text: # coding: utf-8
  
  """
  Copyright 2016 SmartBear Software
  
      Licensed under the Apache License, Version 2.0 (the "License");
      you may not use this file except in compliance with the License.
      You may obtain a copy of the License at
  
          http://www.apache.org/licenses/LICENSE-2.0
  
      Unless required by applicable law or agreed to in writing, software
      distributed under the License is distributed on an "AS IS" BASIS,
      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
      See the License for the specific language governing permissions and
      limitations under the License.
  
      Ref: https://github.com/swagger-api/swagger-codegen
  """
  
  from pprint import pformat
  from six import iteritems
  import re
  import json
  
  from ..utils import sanitize_for_serialization
  
  class LearningAssignmentAggregateParam(object):
      """
      NOTE: This class is auto generated by the swagger code generator program.
      Do not edit the class manually.
      """
      def __init__(self):
          """
          LearningAssignmentAggregateParam - a model defined in Swagger
  
          :param dict swaggerTypes: The key is attribute name
                                    and the value is attribute type.
          :param dict attributeMap: The key is attribute name
                                    and the value is json key in definition.
          """
          self.swagger_types = {
              'interval': 'str',
              'metrics': 'list[str]',
              'group_by': 'list[str]',
              'filter': 'LearningAssignmentAggregateQueryRequestFilter'
          }
  
          self.attribute_map = {
              'interval': 'interval',
              'metrics': 'metrics',
              'group_by': 'groupBy',
              'filter': 'filter'
          }
  
          self._interval = None
          self._metrics = None
          self._group_by = None
          self._filter = None
  
      @property
      def interval(self):
          """
          Gets the interval of this LearningAssignmentAggregateParam.
          Specifies the range of due dates to be used for filtering. Milliseconds will be truncated. A maximum of 1 year can be specified in the range. End date is not inclusive. Intervals are represented as an ISO-8601 string. For example: YYYY-MM-DDThh:mm:ss/YYYY-MM-DDThh:mm:ss
  
          :return: The interval of this LearningAssignmentAggregateParam.
          :rtype: str
          """
          return self._interval
  
      @interval.setter
      def interval(self, interval):
          """
          Sets the interval of this LearningAssignmentAggregateParam.
          Specifies the range of due dates to be used for filtering. Milliseconds will be truncated. A maximum of 1 year can be specified in the range. End date is not inclusive. Intervals are represented as an ISO-8601 string. For example: YYYY-MM-DDThh:mm:ss/YYYY-MM-DDThh:mm:ss
  
          :param interval: The interval of this LearningAssignmentAggregateParam.
          :type: str
          """
          
          self._interval = interval
  
      @property
      def metrics(self):
          """
          Gets the metrics of this LearningAssignmentAggregateParam.
          The list of metrics to be returned. If omitted, all metrics are returned.
  
          :return: The metrics of this LearningAssignmentAggregateParam.
          :rtype: list[str]
          """
          return self._metrics
  
      @metrics.setter
      def metrics(self, metrics):
          """
          Sets the metrics of this LearningAssignmentAggregateParam.
          The list of metrics to be returned. If omitted, all metrics are returned.
  
          :param metrics: The metrics of this LearningAssignmentAggregateParam.
          :type: list[str]
          """
          
          self._metrics = metrics
  
      @property
      def group_by(self):
          """
          Gets the group_by of this LearningAssignmentAggregateParam.
          Specifies if the aggregated data is combined into a single set of metrics (groupBy is empty or not specified), or contains an element per attendeeId (groupBy is \"attendeeId\")
  
          :return: The group_by of this LearningAssignmentAggregateParam.
          :rtype: list[str]
          """
          return self._group_by
  
      @group_by.setter
      def group_by(self, group_by):
          """
          Sets the group_by of this LearningAssignmentAggregateParam.
          Specifies if the aggregated data is combined into a single set of metrics (groupBy is empty or not specified), or contains an element per attendeeId (groupBy is \"attendeeId\")
  
          :param group_by: The group_by of this LearningAssignmentAggregateParam.
          :type: list[str]
          """
          
          self._group_by = group_by
  
      @property
      def filter(self):
          """
          Gets the filter of this LearningAssignmentAggregateParam.
          The filter applied to the data.  This is ANDed with the interval parameter. 
  
          :return: The filter of this LearningAssignmentAggregateParam.
          :rtype: LearningAssignmentAggregateQueryRequestFilter
          """
          return self._filter
  
      @filter.setter
      def filter(self, filter):
          """
          Sets the filter of this LearningAssignmentAggregateParam.
          The filter applied to the data.  This is ANDed with the interval parameter. 
  
          :param filter: The filter of this LearningAssignmentAggregateParam.
          :type: LearningAssignmentAggregateQueryRequestFilter
          """
          
          self._filter = filter
  
      def to_dict(self):
          """
          Returns the model properties as a dict
          """
          result = {}
  
          for attr, _ in iteritems(self.swagger_types):
              value = getattr(self, attr)
              if isinstance(value, list):
                  result[attr] = list(map(
                      lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
                      value
                  ))
              elif hasattr(value, "to_dict"):
                  result[attr] = value.to_dict()
              elif isinstance(value, dict):
                  result[attr] = dict(map(
                      lambda item: (item[0], item[1].to_dict())
                      if hasattr(item[1], "to_dict") else item,
                      value.items()
                  ))
              else:
                  result[attr] = value
  
          return result
  
      def to_json(self):
          """
          Returns the model as raw JSON
          """
          return json.dumps(sanitize_for_serialization(self.to_dict()))
  
      def to_str(self):
          """
          Returns the string representation of the model
          """
          return pformat(self.to_dict())
  
      def __repr__(self):
          """
          For `print` and `pprint`
          """
          return self.to_str()
  
      def __eq__(self, other):
          """
          Returns true if both objects are equal
          """
          return self.__dict__ == other.__dict__
  
      def __ne__(self, other):
          """
          Returns true if both objects are not equal
          """
          return not self == other
  
  