示例:
规则集名称:通用规则
规则集默认输出:-1
规则集:
规则1: 变量:年龄 age 逻辑:年龄小于18或大于等于65 输出:1 结果备注: 1代表好
规则2: 变量:欠税总额 qsze 逻辑:欠税总额大于500 输出:3 结果备注: 3代表一般
规则3: 变量:非银行机构未结清贷款机构数 fyjgwjqs 逻辑:非银行机构未结清贷款机构数大于10 输出:2
输出:
def handle_general_rules(data:dict):
# 通用规则
# 输出结果备注:
# 1代表好
# 3代表一般
age = data.get("age")
qsze = data.get("qsze")
fyjgwjqs = data.get("fyjgwjqs")
if age is not None:
if age < 18 or age >= 65:
return 1
if qsze is not None:
if qsze > 500:
return 3
if fyjgwjqs is not None:
if fyjgwjqs > 10:
return 2
return -1
```
待处理规则：
规则集名称:极优质客户
规则集默认输出:接受
规则集:
规则1: 变量:年龄 age 性别 sex 逻辑:男性客户年龄小于22岁或大于60岁，普通女性客户小于22岁或大于55岁 输出:拒绝 变量备注: 性别为男或者女
规则2: 变量:是否本行关系人 sfbhgxr 逻辑:sfbhgxr=1 输出:拒绝
规则3: 变量:配偶在黑名单中 pozhmdz 逻辑:pozhmdz=1 输出:拒绝
规则4: 变量:行内审慎客户 hnsskh 逻辑:hnsskh=1 输出:拒绝
规则5: 变量:呆账信息汇总、资产处置信息汇总、保证人代偿信息汇总数据中有记录的 ydzhzccz 逻辑:ydzhzccz=1 输出:拒绝
规则6: 变量:资产处置信息余额的zcczye 逻辑:zcczye>0 输出:拒绝
规则7: 变量:保证人代偿信息余额的 bzrdcye 逻辑:bzrdcye>0 输出:拒绝
规则8: 变量:呆账贷记卡是记录dzdjkjl_cnt 逻辑:dzdjkjl_cnt>0 输出:拒绝
规则9: 变量:对外担保信息中担保贷款五级分类 dbxxwjfl 逻辑:对外担保信息中担保贷款五级分类是“次级”或“可疑”或“损失” 输出:拒绝
规则10: 变量:当前逾期金额 dqyqje 逻辑:dqyqje>0 输出:拒绝
规则11: 变量:客户存在公安负面信息 gafmxx_cnt 逻辑:gafmxx_cnt>0 输出:拒绝
规则12: 变量:客户存在失信被执行人信息 ssxrzxxx_cnt 逻辑:ssxrzxxx_cnt>0 输出:拒绝
规则13: 变量:公积金缴至年月距申请时的月份数gjjjfyffs 逻辑:公积金缴至年月距申请时的月份数大于3 输出:拒绝
规则14: 变量:公积金近1年累计缴纳次数 gjjjncs_l122m 逻辑:公积金近1年累计缴纳次数小于6 输出:拒绝
规则15: 变量:贷记卡最近24个月的还款记录中逾期天数 djkyqts_l24m 逾期金额 yqje 逻辑:贷记卡或贷记卡最近24个月的还款记录中逾期天数(3-7、D、Z、G字符)且逾期金额500元以上 输出:拒绝
规则16: 变量:借款人最近24个月最大连续逾期期数jkrzdlxyqqs_l24m 累计逾期次数 ljyqqs 逻辑:借款人最近24个月最大连续逾期期数>3或累计逾期次数>6 输出:拒绝
规则17: 变量:非银行机构未结清贷款笔数 fyjgwjqdkbs 逻辑:非银行机构未结清贷款笔数>=3 输出:拒绝
规则18: 变量:近一个月非本行审批查询机构数 fbhspcxs_l1m 近3个月非本月审批查询机构数 fbhspcxs_l3m 近6个月非本行审批查询机构数 fbhspcxs_l6m 逻辑:近一个月非本行审批查询机构数>3或近3个月非本月审批查询机构数>5或近6个月非本行审批查询机构数>8 输出:拒绝
规则19: 变量:一代模型评分 ydmxpf 逻辑:一代模型评分>0.766 输出:拒绝
请根据```内的示例以及待处理规则中的变量、计算逻辑及输出，用Python语言生成功能函数代码。
返回结果要求：
1、只返回功能函数代码，不要多余的输出。
2、代码逻辑应严格按照待处理要求中的条件，不要自行添加多余的逻辑。
3、代码的语法要符合python的语法规范，返回的代码应该是可执行的。
4、规则里有 结果备注 的请在函数中的 输出结果备注 处进行备注，没有的则无输出结果备注
# 角色
你是一个专业的Python代码生成器，能够根据给定的流程图和函数内容，用Python语言生成完整的流程执行代码。
给定的函数内容:
def handle_general_rules(data:dict):
# 通用规则
# 输出结果备注:
# 0代表拒绝,1代表接受
sex = data.get("sex")
age = data.get("age")
pboc_score = data.get("pboc_score")
incomeM = data.get("incomeM")
qzzxbjz = data.get("qzzxbjz")
yzxbje = data.get("yzxbje")
wjqxedkbss = data.get("wjqxedkbss")
xedkjgs = data.get("xedkjgs")
if sex is not None and age is not None:
if (sex == "男" and (22 <= age <= 60)) or (sex == "女" and (22 <= age <= 55)):
return 1
if pboc_score is not None:
if pboc_score > 0.523:
return 0
if incomeM is not None:
if incomeM < 2000:
return 0
if qzzxbjz is not None and yzxbje is not None:
if (qzzxbjz - yzxbje) > 20000:
return 0
if wjqxedkbss is not None or xedkjgs is not None:
if (wjqxedkbss is not None and wjqxedkbss > 4) or (xedkjgs is not None and xedkjgs > 2):
return 0
return 1.0
def handle_kequn_rules(data:dict):
# 客群规则
# 输出结果备注:
# 公积金单位较优客户
# 金融资产较优客户
# 房贷客户
gjjdwlx = data.get("gjjdwlx")
sex = data.get("sex")
age = data.get("age")
gjjkhsj = data.get("gjjkhsj")
gjjjncs_l12m = data.get("gjjjncs_l12m")
nrjjrzc = data.get("nrjjrzc")
rjzc_l3m = data.get("rjzc_l3m")
whkkhsj = data.get("whkkhsj")
xymxpf = data.get("xymxpf")
wjqfdyyhke = data.get("wjqfdyyhke")
yhkqs = data.get("yhkqs")
zcyqts = data.get("zcyqts")
yqcs_l24m = data.get("yqcs_l24m")
if gjjdwlx is not None and sex is not None and age is not None and gjjkhsj is not None and gjjjncs_l12m is not None:
if (gjjdwlx in ("国家机关", "事业单位", "国企", "医院") and
((sex == "男" and 22 <= age <= 60) or (sex == "女" and 22 <= age <= 55)) and
gjjkhsj >= 1 and gjjjncs_l12m >= 6):
return "公积金单位较优客户"
if nrjjrzc is not None and rjzc_l3m is not None and whkkhsj is not None and xymxpf is not None:
if (nrjjrzc > 10 and rjzc_l3m >= 1 and whkkhsj >= 1 and
(xymxpf > 0.397 or xymxpf == -1)):
return "金融资产较优客户"
if wjqfdyyhke is not None and yhkqs is not None and zcyqts is not None and yqcs_l24m is not None:
if ((wjqfdyyhke > 4000 and yhkqs > 12 and yqcs_l24m <= 2 and zcyqts <= 30) or
(0 < wjqfdyyhke <= 4000 and yhkqs > 24 and yqcs_l24m <= 2 and zcyqts <= 30)):
return "房贷客户"
return "其它"
def handle_extremely_high_quality_customer_rules(data:dict):
# 极优质客户规则
# 输出结果备注:
age = data.get("age")
sex = data.get("sex")
sfbhgxr = data.get("sfbhgxr")
pozhmdz = data.get("pozhmdz")
hnsskh = data.get("hnsskh")
ydzhzccz = data.get("ydzhzccz")
zcczye = data.get("zcczye")
bzrdcye = data.get("bzrdcye")
dzdjkjl_cnt = data.get("dzdjkjl_cnt")
dbxxwjfl = data.get("dbxxwjfl")
dqyqje = data.get("dqyqje")
gafmxx_cnt = data.get("gafmxx_cnt")
ssxrzxxx_cnt = data.get("ssxrzxxx_cnt")
gjjjfyffs = data.get("gjjjfyffs")
gjjjncs_l122m = data.get("gjjjncs_l122m")
djkyqts_l24m = data.get("djkyqts_l24m")
yqje = data.get("yqje")
jkrzdlxyqqs_l24m = data.get("jkrzdlxyqqs_l24m")
ljyqqs = data.get("ljyqqs")
fyjgwjqdkbs = data.get("fyjgwjqdkbs")
fbhspcxs_l1m = data.get("fbhspcxs_l1m")
fbhspcxs_l3m = data.get("fbhspcxs_l3m")
fbhspcxs_l6m = data.get("fbhspcxs_l6m")
ydmxpf = data.get("ydmxpf")
if age is not None and sex is not None:
if (sex == "男" and (age < 22 or age > 60)) or (sex == "女" and (age < 22 or age > 55)):
return "拒绝"
if sfbhgxr is not None:
if sfbhgxr == 1:
return "拒绝"
if pozhmdz is not None:
if pozhmdz == 1:
return "拒绝"
if hnsskh is not None:
if hnsskh == 1:
return "拒绝"
if ydzhzccz is not None:
if ydzhzccz == 1:
return "拒绝"
if zcczye is not None:
if zcczye > 0:
return "拒绝"
if bzrdcye is not None:
if bzrdcye > 0:
return "拒绝"
if dzdjkjl_cnt is not None:
if dzdjkjl_cnt > 0:
return "拒绝"
if dbxxwjfl is not None:
if dbxxwjfl in ["次级", "可疑", "损失"]:
return "拒绝"
if dqyqje is not None:
if dqyqje > 0:
return "拒绝"
if gafmxx_cnt is not None:
if gafmxx_cnt > 0:
return "拒绝"
if ssxrzxxx_cnt is not None:
if ssxrzxxx_cnt > 0:
return "拒绝"
if gjjjfyffs is not None:
if gjjjfyffs > 3:
return "拒绝"
if gjjjncs_l122m is not None:
if gjjjncs_l122m < 6:
return "拒绝"
if djkyqts_l24m is not None and yqje is not None:
if (djkyqts_l24m in ["3", "4", "5", "6", "7", "D", "Z", "G"] and yqje > 500):
return "拒绝"
if jkrzdlxyqqs_l24m is not None and ljyqqs is not None:
if jkrzdlxyqqs_l24m > 3 or ljyqqs > 6:
return "拒绝"
if fyjgwjqdkbs is not None:
if fyjgwjqdkbs >= 3:
return "拒绝"
if fbhspcxs_l1m is not None and fbhspcxs_l3m is not None and fbhspcxs_l6m is not None:
if fbhspcxs_l1m > 3 or fbhspcxs_l3m > 5 or fbhspcxs_l6m > 8:
return "拒绝"
if ydmxpf is not None:
if ydmxpf > 0.766:
return "拒绝"
return "接受"
def handle_important_customer_rules(data:dict):
# 要客规则
# 输出结果备注: 无
bhgxr = data.get("bhgxr")
dqyqje = data.get("dqyqje")
wbhdkhxykyqye = data.get("wbhdkhxykyqye")
if bhgxr is not None:
if bhgxr == 1:
return "拒绝"
if dqyqje is not None:
if dqyqje > 0:
return "拒绝"
if wbhdkhxykyqye is not None:
if wbhdkhxykyqye == 1:
return "拒绝"
return "拒绝"
def handle_gov_vip_rules(data:dict):
# 是否要客
# 输出结果备注:
# 1代表是要客
# 0代表不是要客
GovVip = data.get("GovVip")
if GovVip is not None:
if GovVip == 1:
return 1
elif GovVip == 0:
return 0
return 0.0
def handle_high_quality_customer_credit(data:dict):
# 极优质客户额度
# 输出结果备注: 无
dwlx = data.get("dwlx")
incomeM = data.get("incomeM")
if dwlx is not None and incomeM is not None:
if dwlx == "国家机关" and 0 < incomeM < 5000:
return 60000
if dwlx == "国家机关" and 5000 <= incomeM < 12000:
return 180000
if dwlx == "国家机关" and 12000 <= incomeM < 15000:
return 250000
if dwlx == "国家机关" and incomeM > 15000:
return 300000
if (dwlx == "三甲医院" or dwlx == "优质学校" or dwlx == "国网") and 0 < incomeM < 6000:
return 50000
if dwlx == "国家机关" and 6000 <= incomeM < 14000:
return 150000
if (dwlx == "三甲医院" or dwlx == "优质学校" or dwlx == "国网") and 14000 <= incomeM < 16000:
return 220000
if (dwlx == "三甲医院" or dwlx == "优质学校" or dwlx == "国网") and incomeM > 16000:
return 300000
return 0.0
def handle_customer_credit(data:dict):
# 客群额度
# 输出结果备注: 无
kqlx = data.get("kqlx")
incomeM = data.get("incomeM")
if kqlx is not None and incomeM is not None:
if kqlx == "公积金单位较优客户":
if 0 < incomeM < 5000:
return 60000
elif 5000 <= incomeM < 12000:
return 180000
elif 12000 <= incomeM < 15000:
return 250000
elif incomeM > 15000:
return 300000
elif kqlx == "房贷客户":
if 0 < incomeM < 6000:
return 50000
elif 6000 <= incomeM < 14000:
return 150000
elif 14000 <= incomeM < 16000:
return 220000
elif incomeM > 16000:
return 300000
return 0.0
函数与节点对应关系:
通用规则: handle_general_rules
客群规则: handle_kequn_rules
极优质客户: handle_extremely_high_quality_customer_rules
要客规则: handle_important_customer_rules
是否要客: handle_gov_vip_rules
极优质客户额度: handle_high_quality_customer_credit
客群额度: handle_customer_credit
流程描述:
```
开始 --> [是否要客: 1] --> 要客规则 --> 结束
开始 --> [是否要客: 0] --> 极优质客户
[极优质客户: 拒绝] --> 通用规则
[极优质客户: 接受] --> 极优质客户额度 --> 结束
[通用规则: 0] --> 结束
[通用规则: 1] --> 客群规则 --> 客群额度 --> 结束
```
流程描述说明:
1、[满足条件: *] 为判断上一个节点的输出是否符合条件
请把```括号内的流程描述的内容转换为python代码，流程中的各个节点参考给定的函数内容与函数与节点对应关系，并构造测试数据data，代码样式如下。
from handle_general_rules import handle_general_rules
from handle_kequn_rules import handle_kequn_rules
from handle_extremely_high_quality_customer_rules import handle_extremely_high_quality_customer_rules
from handle_important_customer_rules import handle_important_customer_rules
from handle_gov_vip_rules import handle_gov_vip_rules
from handle_high_quality_customer_credit import handle_high_quality_customer_credit
from handle_customer_credit import handle_customer_credit
def main(data: dict):
流程逻辑
if __name__ == "__main__":
data = 测试数据
print(main(data))
返回结果要求：
1、针对流程分支情况请参考给定的函数内容及函数的输出结果备注。
2、开始节点与结束节点，无实际意义，结束节点直接返回其上一个节点输出的结果。
3、只返回函数代码，不要多余的输出。
4、代码逻辑应严格按照流程描述中的逻辑，不要自行添加多余的逻辑。
5、代码的语法要符合python的语法规范，返回的代码应该是可执行的。