#上证代码
shanghaicode = []
for i in range(600000, 604000, 1):
 shanghaicode.append(str(i))
 
#深证代码
shenzhencode = []
for i in range(1000000, 1005000, 1):
 i = str(i)[1:] 
 shenzhencode.append(i)

def getalldata(code):
  if os.path.exists(datapath + code + '.csv'):
   print(code + 'already existed!')
   return
  metadata = broker.get_stock_pro(code)
  if len(metadata) == 0:
   return
  metadata.to_csv('C:/Users/abc/Desktop/' + code + '.csv',index = False)
  print(code + 'finished!')

from concurrent.futures.thread import ThreadPoolExecutor #多线程

executor = ThreadPoolExecutor(max_workers=3)
 for datatemp in executor.map(getalldata, shenzhencode):
  pass 
 
 executor = ThreadPoolExecutor(max_workers=3)
 for datatemp in executor.map(getalldata, shanghaicode):
  pass 

def martinmulti(code):
 broker = backtesting(200000,'20200101', '20201231')
 #获取股票数据
 metadata = pd.read_csv(datapath + code)
 data = np.array(metadata['close'])
 exdata = np.array(metadata['pre_close'])
 everyChange = np.array(metadata['change'])
 date = metadata['trade_date'].values
 everyChange = everyChange/data
 #开始回测
 broker.startbackmartin(data, exdata, everyChange, date)
 dicttemp = {'股票代码': code,'终止现金': broker.cash}
 return dicttemp

cashlist = pd.DataFrame(columns= ['股票代码','终止现金'])
for code in datalist:
 datatemp = martinmulti(code)
 cashlist = cashlist.append(datatemp,ignore_index=True)

cashlist.mean()
Out[12]: 
终止现金 208279.115166

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.style.use('ggplot')
plt.title("盈利分布(万元)")
bins = []
for i in range(10000, 600000, 10000):
 bins.append(i)
plt.hist(cashlist['终止现金'],bins = bins)
plt.axvline(x = cashlist.mean().values,ls="-",c="green")#添加垂直直线