def conclusion(param):
    """
    结论
    清洗数据库数据，根据需要返回
    Parameters:
        param: 数据库数据
    Returns:
       结论数据
    """
    # Params
    data_01 = param['评价结果']

    # Returns
    result = list()

    def para_01():
        part_01 = dict()
        part_01['describe'] = list()

        def describe():
            # 环境部分得分
            ep_s = data_01['经营评分']['环境']
            if ep_s > 10 * 0.5:
                part_01['describe'].append('公司为环境友好型企业')
            else:
                part_01['describe'].append('公司绿色发展理念相对薄弱')
            # 社会责任部分得分
            sr_s = data_01['经营评分']['社会责任']
            if sr_s > 10 * 0.5:
                part_01['describe'].append('积极履行社会责任')
            else:
                part_01['describe'].append('社会责任履行能力有待进一步提升')
            # 公司治理部分得分
            cg_s = data_01['经营评分']['公司治理']
            if cg_s > 10 * 0.5:
                part_01['describe'].append('内部治理水平较高')
            else:
                part_01['describe'].append('治理水平有待进一步提升')
            part_01['describe'] = '，'.join(part_01['describe'])
        describe()
        return part_01

    def para_02():
        part_02 = dict()

        def enterprise_quality():
            # 企业整体素质
            eq_s = data_01['经营评分']['合计']
            if eq_s >= 30:
                part_02['enterprise_quality'] = '好'
            elif eq_s >= 30 * 0.8:
                part_02['enterprise_quality'] = '较好'
            elif eq_s >= 30 * 0.6:
                part_02['enterprise_quality'] = '一般'
            elif eq_s >= 30 * 0.4:
                part_02['enterprise_quality'] = '较差'
            else:
                part_02['enterprise_quality'] = '差'

        def profitability_detail():
            p = float(data_01['财务评分']['盈利能力']['净资产收益率'])
            s = float(data_01['财务评分']['盈利能力']['总资产报酬率'])
            p_s = p + s
            if p_s >= 16:
                part_02['profitability'] = '强'
            elif p_s >= 16 * 0.8:
                part_02['profitability'] = '较强'
            elif p_s >= 16 * 0.6:
                part_02['profitability'] = '尚可'
            elif p_s >= 16 * 0.4:
                part_02['profitability'] = '较弱'
            else:
                part_02['profitability'] = '弱'

        def asset_quality_detail():
            a = float(data_01['财务评分']['资产质量']['总资产周转率'])
            q = float(data_01['财务评分']['资产质量']['应收账款周转率'])
            s = float(data_01['财务评分']['资产质量']['存货周转率'])
            aq_s = a + q + s
            if aq_s >= 18:
                part_02['asset_quality'] = '好'
            elif aq_s >= 18 * 0.8:
                part_02['asset_quality'] = '较好'
            elif aq_s >= 18 * 0.6:
                part_02['asset_quality'] = '一般'
            elif aq_s >= 18 * 0.4:
                part_02['asset_quality'] = '较差'
            else:
                part_02['asset_quality'] = '差'

        def debt_risk_detail():
            # 债务风险得分
            d = float(data_01['财务评分']['债务风险']['资产负债率'])
            r = float(data_01['财务评分']['债务风险']['已获利息倍数'])
            s = float(data_01['财务评分']['债务风险']['速动比率'])
            dr_s = d + r + s
            if dr_s >= 18:
                part_02['debt_risk'] = '高'
            elif dr_s >= 18 * 0.8:
                part_02['debt_risk'] = '较高'
            elif dr_s >= 18 * 0.6:
                part_02['debt_risk'] = '适中'
            elif dr_s >= 18 * 0.4:
                part_02['debt_risk'] = '较低'
            else:
                part_02['debt_risk'] = '低'

        def growth_ability_detail():
            g = float(data_01['财务评分']['经营增长']['营业增长率'])
            s = float(data_01['财务评分']['经营增长']['总资产增长率'])
            i = float(data_01['财务评分']['经营增长']['技术投入比率'])
            # 成长空间得分
            gs_s = g + s + i
            if gs_s >= 18:
                part_02['growth_ability'] = '大'
            elif gs_s >= 18 * 0.8:
                part_02['growth_ability'] = '较大'
            elif gs_s >= 18 * 0.6:
                part_02['growth_ability'] = '不大'
            elif gs_s >= 18 * 0.4:
                part_02['growth_ability'] = '较小'
            else:
                part_02['growth_ability'] = '小'

        enterprise_quality()
        profitability_detail()
        asset_quality_detail()
        debt_risk_detail()
        growth_ability_detail()
        return part_02

    def para_03():
        part_03 = dict()
        part_03['company'] = data_01['企业名称']
        part_03['credit_rank'] = data_01['信用等级']
        return part_03

    result.append(para_01())
    result.append(para_02())
    result.append(para_03())
    return result