def post(self):
try:
validate_res, request_args = self.validate_phonetag_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
except Exception as e:
logger.error('phonetag request is fail : %s' % e)
return render_error(code=1, msg='验证签名失败')
try:
# 将字典转换成数据帧
x_test = pd.DataFrame.from_dict(request_args, orient='index').T
# 读取model文件进行过滤
path_file_imp = os.getcwd() + "/model/phonetag_imp18122417.model"
imp_model = joblib.load(path_file_imp)
imp_data = imp_model.transform(x_test)
# 读取model文件进行预测
path_file_clf = os.getcwd() + "/model/phonetag_clf18122417.model"
clf_model = joblib.load(path_file_clf)
clf_data = clf_model.predict_proba(imp_data)
# 将numpy.ndarray转list
score = clf_data.tolist()
return render_ok(score)
except Exception as e:
logger.error('phonetag request is fail : %s' % e)
return render_error(code=2, msg='数据格式错误')
def post(self):
"""
分析数据
"""
validate_res, request_args = self.validate_applabel_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
obj = APPLabel(request_args)
result = obj.run()
resCode = result.get('code', -100)
resMsg = result.get('msg', '系统错误')
if resCode == 0:
return render_ok()
return render_error(resCode, resMsg)
def post(self):
validate_res, request_args = self.validate_reloanxg_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
# 将字典的值转换成整数
new_request_args = {}
for key, value in request_args.items():
new_request_args[key] = float(value)
# logger.info("aa---\n%s" % new_request_args)
# 读取model文件进行预测
path_file = os.getcwd() + "/model/xgboost_fd_ending6.model"
# logger.info("path_file---\n%s" % path_file)
pmml_model = joblib.load(path_file)
# 将字典转换成数据框
x_test = pd.DataFrame.from_dict(new_request_args, orient='index').T
# logger.info("aa---\n%s" % x_test)
classes = pmml_model.predict_proba(x_test)
# 将numpy.ndarray转list
classes = classes.tolist()
# logger.info("bbbbbb---\n%s", classes)
resp = render_ok(classes)
return resp
def post(self):
# x_test = {
# 'PROME_V4_SCORE':1,
# 'multi_p2p_p_class_7':1,
# 'loan_all':1,
# 'history_bad_status':1,
# 'addr_phones_nodups':1,
# 'addr_collection_count':1,
# 'addr_tel_count':1,
# 'com_r_duration_mavg':1,
# 'com_c_total_mavg':1,
# 'com_use_time':1,
# 'com_count':1,
# 'com_month_answer_duration':1,
# 'com_mobile_people':1,
# 'com_night_duration_mavg':1,
# 'com_max_tel_connect':1,
# 'vs_duration_match':1,
# 'same_phone_num':1,
# 'shutdown_max_days':1,
# 'advertis_weight_loss_p':1,
# 'express_aeavy_number_p':1,
# 'harass_weight_loss_p':1,
# 'house_agent_aeavy_number_lable':1,
# 'cheat_aeavy_number_sign':1,
# 'taxi_aeavy_number_sign':1,
# 'ring_weight_loss_sign':1
# }
validate_res, request_args = self.validate_xgboostr_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
#将字典的值转换成整数
new_request_args = {}
for key, value in request_args.items():
new_request_args[key] = float(value)
#logger.info("aa---\n%s" % new_request_args)
#读取model文件进行预测
#path_file = os.getcwd()+"\\model\\xgboost_v_0_1_n.model"
#path_file = os.getcwd() + "/model/xgboost_v_0_1_ok.model"
path_file = os.getcwd() + "/model/xgboost_v_0_1_t7.model"
#logger.info("path_file---\n%s" % path_file)
pmml_model = joblib.load(path_file)
#将字典转换成数据框
x_test = pd.DataFrame.from_dict(new_request_args, orient='index').T
#logger.info("aa---\n%s" % x_test)
classes = pmml_model.predict_proba(x_test)
#将numpy.ndarray转list
classes = classes.tolist()
#logger.info("aaa---\n%s", classes)
resp = render_ok(classes)
return resp
def post(self):
"""
分析数据
"""
validate_res, request_args = self.operator_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
# 1. 分析后的数据
obj = OperatorLogic(request_args)
dict_data = obj.run()
if dict_data is None:
return render_error(code=1001, msg='写入请求表失败')
data = {
'credit_id': obj.credit_id,
'base_id': obj.base_id,
'aid': obj.aid,
'data': dict_data
}
resp = render_ok(data)
return resp
def post(self):
"""
分析数据
"""
validate_res, request_args = self.validate_sign()
if not validate_res:
return render_error(code=1, msg='验证签名失败')
# 1. 分析后的数据
obj = PodloanAnalysis(request_args)
dict_data = obj.run()
# 2. 保存到数据库中
oAfDbAgent = AfDbAgent()
res = oAfDbAgent.import_db(dict_data)
logger.info("request_id:%s aid:%s import db result %s" %
(obj.request_id, obj.aid, res))
data = {
'request_id': obj.request_id,
'base_id': obj.base_id,
'aid': obj.aid,
}
resp = render_ok(data)
return resp