Python几种并发实现方案的性能比较
#!/Library/Frameworks/Python.framework/Versions/2.5/bin/python
# encoding: utf-8
import sys, time
import thread
SLEEP_TIME = 0.0001
def run_benchmark(n, m):
# print(">> Python 2.5.1, stackless 3.1b3 here (N=%d, M=%d)!\n" % (n, m))
locks = [thread.allocate_lock() for i in xrange(n)]
firstP = cin = []
cin_lock_id = 0
for s in xrange(1, n):
seqn = s
cout = []
cout_lock_id = s
# print("*> s = %d" % (seqn, ))
thread.start_new_thread(loop, (seqn, locks, cin, cin_lock_id, cout, cout_lock_id))
cin = cout
cin_lock_id = cout_lock_id
else:
seqn = s+1
# print("$> s = %d" % (seqn, ))
thread.start_new_thread(mloop, (seqn, locks, cin, cin_lock_id))
for r in xrange(m-1, -1, -1):
# print("+ sending Msg# %d" % r)
lock = locks[0]
lock.acquire()
firstP.append(r)
lock.release()
time.sleep(SLEEP_TIME)
try:
while True:
time.sleep(SLEEP_TIME)
except:
pass
def loop(s, locks, cin, cin_lock_id, cout, cout_lock_id):
while True:
lock = locks[cin_lock_id]
lock.acquire()
if len(cin) > 0:
r = cin.pop(0)
lock.release()
else:
&n
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import Queue, threading, sys
from threading import Thread
import time,urllib
# working thread
class Worker(Thread):
worker_count = 0
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Thread.__init__( self, **kwds ) ......
