def analyze_type_type_member_access(name: str, typ: TypeType, mx: MemberContext) -> Type:
# Similar to analyze_type_callable_attribute_access.
item = None
fallback = mx.builtin_type('builtins.type')
ignore_messages = mx.msg.copy()
ignore_messages.disable_errors()
if isinstance(typ.item, Instance):
item = typ.item
elif isinstance(typ.item, AnyType):
mx = mx.copy_modified(messages=ignore_messages)
return _analyze_member_access(name, fallback, mx)
elif isinstance(typ.item, TypeVarType):
if isinstance(typ.item.upper_bound, Instance):
item = typ.item.upper_bound
elif isinstance(typ.item, TupleType):
item = tuple_fallback(typ.item)
elif isinstance(typ.item, FunctionLike) and typ.item.is_type_obj():
item = typ.item.fallback
elif isinstance(typ.item, TypeType):
# Access member on metaclass object via Type[Type[C]]
if isinstance(typ.item.item, Instance):
item = typ.item.item.type.metaclass_type
if item and not mx.is_operator:
# See comment above for why operators are skipped
result = analyze_class_attribute_access(item, name, mx)
if result:
if not (isinstance(result, AnyType) and item.type.fallback_to_any):
return result
else:
# We don't want errors on metaclass lookup for classes with Any fallback
mx = mx.copy_modified(messages=ignore_messages)
if item is not None:
fallback = item.type.metaclass_type or fallback
return _analyze_member_access(name, fallback, mx)
def map_type_from_supertype(typ: Type,
sub_info: TypeInfo,
super_info: TypeInfo) -> Type:
"""Map type variables in a type defined in a supertype context to be valid
in the subtype context. Assume that the result is unique; if more than
one type is possible, return one of the alternatives.
For example, assume
. class D(Generic[S]) ...
. class C(D[E[T]], Generic[T]) ...
Now S in the context of D would be mapped to E[T] in the context of C.
"""
# Create the type of self in subtype, of form t[a1, ...].
inst_type = fill_typevars(sub_info)
if isinstance(inst_type, TupleType):
inst_type = tuple_fallback(inst_type)
# Map the type of self to supertype. This gets us a description of the
# supertype type variables in terms of subtype variables, i.e. t[t1, ...]
# so that any type variables in tN are to be interpreted in subtype
# context.
inst_type = map_instance_to_supertype(inst_type, super_info)
# Finally expand the type variables in type with those in the previously
# constructed type. Note that both type and inst_type may have type
# variables, but in type they are interpreted in supertype context while
# in inst_type they are interpreted in subtype context. This works even if
# the names of type variables in supertype and subtype overlap.
return expand_type_by_instance(typ, inst_type)
def _analyze_member_access(name: str,
typ: Type,
mx: MemberContext,
override_info: Optional[TypeInfo] = None) -> Type:
# TODO: This and following functions share some logic with subtypes.find_member;
# consider refactoring.
if isinstance(typ, Instance):
return analyze_instance_member_access(name, typ, mx, override_info)
elif isinstance(typ, AnyType):
# The base object has dynamic type.
return AnyType(TypeOfAny.from_another_any, source_any=typ)
elif isinstance(typ, UnionType):
return analyze_union_member_access(name, typ, mx)
elif isinstance(typ, FunctionLike) and typ.is_type_obj():
return analyze_type_callable_member_access(name, typ, mx)
elif isinstance(typ, TypeType):
return analyze_type_type_member_access(name, typ, mx)
elif isinstance(typ, TupleType):
# Actually look up from the fallback instance type.
return _analyze_member_access(name, tuple_fallback(typ), mx)
elif isinstance(typ, (TypedDictType, LiteralType, FunctionLike)):
# Actually look up from the fallback instance type.
return _analyze_member_access(name, typ.fallback, mx)
elif isinstance(typ, NoneTyp):
return analyze_none_member_access(name, typ, mx)
elif isinstance(typ, TypeVarType):
return _analyze_member_access(name, typ.upper_bound, mx)
elif isinstance(typ, DeletedType):
mx.msg.deleted_as_rvalue(typ, mx.context)
return AnyType(TypeOfAny.from_error)
if mx.chk.should_suppress_optional_error([typ]):
return AnyType(TypeOfAny.from_error)
return mx.msg.has_no_attr(mx.original_type, typ, name, mx.context)
def analyze_type_callable_member_access(name: str,
typ: FunctionLike,
mx: MemberContext) -> Type:
# Class attribute.
# TODO super?
ret_type = typ.items()[0].ret_type
if isinstance(ret_type, TupleType):
ret_type = tuple_fallback(ret_type)
if isinstance(ret_type, Instance):
if not mx.is_operator:
# When Python sees an operator (eg `3 == 4`), it automatically translates that
# into something like `int.__eq__(3, 4)` instead of `(3).__eq__(4)` as an
# optimization.
#
# While it normally it doesn't matter which of the two versions are used, it
# does cause inconsistencies when working with classes. For example, translating
# `int == int` to `int.__eq__(int)` would not work since `int.__eq__` is meant to
# compare two int _instances_. What we really want is `type(int).__eq__`, which
# is meant to compare two types or classes.
#
# This check makes sure that when we encounter an operator, we skip looking up
# the corresponding method in the current instance to avoid this edge case.
# See https://github.com/python/mypy/pull/1787 for more info.
result = analyze_class_attribute_access(ret_type, name, mx)
if result:
return result
# Look up from the 'type' type.
return _analyze_member_access(name, typ.fallback, mx)
else:
assert False, 'Unexpected type {}'.format(repr(ret_type))
def visit_tuple_type(self, t: TupleType) -> Type:
if isinstance(self.s, TupleType) and self.s.length() == t.length():
items = [] # type: List[Type]
for i in range(t.length()):
items.append(self.meet(t.items[i], self.s.items[i]))
# TODO: What if the fallbacks are different?
return TupleType(items, tuple_fallback(t))
elif isinstance(self.s, Instance):
# meet(Tuple[t1, t2, <...>], Tuple[s, ...]) == Tuple[meet(t1, s), meet(t2, s), <...>].
if self.s.type.fullname() == 'builtins.tuple' and self.s.args:
return t.copy_modified(items=[meet_types(it, self.s.args[0]) for it in t.items])
elif is_proper_subtype(t, self.s):
# A named tuple that inherits from a normal class
return t
return self.default(self.s)
def is_overlapping_types(left: Type,
right: Type,
ignore_promotions: bool = False,
prohibit_none_typevar_overlap: bool = False) -> bool:
"""Can a value of type 'left' also be of type 'right' or vice-versa?
If 'ignore_promotions' is True, we ignore promotions while checking for overlaps.
If 'prohibit_none_typevar_overlap' is True, we disallow None from overlapping with
TypeVars (in both strict-optional and non-strict-optional mode).
"""
left = get_proper_type(left)
right = get_proper_type(right)
def _is_overlapping_types(left: Type, right: Type) -> bool:
'''Encode the kind of overlapping check to perform.
This function mostly exists so we don't have to repeat keyword arguments everywhere.'''
return is_overlapping_types(
left,
right,
ignore_promotions=ignore_promotions,
prohibit_none_typevar_overlap=prohibit_none_typevar_overlap)
# We should never encounter this type.
if isinstance(left, PartialType) or isinstance(right, PartialType):
assert False, "Unexpectedly encountered partial type"
# We should also never encounter these types, but it's possible a few
# have snuck through due to unrelated bugs. For now, we handle these
# in the same way we handle 'Any'.
#
# TODO: Replace these with an 'assert False' once we are more confident.
illegal_types = (UnboundType, ErasedType, DeletedType)
if isinstance(left, illegal_types) or isinstance(right, illegal_types):
return True
# 'Any' may or may not be overlapping with the other type
if isinstance(left, AnyType) or isinstance(right, AnyType):
return True
# When running under non-strict optional mode, simplify away types of
# the form 'Union[A, B, C, None]' into just 'Union[A, B, C]'.
if not state.strict_optional:
if isinstance(left, UnionType):
left = UnionType.make_union(left.relevant_items())
if isinstance(right, UnionType):
right = UnionType.make_union(right.relevant_items())
# We check for complete overlaps next as a general-purpose failsafe.
# If this check fails, we start checking to see if there exists a
# *partial* overlap between types.
#
# These checks will also handle the NoneType and UninhabitedType cases for us.
if (is_proper_subtype(left, right, ignore_promotions=ignore_promotions)
or is_proper_subtype(
right, left, ignore_promotions=ignore_promotions)):
return True
# See the docstring for 'get_possible_variants' for more info on what the
# following lines are doing.
left_possible = get_possible_variants(left)
right_possible = get_possible_variants(right)
# We start by checking multi-variant types like Unions first. We also perform
# the same logic if either type happens to be a TypeVar.
#
# Handling the TypeVars now lets us simulate having them bind to the corresponding
# type -- if we deferred these checks, the "return-early" logic of the other
# checks will prevent us from detecting certain overlaps.
#
# If both types are singleton variants (and are not TypeVars), we've hit the base case:
# we skip these checks to avoid infinitely recursing.
def is_none_typevar_overlap(t1: ProperType, t2: ProperType) -> bool:
return isinstance(t1, NoneType) and isinstance(t2, TypeVarType)
if prohibit_none_typevar_overlap:
if is_none_typevar_overlap(left, right) or is_none_typevar_overlap(
right, left):
return False
if (len(left_possible) > 1 or len(right_possible) > 1
or isinstance(left, TypeVarType)
or isinstance(right, TypeVarType)):
for l in left_possible:
for r in right_possible:
if _is_overlapping_types(l, r):
return True
return False
# Now that we've finished handling TypeVars, we're free to end early
# if one one of the types is None and we're running in strict-optional mode.
# (None only overlaps with None in strict-optional mode).
#
# We must perform this check after the TypeVar checks because
# a TypeVar could be bound to None, for example.
if state.strict_optional and isinstance(left, NoneType) != isinstance(
right, NoneType):
return False
# Next, we handle single-variant types that may be inherently partially overlapping:
#
# - TypedDicts
# - Tuples
#
# If we cannot identify a partial overlap and end early, we degrade these two types
# into their 'Instance' fallbacks.
if isinstance(left, TypedDictType) and isinstance(right, TypedDictType):
return are_typed_dicts_overlapping(left,
right,
ignore_promotions=ignore_promotions)
elif typed_dict_mapping_pair(left, right):
# Overlaps between TypedDicts and Mappings require dedicated logic.
return typed_dict_mapping_overlap(left,
right,
overlapping=_is_overlapping_types)
elif isinstance(left, TypedDictType):
left = left.fallback
elif isinstance(right, TypedDictType):
right = right.fallback
if is_tuple(left) and is_tuple(right):
return are_tuples_overlapping(left,
right,
ignore_promotions=ignore_promotions)
elif isinstance(left, TupleType):
left = tuple_fallback(left)
elif isinstance(right, TupleType):
right = tuple_fallback(right)
# Next, we handle single-variant types that cannot be inherently partially overlapping,
# but do require custom logic to inspect.
#
# As before, we degrade into 'Instance' whenever possible.
if isinstance(left, TypeType) and isinstance(right, TypeType):
return _is_overlapping_types(left.item, right.item)
def _type_object_overlap(left: ProperType, right: ProperType) -> bool:
"""Special cases for type object types overlaps."""
# TODO: these checks are a bit in gray area, adjust if they cause problems.
# 1. Type[C] vs Callable[..., C], where the latter is class object.
if isinstance(left, TypeType) and isinstance(
right, CallableType) and right.is_type_obj():
return _is_overlapping_types(left.item, right.ret_type)
# 2. Type[C] vs Meta, where Meta is a metaclass for C.
if isinstance(left, TypeType) and isinstance(right, Instance):
if isinstance(left.item, Instance):
left_meta = left.item.type.metaclass_type
if left_meta is not None:
return _is_overlapping_types(left_meta, right)
# builtins.type (default metaclass) overlaps with all metaclasses
return right.type.has_base('builtins.type')
elif isinstance(left.item, AnyType):
return right.type.has_base('builtins.type')
# 3. Callable[..., C] vs Meta is considered below, when we switch to fallbacks.
return False
if isinstance(left, TypeType) or isinstance(right, TypeType):
return _type_object_overlap(left, right) or _type_object_overlap(
right, left)
if isinstance(left, CallableType) and isinstance(right, CallableType):
return is_callable_compatible(left,
right,
is_compat=_is_overlapping_types,
ignore_pos_arg_names=True,
allow_partial_overlap=True)
elif isinstance(left, CallableType):
left = left.fallback
elif isinstance(right, CallableType):
right = right.fallback
if isinstance(left, LiteralType) and isinstance(right, LiteralType):
if left.value == right.value:
# If values are the same, we still need to check if fallbacks are overlapping,
# this is done below.
left = left.fallback
right = right.fallback
else:
return False
elif isinstance(left, LiteralType):
left = left.fallback
elif isinstance(right, LiteralType):
right = right.fallback
# Finally, we handle the case where left and right are instances.
if isinstance(left, Instance) and isinstance(right, Instance):
# First we need to handle promotions and structural compatibility for instances
# that came as fallbacks, so simply call is_subtype() to avoid code duplication.
if (is_subtype(left, right, ignore_promotions=ignore_promotions) or
is_subtype(right, left, ignore_promotions=ignore_promotions)):
return True
# Two unrelated types cannot be partially overlapping: they're disjoint.
if left.type.has_base(right.type.fullname()):
left = map_instance_to_supertype(left, right.type)
elif right.type.has_base(left.type.fullname()):
right = map_instance_to_supertype(right, left.type)
else:
return False
if len(left.args) == len(right.args):
# Note: we don't really care about variance here, since the overlapping check
# is symmetric and since we want to return 'True' even for partial overlaps.
#
# For example, suppose we have two types Wrapper[Parent] and Wrapper[Child].
# It doesn't matter whether Wrapper is covariant or contravariant since
# either way, one of the two types will overlap with the other.
#
# Similarly, if Wrapper was invariant, the two types could still be partially
# overlapping -- what if Wrapper[Parent] happened to contain only instances of
# specifically Child?
#
# Or, to use a more concrete example, List[Union[A, B]] and List[Union[B, C]]
# would be considered partially overlapping since it's possible for both lists
# to contain only instances of B at runtime.
for left_arg, right_arg in zip(left.args, right.args):
if _is_overlapping_types(left_arg, right_arg):
return True
return False
# We ought to have handled every case by now: we conclude the
# two types are not overlapping, either completely or partially.
#
# Note: it's unclear however, whether returning False is the right thing
# to do when inferring reachability -- see https://github.com/python/mypy/issues/5529
assert type(left) != type(right)
return False
def visit_tuple_type(self, left: TupleType) -> bool:
if isinstance(self.right, TupleType):
return (is_same_type(tuple_fallback(left), tuple_fallback(self.right))
and is_same_types(left.items, self.right.items))
else:
return False
def visit_tuple_type(self, left: TupleType) -> bool:
if isinstance(self.right, TupleType):
return (is_same_type(tuple_fallback(left), tuple_fallback(self.right))
and is_same_types(left.items, self.right.items))
else:
return False
def is_overlapping_types(left: Type,
right: Type,
ignore_promotions: bool = False,
prohibit_none_typevar_overlap: bool = False) -> bool:
"""Can a value of type 'left' also be of type 'right' or vice-versa?
If 'ignore_promotions' is True, we ignore promotions while checking for overlaps.
If 'prohibit_none_typevar_overlap' is True, we disallow None from overlapping with
TypeVars (in both strict-optional and non-strict-optional mode).
"""
def _is_overlapping_types(left: Type, right: Type) -> bool:
'''Encode the kind of overlapping check to perform.
This function mostly exists so we don't have to repeat keyword arguments everywhere.'''
return is_overlapping_types(
left, right,
ignore_promotions=ignore_promotions,
prohibit_none_typevar_overlap=prohibit_none_typevar_overlap)
# We should never encounter this type.
if isinstance(left, PartialType) or isinstance(right, PartialType):
assert False, "Unexpectedly encountered partial type"
# We should also never encounter these types, but it's possible a few
# have snuck through due to unrelated bugs. For now, we handle these
# in the same way we handle 'Any'.
#
# TODO: Replace these with an 'assert False' once we are more confident.
illegal_types = (UnboundType, ErasedType, DeletedType)
if isinstance(left, illegal_types) or isinstance(right, illegal_types):
return True
# 'Any' may or may not be overlapping with the other type
if isinstance(left, AnyType) or isinstance(right, AnyType):
return True
# When running under non-strict optional mode, simplify away types of
# the form 'Union[A, B, C, None]' into just 'Union[A, B, C]'.
if not state.strict_optional:
if isinstance(left, UnionType):
left = UnionType.make_union(left.relevant_items())
if isinstance(right, UnionType):
right = UnionType.make_union(right.relevant_items())
# We check for complete overlaps next as a general-purpose failsafe.
# If this check fails, we start checking to see if there exists a
# *partial* overlap between types.
#
# These checks will also handle the NoneType and UninhabitedType cases for us.
if (is_proper_subtype(left, right, ignore_promotions=ignore_promotions)
or is_proper_subtype(right, left, ignore_promotions=ignore_promotions)):
return True
# See the docstring for 'get_possible_variants' for more info on what the
# following lines are doing.
left_possible = get_possible_variants(left)
right_possible = get_possible_variants(right)
# We start by checking multi-variant types like Unions first. We also perform
# the same logic if either type happens to be a TypeVar.
#
# Handling the TypeVars now lets us simulate having them bind to the corresponding
# type -- if we deferred these checks, the "return-early" logic of the other
# checks will prevent us from detecting certain overlaps.
#
# If both types are singleton variants (and are not TypeVars), we've hit the base case:
# we skip these checks to avoid infinitely recursing.
def is_none_typevar_overlap(t1: Type, t2: Type) -> bool:
return isinstance(t1, NoneType) and isinstance(t2, TypeVarType)
if prohibit_none_typevar_overlap:
if is_none_typevar_overlap(left, right) or is_none_typevar_overlap(right, left):
return False
if (len(left_possible) > 1 or len(right_possible) > 1
or isinstance(left, TypeVarType) or isinstance(right, TypeVarType)):
for l in left_possible:
for r in right_possible:
if _is_overlapping_types(l, r):
return True
return False
# Now that we've finished handling TypeVars, we're free to end early
# if one one of the types is None and we're running in strict-optional mode.
# (None only overlaps with None in strict-optional mode).
#
# We must perform this check after the TypeVar checks because
# a TypeVar could be bound to None, for example.
if state.strict_optional and isinstance(left, NoneType) != isinstance(right, NoneType):
return False
# Next, we handle single-variant types that may be inherently partially overlapping:
#
# - TypedDicts
# - Tuples
#
# If we cannot identify a partial overlap and end early, we degrade these two types
# into their 'Instance' fallbacks.
if isinstance(left, TypedDictType) and isinstance(right, TypedDictType):
return are_typed_dicts_overlapping(left, right, ignore_promotions=ignore_promotions)
elif isinstance(left, TypedDictType):
left = left.fallback
elif isinstance(right, TypedDictType):
right = right.fallback
if is_tuple(left) and is_tuple(right):
return are_tuples_overlapping(left, right, ignore_promotions=ignore_promotions)
elif isinstance(left, TupleType):
left = tuple_fallback(left)
elif isinstance(right, TupleType):
right = tuple_fallback(right)
# Next, we handle single-variant types that cannot be inherently partially overlapping,
# but do require custom logic to inspect.
#
# As before, we degrade into 'Instance' whenever possible.
if isinstance(left, TypeType) and isinstance(right, TypeType):
return _is_overlapping_types(left.item, right.item)
def _type_object_overlap(left: Type, right: Type) -> bool:
"""Special cases for type object types overlaps."""
# TODO: these checks are a bit in gray area, adjust if they cause problems.
# 1. Type[C] vs Callable[..., C], where the latter is class object.
if isinstance(left, TypeType) and isinstance(right, CallableType) and right.is_type_obj():
return _is_overlapping_types(left.item, right.ret_type)
# 2. Type[C] vs Meta, where Meta is a metaclass for C.
if (isinstance(left, TypeType) and isinstance(left.item, Instance) and
isinstance(right, Instance)):
left_meta = left.item.type.metaclass_type
if left_meta is not None:
return _is_overlapping_types(left_meta, right)
# builtins.type (default metaclass) overlaps with all metaclasses
return right.type.has_base('builtins.type')
# 3. Callable[..., C] vs Meta is considered below, when we switch to fallbacks.
return False
if isinstance(left, TypeType) or isinstance(right, TypeType):
return _type_object_overlap(left, right) or _type_object_overlap(right, left)
if isinstance(left, CallableType) and isinstance(right, CallableType):
return is_callable_compatible(left, right,
is_compat=_is_overlapping_types,
ignore_pos_arg_names=True,
allow_partial_overlap=True)
elif isinstance(left, CallableType):
left = left.fallback
elif isinstance(right, CallableType):
right = right.fallback
if isinstance(left, LiteralType) and isinstance(right, LiteralType):
return left == right
elif isinstance(left, LiteralType):
left = left.fallback
elif isinstance(right, LiteralType):
right = right.fallback
# Finally, we handle the case where left and right are instances.
if isinstance(left, Instance) and isinstance(right, Instance):
if left.type.is_protocol and is_protocol_implementation(right, left):
return True
if right.type.is_protocol and is_protocol_implementation(left, right):
return True
# Two unrelated types cannot be partially overlapping: they're disjoint.
# We don't need to handle promotions because they've already been handled
# by the calls to `is_subtype(...)` up above (and promotable types never
# have any generic arguments we need to recurse on).
if left.type.has_base(right.type.fullname()):
left = map_instance_to_supertype(left, right.type)
elif right.type.has_base(left.type.fullname()):
right = map_instance_to_supertype(right, left.type)
else:
return False
if len(left.args) == len(right.args):
# Note: we don't really care about variance here, since the overlapping check
# is symmetric and since we want to return 'True' even for partial overlaps.
#
# For example, suppose we have two types Wrapper[Parent] and Wrapper[Child].
# It doesn't matter whether Wrapper is covariant or contravariant since
# either way, one of the two types will overlap with the other.
#
# Similarly, if Wrapper was invariant, the two types could still be partially
# overlapping -- what if Wrapper[Parent] happened to contain only instances of
# specifically Child?
#
# Or, to use a more concrete example, List[Union[A, B]] and List[Union[B, C]]
# would be considered partially overlapping since it's possible for both lists
# to contain only instances of B at runtime.
for left_arg, right_arg in zip(left.args, right.args):
if _is_overlapping_types(left_arg, right_arg):
return True
return False
# We ought to have handled every case by now: we conclude the
# two types are not overlapping, either completely or partially.
#
# Note: it's unclear however, whether returning False is the right thing
# to do when inferring reachability -- see https://github.com/python/mypy/issues/5529
assert type(left) != type(right)
return False
