sdk/dingdingSdk/alibabacloud_dingtalk/bay_max_1_0/models.py

# -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
from Tea.model import TeaModel
from typing import Dict


class QueryBaymaxSkillLogHeaders(TeaModel):
    def __init__(
        self,
        common_headers: Dict[str, str] = None,
        x_acs_dingtalk_access_token: str = None,
    ):
        self.common_headers = common_headers
        self.x_acs_dingtalk_access_token = x_acs_dingtalk_access_token

    def validate(self):
        pass

    def to_map(self):
        _map = super().to_map()
        if _map is not None:
            return _map

        result = dict()
        if self.common_headers is not None:
            result['commonHeaders'] = self.common_headers
        if self.x_acs_dingtalk_access_token is not None:
            result['x-acs-dingtalk-access-token'] = self.x_acs_dingtalk_access_token
        return result

    def from_map(self, m: dict = None):
        m = m or dict()
        if m.get('commonHeaders') is not None:
            self.common_headers = m.get('commonHeaders')
        if m.get('x-acs-dingtalk-access-token') is not None:
            self.x_acs_dingtalk_access_token = m.get('x-acs-dingtalk-access-token')
        return self


class QueryBaymaxSkillLogRequest(TeaModel):
    def __init__(
        self,
        from_: int = None,
        skill_execute_id: str = None,
        to: int = None,
    ):
        self.from_ = from_
        # This parameter is required.
        self.skill_execute_id = skill_execute_id
        self.to = to

    def validate(self):
        pass

    def to_map(self):
        _map = super().to_map()
        if _map is not None:
            return _map

        result = dict()
        if self.from_ is not None:
            result['from'] = self.from_
        if self.skill_execute_id is not None:
            result['skillExecuteId'] = self.skill_execute_id
        if self.to is not None:
            result['to'] = self.to
        return result

    def from_map(self, m: dict = None):
        m = m or dict()
        if m.get('from') is not None:
            self.from_ = m.get('from')
        if m.get('skillExecuteId') is not None:
            self.skill_execute_id = m.get('skillExecuteId')
        if m.get('to') is not None:
            self.to = m.get('to')
        return self


class QueryBaymaxSkillLogResponseBody(TeaModel):
    def __init__(
        self,
        result: str = None,
    ):
        # This parameter is required.
        self.result = result

    def validate(self):
        pass

    def to_map(self):
        _map = super().to_map()
        if _map is not None:
            return _map

        result = dict()
        if self.result is not None:
            result['result'] = self.result
        return result

    def from_map(self, m: dict = None):
        m = m or dict()
        if m.get('result') is not None:
            self.result = m.get('result')
        return self


class QueryBaymaxSkillLogResponse(TeaModel):
    def __init__(
        self,
        headers: Dict[str, str] = None,
        status_code: int = None,
        body: QueryBaymaxSkillLogResponseBody = None,
    ):
        self.headers = headers
        self.status_code = status_code
        self.body = body

    def validate(self):
        if self.body:
            self.body.validate()

    def to_map(self):
        _map = super().to_map()
        if _map is not None:
            return _map

        result = dict()
        if self.headers is not None:
            result['headers'] = self.headers
        if self.status_code is not None:
            result['statusCode'] = self.status_code
        if self.body is not None:
            result['body'] = self.body.to_map()
        return result

    def from_map(self, m: dict = None):
        m = m or dict()
        if m.get('headers') is not None:
            self.headers = m.get('headers')
        if m.get('statusCode') is not None:
            self.status_code = m.get('statusCode')
        if m.get('body') is not None:
            temp_model = QueryBaymaxSkillLogResponseBody()
            self.body = temp_model.from_map(m['body'])
        return self