120 lines
3.3 KiB
Python
120 lines
3.3 KiB
Python
import copy
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import datetime
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from Esg.db import update_data
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from Esg.scripts.environmental import environmental_rating
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from Esg.scripts.governance import governance_rating
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from Esg.scripts.social import social_rating
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from common.scripts import read_json_file
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class EsgModel:
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"""
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ESG评价模型
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"""
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def __init__(self):
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"""
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初始化数据
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Parameters
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param dict 数据模板
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questionnaire dict 填报问卷
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rid str 评价ID
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cid str 企业ID
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period str 评价年度
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"""
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self.questionnaire = None
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self.company = None
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self.rid = None
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self.cid = None
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self.period = None
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self.esg_score = None
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self.rating_result = None
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def prepare_params(self, param):
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"""
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准备模型数据
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Parameters:
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param dict 数据模板
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Returns:
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-
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"""
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self.rid = param['评价ID']
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self.cid = param['企业ID']
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self.company = param['企业名称']
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self.period = param['评价年度']
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self.esg_score = self.esg_rating_scripts(param)
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self.rating_result = self.esg_rating_result()
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@staticmethod
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def esg_rating_scripts(param):
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"""
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esg打分方法
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Parameters:
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param dict 数据模板
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Returns:
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score dict 分数
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"""
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score = dict()
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score['环境得分'] = environmental_rating(param)
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score['社会得分'] = social_rating(param)
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score['公司治理得分'] = governance_rating(param)
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score['合计'] = score['环境得分']['合计'] + score['社会得分']['合计'] + score['公司治理得分']['合计']
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return score
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def esg_rating_result(self):
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"""
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整合打分结果
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Parameters:
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score dict 打分结果
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Returns:
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result dict esg得分
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"""
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score = copy.deepcopy(self.esg_score)
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result = dict()
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result['企业名称'] = self.company
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result['企业ID'] = self.cid
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result['评价ID'] = self.rid
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result['评价年度'] = self.period
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result['评价等级'] = self.score_rank(score['合计'])
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result['环境得分'] = score['环境得分']
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result['社会得分'] = score['社会得分']
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result['公司治理得分'] = score['公司治理得分']
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result['ESG得分'] = score['合计']
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result['评价时间'] = datetime.datetime.now().strftime('%Y-%m-%d')
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return result
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def save_result(self):
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"""
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保存评价结果
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"""
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rating_result = self.rating_result
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update_data('ESG评价数据', '评价结果', {"企业ID": self.cid, "评价年度": self.period}, rating_result)
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@staticmethod
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def score_rank(param):
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"""
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描述
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Parameters:
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param float esg分数合计
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Returns:
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result str 评价等级
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"""
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if param >= 80:
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level = 'A'
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elif param >= 50:
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level = 'B'
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elif param >= 30:
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level = 'C'
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else:
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level = 'D'
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return level
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if __name__ == '__main__':
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m = EsgModel()
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data = read_json_file('/Esg/static/template_data.json')
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m.prepare_params(data)
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r = m.esg_rating_result()
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