
def visit_type_var(self, t: TypeVarType) -> str:
if t.name is None:
# Anonymous type variable type (only numeric id).
s = f"`{t.id}"
else:
# Named type variable type.
s = f"{t.name}`{t.id}"
if self.id_mapper and t.upper_bound:
s += f"(upper_bound={t.upper_bound.accept(self)})"
if t.has_default():
s += f" = {t.default.accept(self)}"
return s
def visit_param_spec(self, t: ParamSpecType) -> str:
# prefixes are displayed as Concatenate
s = ""
if t.prefix.arg_types:
s += f"[{self.list_str(t.prefix.arg_types)}, **"
if t.name is None:
# Anonymous type variable type (only numeric id).
s += f"`{t.id}"
else:
# Named type variable type.
s += f"{t.name_with_suffix()}`{t.id}"
if t.prefix.arg_types:
s += "]"
if t.has_default():
s += f" = {t.default.accept(self)}"
return s
def visit_parameters(self, t: Parameters) -> str:
# This is copied from visit_callable -- is there a way to decrease duplication?
if t.is_ellipsis_args:
return "..."
s = ""
bare_asterisk = False
for i in range(len(t.arg_types)):
if s != "":
s += ", "
if t.arg_kinds[i].is_named() and not bare_asterisk:
s += "*, "
bare_asterisk = True
if t.arg_kinds[i] == ARG_STAR:
s += "*"
if t.arg_kinds[i] == ARG_STAR2:
s += "**"
name = t.arg_names[i]
if name:
s += f"{name}: "
r = t.arg_types[i].accept(self)
s += r
if t.arg_kinds[i].is_optional():
s += " ="
return f"[{s}]"
def visit_type_var_tuple(self, t: TypeVarTupleType) -> str:
if t.name is None:
# Anonymous type variable type (only numeric id).
s = f"`{t.id}"
else:
# Named type variable type.
s = f"{t.name}`{t.id}"
if t.has_default():
s += f" = {t.default.accept(self)}"
return s
def visit_callable_type(self, t: CallableType) -> str:
param_spec = t.param_spec()
if param_spec is not None:
num_skip = 2
else:
num_skip = 0
s = ""
bare_asterisk = False
for i in range(len(t.arg_types) - num_skip):
if s != "":
s += ", "
if t.arg_kinds[i].is_named() and not bare_asterisk:
s += "*, "
bare_asterisk = True
if t.arg_kinds[i] == ARG_STAR:
s += "*"
if t.arg_kinds[i] == ARG_STAR2:
s += "**"
name = t.arg_names[i]
if name:
s += name + ": "
type_str = t.arg_types[i].accept(self)
if t.arg_kinds[i] == ARG_STAR2 and t.unpack_kwargs:
type_str = f"Unpack[{type_str}]"
s += type_str
if t.arg_kinds[i].is_optional():
s += " ="
if param_spec is not None:
n = param_spec.name
if s:
s += ", "
s += f"*{n}.args, **{n}.kwargs"
if param_spec.has_default():
s += f" = {param_spec.default.accept(self)}"
s = f"({s})"
if not isinstance(get_proper_type(t.ret_type), NoneType):
if t.type_guard is not None:
s += f" -> TypeGuard[{t.type_guard.accept(self)}]"
else:
s += f" -> {t.ret_type.accept(self)}"
if t.variables:
vs = []
for var in t.variables:
if isinstance(var, TypeVarType):
# We reimplement TypeVarType.__repr__ here in order to support id_mapper.
if var.values:
vals = f"({', '.join(val.accept(self) for val in var.values)})"
vs.append(f"{var.name} in {vals}")
elif not is_named_instance(var.upper_bound, "builtins.object"):
vs.append(
f"{var.name} <: {var.upper_bound.accept(self)}{f' = {var.default.accept(self)}' if var.has_default() else ''}"
)
else:
vs.append(
f"{var.name}{f' = {var.default.accept(self)}' if var.has_default() else ''}"
)
else:
# For other TypeVarLikeTypes, use the name and default
vs.append(
f"{var.name}{f' = {var.default.accept(self)}' if var.has_default() else ''}"
)
s = f"[{', '.join(vs)}] {s}"
return f"def {s}"
def visit_overloaded(self, t: Overloaded) -> str:
a = []
for i in t.items:
a.append(i.accept(self))
return f"Overload({', '.join(a)})"
def visit_tuple_type(self, t: TupleType) -> str:
s = self.list_str(t.items)
tuple_name = "tuple" if self.options.use_lowercase_names() else "Tuple"
if t.partial_fallback and t.partial_fallback.type:
fallback_name = t.partial_fallback.type.fullname
if fallback_name != "builtins.tuple":
return f"{tuple_name}[{s}, fallback={t.partial_fallback.accept(self)}]"
return f"{tuple_name}[{s}]"
def visit_typeddict_type(self, t: TypedDictType) -> str:
def item_str(name: str, typ: str) -> str:
if name in t.required_keys:
return f"{name!r}: {typ}"
else:
return f"{name!r}?: {typ}"
s = (
"{"
+ ", ".join(item_str(name, typ.accept(self)) for name, typ in t.items.items())
+ "}"
)
prefix = ""
if t.fallback and t.fallback.type:
if t.fallback.type.fullname not in TPDICT_FB_NAMES:
prefix = repr(t.fallback.type.fullname) + ", "
return f"TypedDict({prefix}{s})"
def visit_raw_expression_type(self, t: RawExpressionType) -> str:
return repr(t.literal_value)
def visit_literal_type(self, t: LiteralType) -> str:
return f"Literal[{t.value_repr()}]"
def visit_union_type(self, t: UnionType) -> str:
s = self.list_str(t.items)
return f"Union[{s}]"
def visit_partial_type(self, t: PartialType) -> str:
if t.type is None:
return "<partial None>"
else:
return "<partial {}[{}]>".format(t.type.name, ", ".join(["?"] * len(t.type.type_vars)))
def visit_ellipsis_type(self, t: EllipsisType) -> str:
return "..."
def visit_type_type(self, t: TypeType) -> str:
return f"Type[{t.item.accept(self)}]"
def visit_placeholder_type(self, t: PlaceholderType) -> str:
return f"<placeholder {t.fullname}>"
def visit_type_alias_type(self, t: TypeAliasType) -> str:
if t.alias is not None:
unrolled, recursed = t._partial_expansion()
self.any_as_dots = recursed
type_str = unrolled.accept(self)
self.any_as_dots = False
return type_str
return "<alias (unfixed)>"
def visit_unpack_type(self, t: UnpackType) -> str:
return f"Unpack[{t.type.accept(self)}]"
def list_str(self, a: Iterable[Type]) -> str:
"""Convert items of an array to strings (pretty-print types)
and join the results with commas.
"""
res = []
for t in a:
res.append(t.accept(self))
return ", ".join(res)
class TrivialSyntheticTypeTranslator(TypeTranslator, SyntheticTypeVisitor[Type]):
"""A base class for type translators that need to be run during semantic analysis."""
def visit_placeholder_type(self, t: PlaceholderType) -> Type:
return t
def visit_callable_argument(self, t: CallableArgument) -> Type:
return t
def visit_ellipsis_type(self, t: EllipsisType) -> Type:
return t
def visit_raw_expression_type(self, t: RawExpressionType) -> Type:
return t
def visit_type_list(self, t: TypeList) -> Type:
return t
class UnrollAliasVisitor(TrivialSyntheticTypeTranslator):
def __init__(self, initial_aliases: set[TypeAliasType]) -> None:
self.recursed = False
self.initial_aliases = initial_aliases
def visit_type_alias_type(self, t: TypeAliasType) -> Type:
if t in self.initial_aliases:
self.recursed = True
return AnyType(TypeOfAny.special_form)
# Create a new visitor on encountering a new type alias, so that an alias like
# A = Tuple[B, B]
# B = int
# will not be detected as recursive on the second encounter of B.
subvisitor = UnrollAliasVisitor(self.initial_aliases | {t})
result = get_proper_type(t).accept(subvisitor)
if subvisitor.recursed:
self.recursed = True
return result
def is_named_instance(t: Type, fullnames: str | tuple[str, ...]) -> TypeGuard[Instance]:
if not isinstance(fullnames, tuple):
fullnames = (fullnames,)
t = get_proper_type(t)
return isinstance(t, Instance) and t.type.fullname in fullnames
class LocationSetter(TypeTraverserVisitor):
# TODO: Should we update locations of other Type subclasses?
def __init__(self, line: int, column: int) -> None:
self.line = line
self.column = column
def visit_instance(self, typ: Instance) -> None:
typ.line = self.line
typ.column = self.column
super().visit_instance(typ)
class HasTypeVars(BoolTypeQuery):
def __init__(self) -> None:
super().__init__(ANY_STRATEGY)
self.skip_alias_target = True
def visit_type_var(self, t: TypeVarType) -> bool:
return True
def visit_type_var_tuple(self, t: TypeVarTupleType) -> bool:
return True
def visit_param_spec(self, t: ParamSpecType) -> bool:
return True
def has_type_vars(typ: Type) -> bool:
"""Check if a type contains any type variables (recursively)."""
return typ.accept(HasTypeVars())
class HasRecursiveType(BoolTypeQuery):
def __init__(self) -> None:
super().__init__(ANY_STRATEGY)
def visit_type_alias_type(self, t: TypeAliasType) -> bool:
return t.is_recursive or self.query_types(t.args)
# Use singleton since this is hot (note: call reset() before using)
_has_recursive_type: Final = HasRecursiveType()
def has_recursive_types(typ: Type) -> bool:
"""Check if a type contains any recursive aliases (recursively)."""
_has_recursive_type.reset()
return typ.accept(_has_recursive_type)
def split_with_prefix_and_suffix(
types: tuple[Type, ...], prefix: int, suffix: int
) -> tuple[tuple[Type, ...], tuple[Type, ...], tuple[Type, ...]]:
if len(types) <= prefix + suffix:
types = extend_args_for_prefix_and_suffix(types, prefix, suffix)
if suffix:
return types[:prefix], types[prefix:-suffix], types[-suffix:]
else:
return types[:prefix], types[prefix:], ()
def extend_args_for_prefix_and_suffix(
types: tuple[Type, ...], prefix: int, suffix: int
) -> tuple[Type, ...]:
"""Extend list of types by eating out from variadic tuple to satisfy prefix and suffix."""
idx = None
item = None
for i, t in enumerate(types):
if isinstance(t, UnpackType):
p_type = get_proper_type(t.type)
if isinstance(p_type, Instance) and p_type.type.fullname == "builtins.tuple":
item = p_type.args[0]
idx = i
break
if idx is None:
return types
assert item is not None
if idx < prefix:
start = (item,) * (prefix - idx)
else:
start = ()
if len(types) - idx - 1 < suffix:
end = (item,) * (suffix - len(types) + idx + 1)
else:
end = ()
return types[:idx] + start + (types[idx],) + end + types[idx + 1 :]
def flatten_nested_unions(
types: Sequence[Type], handle_type_alias_type: bool = True
) -> list[Type]:
"""Flatten nested unions in a type list."""
if not isinstance(types, list):
typelist = list(types)
else:
typelist = cast("list[Type]", types)
# Fast path: most of the time there is nothing to flatten
if not any(isinstance(t, (TypeAliasType, UnionType)) for t in typelist): # type: ignore[misc]
return typelist
flat_items: list[Type] = []
for t in typelist:
tp = get_proper_type(t) if handle_type_alias_type else t
if isinstance(tp, ProperType) and isinstance(tp, UnionType):
flat_items.extend(
flatten_nested_unions(tp.items, handle_type_alias_type=handle_type_alias_type)
)
else:
# Must preserve original aliases when possible.
flat_items.append(t)
return flat_items
def flatten_nested_tuples(types: Sequence[Type]) -> list[Type]:
"""Recursively flatten TupleTypes nested with Unpack.
For example this will transform
Tuple[A, Unpack[Tuple[B, Unpack[Tuple[C, D]]]]]
into
Tuple[A, B, C, D]
"""
res = []
for typ in types:
if not isinstance(typ, UnpackType):
res.append(typ)
continue
p_type = get_proper_type(typ.type)
if not isinstance(p_type, TupleType):
res.append(typ)
continue
res.extend(flatten_nested_tuples(p_type.items))
return res
def is_literal_type(typ: ProperType, fallback_fullname: str, value: LiteralValue) -> bool:
"""Check if this type is a LiteralType with the given fallback type and value."""
if isinstance(typ, Instance) and typ.last_known_value:
typ = typ.last_known_value
return (
isinstance(typ, LiteralType)
and typ.fallback.type.fullname == fallback_fullname
and typ.value == value
)
names: Final = globals().copy()
names.pop("NOT_READY", None)
deserialize_map: Final = {
key: obj.deserialize
for key, obj in names.items()
if isinstance(obj, type) and issubclass(obj, Type) and obj is not Type
}
def callable_with_ellipsis(any_type: AnyType, ret_type: Type, fallback: Instance) -> CallableType:
"""Construct type Callable[..., ret_type]."""
return CallableType(
[any_type, any_type],
[ARG_STAR, ARG_STAR2],
[None, None],
ret_type=ret_type,
fallback=fallback,
is_ellipsis_args=True,
)
# This cyclic import is unfortunate, but to avoid it we would need to move away all uses
# of get_proper_type() from types.py. Majority of them have been removed, but few remaining
# are quite tricky to get rid of, but ultimately we want to do it at some point.
from mypy.expandtype import ExpandTypeVisitor
class InstantiateAliasVisitor(ExpandTypeVisitor):
def visit_union_type(self, t: UnionType) -> Type:
# Unlike regular expand_type(), we don't do any simplification for unions,
# not even removing strict duplicates. There are three reasons for this:
# * get_proper_type() is a very hot function, even slightest slow down will
# cause a perf regression
# * We want to preserve this historical behaviour, to avoid possible
# regressions
# * Simplifying unions may (indirectly) call get_proper_type(), causing
# infinite recursion.
return TypeTranslator.visit_union_type(self, t)