从万得下载A股数据保存到mongodb

from WindPy import *
import pandas as pd
import pymongo
import datetime,time
import os
#获取股票代码
daima2=pd.read_excel('C:/Users/Administrator/Desktop/daima2.xlsx')
daima2.columns=['code_name']
symbols=[u'000001.SZ']
for i in range(len(daima2)):
    code=daima2.ix[i,'code_name']
    if len(code)>0:
        symbols.append(code[7:16])    
len(symbols)
symbols[-400:-370]
symbols.index('601998.SH')
symbols=symbols[3018:]
client=pymongo.MongoClient()
#conn = pymongo.Connection('localhost',27017)
def AStockHisData(symbols,start_date,end_date,step=0):
        '''
        逐个股票代码查询行情数据
        wsd代码可以借助 WindNavigator自动生成copy即可使用;时间参数不设，默认取当前日期，可能是非交易日没数据;
        只有一个时间参数时，默认作为为起始时间，结束时间默认为当前日期；如设置两个时间参数则依次为起止时间
        '''
        for symbol in symbols:
             w.start()
             try:
                 #stock=w.wsd(symbol,'trade_code,open,high,low,close,volume,amt',start_date,end_date)
                 '''
                 wsd代码可以借助 WindNavigator自动生成copy即可使用;
                 时间参数不设，默认取当前日期，可能是非交易日没数据;
                 只有一个时间参数，默认为起始时间到最新；如设置两个时间参数则依次为起止时间
                '''
                 stock=w.wsd(symbol, "trade_code,open,high,low,close,pre_close,volume,amt,dealnum,chg,pct_chg,vwap, adjfactor,close2,turn,free_turn,oi,oi_chg,pre_settle,settle,chg_settlement,pct_chg_settlement, lastradeday_s,last_trade_day,rel_ipo_chg,rel_ipo_pct_chg,susp_reason,close3, pe_ttm,val_pe_deducted_ttm,pe_lyr,pb_lf,ps_ttm,ps_lyr,dividendyield2,ev,mkt_cap_ard,pb_mrq,pcf_ocf_ttm,pcf_ncf_ttm,pcf_ocflyr,pcf_nflyr,trade_status", start_date,end_date)
                 index_data = pd.DataFrame()
                 index_data['trade_date']=stock.Times
                 stock.Data[0]=symbol
                 index_data['stock_code']=stock.Data[0]
                 #index_data['stock_code'] =symbol
                 index_data['open'] =stock.Data[1]
                 index_data['high'] =stock.Data[2]
                 index_data['low']  =stock.Data[3]
                 index_data['close']=stock.Data[4]
                 index_data['pre_close']=stock.Data[5]
                 index_data['volume']=stock.Data[6]
                 index_data['amt']=stock.Data[7]
                 index_data['dealnum']=stock.Data[8]
                 index_data['chg']=stock.Data[9]
                 index_data['pct_chg']=stock.Data[10]
                 #index_data['pct_chg']=index_data['pct_chg']/100
                 index_data['vwap']=stock.Data[11]
                 index_data['adj_factor']=stock.Data[12]
                 index_data['close2']=stock.Data[13]
                 index_data['turn']=stock.Data[14]
                 index_data['free_turn']=stock.Data[15]
                 index_data['oi']=stock.Data[16]
                 index_data['oi_chg']=stock.Data[17]
                 index_data['pre_settle']=stock.Data[18]
                 index_data['settle']=stock.Data[19]
                 index_data['chg_settlement']=stock.Data[20]
                 index_data['pct_chg_settlement']=stock.Data[21]
                 index_data['lastradeday_s']=stock.Data[22]
                 index_data['last_trade_day']=stock.Data[23]
                 index_data['rel_ipo_chg']=stock.Data[24]
                 index_data['rel_ipo_pct_chg']=stock.Data[25]
                 index_data['susp_reason']=stock.Data[26]
                 index_data['close3']=stock.Data[27]
                 index_data['pe_ttm']=stock.Data[28]
                 index_data['val_pe_deducted_ttm']=stock.Data[29]
                 index_data['pe_lyr']=stock.Data[30]
                 index_data['pb_lf']=stock.Data[31]
                 index_data['ps_ttm']=stock.Data[32]
                 index_data['ps_lyr']=stock.Data[33]
                 index_data['dividendyield2']=stock.Data[34]
                 index_data['ev']=stock.Data[35]
                 index_data['mkt_cap_ard']=stock.Data[36]
                 index_data['pb_mrq']=stock.Data[37]
                 index_data['pcf_ocf_ttm']=stock.Data[38]
                 index_data['pcf_ncf_ttm']=stock.Data[39]
                 index_data['pcf_ocflyr']=stock.Data[40]
                 index_data['pcf_ncflyr']=stock.Data[41]
                 index_data['trade_status']=stock.Data[42]
                 index_data['data_source']='Wind'
                 index_data['created_date']=time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
                 index_data['updated_date']=time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
                 index_data = index_data[index_data['open'] > 0]
                 #index_data.fillna(0)
                 try:
                     xx= client.db
                     xx1=xx[symbol]
                     xx1.insert(index_data.to_dict(orient='records'))
                     print symbol
                 except Exception as e:
                     #如果写入数据库失败，写入日志表，便于后续分析处理
                     error_log=pd.DataFrame()
                     error_log['trade_date']=stock.Times
                     error_log['stock_code']=stock.Data[0]
                     error_log['start_date']=start_date
                     error_log['end_date']=end_date
                     error_log['status']=None
                 w.start()
             except Exception as e:
                     #如果读取处理失败，可能是网络中断、频繁访问被限、历史数据缺失等原因。写入相关信息到日志表，便于后续补充处理
                     error_log=pd.DataFrame()
                     error_log['trade_date']=stock.Times
                     error_log['stock_code']=stock.Data[0]
                     error_log['start_date']=start_date
                     error_log['end_date']=end_date
                     w.start()
                     continue
start_date='2000-01-01'
end_date='2017-10-21'
AStockHisData(symbols,start_date,end_date,step=0) 

#注：wind个人版下载数据，下载的不全，有几百支股票仅仅有几十天的数据，对比通达信上面的数据，缺失好多。