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435 lines
15 KiB
Python
435 lines
15 KiB
Python
from jedi.inference.cache import inference_state_method_cache
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from jedi.inference.base_value import ValueSet, NO_VALUES, Value, \
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iterator_to_value_set, LazyValueWrapper, ValueWrapper
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from jedi.inference.compiled import builtin_from_name
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from jedi.inference.value.klass import ClassFilter
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from jedi.inference.value.klass import ClassMixin
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from jedi.inference.utils import to_list
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from jedi.inference.names import AbstractNameDefinition, ValueName
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from jedi.inference.context import ClassContext
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from jedi.inference.gradual.generics import TupleGenericManager
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class _BoundTypeVarName(AbstractNameDefinition):
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"""
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This type var was bound to a certain type, e.g. int.
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"""
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def __init__(self, type_var, value_set):
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self._type_var = type_var
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self.parent_context = type_var.parent_context
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self._value_set = value_set
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def infer(self):
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def iter_():
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for value in self._value_set:
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# Replace any with the constraints if they are there.
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from jedi.inference.gradual.typing import AnyClass
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if isinstance(value, AnyClass):
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yield from self._type_var.constraints
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else:
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yield value
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return ValueSet(iter_())
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def py__name__(self):
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return self._type_var.py__name__()
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def __repr__(self):
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return '<%s %s -> %s>' % (self.__class__.__name__, self.py__name__(), self._value_set)
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class _TypeVarFilter:
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"""
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A filter for all given variables in a class.
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A = TypeVar('A')
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B = TypeVar('B')
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class Foo(Mapping[A, B]):
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...
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In this example we would have two type vars given: A and B
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"""
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def __init__(self, generics, type_vars):
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self._generics = generics
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self._type_vars = type_vars
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def get(self, name):
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for i, type_var in enumerate(self._type_vars):
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if type_var.py__name__() == name:
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try:
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return [_BoundTypeVarName(type_var, self._generics[i])]
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except IndexError:
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return [type_var.name]
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return []
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def values(self):
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# The values are not relevant. If it's not searched exactly, the type
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# vars are just global and should be looked up as that.
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return []
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class _AnnotatedClassContext(ClassContext):
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def get_filters(self, *args, **kwargs):
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filters = super().get_filters(
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*args, **kwargs
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)
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yield from filters
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# The type vars can only be looked up if it's a global search and
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# not a direct lookup on the class.
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yield self._value.get_type_var_filter()
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class DefineGenericBaseClass(LazyValueWrapper):
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def __init__(self, generics_manager):
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self._generics_manager = generics_manager
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def _create_instance_with_generics(self, generics_manager):
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raise NotImplementedError
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@inference_state_method_cache()
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def get_generics(self):
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return self._generics_manager.to_tuple()
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def define_generics(self, type_var_dict):
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from jedi.inference.gradual.type_var import TypeVar
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changed = False
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new_generics = []
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for generic_set in self.get_generics():
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values = NO_VALUES
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for generic in generic_set:
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if isinstance(generic, (DefineGenericBaseClass, TypeVar)):
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result = generic.define_generics(type_var_dict)
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values |= result
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if result != ValueSet({generic}):
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changed = True
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else:
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values |= ValueSet([generic])
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new_generics.append(values)
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if not changed:
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# There might not be any type vars that change. In that case just
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# return itself, because it does not make sense to potentially lose
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# cached results.
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return ValueSet([self])
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return ValueSet([self._create_instance_with_generics(
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TupleGenericManager(tuple(new_generics))
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)])
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def is_same_class(self, other):
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if not isinstance(other, DefineGenericBaseClass):
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return False
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if self.tree_node != other.tree_node:
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# TODO not sure if this is nice.
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return False
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given_params1 = self.get_generics()
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given_params2 = other.get_generics()
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if len(given_params1) != len(given_params2):
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# If the amount of type vars doesn't match, the class doesn't
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# match.
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return False
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# Now compare generics
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return all(
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any(
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# TODO why is this ordering the correct one?
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cls2.is_same_class(cls1)
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# TODO I'm still not sure gather_annotation_classes is a good
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# idea. They are essentially here to avoid comparing Tuple <=>
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# tuple and instead compare tuple <=> tuple, but at the moment
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# the whole `is_same_class` and `is_sub_class` matching is just
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# not in the best shape.
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for cls1 in class_set1.gather_annotation_classes()
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for cls2 in class_set2.gather_annotation_classes()
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) for class_set1, class_set2 in zip(given_params1, given_params2)
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)
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def get_signatures(self):
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return []
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def __repr__(self):
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return '<%s: %s%s>' % (
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self.__class__.__name__,
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self._wrapped_value,
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list(self.get_generics()),
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)
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class GenericClass(DefineGenericBaseClass, ClassMixin):
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"""
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A class that is defined with generics, might be something simple like:
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class Foo(Generic[T]): ...
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my_foo_int_cls = Foo[int]
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"""
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def __init__(self, class_value, generics_manager):
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super().__init__(generics_manager)
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self._class_value = class_value
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def _get_wrapped_value(self):
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return self._class_value
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def get_type_hint(self, add_class_info=True):
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n = self.py__name__()
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# Not sure if this is the best way to do this, but all of these types
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# are a bit special in that they have type aliases and other ways to
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# become lower case. It's probably better to make them upper case,
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# because that's what you can use in annotations.
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n = dict(list="List", dict="Dict", set="Set", tuple="Tuple").get(n, n)
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s = n + self._generics_manager.get_type_hint()
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if add_class_info:
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return 'Type[%s]' % s
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return s
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def get_type_var_filter(self):
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return _TypeVarFilter(self.get_generics(), self.list_type_vars())
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def py__call__(self, arguments):
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instance, = super().py__call__(arguments)
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return ValueSet([_GenericInstanceWrapper(instance)])
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def _as_context(self):
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return _AnnotatedClassContext(self)
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@to_list
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def py__bases__(self):
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for base in self._wrapped_value.py__bases__():
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yield _LazyGenericBaseClass(self, base, self._generics_manager)
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def _create_instance_with_generics(self, generics_manager):
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return GenericClass(self._class_value, generics_manager)
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def is_sub_class_of(self, class_value):
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if super().is_sub_class_of(class_value):
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return True
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return self._class_value.is_sub_class_of(class_value)
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def with_generics(self, generics_tuple):
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return self._class_value.with_generics(generics_tuple)
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def infer_type_vars(self, value_set):
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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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annotation_name = self.py__name__()
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type_var_dict = {}
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if annotation_name == 'Iterable':
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annotation_generics = self.get_generics()
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if annotation_generics:
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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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)
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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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# 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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for py_class in value_set:
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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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else:
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continue
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if py_class.api_type != 'class':
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# Functions & modules don't have an MRO and we're not
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# expecting a Callable (those are handled separately within
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# TypingClassValueWithIndex).
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continue
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for parent_class in py_class.py__mro__():
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class_name = parent_class.py__name__()
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if annotation_name == class_name:
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merge_type_var_dicts(
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type_var_dict,
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merge_pairwise_generics(self, parent_class),
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)
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break
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return type_var_dict
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class _LazyGenericBaseClass:
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def __init__(self, class_value, lazy_base_class, generics_manager):
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self._class_value = class_value
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self._lazy_base_class = lazy_base_class
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self._generics_manager = generics_manager
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@iterator_to_value_set
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def infer(self):
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for base in self._lazy_base_class.infer():
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if isinstance(base, GenericClass):
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# Here we have to recalculate the given types.
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yield GenericClass.create_cached(
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base.inference_state,
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base._wrapped_value,
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TupleGenericManager(tuple(self._remap_type_vars(base))),
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)
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else:
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if base.is_class_mixin():
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# This case basically allows classes like `class Foo(List)`
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# to be used like `Foo[int]`. The generics are not
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# necessary and can be used later.
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yield GenericClass.create_cached(
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base.inference_state,
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base,
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self._generics_manager,
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)
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else:
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yield base
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def _remap_type_vars(self, base):
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from jedi.inference.gradual.type_var import TypeVar
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filter = self._class_value.get_type_var_filter()
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for type_var_set in base.get_generics():
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new = NO_VALUES
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for type_var in type_var_set:
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if isinstance(type_var, TypeVar):
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names = filter.get(type_var.py__name__())
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new |= ValueSet.from_sets(
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name.infer() for name in names
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)
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else:
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# Mostly will be type vars, except if in some cases
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# a concrete type will already be there. In that
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# case just add it to the value set.
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new |= ValueSet([type_var])
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yield new
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def __repr__(self):
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return '<%s: %s>' % (self.__class__.__name__, self._lazy_base_class)
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class _GenericInstanceWrapper(ValueWrapper):
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def py__stop_iteration_returns(self):
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for cls in self._wrapped_value.class_value.py__mro__():
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if cls.py__name__() == 'Generator':
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generics = cls.get_generics()
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try:
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return generics[2].execute_annotation()
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except IndexError:
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pass
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elif cls.py__name__() == 'Iterator':
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return ValueSet([builtin_from_name(self.inference_state, 'None')])
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return self._wrapped_value.py__stop_iteration_returns()
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def get_type_hint(self, add_class_info=True):
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return self._wrapped_value.class_value.get_type_hint(add_class_info=False)
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class _PseudoTreeNameClass(Value):
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"""
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In typeshed, some classes are defined like this:
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Tuple: _SpecialForm = ...
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Now this is not a real class, therefore we have to do some workarounds like
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this class. Essentially this class makes it possible to goto that `Tuple`
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name, without affecting anything else negatively.
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"""
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api_type = 'class'
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def __init__(self, parent_context, tree_name):
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super().__init__(
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parent_context.inference_state,
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parent_context
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)
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self._tree_name = tree_name
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@property
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def tree_node(self):
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return self._tree_name
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def get_filters(self, *args, **kwargs):
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# TODO this is obviously wrong. Is it though?
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class EmptyFilter(ClassFilter):
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def __init__(self):
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pass
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def get(self, name, **kwargs):
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return []
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def values(self, **kwargs):
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return []
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yield EmptyFilter()
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def py__class__(self):
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# This might not be 100% correct, but it is good enough. The details of
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# the typing library are not really an issue for Jedi.
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return builtin_from_name(self.inference_state, 'type')
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@property
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def name(self):
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return ValueName(self, self._tree_name)
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def get_qualified_names(self):
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return (self._tree_name.value,)
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def __repr__(self):
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return '%s(%s)' % (self.__class__.__name__, self._tree_name.value)
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class BaseTypingValue(LazyValueWrapper):
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def __init__(self, parent_context, tree_name):
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self.inference_state = parent_context.inference_state
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self.parent_context = parent_context
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self._tree_name = tree_name
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@property
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def name(self):
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return ValueName(self, self._tree_name)
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def _get_wrapped_value(self):
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return _PseudoTreeNameClass(self.parent_context, self._tree_name)
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def get_signatures(self):
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return self._wrapped_value.get_signatures()
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def __repr__(self):
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return '%s(%s)' % (self.__class__.__name__, self._tree_name.value)
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class BaseTypingClassWithGenerics(DefineGenericBaseClass):
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def __init__(self, parent_context, tree_name, generics_manager):
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super().__init__(generics_manager)
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self.inference_state = parent_context.inference_state
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self.parent_context = parent_context
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self._tree_name = tree_name
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def _get_wrapped_value(self):
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return _PseudoTreeNameClass(self.parent_context, self._tree_name)
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def __repr__(self):
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return '%s(%s%s)' % (self.__class__.__name__, self._tree_name.value,
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self._generics_manager)
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class BaseTypingInstance(LazyValueWrapper):
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def __init__(self, parent_context, class_value, tree_name, generics_manager):
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self.inference_state = class_value.inference_state
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self.parent_context = parent_context
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self._class_value = class_value
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self._tree_name = tree_name
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self._generics_manager = generics_manager
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def py__class__(self):
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return self._class_value
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def get_annotated_class_object(self):
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return self._class_value
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def get_qualified_names(self):
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return (self.py__name__(),)
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@property
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def name(self):
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return ValueName(self, self._tree_name)
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def _get_wrapped_value(self):
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object_, = builtin_from_name(self.inference_state, 'object').execute_annotation()
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return object_
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def __repr__(self):
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return '<%s: %s>' % (self.__class__.__name__, self._generics_manager)
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