Slow multithreading

From my understanding, Redis-py is mostly doing network IO under the hood. Python’s GIL should not kick in for network IO. However, it looks like multithreading is as slow as single-threaded sequential version. Am I missing anything?

r = StrictRedis()

def test():
    for i in range(10000):
        key = 'mykey'+str(i)
        r.set(key, 'ibvjaiuj65s4fa4sd8ear4')
        r.get(key)
        r.delete(key)

def bench1():
    for _ in range(5):
        test() 

def bench2():  # as slow as bench 1
    ts = [threading.Thread(target=test) for i in range(5)]
    [t.start() for t in ts]
    [t.join() for t in ts]

def bench3():  # much faster, which means GIL is in play
    ts = [multiprocessing.Process(target=test) for i in range(5)]
    [t.start() for t in ts]
    [t.join() for t in ts]

[laixintao]

@LinxiFan GIL is always invoked whenever where is thread. GIL grantee there is only one thread running in Python interpreter.

You should noticed that redis in running on memory, so if you test your code in localhost, there is no networking io or file system io.

Compare to single thread, multi thread need switching(which cost), so slower than single thread.

[Grokzen]

@LinxiFan Multithreading and concurency in python is very hard and i would suggest that you dig into the talks from David Beazley has done on this topic to better understand the problem with threads/multiprocessing/async and so on. One of the better presentations he has done is this one https://www.youtube.com/watch?v=MCs5OvhV9S4 where he show code examples live and the performance of the different methods.