#threadpool的内部调用参数解析
result = request.callable(*request.args, **request.kwds)
# coding:utf-8
import threadpool,time
time_list=[]
args_list1=range(1,11)
#如果要输入元组做参数,必须把元组转换成下面的形式
args_list2=[(i,None) for i in zip(range(1,11),range(1,11))]
print args_list2
[((1, 1), None), ((2, 2), None), ((3, 3), None), ((4, 4), None),
((5, 5), None), ((6, 6), None), ((7, 7), None), ((8, 8), None),
((9, 9), None), ((10, 10), None)]
#如果如果要输入字典做参数,必须把字典转换成下面的形式
args_list3=[(None,{"a":1,"b":2}),(None,{"a":3,"c":4}),(None,{"a":5,"b":6})]
#列表
def handle_func1(a):
return a
#元组
def handle_func2(*a,**b):
return a
#字典
def handle_func3(*a,**b):
return b
#回调函数,会把处理函数的结果当参数
def handle_func_callback(request,results):
time_list.append(results)
#创建连接池 ,最大连接数5
pool=threadpool.ThreadPool(5)
#处理函数handle_func*,处理函数的参数args_list*,处理函数的回调函数handle_func_callback(可以没有)
requests1=threadpool.makeRequests(handle_func1,args_list1,handle_func_callback)
requests2=threadpool.makeRequests(handle_func2,args_list2,handle_func_callback)
requests3=threadpool.makeRequests(handle_func3,args_list3,handle_func_callback)
#是将所有要运行多线程的请求扔进线程池
[pool.putRequest(i) for i in requests1+requests2+requests3]
#连接池挂起,第四行是等待所有的线程完成工作后退出
pool.wait()
print time_list
#[1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
(1, 1), (2, 2), (3, 3), (4, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 10),
{'a': 1, 'b': 2}, {'a': 3, 'c': 4}, {'a': 5, 'b': 6}]
import urllib2
from multiprocessing.dummy import Pool as ThreadPool
def handle_func1(a):
return a
pool = ThreadPool(4)
#对range(11)的每一个数调用handle_func1,返回结果集
results = pool.map(handle_func1, range(11))
print results
pool.close()
pool.join()
转载于:https://my.oschina.net/u/1458120/blog/640046