482 lines
19 KiB
Python
482 lines
19 KiB
Python
from common.utils import read_json_file
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from RatingData.scripts.common import *
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def evaluation_results(param):
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"""
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评价结果
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清洗数据库数据，根据需要返回
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Parameters:
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param: 数据库数据
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Returns:
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credit_rank: 信用等级
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rank_date: 评价时间
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"""
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data = param['评价结果']
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result = list()
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part_01 = dict()
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part_02 = dict()
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part_01['credit_rank'] = data['信用等级']
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part_02['rank_date'] = data['评价时间']
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result.append(part_01)
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result.append(part_02)
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return result
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def financial_data(param):
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"""
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主要财务数据
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清洗数据库数据，根据需要返回
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Parameters:
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param: 数据库数据
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Returns:
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三年主要财务数据
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"""
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data_01 = param['综合评价填报']['财务填报']
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data_02 = param['指标明细']
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result = list()
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for key, value in data_01['资产负债表'][0].items():
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insert_list = list()
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insert_list.append(key)
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insert_list.append(value)
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insert_list.append(data_01['资产负债表'][1][key])
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insert_list.append(data_01['资产负债表'][2][key])
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insert_list = judge_list(insert_list)
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result.append(insert_list)
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for key, value in data_01['利润表'][0].items():
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if key != '报告期':
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insert_list = list()
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insert_list.append(key)
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insert_list.append(value)
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insert_list.append(data_01['利润表'][1][key])
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insert_list.append(data_01['利润表'][2][key])
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insert_list = judge_list(insert_list)
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result.append(insert_list)
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for k, v in data_02[0].items():
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if k == '已获利息倍数' or k == '总资产周转率' or k == '技术投入比率' or k == '速动比率':
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try:
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insert_list = list()
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insert_list.append(k)
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insert_list.append(v)
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insert_list.append(data_02[1][k])
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insert_list.append(data_02[2][k])
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insert_list = judge_list(insert_list)
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result.append(insert_list)
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except IndexError:
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insert_list = list()
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insert_list.append(k)
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insert_list.append(str(v))
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insert_list.append(str(data_02[1][k]))
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insert_list.append('-')
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result.append(insert_list)
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return result
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def evaluation_view(param1, param2, param3):
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"""
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评价观点 区分行业
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Parameters:
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param1: 企业名称
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param2: 数据库数据
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param3: 行业
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"""
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if param3[0] == '制造业':
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return evaluation_view_manufacturing(param1, param2)
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elif param3[0] == '信息技术业':
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return evaluation_view_information(param1, param2)
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def evaluation_view_manufacturing(param1, param2):
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"""
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评价观点 制造业
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清洗数据库数据，根据需要返回
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Parameters:
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param1: 企业名称
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param2: 数据库数据
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Returns:
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评价观点数据
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"""
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# Params
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data_01 = param2['基本信息']['基本信息']
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data_02 = param2['综合评价填报']['财务填报']
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data_03 = param2['评价结果']
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# Returns
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result = list()
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def para_01():
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part_01 = dict()
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# 企业名称
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part_01['company'] = param1
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# 省份
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part_01['province'] = data_01['regLocation'][:2]
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# 规模
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def scale():
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income = float(data_02['利润表'][0]['营业收入'])
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# 企业规模
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if income > 40000:
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part_01['scale'] = '大型'
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elif income > 2000:
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part_01['scale'] = '中型'
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elif income > 300:
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part_01['scale'] = '小型'
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else:
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part_01['scale'] = '微型'
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# 优势领域
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def advantage_area():
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advantage_list = list()
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if float(data_02['资产负债表'][0]['资产总计']) > 400000000:
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advantage_list.append('资产规模')
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elif float(data_02['补充数据表'][0]['研发费用']) / float(data_02['利润表'][0]['营业收入'] * 100) > 10:
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advantage_list.append('研发实力')
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elif float(data_02['资产负债表'][0]['短期借款']) != 0 or float(data_02['资产负债表'][0]['一年内到期非流动负债']) != 0 or float(
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data_02['资产负债表'][0]['长期借款']) != 0:
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advantage_list.append('融资渠道')
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part_01['advantage_area'] = '、'.join(advantage_list)
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# 执行子方法
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scale()
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advantage_area()
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return part_01
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def para_02():
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part_02 = dict()
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# esg相关描述
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def esg_desc():
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esg_score = float(data_03['经营评分']['合计'])
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esg_desc_01 = '公司经营符合ESG理念，为环境友好型企业，承担相应社会责任，公司治理较好，为企业运营奠定良好基础。'
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esg_desc_02 = '公司正努力践行ESG理念，实行节能减排措施，积极履行社会责任，改善公司治理状况，公司ESG的提升有望为企业创造更多价值。'
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esg_desc_03 = '公司ESG理念较为薄弱，在经营过程中需增加节能减排措施，加大对供应链、社会公众、员工和地区等的责任，树立良好企业形象，进一步加强公司治理和内部控制，促进经营效率提升和企业价值创造。'
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if esg_score >= 24:
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part_02['esg_desc'] = esg_desc_01
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elif esg_score >= 18:
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part_02['esg_desc'] = esg_desc_02
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else:
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part_02['esg_desc'] = esg_desc_03
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esg_desc()
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return part_02
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def para_03():
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part_03 = dict()
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# 盈利能力
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def profitability():
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profitability_score = float(data_03['财务评分']['盈利能力']['净资产收益率']) + float(data_03['财务评分']['盈利能力']['总资产报酬率'])
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if profitability_score >= 16:
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part_03['profitability'] = '好'
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elif profitability_score >= 16 * 0.8:
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part_03['profitability'] = '较好'
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elif profitability_score >= 16 * 0.6:
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part_03['profitability'] = '处于行业平均水平'
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elif profitability_score >= 16 * 0.4:
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part_03['profitability'] = '较差'
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else:
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part_03['profitability'] = '差'
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# 资产运营效率
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def operational_efficiency():
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operation_score = float(data_03['财务评分']['资产质量']['总资产周转率']) + float(
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data_03['财务评分']['资产质量']['应收账款周转率']) + float(
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data_03['财务评分']['资产质量']['存货周转率'])
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if operation_score >= 18:
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part_03['operational_efficiency'] = '高'
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elif operation_score >= 18 * 0.8:
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part_03['operational_efficiency'] = '较高'
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elif operation_score >= 18 * 0.6:
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part_03['operational_efficiency'] = '尚可'
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elif operation_score >= 18 * 0.4:
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part_03['operational_efficiency'] = '较低'
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else:
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part_03['operational_efficiency'] = '低'
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# 债务风险
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def debt_risk():
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debt_risk_score = float(data_03['财务评分']['债务风险']['资产负债率']) + float(
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data_03['财务评分']['债务风险']['已获利息倍数']) + float(
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data_03['财务评分']['债务风险']['速动比率'])
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if debt_risk_score >= 18:
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part_03['debt_risk'] = '大'
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elif debt_risk_score >= 18 * 0.8:
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part_03['debt_risk'] = '较大'
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elif debt_risk_score >= 18 * 0.6:
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part_03['debt_risk'] = '适中'
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elif debt_risk_score >= 18 * 0.4:
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part_03['debt_risk'] = '较小'
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else:
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part_03['debt_risk'] = '小'
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# 成长能力
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def growth_ability():
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growth_ability_score = float(data_03['财务评分']['经营增长']['营业增长率']) + float(
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data_03['财务评分']['经营增长']['总资产增长率']) + float(
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data_03['财务评分']['经营增长']['技术投入比率'])
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if growth_ability_score >= 18:
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part_03['growth_ability'] = '强'
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elif growth_ability_score >= 18 * 0.8:
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part_03['growth_ability'] = '较强'
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elif growth_ability_score >= 18 * 0.6:
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part_03['growth_ability'] = '一般'
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elif growth_ability_score >= 18 * 0.4:
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part_03['growth_ability'] = '较弱'
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else:
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part_03['growth_ability'] = '弱'
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# 整体信用风险
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def overall_credit_risk():
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overall_credit_score = data_03['信用等级']
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if overall_credit_score == 'AAA' or overall_credit_score == 'AA':
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part_03['overall_credit_risk'] = '很小'
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elif overall_credit_score == 'A':
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part_03['overall_credit_risk'] = '小'
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elif overall_credit_score == 'BBB':
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part_03['overall_credit_risk'] = '可控'
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elif overall_credit_score == 'BB' or overall_credit_score == 'B':
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part_03['overall_credit_risk'] = '较大'
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else:
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part_03['overall_credit_risk'] = '大'
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profitability()
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operational_efficiency()
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debt_risk()
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growth_ability()
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overall_credit_risk()
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return part_03
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def para_04():
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part_04 = dict()
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part_04['company'] = param1
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part_04['credit_rank'] = data_03['信用等级']
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return part_04
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result.append(para_01())
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result.append(para_02())
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result.append(para_03())
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result.append(para_04())
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return result
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def evaluation_view_information(param1, param2):
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"""
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评价观点 信息技术业
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清洗数据库数据，根据需要返回
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Parameters:
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param1: 企业名称
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param2: 数据库数据
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Returns:
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评价观点数据
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"""
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# Params
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data_01 = param2['基本信息']['基本信息']
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data_02 = param2['综合评价填报']['财务填报']
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data_03 = param2['评价结果']
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# Returns
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result = list()
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def para_01():
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part_01 = dict()
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# 企业名称
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part_01['company'] = param1
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# 省份
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part_01['province'] = data_01['regLocation'][:2]
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# 二级行业
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industry = data_02['综合评价填报']['行业选择'][1]
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# 规模-计算机服务与软件业
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def scale_01():
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income = float(data_02['利润表'][0]['营业收入'])
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# 企业规模
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if income > 100000000:
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part_01['scale'] = '大型'
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elif income > 10000000:
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part_01['scale'] = '中型'
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elif income > 500000:
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part_01['scale'] = '小型'
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else:
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part_01['scale'] = '微型'
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# 规模-电信业
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def scale_02():
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income = float(data_02['利润表'][0]['营业收入'])
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# 企业规模
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if income > 100000000:
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part_01['scale'] = '大型'
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elif income > 10000000:
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part_01['scale'] = '中型'
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elif income > 500000:
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part_01['scale'] = '小型'
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else:
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part_01['scale'] = '微型'
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if industry == '计算机服务与软件业':
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scale_01()
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elif industry == '电信业':
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scale_02()
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# 优势领域
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def advantage_area():
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advantage_list = list()
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if float(data_02['资产负债表'][0]['资产总计']) > 10000000:
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advantage_list.append('资产规模')
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elif float(data_02['补充数据表'][0]['研发费用']) / float(data_02['利润表'][0]['营业收入'] * 100) > 8:
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advantage_list.append('研发实力')
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elif float(data_02['资产负债表'][0]['短期借款']) != 0 or float(data_02['资产负债表'][0]['一年内到期非流动负债']) != 0 or float(
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data_02['资产负债表'][0]['长期借款']) != 0:
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advantage_list.append('融资渠道')
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part_01['advantage_area'] = '、'.join(advantage_list)
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# 执行子方法
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advantage_area()
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return part_01
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def para_02():
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part_02 = dict()
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# esg相关描述
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def esg_desc():
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esg_score = float(data_03['经营评分']['合计'])
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esg_desc_01 = '公司经营符合ESG理念，为环境友好型企业，承担相应社会责任，公司治理较好，为企业运营奠定良好基础。'
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esg_desc_02 = '公司正努力践行ESG理念，实行节能减排措施，积极履行社会责任，改善公司治理状况，公司ESG的提升有望为企业创造更多价值。'
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esg_desc_03 = '公司ESG理念较为薄弱，在经营过程中需增加节能减排措施，加大对供应链、社会公众、员工和地区等的责任，树立良好企业形象，进一步加强公司治理和内部控制，促进经营效率提升和企业价值创造。'
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if esg_score >= 24:
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part_02['esg_desc'] = esg_desc_01
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elif esg_score >= 18:
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part_02['esg_desc'] = esg_desc_02
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else:
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part_02['esg_desc'] = esg_desc_03
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esg_desc()
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return part_02
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def para_03():
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part_03 = dict()
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# 盈利能力
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def profitability():
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profitability_score = float(data_03['财务评分']['盈利能力']['净资产收益率']) + float(data_03['财务评分']['盈利能力']['总资产报酬率'])
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if profitability_score >= 16:
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part_03['profitability'] = '好'
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elif profitability_score >= 16 * 0.8:
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part_03['profitability'] = '较好'
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elif profitability_score >= 16 * 0.6:
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part_03['profitability'] = '处于行业平均水平'
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elif profitability_score >= 16 * 0.4:
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part_03['profitability'] = '较差'
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else:
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part_03['profitability'] = '差'
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# 资产运营效率
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def operational_efficiency():
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operation_score = float(data_03['财务评分']['资产质量']['总资产周转率']) + float(
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data_03['财务评分']['资产质量']['应收账款周转率']) + float(
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data_03['财务评分']['资产质量']['存货周转率'])
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if operation_score >= 18:
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part_03['operational_efficiency'] = '高'
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elif operation_score >= 18 * 0.8:
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part_03['operational_efficiency'] = '较高'
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elif operation_score >= 18 * 0.6:
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part_03['operational_efficiency'] = '尚可'
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elif operation_score >= 18 * 0.4:
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part_03['operational_efficiency'] = '较低'
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else:
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part_03['operational_efficiency'] = '低'
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# 债务风险
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def debt_risk():
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debt_risk_score = float(data_03['财务评分']['债务风险']['资产负债率']) + float(
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data_03['财务评分']['债务风险']['已获利息倍数']) + float(
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data_03['财务评分']['债务风险']['速动比率'])
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if debt_risk_score >= 18:
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part_03['debt_risk'] = '大'
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elif debt_risk_score >= 18 * 0.8:
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part_03['debt_risk'] = '较大'
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elif debt_risk_score >= 18 * 0.6:
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part_03['debt_risk'] = '适中'
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elif debt_risk_score >= 18 * 0.4:
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part_03['debt_risk'] = '较小'
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else:
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part_03['debt_risk'] = '小'
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# 成长能力
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def growth_ability():
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growth_ability_score = float(data_03['财务评分']['经营增长']['营业增长率']) + float(
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data_03['财务评分']['经营增长']['总资产增长率']) + float(
|
||
data_03['财务评分']['经营增长']['技术投入比率'])
|
||
if growth_ability_score >= 18:
|
||
part_03['growth_ability'] = '强'
|
||
elif growth_ability_score >= 18 * 0.8:
|
||
part_03['growth_ability'] = '较强'
|
||
elif growth_ability_score >= 18 * 0.6:
|
||
part_03['growth_ability'] = '一般'
|
||
elif growth_ability_score >= 18 * 0.4:
|
||
part_03['growth_ability'] = '较弱'
|
||
else:
|
||
part_03['growth_ability'] = '弱'
|
||
|
||
# 整体信用风险
|
||
def overall_credit_risk():
|
||
overall_credit_score = float(data_03['财务评分']['合计'])
|
||
if overall_credit_score >= 100:
|
||
part_03['overall_credit_risk'] = '很小'
|
||
elif overall_credit_score >= 100 * 0.8:
|
||
part_03['overall_credit_risk'] = '小'
|
||
elif overall_credit_score >= 100 * 0.6:
|
||
part_03['overall_credit_risk'] = '可控'
|
||
elif overall_credit_score >= 100 * 0.4:
|
||
part_03['overall_credit_risk'] = '较大'
|
||
else:
|
||
part_03['overall_credit_risk'] = '大'
|
||
|
||
profitability()
|
||
operational_efficiency()
|
||
debt_risk()
|
||
growth_ability()
|
||
overall_credit_risk()
|
||
return part_03
|
||
|
||
def para_04():
|
||
part_04 = dict()
|
||
part_04['company'] = param1
|
||
part_04['credit_rank'] = data_03['信用等级']
|
||
return part_04
|
||
|
||
result.append(para_01())
|
||
result.append(para_02())
|
||
result.append(para_03())
|
||
result.append(para_04())
|
||
return result
|
||
|
||
|
||
def attention(param):
|
||
"""
|
||
关注
|
||
Parameters:
|
||
param: 数据库数据
|
||
Returns:
|
||
result: 关注结果
|
||
"""
|
||
weight = read_json_file('/rating/static/attention/weights.json')
|
||
describe = read_json_file('/rating/static/attention/describe.json')
|
||
data = param['评价结果']['财务评分']
|
||
del param['评价结果']['财务评分']['合计']
|
||
for k, v in data.items():
|
||
for k_1, v_1 in v.items():
|
||
if k_1 != '合计':
|
||
weight[k_1] = round(v_1 / weight[k_1], 2)
|
||
res = sorted(weight.items(), key=lambda x: x[1])
|
||
result = list()
|
||
part_01 = dict()
|
||
part_02 = dict()
|
||
part_03 = dict()
|
||
part_01['attention_01'] = describe[res[0][0]]
|
||
part_02['attention_02'] = describe[res[1][0]]
|
||
part_03['attention_03'] = describe[res[2][0]]
|
||
result.append(part_01)
|
||
result.append(part_02)
|
||
result.append(part_03)
|
||
return result
|