forked from VimPlug/jedi
Remove is_class_value from infer_type_vars
This commit is contained in:
@@ -268,7 +268,7 @@ class Value(HelperValueMixin):
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def get_type_hint(self, add_class_info=True):
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def get_type_hint(self, add_class_info=True):
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return None
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return None
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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"""
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"""
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When the current instance represents a type annotation, this method
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When the current instance represents a type annotation, this method
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tries to find information about undefined type vars and returns a dict
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tries to find information about undefined type vars and returns a dict
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@@ -294,14 +294,6 @@ class Value(HelperValueMixin):
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we're inferrined for, or (for recursive calls) their types. In the
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we're inferrined for, or (for recursive calls) their types. In the
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above example this would first be the representation of the list
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above example this would first be the representation of the list
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`[1]` and then, when recursing, just of `1`.
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`[1]` and then, when recursing, just of `1`.
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`is_class_value`: tells us whether or not to treat the `value_set` as
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representing the instances or types being passed, which is neccesary
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to correctly cope with `Type[T]` annotations. When it is True, this
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means that we are being called with a nested portion of an
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annotation and that the `value_set` represents the types of the
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arguments, rather than their actual instances. Note: not all
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recursive calls will neccesarily set this to True.
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"""
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"""
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return {}
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return {}
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@@ -538,7 +530,7 @@ class ValueSet(object):
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s = 'Optional[%s]' % s
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s = 'Optional[%s]' % s
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return s
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return s
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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# Circular
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# Circular
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from jedi.inference.gradual.annotation import merge_type_var_dicts
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from jedi.inference.gradual.annotation import merge_type_var_dicts
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@@ -546,7 +538,7 @@ class ValueSet(object):
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for value in self._set:
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for value in self._set:
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merge_type_var_dicts(
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merge_type_var_dicts(
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type_var_dict,
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type_var_dict,
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value.infer_type_vars(value_set, is_class_value),
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value.infer_type_vars(value_set),
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)
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)
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return type_var_dict
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return type_var_dict
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@@ -359,12 +359,7 @@ def merge_pairwise_generics(annotation_value, annotated_argument_class):
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for annotation_generics_set, actual_generic_set in zip(annotation_generics, actual_generics):
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for annotation_generics_set, actual_generic_set in zip(annotation_generics, actual_generics):
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merge_type_var_dicts(
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merge_type_var_dicts(
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type_var_dict,
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type_var_dict,
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annotation_generics_set.infer_type_vars(
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annotation_generics_set.infer_type_vars(actual_generic_set.execute_annotation()),
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actual_generic_set,
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# This is a note to ourselves that we have already
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# converted the instance representation to its class.
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is_class_value=True,
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),
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)
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)
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return type_var_dict
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return type_var_dict
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@@ -200,29 +200,27 @@ class GenericClass(ClassMixin, DefineGenericBase):
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return True
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return True
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return self._class_value.is_sub_class_of(class_value)
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return self._class_value.is_sub_class_of(class_value)
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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# Circular
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# Circular
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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annotation_name = self.py__name__()
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annotation_name = self.py__name__()
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type_var_dict = {}
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type_var_dict = {}
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if annotation_name == 'Iterable' and not is_class_value:
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if annotation_name == 'Iterable':
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annotation_generics = self.get_generics()
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annotation_generics = self.get_generics()
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if annotation_generics:
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if annotation_generics:
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return annotation_generics[0].infer_type_vars(
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return annotation_generics[0].infer_type_vars(
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value_set.merge_types_of_iterate(),
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value_set.merge_types_of_iterate(),
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)
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)
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else:
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else:
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# Note: we need to handle the MRO _in order_, so we need to extract
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# Note: we need to handle the MRO _in order_, so we need to extract
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# the elements from the set first, then handle them, even if we put
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# the elements from the set first, then handle them, even if we put
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# them back in a set afterwards.
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# them back in a set afterwards.
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for py_class in value_set:
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for py_class in value_set:
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if not is_class_value:
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if py_class.is_instance() and not py_class.is_compiled():
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if py_class.is_instance() and not py_class.is_compiled():
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py_class = py_class.get_annotated_class_object()
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py_class = py_class.get_annotated_class_object()
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else:
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else:
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continue
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continue
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if py_class.api_type != u'class':
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if py_class.api_type != u'class':
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# Functions & modules don't have an MRO and we're not
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# Functions & modules don't have an MRO and we're not
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@@ -107,11 +107,9 @@ class TypeVar(BaseTypingValue):
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def execute_annotation(self):
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def execute_annotation(self):
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return self._get_classes().execute_annotation()
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return self._get_classes().execute_annotation()
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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annotation_name = self.py__name__()
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annotation_name = self.py__name__()
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if not is_class_value:
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return {annotation_name: value_set.py__class__()}
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return {annotation_name: value_set.py__class__()}
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return {annotation_name: value_set}
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def __repr__(self):
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def __repr__(self):
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return '<%s: %s>' % (self.__class__.__name__, self.py__name__())
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return '<%s: %s>' % (self.__class__.__name__, self.py__name__())
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@@ -184,7 +184,7 @@ class _TypingClassMixin(ClassMixin):
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class TypingClassValueWithIndex(_TypingClassMixin, TypingValueWithIndex):
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class TypingClassValueWithIndex(_TypingClassMixin, TypingValueWithIndex):
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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# Circular
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# Circular
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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@@ -196,49 +196,18 @@ class TypingClassValueWithIndex(_TypingClassMixin, TypingValueWithIndex):
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annotation_name = self.py__name__()
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annotation_name = self.py__name__()
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if annotation_name == 'Type':
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if annotation_name == 'Type':
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if is_class_value:
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return annotation_generics[0].infer_type_vars(
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# This only applies if we are comparing something like
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value_set.execute_with_values(),
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# List[Type[int]] with Iterable[Type[int]]. First, Jedi tries to
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)
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# match List/Iterable. After that we will land here, because
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# is_class_value will be True at that point. Obviously we also
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# compare below that both sides are `Type`.
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for element in value_set:
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element_name = element.py__name__()
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if element_name == 'Type':
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merge_type_var_dicts(
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type_var_dict,
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merge_pairwise_generics(self, element),
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)
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else:
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return annotation_generics[0].infer_type_vars(
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value_set,
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is_class_value=True,
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)
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elif annotation_name == 'Callable':
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elif annotation_name == 'Callable':
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if len(annotation_generics) == 2:
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return annotation_generics[1].infer_type_vars(
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if is_class_value:
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value_set.execute_annotation(),
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# This only applies if we are comparing something like
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)
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# List[Callable[..., T]] with Iterable[Callable[..., T]].
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# First, Jedi tries to match List/Iterable. After that we
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# will land here, because is_class_value will be True at
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# that point. Obviously we also compare below that both
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# sides are `Callable`.
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for element in value_set:
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element_name = element.py__name__()
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if element_name == 'Callable':
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merge_type_var_dicts(
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type_var_dict,
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merge_pairwise_generics(self, element),
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)
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else:
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return annotation_generics[1].infer_type_vars(
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value_set.execute_annotation(),
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)
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elif annotation_name == 'Tuple':
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elif annotation_name == 'Tuple':
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tuple_annotation, = self.execute_annotation()
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tuple_annotation, = self.execute_annotation()
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return tuple_annotation.infer_type_vars(value_set, is_class_value)
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return tuple_annotation.infer_type_vars(value_set)
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return type_var_dict
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return type_var_dict
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@@ -337,7 +306,7 @@ class Tuple(BaseTypingValueWithGenerics):
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.py__getattribute__('tuple').execute_annotation()
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.py__getattribute__('tuple').execute_annotation()
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return tuple_
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return tuple_
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def infer_type_vars(self, value_set, is_class_value=False):
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def infer_type_vars(self, value_set):
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# Circular
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# Circular
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts
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from jedi.inference.gradual.base import GenericClass
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from jedi.inference.gradual.base import GenericClass
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@@ -346,14 +315,6 @@ class Tuple(BaseTypingValueWithGenerics):
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lambda x: x.py__name__().lower() == 'tuple',
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lambda x: x.py__name__().lower() == 'tuple',
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)
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)
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# Somewhat unusually, this `infer_type_vars` method is on an instance
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# representation of a type, rather than the annotation or class
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# representation. This means that as a starting point, we need to
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# convert the incoming values to their instance style if they're
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# classes, rather than the reverse.
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if is_class_value:
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value_set = value_set.execute_annotation()
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if self._is_homogenous():
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if self._is_homogenous():
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# The parameter annotation is of the form `Tuple[T, ...]`,
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# The parameter annotation is of the form `Tuple[T, ...]`,
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# so we treat the incoming tuple like a iterable sequence
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# so we treat the incoming tuple like a iterable sequence
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@@ -370,11 +331,8 @@ class Tuple(BaseTypingValueWithGenerics):
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type_var_dict = {}
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type_var_dict = {}
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for element in value_set:
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for element in value_set:
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if not is_class_value:
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py_class = element.get_annotated_class_object()
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py_class = element.get_annotated_class_object()
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if not isinstance(py_class, GenericClass):
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if not isinstance(py_class, GenericClass):
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py_class = element
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else:
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py_class = element
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py_class = element
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merge_type_var_dicts(
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merge_type_var_dicts(
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