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applytype.py
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from __future__ import annotations
from typing import Callable, Sequence
import mypy.subtypes
from mypy.erasetype import erase_typevars
from mypy.expandtype import expand_type
from mypy.nodes import Context
from mypy.types import (
AnyType,
CallableType,
ParamSpecType,
PartialType,
Type,
TypeVarId,
TypeVarLikeType,
TypeVarTupleType,
TypeVarType,
UninhabitedType,
UnpackType,
get_proper_type,
)
def get_target_type(
tvar: TypeVarLikeType,
type: Type,
callable: CallableType,
report_incompatible_typevar_value: Callable[[CallableType, Type, str, Context], None],
context: Context,
skip_unsatisfied: bool,
) -> Type | None:
p_type = get_proper_type(type)
if isinstance(p_type, UninhabitedType) and tvar.has_default():
return tvar.default
if isinstance(tvar, ParamSpecType):
return type
if isinstance(tvar, TypeVarTupleType):
return type
assert isinstance(tvar, TypeVarType)
values = tvar.values
if values:
if isinstance(p_type, AnyType):
return type
if isinstance(p_type, TypeVarType) and p_type.values:
# Allow substituting T1 for T if every allowed value of T1
# is also a legal value of T.
if all(any(mypy.subtypes.is_same_type(v, v1) for v in values) for v1 in p_type.values):
return type
matching = []
for value in values:
if mypy.subtypes.is_subtype(type, value):
matching.append(value)
if matching:
best = matching[0]
# If there are more than one matching value, we select the narrowest
for match in matching[1:]:
if mypy.subtypes.is_subtype(match, best):
best = match
return best
if skip_unsatisfied:
return None
report_incompatible_typevar_value(callable, type, tvar.name, context)
else:
upper_bound = tvar.upper_bound
if tvar.name == "Self":
# Internally constructed Self-types contain class type variables in upper bound,
# so we need to erase them to avoid false positives. This is safe because we do
# not support type variables in upper bounds of user defined types.
upper_bound = erase_typevars(upper_bound)
if not mypy.subtypes.is_subtype(type, upper_bound):
if skip_unsatisfied:
return None
report_incompatible_typevar_value(callable, type, tvar.name, context)
return type
def apply_generic_arguments(
callable: CallableType,
orig_types: Sequence[Type | None],
report_incompatible_typevar_value: Callable[[CallableType, Type, str, Context], None],
context: Context,
skip_unsatisfied: bool = False,
) -> CallableType:
"""Apply generic type arguments to a callable type.
For example, applying [int] to 'def [T] (T) -> T' results in
'def (int) -> int'.
Note that each type can be None; in this case, it will not be applied.
If `skip_unsatisfied` is True, then just skip the types that don't satisfy type variable
bound or constraints, instead of giving an error.
"""
tvars = callable.variables
min_arg_count = sum(not tv.has_default() for tv in tvars)
assert min_arg_count <= len(orig_types) <= len(tvars)
# Check that inferred type variable values are compatible with allowed
# values and bounds. Also, promote subtype values to allowed values.
# Create a map from type variable id to target type.
id_to_type: dict[TypeVarId, Type] = {}
for tvar, type in zip(tvars, orig_types):
assert not isinstance(type, PartialType), "Internal error: must never apply partial type"
if type is None:
continue
target_type = get_target_type(
tvar, type, callable, report_incompatible_typevar_value, context, skip_unsatisfied
)
if target_type is not None:
id_to_type[tvar.id] = target_type
# TODO: validate arg_kinds/arg_names for ParamSpec and TypeVarTuple replacements,
# not just type variable bounds above.
param_spec = callable.param_spec()
if param_spec is not None:
nt = id_to_type.get(param_spec.id)
if nt is not None:
# ParamSpec expansion is special-cased, so we need to always expand callable
# as a whole, not expanding arguments individually.
callable = expand_type(callable, id_to_type)
assert isinstance(callable, CallableType)
return callable.copy_modified(
variables=[tv for tv in tvars if tv.id not in id_to_type]
)
# Apply arguments to argument types.
var_arg = callable.var_arg()
if var_arg is not None and isinstance(var_arg.typ, UnpackType):
# Same as for ParamSpec, callable with variadic types needs to be expanded as a whole.
callable = expand_type(callable, id_to_type)
assert isinstance(callable, CallableType)
return callable.copy_modified(variables=[tv for tv in tvars if tv.id not in id_to_type])
else:
callable = callable.copy_modified(
arg_types=[expand_type(at, id_to_type) for at in callable.arg_types]
)
# Apply arguments to TypeGuard and TypeIs if any.
if callable.type_guard is not None:
type_guard = expand_type(callable.type_guard, id_to_type)
else:
type_guard = None
if callable.type_is is not None:
type_is = expand_type(callable.type_is, id_to_type)
else:
type_is = None
# The callable may retain some type vars if only some were applied.
# TODO: move apply_poly() logic from checkexpr.py here when new inference
# becomes universally used (i.e. in all passes + in unification).
# With this new logic we can actually *add* some new free variables.
remaining_tvars: list[TypeVarLikeType] = []
for tv in tvars:
if tv.id in id_to_type:
continue
if not tv.has_default():
remaining_tvars.append(tv)
continue
# TypeVarLike isn't in id_to_type mapping.
# Only expand the TypeVar default here.
typ = expand_type(tv, id_to_type)
assert isinstance(typ, TypeVarLikeType)
remaining_tvars.append(typ)
return callable.copy_modified(
ret_type=expand_type(callable.ret_type, id_to_type),
variables=remaining_tvars,
type_guard=type_guard,
type_is=type_is,
)