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Remove is_class_value from infer_type_vars

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This commit is contained in:
Dave Halter
2020-05-08 17:49:02 +02:00
parent 12090ce74b
commit 2a227dcc7a
5 changed files with 23 additions and 82 deletions
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jedi/inference/gradual/typing.py
+11 -53
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@@ -184,7 +184,7 @@ class _TypingClassMixin(ClassMixin):
class TypingClassValueWithIndex(_TypingClassMixin, TypingValueWithIndex):
def infer_type_vars(self, value_set, is_class_value=False):
def infer_type_vars(self, value_set):
# Circular
from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
@@ -196,49 +196,18 @@ class TypingClassValueWithIndex(_TypingClassMixin, TypingValueWithIndex):
annotation_name = self.py__name__()
if annotation_name == 'Type':
if is_class_value:
# This only applies if we are comparing something like
# List[Type[int]] with Iterable[Type[int]]. First, Jedi tries to
# match List/Iterable. After that we will land here, because
# is_class_value will be True at that point. Obviously we also
# compare below that both sides are `Type`.
for element in value_set:
element_name = element.py__name__()
if element_name == 'Type':
merge_type_var_dicts(
type_var_dict,
merge_pairwise_generics(self, element),
)
else:
return annotation_generics[0].infer_type_vars(
value_set,
is_class_value=True,
)
return annotation_generics[0].infer_type_vars(
value_set.execute_with_values(),
)
elif annotation_name == 'Callable':
if len(annotation_generics) == 2:
if is_class_value:
# This only applies if we are comparing something like
# List[Callable[..., T]] with Iterable[Callable[..., T]].
# First, Jedi tries to match List/Iterable. After that we
# will land here, because is_class_value will be True at
# that point. Obviously we also compare below that both
# sides are `Callable`.
for element in value_set:
element_name = element.py__name__()
if element_name == 'Callable':
merge_type_var_dicts(
type_var_dict,
merge_pairwise_generics(self, element),
)
else:
return annotation_generics[1].infer_type_vars(
value_set.execute_annotation(),
)
return annotation_generics[1].infer_type_vars(
value_set.execute_annotation(),
)
elif annotation_name == 'Tuple':
tuple_annotation, = self.execute_annotation()
return tuple_annotation.infer_type_vars(value_set, is_class_value)
return tuple_annotation.infer_type_vars(value_set)
return type_var_dict
@@ -337,7 +306,7 @@ class Tuple(BaseTypingValueWithGenerics):
.py__getattribute__('tuple').execute_annotation()
return tuple_
def infer_type_vars(self, value_set, is_class_value=False):
def infer_type_vars(self, value_set):
# Circular
from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
from jedi.inference.gradual.base import GenericClass
@@ -346,14 +315,6 @@ class Tuple(BaseTypingValueWithGenerics):
lambda x: x.py__name__().lower() == 'tuple',
)
# Somewhat unusually, this `infer_type_vars` method is on an instance
# representation of a type, rather than the annotation or class
# representation. This means that as a starting point, we need to
# convert the incoming values to their instance style if they're
# classes, rather than the reverse.
if is_class_value:
value_set = value_set.execute_annotation()
if self._is_homogenous():
# The parameter annotation is of the form `Tuple[T, ...]`,
# so we treat the incoming tuple like a iterable sequence
@@ -370,11 +331,8 @@ class Tuple(BaseTypingValueWithGenerics):
type_var_dict = {}
for element in value_set:
if not is_class_value:
py_class = element.get_annotated_class_object()
if not isinstance(py_class, GenericClass):
py_class = element
else:
py_class = element.get_annotated_class_object()
if not isinstance(py_class, GenericClass):
py_class = element
merge_type_var_dicts(