Uploaded Test files

venv/Lib/site-packages/jedi/inference/value/function.py

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+from parso.python import tree
+
+from jedi._compatibility import use_metaclass
+from jedi import debug
+from jedi.inference.cache import inference_state_method_cache, CachedMetaClass
+from jedi.inference import compiled
+from jedi.inference import recursion
+from jedi.inference import docstrings
+from jedi.inference import flow_analysis
+from jedi.inference.signature import TreeSignature
+from jedi.inference.filters import ParserTreeFilter, FunctionExecutionFilter, \
+    AnonymousFunctionExecutionFilter
+from jedi.inference.names import ValueName, AbstractNameDefinition, \
+    AnonymousParamName, ParamName, NameWrapper
+from jedi.inference.base_value import ContextualizedNode, NO_VALUES, \
+    ValueSet, TreeValue, ValueWrapper
+from jedi.inference.lazy_value import LazyKnownValues, LazyKnownValue, \
+    LazyTreeValue
+from jedi.inference.context import ValueContext, TreeContextMixin
+from jedi.inference.value import iterable
+from jedi import parser_utils
+from jedi.inference.parser_cache import get_yield_exprs
+from jedi.inference.helpers import values_from_qualified_names
+from jedi.inference.gradual.generics import TupleGenericManager
+
+
+class LambdaName(AbstractNameDefinition):
+    string_name = '<lambda>'
+    api_type = u'function'
+
+    def __init__(self, lambda_value):
+        self._lambda_value = lambda_value
+        self.parent_context = lambda_value.parent_context
+
+    @property
+    def start_pos(self):
+        return self._lambda_value.tree_node.start_pos
+
+    def infer(self):
+        return ValueSet([self._lambda_value])
+
+
+class FunctionAndClassBase(TreeValue):
+    def get_qualified_names(self):
+        if self.parent_context.is_class():
+            n = self.parent_context.get_qualified_names()
+            if n is None:
+                # This means that the parent class lives within a function.
+                return None
+            return n + (self.py__name__(),)
+        elif self.parent_context.is_module():
+            return (self.py__name__(),)
+        else:
+            return None
+
+
+class FunctionMixin(object):
+    api_type = u'function'
+
+    def get_filters(self, origin_scope=None):
+        cls = self.py__class__()
+        for instance in cls.execute_with_values():
+            for filter in instance.get_filters(origin_scope=origin_scope):
+                yield filter
+
+    def py__get__(self, instance, class_value):
+        from jedi.inference.value.instance import BoundMethod
+        if instance is None:
+            # Calling the Foo.bar results in the original bar function.
+            return ValueSet([self])
+        return ValueSet([BoundMethod(instance, class_value.as_context(), self)])
+
+    def get_param_names(self):
+        return [AnonymousParamName(self, param.name)
+                for param in self.tree_node.get_params()]
+
+    @property
+    def name(self):
+        if self.tree_node.type == 'lambdef':
+            return LambdaName(self)
+        return ValueName(self, self.tree_node.name)
+
+    def is_function(self):
+        return True
+
+    def py__name__(self):
+        return self.name.string_name
+
+    def get_type_hint(self, add_class_info=True):
+        return_annotation = self.tree_node.annotation
+        if return_annotation is None:
+            def param_name_to_str(n):
+                s = n.string_name
+                annotation = n.infer().get_type_hint()
+                if annotation is not None:
+                    s += ': ' + annotation
+                if n.default_node is not None:
+                    s += '=' + n.default_node.get_code(include_prefix=False)
+                return s
+
+            function_execution = self.as_context()
+            result = function_execution.infer()
+            return_hint = result.get_type_hint()
+            body = self.py__name__() + '(%s)' % ', '.join([
+                param_name_to_str(n)
+                for n in function_execution.get_param_names()
+            ])
+            if return_hint is None:
+                return body
+        else:
+            return_hint = return_annotation.get_code(include_prefix=False)
+            body = self.py__name__() + self.tree_node.children[2].get_code(include_prefix=False)
+
+        return body + ' -> ' + return_hint
+
+    def py__call__(self, arguments):
+        function_execution = self.as_context(arguments)
+        return function_execution.infer()
+
+    def _as_context(self, arguments=None):
+        if arguments is None:
+            return AnonymousFunctionExecution(self)
+        return FunctionExecutionContext(self, arguments)
+
+    def get_signatures(self):
+        return [TreeSignature(f) for f in self.get_signature_functions()]
+
+
+class FunctionValue(use_metaclass(CachedMetaClass, FunctionMixin, FunctionAndClassBase)):
+    @classmethod
+    def from_context(cls, context, tree_node):
+        def create(tree_node):
+            if context.is_class():
+                return MethodValue(
+                    context.inference_state,
+                    context,
+                    parent_context=parent_context,
+                    tree_node=tree_node
+                )
+            else:
+                return cls(
+                    context.inference_state,
+                    parent_context=parent_context,
+                    tree_node=tree_node
+                )
+
+        overloaded_funcs = list(_find_overload_functions(context, tree_node))
+
+        parent_context = context
+        while parent_context.is_class() or parent_context.is_instance():
+            parent_context = parent_context.parent_context
+
+        function = create(tree_node)
+
+        if overloaded_funcs:
+            return OverloadedFunctionValue(
+                function,
+                # Get them into the correct order: lower line first.
+                list(reversed([create(f) for f in overloaded_funcs]))
+            )
+        return function
+
+    def py__class__(self):
+        c, = values_from_qualified_names(self.inference_state, u'types', u'FunctionType')
+        return c
+
+    def get_default_param_context(self):
+        return self.parent_context
+
+    def get_signature_functions(self):
+        return [self]
+
+
+class FunctionNameInClass(NameWrapper):
+    def __init__(self, class_context, name):
+        super(FunctionNameInClass, self).__init__(name)
+        self._class_context = class_context
+
+    def get_defining_qualified_value(self):
+        return self._class_context.get_value()  # Might be None.
+
+
+class MethodValue(FunctionValue):
+    def __init__(self, inference_state, class_context, *args, **kwargs):
+        super(MethodValue, self).__init__(inference_state, *args, **kwargs)
+        self.class_context = class_context
+
+    def get_default_param_context(self):
+        return self.class_context
+
+    def get_qualified_names(self):
+        # Need to implement this, because the parent value of a method
+        # value is not the class value but the module.
+        names = self.class_context.get_qualified_names()
+        if names is None:
+            return None
+        return names + (self.py__name__(),)
+
+    @property
+    def name(self):
+        return FunctionNameInClass(self.class_context, super(MethodValue, self).name)
+
+
+class BaseFunctionExecutionContext(ValueContext, TreeContextMixin):
+    def infer_annotations(self):
+        raise NotImplementedError
+
+    @inference_state_method_cache(default=NO_VALUES)
+    @recursion.execution_recursion_decorator()
+    def get_return_values(self, check_yields=False):
+        funcdef = self.tree_node
+        if funcdef.type == 'lambdef':
+            return self.infer_node(funcdef.children[-1])
+
+        if check_yields:
+            value_set = NO_VALUES
+            returns = get_yield_exprs(self.inference_state, funcdef)
+        else:
+            value_set = self.infer_annotations()
+            if value_set:
+                # If there are annotations, prefer them over anything else.
+                # This will make it faster.
+                return value_set
+            value_set |= docstrings.infer_return_types(self._value)
+            returns = funcdef.iter_return_stmts()
+
+        for r in returns:
+            if check_yields:
+                value_set |= ValueSet.from_sets(
+                    lazy_value.infer()
+                    for lazy_value in self._get_yield_lazy_value(r)
+                )
+            else:
+                check = flow_analysis.reachability_check(self, funcdef, r)
+                if check is flow_analysis.UNREACHABLE:
+                    debug.dbg('Return unreachable: %s', r)
+                else:
+                    try:
+                        children = r.children
+                    except AttributeError:
+                        ctx = compiled.builtin_from_name(self.inference_state, u'None')
+                        value_set |= ValueSet([ctx])
+                    else:
+                        value_set |= self.infer_node(children[1])
+                if check is flow_analysis.REACHABLE:
+                    debug.dbg('Return reachable: %s', r)
+                    break
+        return value_set
+
+    def _get_yield_lazy_value(self, yield_expr):
+        if yield_expr.type == 'keyword':
+            # `yield` just yields None.
+            ctx = compiled.builtin_from_name(self.inference_state, u'None')
+            yield LazyKnownValue(ctx)
+            return
+
+        node = yield_expr.children[1]
+        if node.type == 'yield_arg':  # It must be a yield from.
+            cn = ContextualizedNode(self, node.children[1])
+            for lazy_value in cn.infer().iterate(cn):
+                yield lazy_value
+        else:
+            yield LazyTreeValue(self, node)
+
+    @recursion.execution_recursion_decorator(default=iter([]))
+    def get_yield_lazy_values(self, is_async=False):
+        # TODO: if is_async, wrap yield statements in Awaitable/async_generator_asend
+        for_parents = [(y, tree.search_ancestor(y, 'for_stmt', 'funcdef',
+                                                'while_stmt', 'if_stmt'))
+                       for y in get_yield_exprs(self.inference_state, self.tree_node)]
+
+        # Calculate if the yields are placed within the same for loop.
+        yields_order = []
+        last_for_stmt = None
+        for yield_, for_stmt in for_parents:
+            # For really simple for loops we can predict the order. Otherwise
+            # we just ignore it.
+            parent = for_stmt.parent
+            if parent.type == 'suite':
+                parent = parent.parent
+            if for_stmt.type == 'for_stmt' and parent == self.tree_node \
+                    and parser_utils.for_stmt_defines_one_name(for_stmt):  # Simplicity for now.
+                if for_stmt == last_for_stmt:
+                    yields_order[-1][1].append(yield_)
+                else:
+                    yields_order.append((for_stmt, [yield_]))
+            elif for_stmt == self.tree_node:
+                yields_order.append((None, [yield_]))
+            else:
+                types = self.get_return_values(check_yields=True)
+                if types:
+                    yield LazyKnownValues(types, min=0, max=float('inf'))
+                return
+            last_for_stmt = for_stmt
+
+        for for_stmt, yields in yields_order:
+            if for_stmt is None:
+                # No for_stmt, just normal yields.
+                for yield_ in yields:
+                    for result in self._get_yield_lazy_value(yield_):
+                        yield result
+            else:
+                input_node = for_stmt.get_testlist()
+                cn = ContextualizedNode(self, input_node)
+                ordered = cn.infer().iterate(cn)
+                ordered = list(ordered)
+                for lazy_value in ordered:
+                    dct = {str(for_stmt.children[1].value): lazy_value.infer()}
+                    with self.predefine_names(for_stmt, dct):
+                        for yield_in_same_for_stmt in yields:
+                            for result in self._get_yield_lazy_value(yield_in_same_for_stmt):
+                                yield result
+
+    def merge_yield_values(self, is_async=False):
+        return ValueSet.from_sets(
+            lazy_value.infer()
+            for lazy_value in self.get_yield_lazy_values()
+        )
+
+    def is_generator(self):
+        return bool(get_yield_exprs(self.inference_state, self.tree_node))
+
+    def infer(self):
+        """
+        Created to be used by inheritance.
+        """
+        inference_state = self.inference_state
+        is_coroutine = self.tree_node.parent.type in ('async_stmt', 'async_funcdef')
+        from jedi.inference.gradual.base import GenericClass
+
+        if is_coroutine:
+            if self.is_generator():
+                if inference_state.environment.version_info < (3, 6):
+                    return NO_VALUES
+                async_generator_classes = inference_state.typing_module \
+                    .py__getattribute__('AsyncGenerator')
+
+                yield_values = self.merge_yield_values(is_async=True)
+                # The contravariant doesn't seem to be defined.
+                generics = (yield_values.py__class__(), NO_VALUES)
+                return ValueSet(
+                    # In Python 3.6 AsyncGenerator is still a class.
+                    GenericClass(c, TupleGenericManager(generics))
+                    for c in async_generator_classes
+                ).execute_annotation()
+            else:
+                if inference_state.environment.version_info < (3, 5):
+                    return NO_VALUES
+                async_classes = inference_state.typing_module.py__getattribute__('Coroutine')
+                return_values = self.get_return_values()
+                # Only the first generic is relevant.
+                generics = (return_values.py__class__(), NO_VALUES, NO_VALUES)
+                return ValueSet(
+                    GenericClass(c, TupleGenericManager(generics)) for c in async_classes
+                ).execute_annotation()
+        else:
+            if self.is_generator():
+                return ValueSet([iterable.Generator(inference_state, self)])
+            else:
+                return self.get_return_values()
+
+
+class FunctionExecutionContext(BaseFunctionExecutionContext):
+    def __init__(self, function_value, arguments):
+        super(FunctionExecutionContext, self).__init__(function_value)
+        self._arguments = arguments
+
+    def get_filters(self, until_position=None, origin_scope=None):
+        yield FunctionExecutionFilter(
+            self, self._value,
+            until_position=until_position,
+            origin_scope=origin_scope,
+            arguments=self._arguments
+        )
+
+    def infer_annotations(self):
+        from jedi.inference.gradual.annotation import infer_return_types
+        return infer_return_types(self._value, self._arguments)
+
+    def get_param_names(self):
+        return [
+            ParamName(self._value, param.name, self._arguments)
+            for param in self._value.tree_node.get_params()
+        ]
+
+
+class AnonymousFunctionExecution(BaseFunctionExecutionContext):
+    def infer_annotations(self):
+        # I don't think inferring anonymous executions is a big thing.
+        # Anonymous contexts are mostly there for the user to work in. ~ dave
+        return NO_VALUES
+
+    def get_filters(self, until_position=None, origin_scope=None):
+        yield AnonymousFunctionExecutionFilter(
+            self, self._value,
+            until_position=until_position,
+            origin_scope=origin_scope,
+        )
+
+    def get_param_names(self):
+        return self._value.get_param_names()
+
+
+class OverloadedFunctionValue(FunctionMixin, ValueWrapper):
+    def __init__(self, function, overloaded_functions):
+        super(OverloadedFunctionValue, self).__init__(function)
+        self._overloaded_functions = overloaded_functions
+
+    def py__call__(self, arguments):
+        debug.dbg("Execute overloaded function %s", self._wrapped_value, color='BLUE')
+        function_executions = []
+        for signature in self.get_signatures():
+            function_execution = signature.value.as_context(arguments)
+            function_executions.append(function_execution)
+            if signature.matches_signature(arguments):
+                return function_execution.infer()
+
+        if self.inference_state.is_analysis:
+            # In this case we want precision.
+            return NO_VALUES
+        return ValueSet.from_sets(fe.infer() for fe in function_executions)
+
+    def get_signature_functions(self):
+        return self._overloaded_functions
+
+    def get_type_hint(self, add_class_info=True):
+        return 'Union[%s]' % ', '.join(f.get_type_hint() for f in self._overloaded_functions)
+
+
+def _find_overload_functions(context, tree_node):
+    def _is_overload_decorated(funcdef):
+        if funcdef.parent.type == 'decorated':
+            decorators = funcdef.parent.children[0]
+            if decorators.type == 'decorator':
+                decorators = [decorators]
+            else:
+                decorators = decorators.children
+            for decorator in decorators:
+                dotted_name = decorator.children[1]
+                if dotted_name.type == 'name' and dotted_name.value == 'overload':
+                    # TODO check with values if it's the right overload
+                    return True
+        return False
+
+    if tree_node.type == 'lambdef':
+        return
+
+    if _is_overload_decorated(tree_node):
+        yield tree_node
+
+    while True:
+        filter = ParserTreeFilter(
+            context,
+            until_position=tree_node.start_pos
+        )
+        names = filter.get(tree_node.name.value)
+        assert isinstance(names, list)
+        if not names:
+            break
+
+        found = False
+        for name in names:
+            funcdef = name.tree_name.parent
+            if funcdef.type == 'funcdef' and _is_overload_decorated(funcdef):
+                tree_node = funcdef
+                found = True
+                yield funcdef
+
+        if not found:
+            break