import consts
import numpy as np;# 近3月开户最高贷款本金
import utils
import time;
#近3月开户最高贷款本金
def getLastLoanAmtMax(df,reportTime,month):
    openAccoutDf = df[df['开立日期']>=utils.getLastMonthDate(reportTime,month)]
    return np.max(openAccoutDf['借款金额（本金)'])

#近3月开户最高贷款本金
def getLastLoanAmtMin(df,reportTime,month):
    openAccoutDf = df[df['开立日期']>=utils.getLastMonthDate(reportTime,month)]
    return np.min(openAccoutDf['借款金额（本金)'])
#近3月开户最高贷款本金
def getLastLoanAmtAvg(df,reportTime,month):
    openAccoutDf = df[df['开立日期']>=utils.getLastMonthDate(reportTime,month)]
    return round(np.mean(openAccoutDf['借款金额（本金)']),2)

#贷款最近一次还款日期距今时长
#从“贷款信息”中提取，取客户的正常还款行为，不取因为某种特定的行为而产生的还款，
# 剔除转出、结清、呆账、呆帐后，取各贷款记录的“最近一次还款日期”的最小值，然后计算距离报告时间的天数，MIN(day(报告时间-最近一次还款日期))
def getLastPayDateMinDays(df,reportTime):
    return utils.difDateReportTime(reportTime,np.max(df['最近一次还款日期']))

#从“贷款信息”计算客户符合以下条件的贷款额度
# 1.近12个月（开户日期<90）
# 2.贷款额度>100元
# 3.贷款类型=‘个人消费贷款’
def getLastPerConsumeAmt(df,month,reportTime):
    openAccountDf = df[df['开立日期']>=utils.getLastMonthDate(reportTime,month)]
    openAccountDf = openAccountDf[(openAccountDf['借款金额（本金)']>100) & (openAccountDf['业务种类']=='其他个人消费贷款')]
    return round(np.sum(openAccountDf['借款金额（本金)']),2)

#当前贷款
def getCurLtv(tmpDf,bizTypeList):

    ltvDf = tmpDf[tmpDf['业务种类'].isin(bizTypeList)]
    key = bizTypeList[0][-1];
    if len(key)==1:
        rules = r'.*?'+key+'.*'
        houseDf = tmpDf[tmpDf['业务种类'].str.contains(rules)]
        ltvDf.append(houseDf)
    if not ltvDf.empty:
        return round(np.divide(np.sum(ltvDf['余额（本金)'].astype('int')), np.sum(ltvDf['借款金额（本金)'].astype('int'))), 2)
    return None

#按管理机构类型统计当前贷款比例
def getCurBankLtv(tmpDf,bizTypeList):
    ltvDf = tmpDf[tmpDf['管理机构类型'].isin(bizTypeList)]
    if not ltvDf.empty:
        return round(np.divide(np.sum(ltvDf['余额（本金)'].astype('int')), np.sum(ltvDf['借款金额（本金)'].astype('int'))), 2)
    return None

#贷款开户数
def getOpenAccount(df,reportTime,month,bizTypeList):
    tmpDf = df
    if not tmpDf.empty:
        if len(bizTypeList)>0:
            tmpDf = tmpDf[tmpDf['管理机构类型'].isin(bizTypeList)];
        tmpDf = tmpDf.sort_values(by=["开立日期"], ascending=(False))
        openAccountDf = tmpDf[tmpDf['开立日期'] >= utils.getLastMonthDate(reportTime, month)]
        return openAccountDf.index.size
    return 0;

#计算最大授信额度-汇算帐0630
def getLoanCreditAmtMax(df,reportTime,month):
    loanCreditAmtDf = df[df['担保方式'].isin(['信用/免担保'])]
    loanCreditAmtDf = loanCreditAmtDf[(~loanCreditAmtDf['业务种类'].isin(consts.notMortgageList))]
    creditDate = utils.getLastMonthDate(reportTime, month)
    loanCreditAmtDf = loanCreditAmtDf[loanCreditAmtDf["开立日期"] >= creditDate]
    if not loanCreditAmtDf.empty:
        return np.max(loanCreditAmtDf['借款金额（本金)'])
    else:
        return None
#小额贷款笔数近1个月小额贷款笔数
def getSmallLoanCount(df,reportTime,month):
    openAccoutDf = df[df['开立日期']>=utils.getLastMonthDate(reportTime,month)]
    if not openAccoutDf.empty:
        smallDf = openAccoutDf[openAccoutDf['借款金额（本金)']<=20000]
        return smallDf.index.size
    return None