'''求出查询日之前的连续的4个季度, 返回季度列表
'''
def get_statDate(date = '2019-08-24'):

    # 年
    year = int(date[:4])
    # 月日
    month_and_day = date[5:10]

    # 季度列表
    if month_and_day < '05-01':
        statDate_list = [str(year-2) + "q4", str(year-1) + "q1", str(year-1) + "q2", str(year-1) + "q3"]
    elif month_and_day >= '05-01' and month_and_day < '09-01':
        statDate_list = [str(year-1) + "q2", str(year-1) + "q3", str(year-1) + "q4", str(year) + "q1"]
    elif month_and_day >= '09-01' and month_and_day < '11-01':
        statDate_list = [str(year-1) + "q3", str(year-1) + "q4", str(year) + "q1", str(year) + "q2"]
    elif month_and_day >= '11-01':
        statDate_list = [str(year-1) + "q4", str(year) + "q1", str(year) + "q2", str(year) + "q3"]

    print ('\ndate={}, statDate={}'.format(date, statDate_list))
    return statDate_list

''' 依据公式自己求出eps_ttm, 然后与聚宽的查询结果对比, 然后打印结果
'''
codes = ['000069.XSHE']
date = '2019-08-24'
def validate_pe(codes=codes, date=date, ):
    '''
    '''
    statDate = get_statDate(date)

    q = query(
            valuation.code,
            income.basic_eps,
            indicator.eps,
            indicator.pubDate,     
        ).filter(
            valuation.code.in_(codes)
        ).order_by(
            valuation.code.asc()
        )
    for sdate in statDate:
        jbm_df  = get_fundamentals(q,statDate=sdate,) # 基本面df
        print(jbm_df)
    eps_list = [get_fundamentals(q,statDate=sdate,).eps.values[0]     for sdate in statDate]
    now_p2 = get_price(codes[0], end_date=date, fq=None)['close'][-1]
    now_p3 = get_price(codes[0], end_date=date, fq='post')['close'][-1]
    now_p = get_price(codes[0], end_date=date, fq='pre')['close'][-1]
    print('前复权价格, 原始成交价, 后复权价格分别是: {}, {}, {}'.format(now_p, now_p2, now_p3))
    
    pe_ttm = now_p2 / sum(eps_list)

    
    jbm_df = get_fundamentals(
             query(
                 valuation.code, 
                 valuation.pe_ratio, 
             ).filter(
                 valuation.code.in_(codes)
             ),
             date=date)
    res =  [round(pe_ttm,3), round(jbm_df.pe_ratio.values[0], 3)]
    res.append(res[0] - res[1])
    res = '代码={}, 日期={}, TTM_PE(12个月滚动市盈率)={}, 直接读取的pe_ratio={}, 相差= {}'.format(
        codes[0], date, *res)
    return res

print(validate_pe(codes, '2018-01-24'))
print(validate_pe(codes, '2017-01-24'))
print(validate_pe(codes, '2015-08-22'))
print(validate_pe(codes, '2015-01-24'))

8.8/(.124+.2697+.071+.1235)

7.55/(.124+.2697+.071+.1235)

a.