forked from VimPlug/jedi
Start splitting up gradual/typing.py
This commit is contained in:
Dave Halter
41
jedi/inference/gradual/base.py
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41
jedi/inference/gradual/base.py
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@@ -0,0 +1,41 @@
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from jedi.inference.base_value import Value
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from jedi.inference.value.klass import ClassFilter
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from jedi.inference.names import ValueName
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from jedi.inference.compiled import builtin_from_name
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class BaseTypingValue(Value):
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def __init__(self, inference_state, parent_context, tree_name):
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super(BaseTypingValue, self).__init__(inference_state, parent_context)
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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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# TODO this is obviously not correct, but at least gives us a class if
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# we have none. Some of these objects don't really have a base class in
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# typeshed.
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return builtin_from_name(self.inference_state, u'object')
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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 __repr__(self):
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return '%s(%s)' % (self.__class__.__name__, self._tree_name.value)
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111
jedi/inference/gradual/type_var.py
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111
jedi/inference/gradual/type_var.py
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@@ -0,0 +1,111 @@
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from jedi._compatibility import unicode, force_unicode
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from jedi import debug
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from jedi.inference.base_value import ValueSet, NO_VALUES
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from jedi.inference.gradual.base import BaseTypingValue
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class TypeVarClass(BaseTypingValue):
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def py__call__(self, arguments):
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unpacked = arguments.unpack()
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key, lazy_value = next(unpacked, (None, None))
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var_name = self._find_string_name(lazy_value)
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# The name must be given, otherwise it's useless.
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if var_name is None or key is not None:
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debug.warning('Found a variable without a name %s', arguments)
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return NO_VALUES
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return ValueSet([TypeVar.create_cached(
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self.inference_state,
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self.parent_context,
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self._tree_name,
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var_name,
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unpacked
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)])
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def _find_string_name(self, lazy_value):
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if lazy_value is None:
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return None
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value_set = lazy_value.infer()
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if not value_set:
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return None
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if len(value_set) > 1:
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debug.warning('Found multiple values for a type variable: %s', value_set)
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name_value = next(iter(value_set))
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try:
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method = name_value.get_safe_value
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except AttributeError:
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return None
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else:
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safe_value = method(default=None)
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if self.inference_state.environment.version_info.major == 2:
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if isinstance(safe_value, bytes):
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return force_unicode(safe_value)
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if isinstance(safe_value, (str, unicode)):
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return safe_value
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return None
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class TypeVar(BaseTypingValue):
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def __init__(self, inference_state, parent_context, tree_name, var_name, unpacked_args):
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super(TypeVar, self).__init__(inference_state, parent_context, tree_name)
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self._var_name = var_name
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self._constraints_lazy_values = []
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self._bound_lazy_value = None
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self._covariant_lazy_value = None
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self._contravariant_lazy_value = None
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for key, lazy_value in unpacked_args:
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if key is None:
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self._constraints_lazy_values.append(lazy_value)
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else:
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if key == 'bound':
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self._bound_lazy_value = lazy_value
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elif key == 'covariant':
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self._covariant_lazy_value = lazy_value
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elif key == 'contravariant':
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self._contra_variant_lazy_value = lazy_value
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else:
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debug.warning('Invalid TypeVar param name %s', key)
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def py__name__(self):
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return self._var_name
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def get_filters(self, *args, **kwargs):
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return iter([])
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def _get_classes(self):
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if self._bound_lazy_value is not None:
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return self._bound_lazy_value.infer()
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if self._constraints_lazy_values:
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return self.constraints
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debug.warning('Tried to infer the TypeVar %s without a given type', self._var_name)
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return NO_VALUES
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def is_same_class(self, other):
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# Everything can match an undefined type var.
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return True
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@property
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def constraints(self):
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return ValueSet.from_sets(
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lazy.infer() for lazy in self._constraints_lazy_values
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)
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def define_generics(self, type_var_dict):
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try:
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found = type_var_dict[self.py__name__()]
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except KeyError:
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pass
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else:
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if found:
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return found
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return self._get_classes() or ValueSet({self})
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def execute_annotation(self):
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return self._get_classes().execute_annotation()
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def __repr__(self):
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return '<%s: %s>' % (self.__class__.__name__, self.py__name__())
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@@ -5,7 +5,6 @@ values.
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This file deals with all the typing.py cases.
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"""
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from jedi._compatibility import unicode, force_unicode
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from jedi import debug
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from jedi.inference.cache import inference_state_method_cache
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from jedi.inference.compiled import builtin_from_name
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@@ -19,8 +18,10 @@ from jedi.inference.filters import FilterWrapper
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from jedi.inference.names import NameWrapper, AbstractTreeName, \
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AbstractNameDefinition, ValueName
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from jedi.inference.helpers import is_string
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from jedi.inference.value.klass import ClassMixin, ClassFilter
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from jedi.inference.value.klass import ClassMixin
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from jedi.inference.context import ClassContext
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from jedi.inference.gradual.base import BaseTypingValue
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from jedi.inference.gradual.type_var import TypeVarClass, TypeVar
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_PROXY_CLASS_TYPES = 'Tuple Generic Protocol Callable Type'.split()
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_TYPE_ALIAS_TYPES = {
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@@ -45,43 +46,6 @@ class TypingName(AbstractTreeName):
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return ValueSet([self._value])
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class _BaseTypingValue(Value):
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def __init__(self, inference_state, parent_context, tree_name):
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super(_BaseTypingValue, self).__init__(inference_state, parent_context)
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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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# TODO this is obviously not correct, but at least gives us a class if
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# we have none. Some of these objects don't really have a base class in
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# typeshed.
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return builtin_from_name(self.inference_state, u'object')
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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 __repr__(self):
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return '%s(%s)' % (self.__class__.__name__, self._tree_name.value)
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class TypingModuleName(NameWrapper):
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def infer(self):
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return ValueSet(self._remap())
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@@ -138,7 +102,7 @@ class TypingModuleFilterWrapper(FilterWrapper):
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name_wrapper_class = TypingModuleName
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class _WithIndexBase(_BaseTypingValue):
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class _WithIndexBase(BaseTypingValue):
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def __init__(self, inference_state, parent_context, name, index_value, value_of_index):
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super(_WithIndexBase, self).__init__(inference_state, parent_context, name)
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self._index_value = index_value
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@@ -187,7 +151,7 @@ class TypingValueWithIndex(_WithIndexBase):
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)
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class TypingValue(_BaseTypingValue):
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class TypingValue(BaseTypingValue):
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index_class = TypingValueWithIndex
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py__simple_getitem__ = None
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@@ -358,127 +322,20 @@ class Protocol(_WithIndexBase, _GetItemMixin):
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pass
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class Any(_BaseTypingValue):
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class Any(BaseTypingValue):
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def execute_annotation(self):
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debug.warning('Used Any - returned no results')
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return NO_VALUES
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class TypeVarClass(_BaseTypingValue):
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def py__call__(self, arguments):
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unpacked = arguments.unpack()
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key, lazy_value = next(unpacked, (None, None))
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var_name = self._find_string_name(lazy_value)
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# The name must be given, otherwise it's useless.
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if var_name is None or key is not None:
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debug.warning('Found a variable without a name %s', arguments)
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return NO_VALUES
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return ValueSet([TypeVar.create_cached(
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self.inference_state,
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self.parent_context,
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self._tree_name,
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var_name,
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unpacked
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)])
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def _find_string_name(self, lazy_value):
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if lazy_value is None:
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return None
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value_set = lazy_value.infer()
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if not value_set:
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return None
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if len(value_set) > 1:
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debug.warning('Found multiple values for a type variable: %s', value_set)
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name_value = next(iter(value_set))
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try:
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method = name_value.get_safe_value
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except AttributeError:
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return None
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else:
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safe_value = method(default=None)
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if self.inference_state.environment.version_info.major == 2:
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if isinstance(safe_value, bytes):
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return force_unicode(safe_value)
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if isinstance(safe_value, (str, unicode)):
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return safe_value
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return None
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class TypeVar(_BaseTypingValue):
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def __init__(self, inference_state, parent_context, tree_name, var_name, unpacked_args):
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super(TypeVar, self).__init__(inference_state, parent_context, tree_name)
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self._var_name = var_name
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self._constraints_lazy_values = []
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self._bound_lazy_value = None
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self._covariant_lazy_value = None
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self._contravariant_lazy_value = None
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for key, lazy_value in unpacked_args:
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if key is None:
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self._constraints_lazy_values.append(lazy_value)
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else:
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if key == 'bound':
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self._bound_lazy_value = lazy_value
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elif key == 'covariant':
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self._covariant_lazy_value = lazy_value
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elif key == 'contravariant':
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self._contra_variant_lazy_value = lazy_value
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else:
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debug.warning('Invalid TypeVar param name %s', key)
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def py__name__(self):
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return self._var_name
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def get_filters(self, *args, **kwargs):
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return iter([])
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def _get_classes(self):
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if self._bound_lazy_value is not None:
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return self._bound_lazy_value.infer()
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if self._constraints_lazy_values:
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return self.constraints
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debug.warning('Tried to infer the TypeVar %s without a given type', self._var_name)
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return NO_VALUES
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def is_same_class(self, other):
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# Everything can match an undefined type var.
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return True
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@property
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def constraints(self):
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return ValueSet.from_sets(
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lazy.infer() for lazy in self._constraints_lazy_values
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)
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def define_generics(self, type_var_dict):
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try:
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found = type_var_dict[self.py__name__()]
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except KeyError:
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pass
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else:
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if found:
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return found
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return self._get_classes() or ValueSet({self})
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def execute_annotation(self):
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return self._get_classes().execute_annotation()
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def __repr__(self):
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return '<%s: %s>' % (self.__class__.__name__, self.py__name__())
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class OverloadFunction(_BaseTypingValue):
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class OverloadFunction(BaseTypingValue):
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@repack_with_argument_clinic('func, /')
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def py__call__(self, func_value_set):
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# Just pass arguments through.
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return func_value_set
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class NewTypeFunction(_BaseTypingValue):
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class NewTypeFunction(BaseTypingValue):
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def py__call__(self, arguments):
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ordered_args = arguments.unpack()
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next(ordered_args, (None, None))
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@@ -504,7 +361,7 @@ class NewType(Value):
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return self._type_value_set.execute_annotation()
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class CastFunction(_BaseTypingValue):
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class CastFunction(BaseTypingValue):
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@repack_with_argument_clinic('type, object, /')
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def py__call__(self, type_value_set, object_value_set):
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return type_value_set.execute_annotation()
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