Пример #1
0
 def to_dict(self):
     return {'user_id': self.user_id,
             'project_id': self.project_id,
             'is_admin': self.is_admin,
             'read_deleted': self.read_deleted,
             'roles': self.roles,
             'remote_address': self.remote_address,
             'timestamp': timeutils.strtime(self.timestamp),
             'request_id': self.request_id,
             'auth_token': self.auth_token,
             'quota_class': self.quota_class,
             'tenant': self.tenant,
             'service_catalog': self.service_catalog,
             'user': self.user}
Пример #2
0
 def to_dict(self):
     return {'user_id': self.user_id,
             'project_id': self.project_id,
             'is_admin': self.is_admin,
             'read_deleted': self.read_deleted,
             'roles': self.roles,
             'remote_address': self.remote_address,
             'timestamp': timeutils.strtime(self.timestamp),
             'request_id': self.request_id,
             'auth_token': self.auth_token,
             'quota_class': self.quota_class,
             'tenant': self.tenant,
             'service_catalog': self.service_catalog,
             'user': self.user}
Пример #3
0
 def to_dict(self):
     return {
         "user_id": self.user_id,
         "project_id": self.project_id,
         "is_admin": self.is_admin,
         "read_deleted": self.read_deleted,
         "roles": self.roles,
         "remote_address": self.remote_address,
         "timestamp": timeutils.strtime(self.timestamp),
         "request_id": self.request_id,
         "auth_token": self.auth_token,
         "quota_class": self.quota_class,
         "tenant": self.tenant,
         "user": self.user,
     }
Пример #4
0
def to_primitive(value,
                 convert_instances=False,
                 convert_datetime=True,
                 level=0,
                 max_depth=3):
    """Convert a complex object into primitives.

    Handy for JSON serialization. We can optionally handle instances,
    but since this is a recursive function, we could have cyclical
    data structures.

    To handle cyclical data structures we could track the actual objects
    visited in a set, but not all objects are hashable. Instead we just
    track the depth of the object inspections and don't go too deep.

    Therefore, convert_instances=True is lossy ... be aware.

    """
    # handle obvious types first - order of basic types determined by running
    # full tests on nova project, resulting in the following counts:
    # 572754 <type 'NoneType'>
    # 460353 <type 'int'>
    # 379632 <type 'unicode'>
    # 274610 <type 'str'>
    # 199918 <type 'dict'>
    # 114200 <type 'datetime.datetime'>
    #  51817 <type 'bool'>
    #  26164 <type 'list'>
    #   6491 <type 'float'>
    #    283 <type 'tuple'>
    #     19 <type 'long'>
    if isinstance(value, _simple_types):
        return value

    if isinstance(value, datetime.datetime):
        if convert_datetime:
            return timeutils.strtime(value)
        else:
            return value

    # value of itertools.count doesn't get caught by nasty_type_tests
    # and results in infinite loop when list(value) is called.
    if type(value) == itertools.count:
        return six.text_type(value)

    # FIXME(vish): Workaround for LP bug 852095. Without this workaround,
    #              tests that raise an exception in a mocked method that
    #              has a @wrap_exception with a notifier will fail. If
    #              we up the dependency to 0.5.4 (when it is released) we
    #              can remove this workaround.
    if getattr(value, '__module__', None) == 'mox':
        return 'mock'

    if level > max_depth:
        return '?'

    # The try block may not be necessary after the class check above,
    # but just in case ...
    try:
        recursive = functools.partial(to_primitive,
                                      convert_instances=convert_instances,
                                      convert_datetime=convert_datetime,
                                      level=level,
                                      max_depth=max_depth)
        if isinstance(value, dict):
            return dict((k, recursive(v)) for k, v in six.iteritems(value))
        elif isinstance(value, (list, tuple)):
            return [recursive(lv) for lv in value]

        # It's not clear why xmlrpclib created their own DateTime type, but
        # for our purposes, make it a datetime type which is explicitly
        # handled
        if isinstance(value, xmlrpclib.DateTime):
            value = datetime.datetime(*tuple(value.timetuple())[:6])

        if convert_datetime and isinstance(value, datetime.datetime):
            return timeutils.strtime(value)
        elif isinstance(value, gettextutils.Message):
            return value.data
        elif hasattr(value, 'iteritems'):
            return recursive(dict(value.iteritems()), level=level + 1)
        elif hasattr(value, '__iter__'):
            return recursive(list(value))
        elif convert_instances and hasattr(value, '__dict__'):
            # Likely an instance of something. Watch for cycles.
            # Ignore class member vars.
            return recursive(value.__dict__, level=level + 1)
        elif netaddr and isinstance(value, netaddr.IPAddress):
            return six.text_type(value)
        else:
            if any(test(value) for test in _nasty_type_tests):
                return six.text_type(value)
            return value
    except TypeError:
        # Class objects are tricky since they may define something like
        # __iter__ defined but it isn't callable as list().
        return six.text_type(value)
Пример #5
0
def to_primitive(value, convert_instances=False, convert_datetime=True,
                 level=0, max_depth=3):
    """Convert a complex object into primitives.

    Handy for JSON serialization. We can optionally handle instances,
    but since this is a recursive function, we could have cyclical
    data structures.

    To handle cyclical data structures we could track the actual objects
    visited in a set, but not all objects are hashable. Instead we just
    track the depth of the object inspections and don't go too deep.

    Therefore, convert_instances=True is lossy ... be aware.

    """
    # handle obvious types first - order of basic types determined by running
    # full tests on nova project, resulting in the following counts:
    # 572754 <type 'NoneType'>
    # 460353 <type 'int'>
    # 379632 <type 'unicode'>
    # 274610 <type 'str'>
    # 199918 <type 'dict'>
    # 114200 <type 'datetime.datetime'>
    #  51817 <type 'bool'>
    #  26164 <type 'list'>
    #   6491 <type 'float'>
    #    283 <type 'tuple'>
    #     19 <type 'long'>
    if isinstance(value, _simple_types):
        return value

    if isinstance(value, datetime.datetime):
        if convert_datetime:
            return timeutils.strtime(value)
        else:
            return value

    # value of itertools.count doesn't get caught by nasty_type_tests
    # and results in infinite loop when list(value) is called.
    if type(value) == itertools.count:
        return six.text_type(value)

    # FIXME(vish): Workaround for LP bug 852095. Without this workaround,
    #              tests that raise an exception in a mocked method that
    #              has a @wrap_exception with a notifier will fail. If
    #              we up the dependency to 0.5.4 (when it is released) we
    #              can remove this workaround.
    if getattr(value, '__module__', None) == 'mox':
        return 'mock'

    if level > max_depth:
        return '?'

    # The try block may not be necessary after the class check above,
    # but just in case ...
    try:
        recursive = functools.partial(to_primitive,
                                      convert_instances=convert_instances,
                                      convert_datetime=convert_datetime,
                                      level=level,
                                      max_depth=max_depth)
        if isinstance(value, dict):
            return dict((k, recursive(v)) for k, v in six.iteritems(value))
        elif isinstance(value, (list, tuple)):
            return [recursive(lv) for lv in value]

        # It's not clear why xmlrpclib created their own DateTime type, but
        # for our purposes, make it a datetime type which is explicitly
        # handled
        if isinstance(value, xmlrpclib.DateTime):
            value = datetime.datetime(*tuple(value.timetuple())[:6])

        if convert_datetime and isinstance(value, datetime.datetime):
            return timeutils.strtime(value)
        elif isinstance(value, gettextutils.Message):
            return value.data
        elif hasattr(value, 'iteritems'):
            return recursive(dict(value.iteritems()), level=level + 1)
        elif hasattr(value, '__iter__'):
            return recursive(list(value))
        elif convert_instances and hasattr(value, '__dict__'):
            # Likely an instance of something. Watch for cycles.
            # Ignore class member vars.
            return recursive(value.__dict__, level=level + 1)
        elif netaddr and isinstance(value, netaddr.IPAddress):
            return six.text_type(value)
        else:
            if any(test(value) for test in _nasty_type_tests):
                return six.text_type(value)
            return value
    except TypeError:
        # Class objects are tricky since they may define something like
        # __iter__ defined but it isn't callable as list().
        return six.text_type(value)