在python multiprocessing中，queue.put將阻止子進程

Question

如果僅輸入10個數據，則輸出如下。

if cnt>10:   # kk's size is about 2000. 

Begin CountChangePercentMT1 at 2016-06-16 15:19:30.706000:
end-in 0 2016-06-16 15:19:33.291000
end-in 1 2016-06-16 15:19:34.990000
end-in 2 2016-06-16 15:19:36.921000
end 0
end 1
end 2
end-in 3 2016-06-16 15:19:38.748000
end 3
End CountChangePercentMT1 at 2016-06-16 15:20:06.665000:

如果放入q 20個數據，輸出如下：

if cnt>20:   # kk's size is about 2000. 

Begin CountChangePercentMT1 at 2016-06-16 15:35:36.661000:
end-in 0 2016-06-16 15:35:39.330000
end-in 1 2016-06-16 15:35:40.954000
end-in 2 2016-06-16 15:35:42.828000
end 0
end 1
end 2
end-in 3 2016-06-16 15:35:44.669000

如果放入q 50個數據，輸出如下：

if cnt>50:   # kk's size is about 2000. 

Begin CountChangePercentMT1 at 2016-06-16 15:36:54.518000:
end-in 0 2016-06-16 15:36:57.583000
end-in 1 2016-06-16 15:36:58.886000
end-in 2 2016-06-16 15:37:00.757000
end-in 3 2016-06-16 15:37:02.648000

Answer 1

def do_somthing(q_out,q,i,trueStartDate,trueEndDate,preStartDate,allExistTables,stock_gainian):
#Init conn
conn = MySQLdb.connect(host='localhost',db='tushare',user='root',passwd='',port=3306,charset='UTF8')
#Init df_Cc
df_Cc = pd.DataFrame()
df_Cc['ticker'] = pd.Series(dtype=numpy.int64,index=df_Cc.index)
df_Cc['secShortName'] = pd.Series(dtype=numpy.object,index=df_Cc.index)
df_Cc['percent'] = pd.Series(dtype=numpy.float64,index=df_Cc.index)
df_Cc['startPrice'] = pd.Series(dtype=numpy.float64,index=df_Cc.index)
df_Cc['endPrice'] = pd.Series(dtype=numpy.float64,index=df_Cc.index)
df_Cc['startDate'] = pd.Series(dtype=numpy.object,index=df_Cc.index)
df_Cc['endDate'] = pd.Series(dtype=numpy.object,index=df_Cc.index)
df_Cc['gainian'] = pd.Series(dtype=numpy.object,index=df_Cc.index)
df_Cc['shizhi'] = pd.Series(dtype=numpy.float64,index=df_Cc.index)
df_Cc['liutong'] = pd.Series(dtype=numpy.float64,index=df_Cc.index)
while True:
    aa = q.get()
    if aa != None:
        ticker = aa[0]
        secShortName = aa[1]
        totalShares = aa[2]
        nonrestfloatA = aa[3]
        listDate = datetime.datetime.strptime(aa[4], "%Y-%m-%d")
        stock_mktequd_name = '%s%06d' % (init.g_mktequd,ticker)
        if (stock_mktequd_name in allExistTables) & (trueEndDate>=listDate>=trueStartDate)==False:
            str = 'select * from %s where tradeDate>=\'%s\' and tradeDate<=\'%s\' order by tradeDate' % (stock_mktequd_name,trueStartDate.strftime("%Y-%m-%d"),trueEndDate.strftime("%Y-%m-%d"))
            df = pd.read_sql(str,conn)

            l = len(df_Cc)
            df_Cc.at[l,'ticker'] = ticker
            df_Cc.at[l,'secShortName'] = secShortName
            nn = df.shape[0]
            if nn>0:
                #
                startPrice = df.iloc[0]['preClosePrice']*GetQfq(ticker,preStartDate,conn)  # if nn>=n else df.iloc[0]['preClosePrice']*1
                endPrice = df.iloc[nn-1]['closePrice']*df.iloc[nn-1]['accumAdjFactor']
                percent = (endPrice-startPrice)/startPrice*100 # if startPrice!=0 else -100
                df_Cc.at[l,'startDate'] = df.iloc[0]['tradeDate']
                df_Cc.at[l,'endDate'] = df.iloc[nn-1]['tradeDate']
                df_Cc.at[l,'percent'] = percent
                df_Cc.at[l,'startPrice'] = startPrice
                df_Cc.at[l,'endPrice'] = endPrice
                df_gn = stock_gainian.query('ticker==%s' % ticker)
                if df_gn.shape[0]==1:
                    df_Cc.at[l,'gainian'] = df_gn.iloc[0]['ref_gainian']
                df_Cc.at[l,'shizhi'] = totalShares*startPrice/100000000
                df_Cc.at[l,'liutong'] = nonrestfloatA*startPrice/100000000
    else:
        break

q_out.put(df_Cc)
conn.close()
print 'end-in %s %s' % (i,datetime.datetime.now())