# coding: utf-8

#
# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file
# except in compliance with the License. A copy of the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file 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.
#

import pprint
import re  # noqa: F401
import six
import typing
from enum import Enum


if typing.TYPE_CHECKING:
    from typing import Dict, List, Optional, Union
    from datetime import datetime
    from ask_smapi_model.v1.skill.invocations.metrics import MetricsV1
    from ask_smapi_model.v1.skill.invocations.request import RequestV1
    from ask_smapi_model.v1.skill.invocations.response import ResponseV1


class SkillExecutionInfo(object):
    """

    :param invocation_request: 
    :type invocation_request: (optional) dict(str, ask_smapi_model.v1.skill.invocations.request.Request)
    :param invocation_response: 
    :type invocation_response: (optional) dict(str, ask_smapi_model.v1.skill.invocations.response.Response)
    :param metrics: 
    :type metrics: (optional) dict(str, ask_smapi_model.v1.skill.invocations.metrics.Metrics)

    """
    deserialized_types = {
        'invocation_request': 'dict(str, ask_smapi_model.v1.skill.invocations.request.Request)',
        'invocation_response': 'dict(str, ask_smapi_model.v1.skill.invocations.response.Response)',
        'metrics': 'dict(str, ask_smapi_model.v1.skill.invocations.metrics.Metrics)'
    }  # type: Dict

    attribute_map = {
        'invocation_request': 'invocationRequest',
        'invocation_response': 'invocationResponse',
        'metrics': 'metrics'
    }  # type: Dict
    supports_multiple_types = False

    def __init__(self, invocation_request=None, invocation_response=None, metrics=None):
        # type: (Optional[Dict[str, RequestV1]], Optional[Dict[str, ResponseV1]], Optional[Dict[str, MetricsV1]]) -> None
        """

        :param invocation_request: 
        :type invocation_request: (optional) dict(str, ask_smapi_model.v1.skill.invocations.request.Request)
        :param invocation_response: 
        :type invocation_response: (optional) dict(str, ask_smapi_model.v1.skill.invocations.response.Response)
        :param metrics: 
        :type metrics: (optional) dict(str, ask_smapi_model.v1.skill.invocations.metrics.Metrics)
        """
        self.__discriminator_value = None  # type: str

        self.invocation_request = invocation_request
        self.invocation_response = invocation_response
        self.metrics = metrics

    def to_dict(self):
        # type: () -> Dict[str, object]
        """Returns the model properties as a dict"""
        result = {}  # type: Dict

        for attr, _ in six.iteritems(self.deserialized_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 if isinstance(x, Enum) else x,
                    value
                ))
            elif isinstance(value, Enum):
                result[attr] = value.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[0], item[1].value)
                    if isinstance(item[1], Enum) else item,
                    value.items()
                ))
            else:
                result[attr] = value

        return result

    def to_str(self):
        # type: () -> str
        """Returns the string representation of the model"""
        return pprint.pformat(self.to_dict())

    def __repr__(self):
        # type: () -> str
        """For `print` and `pprint`"""
        return self.to_str()

    def __eq__(self, other):
        # type: (object) -> bool
        """Returns true if both objects are equal"""
        if not isinstance(other, SkillExecutionInfo):
            return False

        return self.__dict__ == other.__dict__

    def __ne__(self, other):
        # type: (object) -> bool
        """Returns true if both objects are not equal"""
        return not self == other
