63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
import json
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import pandas as pd
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from RatingData.db import FIND_DATA_N_TYC
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def associate_risk_detail(param):
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"""
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关联风险
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根据企业名称，查询企业关联风险类型和数量
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Parameters:
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param: 企业名称
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Returns:
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result: 企业关联风险类型和数量
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"""
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res = FIND_DATA_N_TYC(db='天眼风险', col='周边风险', query={'企业名称': param})
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result = []
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if res:
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pass
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else:
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return result
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if res[0]['周边风险']['list']:
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pass
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else:
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return result
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df = pd.DataFrame(res[0]['周边风险']['list'])[['total', 'title', 'list']]
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detail_list = list()
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for row in df.iterrows():
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df_sub1 = pd.DataFrame(row[1]['list'])
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detail_list.append((df_sub1['title'] + df_sub1['riskCount'].apply(lambda x: ' ' + str(x) + '条')).to_list())
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df['detail'] = detail_list
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result = list(json.loads(df[['title', 'total', 'detail']].T.to_json()).values())
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return result
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def change_log_detail(param):
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"""
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变更记录详情
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Parameters:
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param: desc
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Returns:
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res: desc
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"""
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res = FIND_DATA_N_TYC(db='天眼风险', col='预警提醒', query={'企业名称': param})
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result = []
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if res:
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df = pd.DataFrame(res[0]['预警提醒']['list'])[['total', 'title', 'list']]
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detail_list = list()
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id_list = list()
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for row in df.iterrows():
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df_sub1 = pd.DataFrame(row[1]['list'])
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detail_list.append((df_sub1['title'] + df_sub1['riskCount'].apply(lambda x: ' ' + str(x) + '条')).to_list())
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id_list.append(1 if df_sub1['companyId'].values[0] is None else 0)
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df['detail'] = detail_list
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df['companyId'] = id_list
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df.drop(df[df['companyId'] == 0].index)
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result = list(json.loads(df[['title', 'total', 'detail']].T.to_json()).values())
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return result
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