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zhichan
Commit eefcb9ed by 宋毅
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fanhui_second

parent 87f1c181
Showing with 18 additions and 18 deletions
rpt_result/main.py
...@@ -5,8 +5,8 @@ ...@@ -5,8 +5,8 @@
# @File : sql_tax_test.py # @File : sql_tax_test.py
# @Software: PyCharm # @Software: PyCharm
import pymysql, os, sys, time, datetime import os, sys
from flask import request, Flask, jsonify from flask import request, Flask,jsonify
from flask_cors import * from flask_cors import *
import json import json
...@@ -74,25 +74,25 @@ def CreatBdictFromJson(new_status): ...@@ -74,25 +74,25 @@ def CreatBdictFromJson(new_status):
def RiskAbnormal(t_r1): def RiskAbnormal(t_r1):
RiskA = {} RiskA = {}
t_r1 = t_r1 t_r1 = t_r1
rules_1 = {"t_r1<='30%'": "企业风险异常同⽐其他企业⽐例较低", rules_1 = {"t_r1<='30%'": "企业风险异常同比其他企业比例较低",
"t_r1>'30%'": "企业风险异常同⽐其他企业⽐例明显偏高" "t_r1>'30%'": "企业风险异常同比其他企业比例明显偏高"
} }
for k1, v1 in rules_1.items(): for k1, v1 in rules_1.items():
if eval(str(k1)): if eval(str(k1)):
RiskA = {t_r1: v1} RiskA = {"score":t_r1,"describe":v1}
return RiskA return RiskA
# 输入计算出的被检测风险值，判断被监测风险结果 # 输入计算出的被检测风险值，判断被监测风险结果
def MonitoredRisk(t_r2): def MonitoredRisk(t_r2):
MRisk = {} MRisk = {}
t_r2 = t_r2 t_r2 = t_r2
rules_2 = {"t_r2<='10%'": "企业被监控的风险同⽐其他企业⽐例较低", rules_2 = {"t_r2<='10%'": "企业被监控的风险同比其他企业比例较低",
"t_r2>'10%' and t_r2<='50%'": "经检测，企业有⼀定可能性被选为税务监控对象", "t_r2>'10%' and t_r2<='50%'": "经检测，企业有一定可能性被选为税务监控对象",
"t_r2>'50%'": "经检测，企业有很⼤可能性被选为税务监控对象" "t_r2>'50%'": "经检测，企业有很大可能性被选为税务监控对象"
} }
for k2, v2 in rules_2.items(): for k2, v2 in rules_2.items():
if eval(str(k2)): if eval(str(k2)):
MRisk = {t_r2: v2} MRisk = {"score":t_r2,"describe":v2}
return MRisk return MRisk
# 输入计算出的被稽查风险值，判断被稽查风险结果 # 输入计算出的被稽查风险值，判断被稽查风险结果
...@@ -100,26 +100,26 @@ def AuditedRisk(t_r3): ...@@ -100,26 +100,26 @@ def AuditedRisk(t_r3):
ARisk = {} ARisk = {}
t_r3 = t_r3 t_r3 = t_r3
rules_3 = {"t_r3<='10%'": "企业被税务稽查的可能性较低", rules_3 = {"t_r3<='10%'": "企业被税务稽查的可能性较低",
"t_r3>'10%' and t_r3<='30%'": "企业有⼀定可能性被税务稽查", "t_r3>'10%' and t_r3<='30%'": "企业有一定可能性被税务稽查",
"t_r3>'30%'": "企业有很⼤可能性被税务稽查" "t_r3>'30%'": "企业有很大可能性被税务稽查"
} }
for k3, v3 in rules_3.items(): for k3, v3 in rules_3.items():
if eval(str(k3)): if eval(str(k3)):
ARisk = {t_r3: v3} ARisk = {"score":t_r3,"describe":v3}
return ARisk return ARisk
# 输入总体计算的风险异常比例，得到提示语（也可与RiskAbnormal函数合并） # 输入总体计算的风险异常比例，得到提示语（也可与RiskAbnormal函数合并）
def information(t_r1): def information(t_r1):
info = {} info = {}
t_r1 = t_r1 t_r1 = t_r1
rules_0 = {"t_r1<='30%'": "贵企业的风险异常情况同比其它企业较少，如需更多更详细的诊断服务，请联系我们>>", rules_0 = {"t_r1<='30%'": "贵企业的风险异常情况同比其他企业较少，如需更多更详细的诊断服务，请联系我们>>",
"t_r1>'30%' and t_r1<='60%'": "企业的风险异常情况同比其它企业明显偏多，有较⼤可能性成为税务系统监控的对象，请企业的财税⼈员参考以下详细检测情况进行自查，如需要进行更详细的诊断服务请联系我们>>", "t_r1>'30%' and t_r1<='60%'": "企业的风险异常情况同比其他企业明显偏多，有较大可能性成为税务系统监控的对象，请企业的财税人员参考以下详细检测情况进行自查，如需进行更详细的诊断服务请联系我们>>",
"t_r1>'60%' and t_r1<='80%'": "如果税务局选择企业所在行业进行行业稽查，该企业有⼀定可能性成为被选案例，请财税⼈员尽快参照以下比例进行自查。如需要进行更详细的诊断服务请联系我们>>", "t_r1>'60%' and t_r1<='80%'": "如果税务局选择企业所在行业进行行业稽查，该企业有一定可能性成为被选案例，请财税人员尽快参照以下比例进行自查，如需进行更详细的诊断服务请联系我们>>",
"t_r1>'80%'": "如果税务局选择企业所在行业进行行业稽查，该企业有很⼤可能性成为被选案例，请财税⼈员尽快参照以下比例进行自查。如需要进行更详细的诊断服务请联系我们>>" "t_r1>'80%'": "如果税务局选择企业所在行业进行行业稽查，该企业有很大可能性成为被选案例，请财税人员尽快参照以下比例进行自查，如需进行更详细的诊断服务请联系我们>>"
} }
for k0, v0 in rules_0.items(): for k0, v0 in rules_0.items():
if eval(str(k0)): if eval(str(k0)):
info = {t_r1: v0} info = {{"score":t_r1,"describe":v0}}
return info return info
...@@ -694,7 +694,7 @@ def report(): ...@@ -694,7 +694,7 @@ def report():
"Risk_ALLT_FX": Risk_ALLT_FX "Risk_ALLT_FX": Risk_ALLT_FX
} }
print(result,"------------------------------") print(result,"------------------------------")
return result return jsonify(result)
server.run(host='121.0.0.1', port=80, debug=True) server.run(host='121.0.0.1', port=80, debug=True)
......
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