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Clarify generic tuple inference

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This hoist a loop invariant conditional check outside the loop
making it clearer and one branch more obviously similar to the
general type handling.
This commit is contained in:
Peter Law
2020-03-07 17:35:29 +00:00
parent 5d273f4630
commit 96132587b7
1 changed files with 28 additions and 28 deletions
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56
jedi/inference/gradual/annotation.py
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@@ -445,37 +445,37 @@ def _infer_type_vars(annotation_value, value_set, is_class_value=False):
)
)
elif annotation_name == 'Tuple':
# TODO: this logic is pretty similar to the general logic below, can
# we combine them?
annotation_generics = annotation_value.get_generics()
tuple_annotation, = annotation_value.execute_annotation()
# TODO: is can we avoid using this private method?
if tuple_annotation._is_homogenous():
# The parameter annotation is of the form `Tuple[T, ...]`,
# so we treat the incoming tuple like a iterable sequence
# rather than a positional container of elements.
for nested_annotation_value in annotation_generics[0]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_set.merge_types_of_iterate(),
),
)
else:
# The parameter annotation has only explicit type parameters
# (e.g: `Tuple[T]`, `Tuple[T, U]`, `Tuple[T, U, V]`, etc.) so we
# treat the incoming values as needing to match the annotation
# exactly, just as we would for non-tuple annotations.
for element in value_set:
py_class = element.get_annotated_class_object()
if not isinstance(py_class, GenericClass):
py_class = element
# TODO: this logic is pretty similar to the general logic below, can
# we combine them?
if not isinstance(py_class, DefineGenericBase):
continue
for element in value_set:
py_class = element.get_annotated_class_object()
if not isinstance(py_class, GenericClass):
py_class = element
annotation_generics = annotation_value.get_generics()
tuple_annotation, = annotation_value.execute_annotation()
# TODO: is can we avoid using this private method?
if tuple_annotation._is_homogenous():
# The parameter annotation is of the form `Tuple[T, ...]`,
# so we treat the incoming tuple like a iterable sequence
# rather than a positional container of elements.
for nested_annotation_value in annotation_generics[0]:
_merge_type_var_dicts(
type_var_dict,
_infer_type_vars(
nested_annotation_value,
value_set.merge_types_of_iterate(),
),
)
else:
# The parameter annotation has only explicit type parameters
# (e.g: `Tuple[T]`, `Tuple[T, U]`, `Tuple[T, U, V]`, etc.) so we
# treat the incoming values as needing to match the annotation
# exactly, just as we would for non-tuple annotations.
if not isinstance(py_class, DefineGenericBase):
continue
actual_generics = py_class.get_generics()
merge_pairwise_generics(annotation_generics, actual_generics)