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Peter Law
2020-03-07 17:35:03 +00:00
parent 95cec459a8
commit 5d273f4630
1 changed files with 8 additions and 0 deletions
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8
jedi/inference/gradual/annotation.py
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@@ -460,6 +460,9 @@ def _infer_type_vars(annotation_value, value_set, is_class_value=False):
tuple_annotation, = annotation_value.execute_annotation() tuple_annotation, = annotation_value.execute_annotation()
# TODO: is can we avoid using this private method? # TODO: is can we avoid using this private method?
if tuple_annotation._is_homogenous(): 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]: for nested_annotation_value in annotation_generics[0]:
_merge_type_var_dicts( _merge_type_var_dicts(
type_var_dict, type_var_dict,
@@ -469,6 +472,11 @@ def _infer_type_vars(annotation_value, value_set, is_class_value=False):
), ),
) )
else: 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.
actual_generics = py_class.get_generics() actual_generics = py_class.get_generics()
merge_pairwise_generics(annotation_generics, actual_generics) merge_pairwise_generics(annotation_generics, actual_generics)