Python six.get_function_closure函数代码示例

def _update_function(oldfunc, newfunc):
    """Update a function object."""
    if _closure_changed(six.get_function_closure(oldfunc),
                        six.get_function_closure(newfunc)):
        raise ClosureChanged()
    setattr(oldfunc, six._func_code, six.get_function_code(newfunc))
    setattr(oldfunc, six._func_defaults, six.get_function_defaults(newfunc))
    _update_scope(six.get_function_globals(oldfunc),
                  six.get_function_globals(newfunc))
    # XXX What else?
    return oldfunc

    def test_throttler(self):
        threshold = 1
        orig_function = mock.Mock()
        # Add this magic name as it's required by functools
        orig_function.__name__ = 'mock_func'
        throttled_func = utils.throttler(threshold)(orig_function)

        throttled_func()

        sleep = utils.eventlet.sleep

        def sleep_mock(amount_to_sleep):
            sleep(amount_to_sleep)
            self.assertGreater(threshold, amount_to_sleep)

        with mock.patch.object(utils.eventlet, "sleep",
                               side_effect=sleep_mock):
            throttled_func()

        self.assertEqual(2, orig_function.call_count)

        lock_with_timer = six.get_function_closure(
            throttled_func)[1].cell_contents
        timestamp = lock_with_timer.timestamp - threshold
        lock_with_timer.timestamp = timestamp

        throttled_func()

        self.assertEqual(3, orig_function.call_count)
        self.assertLess(timestamp, lock_with_timer.timestamp)

def run_while(cond_fn, body_fn, init_args):
  """Type-dependent functional while loop.

  Args:
    cond_fn: A Python callable implementing the stop conditions of the loop.
    body_fn: A Python callable implementing the body of the loop.
    init_args: The initial values of the arguments that will be passed to both
      cond_fn and body_fn.

  Returns:
    result: A list of values with the same shape and type as init_args. If any
    of the init_args, or any variables closed-over in cond_fn are Tensors,
    tf.while_loop will be used, otherwise a Python while loop will be ran.

  Raises:
    ValueError: if init_args is not a tuple or list with one or more elements.
  """
  if not isinstance(init_args, (tuple, list)) or not init_args:
    raise ValueError(
        'init_args must be a non-empty list or tuple, found %s' % init_args)

  # TODO(alexbw): statically determine all active variables in cond_fn,
  # and pass them directly
  closure_vars = tuple(
      [c.cell_contents for c in six.get_function_closure(cond_fn) or []])
  possibly_tensors = tuple(init_args) + closure_vars
  if is_tensor(*possibly_tensors):
    return control_flow_ops.while_loop(cond_fn, body_fn, init_args)
  else:
    return py_while_loop(cond_fn, body_fn, init_args)

    def inspect_function_closures(self, func):
        if self.found_req and self.stop_on_request_find:
            return
        if not get_function_closure(func):
            if self.logger:
                self.logger.debug('Function does not have any closure, skipping')
            return
        closures = function_closure_dict(func)
        if func.__name__ == 'inner' and function_module(func) == 'tornado.gen':
            # We are inside tornado.gen.Runner.run, continue to actual wrapped generator
            generator_obj = closures['self'].gen
            gen_frame = generator_obj.gi_frame
            if gen_frame:  # frame may be empty
                if self.logger:
                    self.logger.debug('Found `tornado.gen` instance, running: %s, has_frame: %s'
                                      % (generator_obj.gi_running, bool(gen_frame)))
                # why? need test
                # if not generator_obj.gi_running:
                #     # only write this line as async calls if generator is NOT running, if it's running it's present
                #     # on the normal traceback
                self.async_frames.append(gen_frame)
                if self.logger:
                    self.logger.debug('Diving into `tornado.gen` frame: %s' % traceback.format_stack(gen_frame, 1)[0])
                self.inspect_dict(gen_frame.f_locals)
            elif self.logger:
                self.logger.debug('Found dead `tornado.gen` instance (without any frame), skipping')
            return  # it's a `tornado.gen` object, not need to dive into closures

        if self.logger:
            self.logger.debug('Cannot find generator, diving into closure variables')
        return self.inspect_dict(closures)

def function_to_graph(f, conversion_map, param_value_hints, owner_type=None):
  """Specialization of `object_to_graph` for callable functions."""
  node = parser.parse_object(f).body[0]
  node_globals = six.get_function_globals(f)

  # This is needed for non-global functions.
  closure = six.get_function_closure(f)
  if closure:
    for e in closure:
      if callable(e.cell_contents):
        fn = e.cell_contents
        node_globals[fn.__name__] = fn

  namer = conversion_map.new_namer(node_globals)
  node = node_to_graph(node, namer, node_globals, param_value_hints)

  # Simulate a rename to ensure the top level is in the name map. This is needed
  # for top level functions, and it also helps the consistency verification made
  # by update_name_map.
  if owner_type is not None:
    new_name = namer.compiled_function_name(f.__name__, f, owner_type)
  else:
    new_name = namer.compiled_function_name(f.__name__, f)
  node.name = new_name
  conversion_map.update_name_map(namer)
  return node, conversion_map.name_map[f]

def parse_args(args, path, query, specials):
    def one_or_many(fn_, dict_, key):
        result = [fn_(value) for value in dict_[key]]
        return result[0] if len(result) == 1 else result

    kwargs = {}
    for arg, parse_fn in six.iteritems(args):
        if arg in specials:
            kwargs[arg] = specials[arg]()
        elif parse_fn is None:
            kwargs[arg] = one_or_many(lambda x: x, query, arg)
        elif isinstance(parse_fn, tuple):
            kwargs[arg] = parse_fn[DEFAULT] if arg not in query else one_or_many(parse_fn[CALLABLE], query, arg)
        elif isalambda(parse_fn):
            _code = six.get_function_code(parse_fn)
            closures = six.get_function_closure(parse_fn)
            if closures:
                assert len(closures) <= 1
                fn = closures[0].cell_contents
            else:
                fn = eval(".".join(_code.co_names), six.get_function_globals(parse_fn))
            kwargs[arg] = fn(**parse_args(get_function_args(parse_fn), path, query, specials))
        else:
            kwargs[arg] = one_or_many(parse_fn, query, arg)
    return kwargs

def getrealname(method):
    """attempt to get a method's real name."""
    argspec = inspect.getargspec(method)
    args = argspec[0]
    if args and args[0] == 'self':
        return method.__name__
    if hasattr(method, '__func__'):
        method = method.__func__

    func_closure = six.get_function_closure(method)

    # NOTE(sileht): if the closure is None we cannot look deeper,
    # so return actual argspec, this occurs when the method
    # is static for example.
    if func_closure is None:
        return method.__name__

    closure = next(
        (
            c for c in func_closure if six.callable(c.cell_contents)
        ),
        None
    )
    method = closure.cell_contents
    return getrealname(method)

def function_to_graph(f, conversion_map, param_value_hints):
  """Specialization of `object_to_graph` for callable functions."""
  node = parser.parse_object(f).body[0]
  node_globals = six.get_function_globals(f)

  # This is needed for non-global functions.
  closure = six.get_function_closure(f)
  if closure:
    for e in closure:
      if callable(e.cell_contents):
        fn = e.cell_contents
        node_globals[fn.__name__] = fn

  namer = conversion_map.new_namer(node_globals)
  node = node_to_graph(node, namer, node_globals, param_value_hints)

  # Simulate a rename to ensure the top level is in the name map. This is needed
  # for top level functions, and it also helps the consistency verification made
  # by update_name_map.
  namer.compiled_function_name(f.__name__, f)

  conversion_map.add_to_cache(f, node)
  conversion_map.update_name_map(namer)

  # Recursively convert any remaining dependencies.
  for obj in conversion_map.name_map.keys():
    if obj not in conversion_map.dependency_cache:
      object_to_graph(obj, conversion_map, None)
  return node, conversion_map.name_map[f]

def construct_new_test_function(original_func, name, build_params):
    """Builds a new test function based on parameterized data.

    :param original_func: The original test function that is used as a template
    :param name: The fullname of the new test function
    :param build_params: A dictionary or list containing args or kwargs
        for the new test
    :return: A new function object
    """
    new_func = types.FunctionType(
        six.get_function_code(original_func),
        six.get_function_globals(original_func),
        name=name,
        argdefs=six.get_function_defaults(original_func),
        closure=six.get_function_closure(original_func)
    )

    for key, val in original_func.__dict__.items():
        if key != 'build_data':
            new_func.__dict__[key] = val

    # Support either an arg list or kwarg dict for our data
    build_args = build_params if isinstance(build_params, list) else []
    build_kwargs = build_params if isinstance(build_params, dict) else {}

    # Build a test wrapper to execute with our kwargs
    def test_wrapper(func, test_args, test_kwargs):
        @functools.wraps(func)
        def wrapper(self):
            return func(self, *test_args, **test_kwargs)
        return wrapper

    return test_wrapper(new_func, build_args, build_kwargs)

def get_wrapped_function(function):
    """Get the method at the bottom of a stack of decorators."""

    if not hasattr(function, six._func_closure) or \
       not six.get_function_closure(function):
        return function

    def _get_wrapped_function(function):
        if not hasattr(function, six._func_closure):
            return None

        func_closure = six.get_function_closure(function)
        if not func_closure:
            return None

        for closure in func_closure:
            func = closure.cell_contents

            deeper_func = _get_wrapped_function(func)
            if deeper_func:
                return deeper_func
            elif hasattr(closure.cell_contents, '__call__'):
                return closure.cell_contents

    return _get_wrapped_function(function)

def function_to_graph(f, conversion_map, arg_values, arg_types,
                      owner_type=None):
  """Specialization of `entity_to_graph` for callable functions."""
  node = parser.parse_object(f).body[0]
  namespace = six.get_function_globals(f)

  # This is needed for non-global functions.
  closure = six.get_function_closure(f)
  if closure:
    for e in closure:
      if callable(e.cell_contents):
        fn = e.cell_contents
        namespace[fn.__name__] = fn

  namer = conversion_map.new_namer(namespace)
  ctx = context.EntityContext(
      namer=namer,
      source_code=tf_inspect.getsource(f),
      source_file=tf_inspect.getfile(f),
      namespace=namespace,
      arg_values=arg_values,
      arg_types=arg_types)
  node = node_to_graph(node, ctx, conversion_map.nocompile_decorators)

  # Simulate a rename to ensure the top level is in the name map. This is needed
  # for top level functions, and it also helps the consistency verification made
  # by update_name_map.
  if owner_type is not None:
    new_name = namer.compiled_function_name(f.__name__, f, owner_type)
  else:
    new_name = namer.compiled_function_name(f.__name__, f)
  node.name = new_name
  conversion_map.update_name_map(namer)
  return node, conversion_map.name_map[f]

def getargspec(method):
    """
    Drill through layers of decorators attempting to locate the actual argspec
    for a method.
    """

    argspec = inspect.getargspec(method)
    args = argspec[0]
    if args and args[0] == 'self':
        return argspec
    if hasattr(method, '__func__'):
        method = method.__func__

    func_closure = six.get_function_closure(method)

    # NOTE(sileht): if the closure is None we cannot look deeper,
    # so return actual argspec, this occurs when the method
    # is static for example.
    if func_closure is None:
        return argspec

    closure = next(
        (
            c for c in func_closure if six.callable(c.cell_contents)
        ),
        None
    )
    method = closure.cell_contents
    return getargspec(method)

def serialize(cust_obj):
    """A function to serialize custom objects passed to a model

    Args:
        cust_obj(callable): a custom layer or function to serialize

    Returns:
        a dict of the serialized components of the object"""
    ser_func = dict()
    if isinstance(cust_obj, types.FunctionType):

        func_code = six.get_function_code(cust_obj)
        func_code_d = dill.dumps(func_code).decode('raw_unicode_escape')
        ser_func['func_code_d'] = func_code_d
        ser_func['name_d'] = pickle.dumps(
            cust_obj.__name__).decode('raw_unicode_escape')
        ser_func['args_d'] = pickle.dumps(
            six.get_function_defaults(cust_obj)).decode('raw_unicode_escape')
        clos = dill.dumps(
            six.get_function_closure(cust_obj)).decode('raw_unicode_escape')
        ser_func['clos_d'] = clos
        ser_func['type_obj'] = 'func'
    else:
        if hasattr(cust_obj, '__module__'):  # pragma: no cover
            cust_obj.__module__ = '__main__'
        ser_func['name_d'] = None
        ser_func['args_d'] = None
        ser_func['clos_d'] = None
        ser_func['type_obj'] = 'class'
        loaded = dill.dumps(cust_obj).decode('raw_unicode_escape')
        ser_func['func_code_d'] = loaded
    return ser_func

def _build_new_function(func, name):
    code = six.get_function_code(func)
    func_globals = six.get_function_globals(func)
    func_defaults = six.get_function_defaults(func)
    func_closure = six.get_function_closure(func)
    return types.FunctionType(code, func_globals,
                              name, func_defaults,
                              func_closure)

def test_get_function_closure():
    def f():
        x = 42
        def g():
            return x
        return g
    cell = six.get_function_closure(f())[0]
    assert type(cell).__name__ == "cell"