def update(self, doc, process=None):
        if process is None:
            pk = 'id'
            id = doc.id
            doc.synced = False
            set = doc
        elif process == UPDATE_PROCESS:
            if self.db.docs.find({'sid': doc.sid}).count() == 0:
                return self.insert(doc, synced=True)
            pk = 'sid'
            id = doc.sid
            doc.synced = not doc.merged() # must be commited if was merged
            doc.merged(False)
            set = {'tid': doc.tid, 'data': doc.data, 'user': doc.user,
                   'public': doc.public, 'synced': doc.synced}
        elif process == COMMIT_PROCESS:
            pk = 'id'
            id = doc.id
            doc.synced = True
            set = {'sid': doc.sid, 'tid': doc.tid, 'synced': doc.synced}
        else:
            raise DatabaseException('Incorrect update process')

        try:
            rs = self.db.docs.update({pk: id}, {'$set': set}, safe=True)
            assert rs['n'] == 1
        except Exception as e:
            raise DatabaseException(e)
        return doc
def _check_target_vars(target_names):
    """Error-checks list of target variables.

    Target variables must all have the same mean lead time (average of min and
    max lead times) and event type (tornado or wind).

    :param target_names: 1-D list with names of target variables.  Each must be
        accepted by `target_val_utils.target_name_to_params`.
    :return: mean_lead_time_seconds: Mean lead time (shared by all target
        variables).
    :return: event_type_string: Event type.
    :raises: ValueError: if target variables do not all have the same mean lead
        time or event type.
    """

    error_checking.assert_is_string_list(target_names)
    error_checking.assert_is_numpy_array(
        numpy.array(target_names), num_dimensions=1
    )

    num_target_vars = len(target_names)
    mean_lead_times = numpy.full(num_target_vars, -1, dtype=int)
    event_type_strings = numpy.full(num_target_vars, '', dtype=object)

    for k in range(num_target_vars):
        this_param_dict = target_val_utils.target_name_to_params(
            target_names[k]
        )

        event_type_strings[k] = this_param_dict[target_val_utils.EVENT_TYPE_KEY]

        mean_lead_times[k] = int(numpy.round(
            (this_param_dict[target_val_utils.MAX_LEAD_TIME_KEY] +
             this_param_dict[target_val_utils.MIN_LEAD_TIME_KEY])
            / 2
        ))

    if len(numpy.unique(mean_lead_times)) != 1:
        error_string = (
            'Target variables (listed below) have different mean lead times.'
            '\n{0:s}'
        ).format(str(target_names))

        raise ValueError(error_string)

    if len(numpy.unique(event_type_strings)) != 1:
        error_string = (
            'Target variables (listed below) have different event types.\n{0:s}'
        ).format(str(target_names))

        raise ValueError(error_string)

    return mean_lead_times[0], event_type_strings[0]