基本思路如下:
请求到views1
并首先返回用户名。在views1完成后,do_something_else
完成了一些繁重的工作。您可以将此视为创建新用户,但必须对后台进行大量检查。
def views1(..):
username = get_uername(...)
return username
from lib import do_something_else
def do_something_else(...):
// do heavy stuff here
gevent.joinall([
gevent.spawn(views1, parmeter1, parmeter2, ...),
gevent.spawn(do_something_else, parmeter1, parmeter2, ...)
])
问题是我不认为根据我的日志记录调用了do_something_else
。
我阅读了教程,但我不知道在哪里放置gevent.sleep(0)
。我不想要阻止。我希望用户立即看到用户名,让do_something_else
在后台运行。
有什么想法吗?
答案 0 :(得分:3)
重要的是要了解您需要将“重载”处理分离为线程池[1]。
在gevent线程中发生的每个处理(并且每个本机线程可以有一个gevent HUB)必须只关注处理网络请求和发送响应。
from gevent import spawn, run
from gevent.threadpool import ThreadPool
from time import sleep as heavy_load, time as now
class Globals:
jobs = 4
index = 0
greenlets = []
pool = ThreadPool(3) # change size of the pool appropriately
start = now()
def get_uername():
heavy_load(0.1)
Globals.index += 1
return "Alex {0}".format(Globals.index)
def do_something_else(username):
heavy_load(2.0)
print "Heavy job done for", username, now() - start
def views1():
"a request comes to views1 and it first returns the username"
username = get_uername()
## There is some heavy job separate done by do_something_else right after views1 is done
Globals.greenlets.append(
Globals.pool.spawn(do_something_else, username)
)
# return username
print "Returned requested username", username, now() - start
if __name__ == '__main__':
## simulate clients
for job_index in xrange(Globals.jobs):
Globals.greenlets.append( spawn(views1) )
## wait for all tasks to complete
# for greenlet in Globals.greenlets:
# try:
# greenlet.join()
# except AttributeError, e:
# greenlet.get()
run()
print "Test done", now() - start
这是测试的输出:
python threadpool_test.py
Returned requested username Alex 1 0.101000070572
Returned requested username Alex 2 0.201999902725
Returned requested username Alex 3 0.302999973297
Returned requested username Alex 4 0.40299987793
Heavy job done for Alex 1 2.10100007057
Heavy job done for Alex 2 2.2009999752
Heavy job done for Alex 3 2.3029999733
Heavy job done for Alex 4 4.10299992561
Test done 4.10500001907
注意所有请求是如何首先完成的并行do_something_else
任务是以3个批量完成的。
当没有使用ThreadPool时,每个请求都会花费do_something_else
引入的额外时间,而不是gevent必须提供的asynchronous programming
。在这种情况下,输出将如下所示:
Heavy job done for Alex 1 2.10100007057
Returned requested username Alex 1 2.10100007057
Heavy job done for Alex 2 4.2009999752
Returned requested username Alex 2 4.20199990273
Heavy job done for Alex 3 6.30200004578
Returned requested username Alex 3 6.3029999733
Heavy job done for Alex 4 8.40299987793
Returned requested username Alex 4 8.40400004387
Test done 8.40400004387
注意第4个请求是如何在8.4秒内完成的,而不是异步处理的0.4秒。
[1] http://code.google.com/p/gevent/source/browse/examples/threadpool.py