730 lines
23 KiB
Python
730 lines
23 KiB
Python
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# -*- coding: utf-8 -*-
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# This file is auto-generated, don't edit it. Thanks.
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from Tea.model import TeaModel
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from typing import Dict, List
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class NlpWordDistinguishHeaders(TeaModel):
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def __init__(
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self,
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common_headers: Dict[str, str] = None,
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x_acs_dingtalk_access_token: str = None,
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):
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self.common_headers = common_headers
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self.x_acs_dingtalk_access_token = x_acs_dingtalk_access_token
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def validate(self):
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pass
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.common_headers is not None:
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result['commonHeaders'] = self.common_headers
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if self.x_acs_dingtalk_access_token is not None:
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result['x-acs-dingtalk-access-token'] = self.x_acs_dingtalk_access_token
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('commonHeaders') is not None:
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self.common_headers = m.get('commonHeaders')
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if m.get('x-acs-dingtalk-access-token') is not None:
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self.x_acs_dingtalk_access_token = m.get('x-acs-dingtalk-access-token')
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return self
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class NlpWordDistinguishRequestAttachExtractDecisionInfo(TeaModel):
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def __init__(
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self,
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black_words: List[str] = None,
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candidate_words: List[str] = None,
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corp_id: str = None,
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dept_ids: List[str] = None,
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user_id: str = None,
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):
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self.black_words = black_words
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self.candidate_words = candidate_words
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# This parameter is required.
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self.corp_id = corp_id
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# This parameter is required.
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self.dept_ids = dept_ids
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# This parameter is required.
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self.user_id = user_id
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def validate(self):
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pass
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.black_words is not None:
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result['blackWords'] = self.black_words
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if self.candidate_words is not None:
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result['candidateWords'] = self.candidate_words
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if self.corp_id is not None:
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result['corpId'] = self.corp_id
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if self.dept_ids is not None:
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result['deptIds'] = self.dept_ids
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if self.user_id is not None:
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result['userId'] = self.user_id
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('blackWords') is not None:
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self.black_words = m.get('blackWords')
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if m.get('candidateWords') is not None:
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self.candidate_words = m.get('candidateWords')
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if m.get('corpId') is not None:
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self.corp_id = m.get('corpId')
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if m.get('deptIds') is not None:
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self.dept_ids = m.get('deptIds')
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if m.get('userId') is not None:
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self.user_id = m.get('userId')
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return self
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class NlpWordDistinguishRequest(TeaModel):
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def __init__(
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self,
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attach_extract_decision_info: NlpWordDistinguishRequestAttachExtractDecisionInfo = None,
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isv_app_id: str = None,
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text: str = None,
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):
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# This parameter is required.
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self.attach_extract_decision_info = attach_extract_decision_info
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# This parameter is required.
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self.isv_app_id = isv_app_id
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# This parameter is required.
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self.text = text
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def validate(self):
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if self.attach_extract_decision_info:
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self.attach_extract_decision_info.validate()
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.attach_extract_decision_info is not None:
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result['attachExtractDecisionInfo'] = self.attach_extract_decision_info.to_map()
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if self.isv_app_id is not None:
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result['isvAppId'] = self.isv_app_id
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if self.text is not None:
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result['text'] = self.text
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('attachExtractDecisionInfo') is not None:
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temp_model = NlpWordDistinguishRequestAttachExtractDecisionInfo()
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self.attach_extract_decision_info = temp_model.from_map(m['attachExtractDecisionInfo'])
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if m.get('isvAppId') is not None:
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self.isv_app_id = m.get('isvAppId')
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if m.get('text') is not None:
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self.text = m.get('text')
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return self
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class NlpWordDistinguishResponseBodyWordEntities(TeaModel):
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def __init__(
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self,
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word: str = None,
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):
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self.word = word
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def validate(self):
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pass
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.word is not None:
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result['word'] = self.word
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('word') is not None:
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self.word = m.get('word')
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return self
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class NlpWordDistinguishResponseBody(TeaModel):
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def __init__(
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self,
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request_id: str = None,
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word_entities: List[NlpWordDistinguishResponseBodyWordEntities] = None,
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):
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# This parameter is required.
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self.request_id = request_id
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self.word_entities = word_entities
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def validate(self):
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if self.word_entities:
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for k in self.word_entities:
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if k:
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k.validate()
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.request_id is not None:
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result['requestId'] = self.request_id
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result['wordEntities'] = []
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if self.word_entities is not None:
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for k in self.word_entities:
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result['wordEntities'].append(k.to_map() if k else None)
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('requestId') is not None:
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self.request_id = m.get('requestId')
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self.word_entities = []
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if m.get('wordEntities') is not None:
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for k in m.get('wordEntities'):
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temp_model = NlpWordDistinguishResponseBodyWordEntities()
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self.word_entities.append(temp_model.from_map(k))
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return self
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class NlpWordDistinguishResponse(TeaModel):
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def __init__(
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self,
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headers: Dict[str, str] = None,
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status_code: int = None,
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body: NlpWordDistinguishResponseBody = None,
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):
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self.headers = headers
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self.status_code = status_code
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self.body = body
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def validate(self):
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if self.body:
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self.body.validate()
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.headers is not None:
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result['headers'] = self.headers
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if self.status_code is not None:
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result['statusCode'] = self.status_code
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if self.body is not None:
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result['body'] = self.body.to_map()
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('headers') is not None:
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self.headers = m.get('headers')
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if m.get('statusCode') is not None:
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self.status_code = m.get('statusCode')
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if m.get('body') is not None:
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temp_model = NlpWordDistinguishResponseBody()
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self.body = temp_model.from_map(m['body'])
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return self
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class OkrOpenRecommendHeaders(TeaModel):
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def __init__(
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self,
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common_headers: Dict[str, str] = None,
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x_acs_dingtalk_access_token: str = None,
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):
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self.common_headers = common_headers
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self.x_acs_dingtalk_access_token = x_acs_dingtalk_access_token
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def validate(self):
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pass
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.common_headers is not None:
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result['commonHeaders'] = self.common_headers
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if self.x_acs_dingtalk_access_token is not None:
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result['x-acs-dingtalk-access-token'] = self.x_acs_dingtalk_access_token
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('commonHeaders') is not None:
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self.common_headers = m.get('commonHeaders')
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if m.get('x-acs-dingtalk-access-token') is not None:
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self.x_acs_dingtalk_access_token = m.get('x-acs-dingtalk-access-token')
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return self
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class OkrOpenRecommendRequestCandidateOkrItemsOkrInfosKeyResultInfos(TeaModel):
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def __init__(
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self,
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kr: str = None,
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kr_id: str = None,
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words: List[str] = None,
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):
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self.kr = kr
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self.kr_id = kr_id
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self.words = words
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def validate(self):
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pass
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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if self.kr is not None:
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result['kr'] = self.kr
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if self.kr_id is not None:
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result['krId'] = self.kr_id
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if self.words is not None:
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result['words'] = self.words
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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if m.get('kr') is not None:
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self.kr = m.get('kr')
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if m.get('krId') is not None:
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self.kr_id = m.get('krId')
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if m.get('words') is not None:
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self.words = m.get('words')
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return self
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class OkrOpenRecommendRequestCandidateOkrItemsOkrInfos(TeaModel):
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def __init__(
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self,
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key_result_infos: List[OkrOpenRecommendRequestCandidateOkrItemsOkrInfosKeyResultInfos] = None,
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objective: str = None,
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objective_id: str = None,
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words: List[str] = None,
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):
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self.key_result_infos = key_result_infos
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self.objective = objective
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self.objective_id = objective_id
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self.words = words
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def validate(self):
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if self.key_result_infos:
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for k in self.key_result_infos:
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if k:
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k.validate()
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def to_map(self):
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_map = super().to_map()
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if _map is not None:
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return _map
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result = dict()
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result['keyResultInfos'] = []
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if self.key_result_infos is not None:
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for k in self.key_result_infos:
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result['keyResultInfos'].append(k.to_map() if k else None)
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if self.objective is not None:
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result['objective'] = self.objective
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if self.objective_id is not None:
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result['objectiveId'] = self.objective_id
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if self.words is not None:
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result['words'] = self.words
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return result
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def from_map(self, m: dict = None):
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m = m or dict()
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self.key_result_infos = []
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if m.get('keyResultInfos') is not None:
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for k in m.get('keyResultInfos'):
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temp_model = OkrOpenRecommendRequestCandidateOkrItemsOkrInfosKeyResultInfos()
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self.key_result_infos.append(temp_model.from_map(k))
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if m.get('objective') is not None:
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self.objective = m.get('objective')
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if m.get('objectiveId') is not None:
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self.objective_id = m.get('objectiveId')
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if m.get('words') is not None:
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self.words = m.get('words')
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return self
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class OkrOpenRecommendRequestCandidateOkrItems(TeaModel):
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def __init__(
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self,
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okr_infos: List[OkrOpenRecommendRequestCandidateOkrItemsOkrInfos] = None,
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relation: str = None,
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user_id: str = None,
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):
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self.okr_infos = okr_infos
|
||
|
|
# This parameter is required.
|
||
|
|
self.relation = relation
|
||
|
|
# This parameter is required.
|
||
|
|
self.user_id = user_id
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
if self.okr_infos:
|
||
|
|
for k in self.okr_infos:
|
||
|
|
if k:
|
||
|
|
k.validate()
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
result['okrInfos'] = []
|
||
|
|
if self.okr_infos is not None:
|
||
|
|
for k in self.okr_infos:
|
||
|
|
result['okrInfos'].append(k.to_map() if k else None)
|
||
|
|
if self.relation is not None:
|
||
|
|
result['relation'] = self.relation
|
||
|
|
if self.user_id is not None:
|
||
|
|
result['userId'] = self.user_id
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
self.okr_infos = []
|
||
|
|
if m.get('okrInfos') is not None:
|
||
|
|
for k in m.get('okrInfos'):
|
||
|
|
temp_model = OkrOpenRecommendRequestCandidateOkrItemsOkrInfos()
|
||
|
|
self.okr_infos.append(temp_model.from_map(k))
|
||
|
|
if m.get('relation') is not None:
|
||
|
|
self.relation = m.get('relation')
|
||
|
|
if m.get('userId') is not None:
|
||
|
|
self.user_id = m.get('userId')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendRequest(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
candidate_okr_items: List[OkrOpenRecommendRequestCandidateOkrItems] = None,
|
||
|
|
corp_id: str = None,
|
||
|
|
dept_ids: List[str] = None,
|
||
|
|
isv_app_id: str = None,
|
||
|
|
user_id: str = None,
|
||
|
|
words: List[str] = None,
|
||
|
|
):
|
||
|
|
# This parameter is required.
|
||
|
|
self.candidate_okr_items = candidate_okr_items
|
||
|
|
# This parameter is required.
|
||
|
|
self.corp_id = corp_id
|
||
|
|
# This parameter is required.
|
||
|
|
self.dept_ids = dept_ids
|
||
|
|
# This parameter is required.
|
||
|
|
self.isv_app_id = isv_app_id
|
||
|
|
# This parameter is required.
|
||
|
|
self.user_id = user_id
|
||
|
|
self.words = words
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
if self.candidate_okr_items:
|
||
|
|
for k in self.candidate_okr_items:
|
||
|
|
if k:
|
||
|
|
k.validate()
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
result['candidateOkrItems'] = []
|
||
|
|
if self.candidate_okr_items is not None:
|
||
|
|
for k in self.candidate_okr_items:
|
||
|
|
result['candidateOkrItems'].append(k.to_map() if k else None)
|
||
|
|
if self.corp_id is not None:
|
||
|
|
result['corpId'] = self.corp_id
|
||
|
|
if self.dept_ids is not None:
|
||
|
|
result['deptIds'] = self.dept_ids
|
||
|
|
if self.isv_app_id is not None:
|
||
|
|
result['isvAppId'] = self.isv_app_id
|
||
|
|
if self.user_id is not None:
|
||
|
|
result['userId'] = self.user_id
|
||
|
|
if self.words is not None:
|
||
|
|
result['words'] = self.words
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
self.candidate_okr_items = []
|
||
|
|
if m.get('candidateOkrItems') is not None:
|
||
|
|
for k in m.get('candidateOkrItems'):
|
||
|
|
temp_model = OkrOpenRecommendRequestCandidateOkrItems()
|
||
|
|
self.candidate_okr_items.append(temp_model.from_map(k))
|
||
|
|
if m.get('corpId') is not None:
|
||
|
|
self.corp_id = m.get('corpId')
|
||
|
|
if m.get('deptIds') is not None:
|
||
|
|
self.dept_ids = m.get('deptIds')
|
||
|
|
if m.get('isvAppId') is not None:
|
||
|
|
self.isv_app_id = m.get('isvAppId')
|
||
|
|
if m.get('userId') is not None:
|
||
|
|
self.user_id = m.get('userId')
|
||
|
|
if m.get('words') is not None:
|
||
|
|
self.words = m.get('words')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendResponseBodyOkrRecommendItemsKrResultRelatedResults(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
kr_id: str = None,
|
||
|
|
semantic_level: int = None,
|
||
|
|
words: List[str] = None,
|
||
|
|
):
|
||
|
|
# This parameter is required.
|
||
|
|
self.kr_id = kr_id
|
||
|
|
# This parameter is required.
|
||
|
|
self.semantic_level = semantic_level
|
||
|
|
# This parameter is required.
|
||
|
|
self.words = words
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
pass
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
if self.kr_id is not None:
|
||
|
|
result['krId'] = self.kr_id
|
||
|
|
if self.semantic_level is not None:
|
||
|
|
result['semanticLevel'] = self.semantic_level
|
||
|
|
if self.words is not None:
|
||
|
|
result['words'] = self.words
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
if m.get('krId') is not None:
|
||
|
|
self.kr_id = m.get('krId')
|
||
|
|
if m.get('semanticLevel') is not None:
|
||
|
|
self.semantic_level = m.get('semanticLevel')
|
||
|
|
if m.get('words') is not None:
|
||
|
|
self.words = m.get('words')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendResponseBodyOkrRecommendItemsObjectiveRelatedResults(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
objective_id: str = None,
|
||
|
|
semantic_level: int = None,
|
||
|
|
words: List[str] = None,
|
||
|
|
):
|
||
|
|
# This parameter is required.
|
||
|
|
self.objective_id = objective_id
|
||
|
|
# This parameter is required.
|
||
|
|
self.semantic_level = semantic_level
|
||
|
|
# This parameter is required.
|
||
|
|
self.words = words
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
pass
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
if self.objective_id is not None:
|
||
|
|
result['objectiveId'] = self.objective_id
|
||
|
|
if self.semantic_level is not None:
|
||
|
|
result['semanticLevel'] = self.semantic_level
|
||
|
|
if self.words is not None:
|
||
|
|
result['words'] = self.words
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
if m.get('objectiveId') is not None:
|
||
|
|
self.objective_id = m.get('objectiveId')
|
||
|
|
if m.get('semanticLevel') is not None:
|
||
|
|
self.semantic_level = m.get('semanticLevel')
|
||
|
|
if m.get('words') is not None:
|
||
|
|
self.words = m.get('words')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendResponseBodyOkrRecommendItems(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
kr_result_related_results: List[OkrOpenRecommendResponseBodyOkrRecommendItemsKrResultRelatedResults] = None,
|
||
|
|
objective_related_results: List[OkrOpenRecommendResponseBodyOkrRecommendItemsObjectiveRelatedResults] = None,
|
||
|
|
related_level: int = None,
|
||
|
|
semantic_level: int = None,
|
||
|
|
user_id: str = None,
|
||
|
|
):
|
||
|
|
self.kr_result_related_results = kr_result_related_results
|
||
|
|
self.objective_related_results = objective_related_results
|
||
|
|
# This parameter is required.
|
||
|
|
self.related_level = related_level
|
||
|
|
# This parameter is required.
|
||
|
|
self.semantic_level = semantic_level
|
||
|
|
# This parameter is required.
|
||
|
|
self.user_id = user_id
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
if self.kr_result_related_results:
|
||
|
|
for k in self.kr_result_related_results:
|
||
|
|
if k:
|
||
|
|
k.validate()
|
||
|
|
if self.objective_related_results:
|
||
|
|
for k in self.objective_related_results:
|
||
|
|
if k:
|
||
|
|
k.validate()
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
result['krResultRelatedResults'] = []
|
||
|
|
if self.kr_result_related_results is not None:
|
||
|
|
for k in self.kr_result_related_results:
|
||
|
|
result['krResultRelatedResults'].append(k.to_map() if k else None)
|
||
|
|
result['objectiveRelatedResults'] = []
|
||
|
|
if self.objective_related_results is not None:
|
||
|
|
for k in self.objective_related_results:
|
||
|
|
result['objectiveRelatedResults'].append(k.to_map() if k else None)
|
||
|
|
if self.related_level is not None:
|
||
|
|
result['relatedLevel'] = self.related_level
|
||
|
|
if self.semantic_level is not None:
|
||
|
|
result['semanticLevel'] = self.semantic_level
|
||
|
|
if self.user_id is not None:
|
||
|
|
result['userId'] = self.user_id
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
self.kr_result_related_results = []
|
||
|
|
if m.get('krResultRelatedResults') is not None:
|
||
|
|
for k in m.get('krResultRelatedResults'):
|
||
|
|
temp_model = OkrOpenRecommendResponseBodyOkrRecommendItemsKrResultRelatedResults()
|
||
|
|
self.kr_result_related_results.append(temp_model.from_map(k))
|
||
|
|
self.objective_related_results = []
|
||
|
|
if m.get('objectiveRelatedResults') is not None:
|
||
|
|
for k in m.get('objectiveRelatedResults'):
|
||
|
|
temp_model = OkrOpenRecommendResponseBodyOkrRecommendItemsObjectiveRelatedResults()
|
||
|
|
self.objective_related_results.append(temp_model.from_map(k))
|
||
|
|
if m.get('relatedLevel') is not None:
|
||
|
|
self.related_level = m.get('relatedLevel')
|
||
|
|
if m.get('semanticLevel') is not None:
|
||
|
|
self.semantic_level = m.get('semanticLevel')
|
||
|
|
if m.get('userId') is not None:
|
||
|
|
self.user_id = m.get('userId')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendResponseBody(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
okr_recommend_items: List[OkrOpenRecommendResponseBodyOkrRecommendItems] = None,
|
||
|
|
request_id: str = None,
|
||
|
|
):
|
||
|
|
self.okr_recommend_items = okr_recommend_items
|
||
|
|
# This parameter is required.
|
||
|
|
self.request_id = request_id
|
||
|
|
|
||
|
|
def validate(self):
|
||
|
|
if self.okr_recommend_items:
|
||
|
|
for k in self.okr_recommend_items:
|
||
|
|
if k:
|
||
|
|
k.validate()
|
||
|
|
|
||
|
|
def to_map(self):
|
||
|
|
_map = super().to_map()
|
||
|
|
if _map is not None:
|
||
|
|
return _map
|
||
|
|
|
||
|
|
result = dict()
|
||
|
|
result['okrRecommendItems'] = []
|
||
|
|
if self.okr_recommend_items is not None:
|
||
|
|
for k in self.okr_recommend_items:
|
||
|
|
result['okrRecommendItems'].append(k.to_map() if k else None)
|
||
|
|
if self.request_id is not None:
|
||
|
|
result['requestId'] = self.request_id
|
||
|
|
return result
|
||
|
|
|
||
|
|
def from_map(self, m: dict = None):
|
||
|
|
m = m or dict()
|
||
|
|
self.okr_recommend_items = []
|
||
|
|
if m.get('okrRecommendItems') is not None:
|
||
|
|
for k in m.get('okrRecommendItems'):
|
||
|
|
temp_model = OkrOpenRecommendResponseBodyOkrRecommendItems()
|
||
|
|
self.okr_recommend_items.append(temp_model.from_map(k))
|
||
|
|
if m.get('requestId') is not None:
|
||
|
|
self.request_id = m.get('requestId')
|
||
|
|
return self
|
||
|
|
|
||
|
|
|
||
|
|
class OkrOpenRecommendResponse(TeaModel):
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
headers: Dict[str, str] = None,
|
||
|
|
status_code: int = None,
|
||
|
|
body: OkrOpenRecommendResponseBody = 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 = OkrOpenRecommendResponseBody()
|
||
|
|
self.body = temp_model.from_map(m['body'])
|
||
|
|
return self
|
||
|
|
|
||
|
|
|