示例#1
0
def _apply_decorators(context, node):
    """
    Returns the function, that should to be executed in the end.
    This is also the places where the decorators are processed.
    """
    if node.type == 'classdef':
        decoratee_value = ClassValue(
            context.inference_state,
            parent_context=context,
            tree_node=node
        )
    else:
        decoratee_value = FunctionValue.from_context(context, node)
    initial = values = ValueSet([decoratee_value])
    for dec in reversed(node.get_decorators()):
        debug.dbg('decorator: %s %s', dec, values, color="MAGENTA")
        with debug.increase_indent_cm():
            dec_values = context.infer_node(dec.children[1])
            trailer_nodes = dec.children[2:-1]
            if trailer_nodes:
                # Create a trailer and infer it.
                trailer = tree.PythonNode('trailer', trailer_nodes)
                trailer.parent = dec
                dec_values = infer_trailer(context, dec_values, trailer)

            if not len(dec_values):
                code = dec.get_code(include_prefix=False)
                # For the short future, we don't want to hear about the runtime
                # decorator in typing that was intentionally omitted. This is not
                # "correct", but helps with debugging.
                if code != '@runtime\n':
                    debug.warning('decorator not found: %s on %s', dec, node)
                return initial

            values = dec_values.execute(arguments.ValuesArguments([values]))
            if not len(values):
                debug.warning('not possible to resolve wrappers found %s', node)
                return initial

        debug.dbg('decorator end %s', values, color="MAGENTA")
    if values != initial:
        return ValueSet([Decoratee(c, decoratee_value) for c in values])
    return values
示例#2
0
    def infer(self, context, name):
        def_ = name.get_definition(import_name_always=True)
        if def_ is not None:
            type_ = def_.type
            is_classdef = type_ == 'classdef'
            if is_classdef or type_ == 'funcdef':
                if is_classdef:
                    c = ClassValue(self, context, name.parent)
                else:
                    c = FunctionValue.from_context(context, name.parent)
                return ValueSet([c])

            if type_ == 'expr_stmt':
                is_simple_name = name.parent.type not in ('power', 'trailer')
                if is_simple_name:
                    return infer_expr_stmt(context, def_, name)
            if type_ == 'for_stmt':
                container_types = context.infer_node(def_.children[3])
                cn = ContextualizedNode(context, def_.children[3])
                for_types = iterate_values(container_types, cn)
                n = TreeNameDefinition(context, name)
                return check_tuple_assignments(n, for_types)
            if type_ in ('import_from', 'import_name'):
                return imports.infer_import(context, name)
            if type_ == 'with_stmt':
                return tree_name_to_values(self, context, name)
            elif type_ == 'param':
                return context.py__getattribute__(name.value,
                                                  position=name.end_pos)
            elif type_ == 'namedexpr_test':
                return context.infer_node(def_)
        else:
            result = follow_error_node_imports_if_possible(context, name)
            if result is not None:
                return result

        return helpers.infer_call_of_leaf(context, name)
示例#3
0
def _infer_node(context, element):
    debug.dbg('infer_node %s@%s in %s', element, element.start_pos, context)
    inference_state = context.inference_state
    typ = element.type
    if typ in ('name', 'number', 'string', 'atom', 'strings', 'keyword',
               'fstring'):
        return infer_atom(context, element)
    elif typ == 'lambdef':
        return ValueSet([FunctionValue.from_context(context, element)])
    elif typ == 'expr_stmt':
        return infer_expr_stmt(context, element)
    elif typ in ('power', 'atom_expr'):
        first_child = element.children[0]
        children = element.children[1:]
        had_await = False
        if first_child.type == 'keyword' and first_child.value == 'await':
            had_await = True
            first_child = children.pop(0)

        value_set = context.infer_node(first_child)
        for (i, trailer) in enumerate(children):
            if trailer == '**':  # has a power operation.
                right = context.infer_node(children[i + 1])
                value_set = _infer_comparison(context, value_set, trailer,
                                              right)
                break
            value_set = infer_trailer(context, value_set, trailer)

        if had_await:
            return value_set.py__await__().py__stop_iteration_returns()
        return value_set
    elif typ in (
            'testlist_star_expr',
            'testlist',
    ):
        # The implicit tuple in statements.
        return ValueSet(
            [iterable.SequenceLiteralValue(inference_state, context, element)])
    elif typ in ('not_test', 'factor'):
        value_set = context.infer_node(element.children[-1])
        for operator in element.children[:-1]:
            value_set = infer_factor(value_set, operator)
        return value_set
    elif typ == 'test':
        # `x if foo else y` case.
        return (context.infer_node(element.children[0])
                | context.infer_node(element.children[-1]))
    elif typ == 'operator':
        # Must be an ellipsis, other operators are not inferred.
        if element.value != '...':
            origin = element.parent
            raise AssertionError("unhandled operator %s in %s " %
                                 (repr(element.value), origin))
        return ValueSet(
            [compiled.builtin_from_name(inference_state, 'Ellipsis')])
    elif typ == 'dotted_name':
        value_set = infer_atom(context, element.children[0])
        for next_name in element.children[2::2]:
            value_set = value_set.py__getattribute__(next_name,
                                                     name_context=context)
        return value_set
    elif typ == 'eval_input':
        return context.infer_node(element.children[0])
    elif typ == 'annassign':
        return annotation.infer_annotation(context, element.children[1]) \
            .execute_annotation()
    elif typ == 'yield_expr':
        if len(element.children) and element.children[1].type == 'yield_arg':
            # Implies that it's a yield from.
            element = element.children[1].children[1]
            generators = context.infer_node(element) \
                .py__getattribute__('__iter__').execute_with_values()
            return generators.py__stop_iteration_returns()

        # Generator.send() is not implemented.
        return NO_VALUES
    elif typ == 'namedexpr_test':
        return context.infer_node(element.children[2])
    else:
        return infer_or_test(context, element)