import pp
#设置并行计算
ppservers = ()
job_server = pp.Server(ppservers=ppservers)
job_server.get_ncpus()
def myfunction(……):
……
return(myresult)
#获取全部的Access数据文件
files=os.listdir("C:/")
#开启并行计算
jobs = [(input, job_server.submit(myfunction,(input,), (), ("pypyodbc","pandas","numpy","datetime","os"))) for input in files]
#获取并行计算的结果
for input, job in jobs:
temp=job()
#合成数据框
frames=[pandas.DataFrame(job()) for input, job in jobs]
finalresult=pandas.concat(frames)
#设置并行计算
ppservers = ()
job_server = pp.Server(ppservers=ppservers)
job_server.get_ncpus()
def myfunction(……):
……
return(myresult)
#获取全部的Access数据文件
files=os.listdir("C:/")
#开启并行计算
jobs = [(input, job_server.submit(myfunction,(input,), (), ("pypyodbc","pandas","numpy","datetime","os"))) for input in files]
#获取并行计算的结果
for input, job in jobs:
temp=job()
#合成数据框
frames=[pandas.DataFrame(job()) for input, job in jobs]
finalresult=pandas.concat(frames)