read_pdf_plt/utils.py12

import consts;
import numpy as np;# 近3月开户最高贷款本金
import time;
import math;
import logResult;
log4r = logResult.logger
import json;
#某个日期离当前时间
def difDate(dateStr):
    return int(str(np.datetime64(np.datetime64(time.strftime("%Y-%m-%d")), "D") -np.datetime64(dateStr, "D")).split(" ")[0]);

#某个日期离报告期天数
def difDateReportTime(reportTime,dateStr):
    return int(str(np.datetime64(reportTime, "D") -np.datetime64(dateStr, "D")).split(" ")[0])

# 最近几个月的日期
def getLastMonthDate(dateStr,month):
    lastMonthDateStr = dateStr.replace(".", "-")
    # 最近一个月
    lastMonthDate = np.datetime64(lastMonthDateStr, "D") - np.timedelta64(30 * month, 'D')
    return str(lastMonthDate);

#离当前时间月份
def difMonthNow(dateStr):
    return math.ceil(int(str(np.datetime64(time.strftime("%Y-%m-%d")) - np.datetime64(dateStr.replace('.', '-'), "D")).split(" ")[0]) / 30);

#离报告时间月份
def difMonthReportTime(dateStr,reportTime):
    try:
        reportTimeTmp = np.datetime64(reportTime, "D");
        dateStrTmp = np.datetime64(dateStr, "D");
    except:
        print(dateStr+' 解析截止日期报错')
    month = int(str(reportTimeTmp - dateStrTmp ).split(" ")[0]) / 30;
    return math.ceil(month)
#转json
def toJson(df):
    jsonStr = df.to_json(orient="index",force_ascii=False);
    # print(json)
    log4r.info(jsonStr)
    reult = formatJson(json.loads(jsonStr));
    return reult
def formatJson(jsonObj):
    json_dicts = json.dumps(jsonObj, indent=4, ensure_ascii=False)
    return json_dicts;
# 判断是否有表头
def checkHeader(df,allHeaders):
    result = False
    headerList = df.loc[0, :].tolist()  # 第0行为表头
    headerList1 = []
    if df.index.size>1:
        headerList1 = df.loc[1, :].tolist()  # 第1行为表头
    for header in allHeaders:  # 第0行或者1行为表头的话，代表不是数据，否则是数据
        if list(filter(None, header)) == list(filter(None, headerList)) or list(filter(None, header)) == list(
                filter(None, headerList1)):
            result = True;
            break;
    return result;

#替换还款状态规则
#1、2、3、4、5、6、7、D、Z、G、B Z/B=7
def replacePayRcdStatus(df):
    if df.empty:
        return df;
    df['还款状态'] = df['还款状态'].map({"/":0,"*":0,"C":0,"N":0,"#":0,"M":0,"G":7,"D":1,"":0,"1":1,"2":2,"3":3,"4":4,"5":5,"6":6,"7":7})
    return df;

def doFilterCalc(self,dfx):
    dfx = dfx.replace('--', 0)
    return dfx;

#开户数使用，出现逾期的情况
def replacePayRcdStatusOverdue(df):
    if df.empty:
        return df;
    df['还款状态'] = df['还款状态'].map({"/":0,"*":0,"C":0,"N":0,"#":0,"M":0,"G":7,"B":7,"Z":7,"D":1,"":0,"1":1,"2":2,"3":3,"4":4,"5":5,"6":6,"7":7})
    return df;


# 替换日期格式转换briefInfo
def replaceDateCol(dfx):
    if not dfx.empty:
        dfx[1] = dfx[1].str.replace(".", '-')  # 2018.09.02->>2018-09-02
    return dfx;

# 替换日期格式转换briefInfo
def replaceDateColIdx(dfx,idx):
    if not dfx.empty:
        dfx[idx] = dfx[idx].str.replace(".", '-')  # 2018.09.02->>2018-09-02
    return dfx;

# 科学计数法转换
def replaceAmt(value):
    if str(value)=="" or str(value)=="--" or str(value)=="nan":
        # return value.replace(',', '')
        return 0.0
    else:
        return float(value.replace(',', ''))
#转整型
def toInt(value):
    if str(value)=="" or str(value)=="--" or str(value)=="nan":
        return 0
    else:
        return int(value)

#替换日期
def formatDate(str):
    return st