from jedi.inference.cache import inference_state_method_cache from jedi.inference.base_value import ValueSet, NO_VALUES, Value, \ iterator_to_value_set, LazyValueWrapper, ValueWrapper from jedi.inference.compiled import builtin_from_name from jedi.inference.value.klass import ClassFilter from jedi.inference.value.klass import ClassMixin from jedi.inference.utils import to_list from jedi.inference.names import AbstractNameDefinition, ValueName from jedi.inference.context import ClassContext from jedi.inference.gradual.generics import TupleGenericManager class _BoundTypeVarName(AbstractNameDefinition): """ This type var was bound to a certain type, e.g. int. """ def __init__(self, type_var, value_set): self._type_var = type_var self.parent_context = type_var.parent_context self._value_set = value_set def infer(self): def iter_(): for value in self._value_set: # Replace any with the constraints if they are there. from jedi.inference.gradual.typing import AnyClass if isinstance(value, AnyClass): for constraint in self._type_var.constraints: yield constraint else: yield value return ValueSet(iter_()) def py__name__(self): return self._type_var.py__name__() def __repr__(self): return '<%s %s -> %s>' % (self.__class__.__name__, self.py__name__(), self._value_set) class _TypeVarFilter(object): """ A filter for all given variables in a class. A = TypeVar('A') B = TypeVar('B') class Foo(Mapping[A, B]): ... In this example we would have two type vars given: A and B """ def __init__(self, generics, type_vars): self._generics = generics self._type_vars = type_vars def get(self, name): for i, type_var in enumerate(self._type_vars): if type_var.py__name__() == name: try: return [_BoundTypeVarName(type_var, self._generics[i])] except IndexError: return [type_var.name] return [] def values(self): # The values are not relevant. If it's not searched exactly, the type # vars are just global and should be looked up as that. return [] class _AnnotatedClassContext(ClassContext): def get_filters(self, *args, **kwargs): filters = super(_AnnotatedClassContext, self).get_filters( *args, **kwargs ) for f in filters: yield f # The type vars can only be looked up if it's a global search and # not a direct lookup on the class. yield self._value.get_type_var_filter() class DefineGenericBaseClass(LazyValueWrapper): def __init__(self, generics_manager): self._generics_manager = generics_manager def _create_instance_with_generics(self, generics_manager): raise NotImplementedError @inference_state_method_cache() def get_generics(self): return self._generics_manager.to_tuple() def define_generics(self, type_var_dict): from jedi.inference.gradual.type_var import TypeVar changed = False new_generics = [] for generic_set in self.get_generics(): values = NO_VALUES for generic in generic_set: if isinstance(generic, (DefineGenericBaseClass, TypeVar)): result = generic.define_generics(type_var_dict) values |= result if result != ValueSet({generic}): changed = True else: values |= ValueSet([generic]) new_generics.append(values) if not changed: # There might not be any type vars that change. In that case just # return itself, because it does not make sense to potentially lose # cached results. return ValueSet([self]) return ValueSet([self._create_instance_with_generics( TupleGenericManager(tuple(new_generics)) )]) def is_same_class(self, other): if not isinstance(other, DefineGenericBaseClass): return False if self.tree_node != other.tree_node: # TODO not sure if this is nice. return False given_params1 = self.get_generics() given_params2 = other.get_generics() if len(given_params1) != len(given_params2): # If the amount of type vars doesn't match, the class doesn't # match. return False # Now compare generics return all( any( # TODO why is this ordering the correct one? cls2.is_same_class(cls1) # TODO I'm still not sure gather_annotation_classes is a good # idea. They are essentially here to avoid comparing Tuple <=> # tuple and instead compare tuple <=> tuple, but at the moment # the whole `is_same_class` and `is_sub_class` matching is just # not in the best shape. for cls1 in class_set1.gather_annotation_classes() for cls2 in class_set2.gather_annotation_classes() ) for class_set1, class_set2 in zip(given_params1, given_params2) ) def __repr__(self): return '<%s: %s%s>' % ( self.__class__.__name__, self._wrapped_value, list(self.get_generics()), ) class GenericClass(DefineGenericBaseClass, ClassMixin): """ A class that is defined with generics, might be something simple like: class Foo(Generic[T]): ... my_foo_int_cls = Foo[int] """ def __init__(self, class_value, generics_manager): super(GenericClass, self).__init__(generics_manager) self._class_value = class_value def _get_wrapped_value(self): return self._class_value def get_type_hint(self, add_class_info=True): n = self.py__name__() # Not sure if this is the best way to do this, but all of these types # are a bit special in that they have type aliases and other ways to # become lower case. It's probably better to make them upper case, # because that's what you can use in annotations. n = dict(list="List", dict="Dict", set="Set", tuple="Tuple").get(n, n) s = n + self._generics_manager.get_type_hint() if add_class_info: return 'Type[%s]' % s return s def get_type_var_filter(self): return _TypeVarFilter(self.get_generics(), self.list_type_vars()) def py__call__(self, arguments): instance, = super(GenericClass, self).py__call__(arguments) return ValueSet([_GenericInstanceWrapper(instance)]) def _as_context(self): return _AnnotatedClassContext(self) @to_list def py__bases__(self): for base in self._wrapped_value.py__bases__(): yield _LazyGenericBaseClass(self, base, self._generics_manager) def _create_instance_with_generics(self, generics_manager): return GenericClass(self._class_value, generics_manager) def is_sub_class_of(self, class_value): if super(GenericClass, self).is_sub_class_of(class_value): return True return self._class_value.is_sub_class_of(class_value) def with_generics(self, generics_tuple): return self._class_value.with_generics(generics_tuple) def infer_type_vars(self, value_set): # Circular from jedi.inference.gradual.annotation import merge_pairwise_generics, merge_type_var_dicts annotation_name = self.py__name__() type_var_dict = {} if annotation_name == 'Iterable': annotation_generics = self.get_generics() if annotation_generics: return annotation_generics[0].infer_type_vars( value_set.merge_types_of_iterate(), ) else: # Note: we need to handle the MRO _in order_, so we need to extract # the elements from the set first, then handle them, even if we put # them back in a set afterwards. for py_class in value_set: if py_class.is_instance() and not py_class.is_compiled(): py_class = py_class.get_annotated_class_object() else: continue if py_class.api_type != u'class': # Functions & modules don't have an MRO and we're not # expecting a Callable (those are handled separately within # TypingClassValueWithIndex). continue for parent_class in py_class.py__mro__(): class_name = parent_class.py__name__() if annotation_name == class_name: merge_type_var_dicts( type_var_dict, merge_pairwise_generics(self, parent_class), ) break return type_var_dict class _LazyGenericBaseClass(object): def __init__(self, class_value, lazy_base_class, generics_manager): self._class_value = class_value self._lazy_base_class = lazy_base_class self._generics_manager = generics_manager @iterator_to_value_set def infer(self): for base in self._lazy_base_class.infer(): if isinstance(base, GenericClass): # Here we have to recalculate the given types. yield GenericClass.create_cached( base.inference_state, base._wrapped_value, TupleGenericManager(tuple(self._remap_type_vars(base))), ) else: if base.is_class_mixin(): # This case basically allows classes like `class Foo(List)` # to be used like `Foo[int]`. The generics are not # necessary and can be used later. yield GenericClass.create_cached( base.inference_state, base, self._generics_manager, ) else: yield base def _remap_type_vars(self, base): from jedi.inference.gradual.type_var import TypeVar filter = self._class_value.get_type_var_filter() for type_var_set in base.get_generics(): new = NO_VALUES for type_var in type_var_set: if isinstance(type_var, TypeVar): names = filter.get(type_var.py__name__()) new |= ValueSet.from_sets( name.infer() for name in names ) else: # Mostly will be type vars, except if in some cases # a concrete type will already be there. In that # case just add it to the value set. new |= ValueSet([type_var]) yield new def __repr__(self): return '<%s: %s>' % (self.__class__.__name__, self._lazy_base_class) class _GenericInstanceWrapper(ValueWrapper): def py__stop_iteration_returns(self): for cls in self._wrapped_value.class_value.py__mro__(): if cls.py__name__() == 'Generator': generics = cls.get_generics() try: return generics[2].execute_annotation() except IndexError: pass elif cls.py__name__() == 'Iterator': return ValueSet([builtin_from_name(self.inference_state, u'None')]) return self._wrapped_value.py__stop_iteration_returns() def get_type_hint(self, add_class_info=True): return self._wrapped_value.class_value.get_type_hint(add_class_info=False) class _PseudoTreeNameClass(Value): """ In typeshed, some classes are defined like this: Tuple: _SpecialForm = ... Now this is not a real class, therefore we have to do some workarounds like this class. Essentially this class makes it possible to goto that `Tuple` name, without affecting anything else negatively. """ api_type = u'class' def __init__(self, parent_context, tree_name): super(_PseudoTreeNameClass, self).__init__( parent_context.inference_state, parent_context ) self._tree_name = tree_name @property def tree_node(self): return self._tree_name def get_filters(self, *args, **kwargs): # TODO this is obviously wrong. Is it though? class EmptyFilter(ClassFilter): def __init__(self): pass def get(self, name, **kwargs): return [] def values(self, **kwargs): return [] yield EmptyFilter() def py__class__(self): # This might not be 100% correct, but it is good enough. The details of # the typing library are not really an issue for Jedi. return builtin_from_name(self.inference_state, u'type') @property def name(self): return ValueName(self, self._tree_name) def get_qualified_names(self): return (self._tree_name.value,) def __repr__(self): return '%s(%s)' % (self.__class__.__name__, self._tree_name.value) class BaseTypingValue(LazyValueWrapper): def __init__(self, parent_context, tree_name): self.inference_state = parent_context.inference_state self.parent_context = parent_context self._tree_name = tree_name @property def name(self): return ValueName(self, self._tree_name) def _get_wrapped_value(self): return _PseudoTreeNameClass(self.parent_context, self._tree_name) def __repr__(self): return '%s(%s)' % (self.__class__.__name__, self._tree_name.value) class BaseTypingClassWithGenerics(DefineGenericBaseClass): def __init__(self, parent_context, tree_name, generics_manager): super(BaseTypingClassWithGenerics, self).__init__(generics_manager) self.inference_state = parent_context.inference_state self.parent_context = parent_context self._tree_name = tree_name def _get_wrapped_value(self): return _PseudoTreeNameClass(self.parent_context, self._tree_name) def __repr__(self): return '%s(%s%s)' % (self.__class__.__name__, self._tree_name.value, self._generics_manager) class BaseTypingInstance(LazyValueWrapper): def __init__(self, parent_context, class_value, tree_name, generics_manager): self.inference_state = class_value.inference_state self.parent_context = parent_context self._class_value = class_value self._tree_name = tree_name self._generics_manager = generics_manager def py__class__(self): return self._class_value def get_annotated_class_object(self): return self._class_value def get_qualified_names(self): return (self.py__name__(),) @property def name(self): return ValueName(self, self._tree_name) def _get_wrapped_value(self): object_, = builtin_from_name(self.inference_state, u'object').execute_annotation() return object_ def __repr__(self): return '<%s: %s>' % (self.__class__.__name__, self._generics_manager)