Implement support for TypeVar inference for __new__

jedi/inference/value/instance.py

@@ -17,7 +17,7 @@ from jedi.inference.arguments import ValuesArguments, TreeArgumentsWrapper
 from jedi.inference.value.function import \
     FunctionValue, FunctionMixin, OverloadedFunctionValue, \
     BaseFunctionExecutionContext, FunctionExecutionContext, FunctionNameInClass
-from jedi.inference.value.klass import ClassFilter
+from jedi.inference.value.klass import ClassFilter, init_or_new_func
 from jedi.inference.value.dynamic_arrays import get_dynamic_array_instance
 from jedi.parser_utils import function_is_staticmethod, function_is_classmethod
 
@@ -327,7 +327,7 @@ class TreeInstance(_BaseTreeInstance):
             infer_type_vars_for_execution
 
         args = InstanceArguments(self, self._arguments)
-        for signature in self.class_value.py__getattribute__('__init__').get_signatures():
+        for signature in init_or_new_func(self.class_value).get_signatures():
             # Just take the first result, it should always be one, because we
             # control the typeshed code.
             funcdef = signature.value.tree_node

jedi/inference/value/klass.py

@@ -376,19 +376,8 @@ class ClassMixin:
             if sigs:
                 return sigs
         args = ValuesArguments([])
-        init_funcs = self.py__call__(args).py__getattribute__('__init__')
-        if len(init_funcs) == 1:
-            init = next(iter(init_funcs))
-            try:
-                class_context = init.class_context
-            except AttributeError:
-                pass
-            else:
-                # In the case where we are on object.__init__, we try to use
-                # __new__.
-                if class_context.get_root_context().is_builtins_module() \
-                        and init.class_context.name.string_name == "object":
-                    init_funcs = self.py__call__(args).py__getattribute__('__new__')
+        instance = self.py__call__(args)
+        init_funcs = init_or_new_func(instance)
 
         dataclass_sigs = self._get_dataclass_transform_signatures()
         if dataclass_sigs:
@@ -481,6 +470,23 @@ class ClassMixin:
         return ValueSet({self})
 
 
+def init_or_new_func(value):
+    init_funcs = value.py__getattribute__('__init__')
+    if len(init_funcs) == 1:
+        init = next(iter(init_funcs))
+        try:
+            class_context = init.class_context
+        except AttributeError:
+            pass
+        else:
+            # In the case where we are on object.__init__, we try to use
+            # __new__.
+            if class_context.get_root_context().is_builtins_module() \
+                    and init.class_context.name.string_name == "object":
+                return value.py__getattribute__('__new__')
+    return init_funcs
+
+
 class DataclassParamName(BaseTreeParamName):
     """
     Represent a field declaration on a class with dataclass semantics.