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  • Python gevent学习笔记－2

    在上一篇里面介绍了gevent的最主要的功能，先来来了解一下gevent里面一些更加高级的功能。

    事件

    事件是一种可以让greenlet进行异步通信的手段。

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    import gevent
    from gevent.event import AsyncResult
     
    a = AsyncResult()
     
    def setter():
        """
        After 3 seconds set wake all threads waiting on the value of
        a.
        """
        gevent.sleep(3)
        a.set()
     
    def waiter():
        """
        After 3 seconds the get call will unblock.
        """
        a.get() # blocking
        print 'I live!'
     
    gevent.joinall([
        gevent.spawn(setter),
        gevent.spawn(waiter),
    ])

    AsyncResult 是 event对象的扩展能够让你来发送值并且带有一定延迟。这种功能被成为feature或deferred，当它拿到一个未来的值的引用时，能够在任意安排好的时间内让它起作用。

    队列

    队列是一个有序的数据集合，通常有 put/get 的操作，这样能让队列在有在有greenletJ进行操作的时候能够进行安全的管理。

    例如，如果greenlet从队列中取出了一项数据，那么这份数据就不能被另一个greenlet取出。

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    import gevent
    from gevent.queue import Queue
     
    tasks = Queue()
     
    def worker(n):
        while not tasks.empty():
            task = tasks.get()
            print('Worker %s got task %s' % (n, task))
            gevent.sleep(0)
     
        print('Quitting time!')
     
    def boss():
        for i in xrange(1,25):
            tasks.put_nowait(i)
     
    gevent.spawn(boss).join()
     
    gevent.joinall([
        gevent.spawn(worker, 'steve'),
        gevent.spawn(worker, 'john'),
        gevent.spawn(worker, 'nancy'),
    ])

    执行的结果如下：

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    Worker steve got task 1
    Worker john got task 2
    Worker nancy got task 3
    Worker steve got task 4
    Worker nancy got task 5
    Worker john got task 6
    Worker steve got task 7
    Worker john got task 8
    Worker nancy got task 9
    Worker steve got task 10
    Worker nancy got task 11
    Worker john got task 12
    Worker steve got task 13
    Worker john got task 14
    Worker nancy got task 15
    Worker steve got task 16
    Worker nancy got task 17
    Worker john got task 18
    Worker steve got task 19
    Worker john got task 20
    Worker nancy got task 21
    Worker steve got task 22
    Worker nancy got task 23
    Worker john got task 24
    Quitting time!
    Quitting time!
    Quitting time!

    队列的 put/get 操作在需要的情况下也可以阻塞程序的执行。

    put 和 get 操作都有非阻塞的副本，就是 put_nowait 和 get_nowait。

    在下面代码的例子里，运行一个叫boss的方法，同时运行worker方法，并且对队列有一个限制：队列的子项不能超过3个。这个限制意味着 put 操作在队列里面有足够空间之前会阻塞。相反，如果队列里没有任何子项，get操作会阻塞，同时也需要超时的机制，当一个操作在阻塞超过一定时间后会抛出异常。

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    import gevent
    from gevent.queue import Queue, Empty
     
    tasks = Queue(maxsize=3)
     
    def worker(n):
        try:
            while True:
                task = tasks.get(timeout=1) # decrements queue size by 1
                print('Worker %s got task %s' % (n, task))
                gevent.sleep(0)
        except Empty:
            print('Quitting time!')
     
    def boss():
        """
        Boss will wait to hand out work until a individual worker is
        free since the maxsize of the task queue is 3.
        """
     
        for i in xrange(1,10):
            tasks.put(i)
        print('Assigned all work in iteration 1')
     
        for i in xrange(10,20):
            tasks.put(i)
        print('Assigned all work in iteration 2')
     
    gevent.joinall([
        gevent.spawn(boss),
        gevent.spawn(worker, 'steve'),
        gevent.spawn(worker, 'john'),
        gevent.spawn(worker, 'bob'),
    ])

    代码的执行结果如下：

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    Worker steve got task 1
    Worker john got task 2
    Worker bob got task 3
    Worker steve got task 4
    Worker bob got task 5
    Worker john got task 6
    Assigned all work in iteration 1
    Worker steve got task 7
    Worker john got task 8
    Worker bob got task 9
    Worker steve got task 10
    Worker bob got task 11
    Worker john got task 12
    Worker steve got task 13
    Worker john got task 14
    Worker bob got task 15
    Worker steve got task 16
    Worker bob got task 17
    Worker john got task 18
    Assigned all work in iteration 2
    Worker steve got task 19
    Quitting time!
    Quitting time!
    Quitting time!

    组和池

    组是一个由greenlet组成的集合，并且能够被统一管理。

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    import gevent
    from gevent.pool import Group
     
    def talk(msg):
        for i in xrange(3):
            print(msg)
     
    g1 = gevent.spawn(talk, 'bar')
    g2 = gevent.spawn(talk, 'foo')
    g3 = gevent.spawn(talk, 'fizz')
     
    group = Group()
    group.add(g1)
    group.add(g2)
    group.join()
     
    group.add(g3)
    group.join()

    这在管理一组异步任务的时候会很有用。

    Group还提供了一个API来分配成组的greenlet任务，并且通过不同的方法来获取结果。

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    import gevent
    from gevent import getcurrent
    from gevent.pool import Group
     
    group = Group()
     
    def hello_from(n):
        print('Size of group', len(group))
        print('Hello from Greenlet %s' % id(getcurrent()))
     
    group.map(hello_from, xrange(3))
     
    def intensive(n):
        gevent.sleep(3 - n)
        return 'task', n
     
    print('Ordered')
     
    ogroup = Group()
    for i in ogroup.imap(intensive, xrange(3)):
        print(i)
     
    print('Unordered')
     
    igroup = Group()
    for i in igroup.imap_unordered(intensive, xrange(3)):
        print(i)

    执行结果如下：

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    Size of group 3
    Hello from Greenlet 10769424
    Size of group 3
    Hello from Greenlet 10770544
    Size of group 3
    Hello from Greenlet 10772304
    Ordered
    ('task', 0)
    ('task', 1)
    ('task', 2)
    Unordered
    ('task', 2)
    ('task', 1)
    ('task', 0)

    池是用来处理当拥有动态数量的greenlet需要进行并发管理（限制并发数）时使用的。

    这在处理大量的网络和IO操作的时候是非常需要的。

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    import gevent
    from gevent.pool import Pool
     
    pool = Pool(2)
     
    def hello_from(n):
        print('Size of pool', len(pool))
     
    pool.map(hello_from, xrange(3))
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    Size of pool 2
    Size of pool 2
    Size of pool 1

    经常在创建gevent驱动程序的时候，整个服务需要围绕一个池的结构来执行。

    锁和信号量

    信号量是低级别的同步机制，能够让greenlet在执行的时候互相协调并且限制其并发数。信号量暴露了两个方法，acquire 和 release。如果信号量范围变成0，那么它会阻塞住直到另一个greenlet释放它的获得物。

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    from gevent import sleep
    from gevent.pool import Pool
    from gevent.coros import BoundedSemaphore
     
    sem = BoundedSemaphore(2)
     
    def worker1(n):
        sem.acquire()
        print('Worker %i acquired semaphore' % n)
        sleep(0)
        sem.release()
        print('Worker %i released semaphore' % n)
     
    def worker2(n):
        with sem:
            print('Worker %i acquired semaphore' % n)
            sleep(0)
        print('Worker %i released semaphore' % n)
     
    pool = Pool()
    pool.map(worker1, xrange(0,2))
    pool.map(worker2, xrange(3,6))

    一下是代码的执行结果：

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    Worker 0 acquired semaphore
    Worker 1 acquired semaphore
    Worker 0 released semaphore
    Worker 1 released semaphore
    Worker 3 acquired semaphore
    Worker 4 acquired semaphore
    Worker 3 released semaphore
    Worker 4 released semaphore
    Worker 5 acquired semaphore
    Worker 5 released semaphore

     如果把信号量的数量限制为1那么它就成为了锁。它经常会在多个greenlet访问相同资源的时候用到。

    本地线程

    Gevent还能够让你给gevent上下文来指定那些数据是本地的。

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    import gevent
    from gevent.local import local
     
    stash = local()
     
    def f1():
        stash.x = 1
        print(stash.x)
     
    def f2():
        stash.y = 2
        print(stash.y)
     
        try:
            stash.x
        except AttributeError:
            print("x is not local to f2")
     
    g1 = gevent.spawn(f1)
    g2 = gevent.spawn(f2)
     
    gevent.joinall([g1, g2])

     以下是执行结果：

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    x is not local to f2

     很多集成了gevent的框架把HTTP的session对象存在gevent 本地线程里面。比如下面的例子：

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    from werkzeug.local import LocalProxy
    from werkzeug.wrappers import Request
    from contextlib import contextmanager
     
    from gevent.wsgi import WSGIServer
     
    _requests = local()
    request = LocalProxy(lambda: _requests.request)
     
    @contextmanager
    def sessionmanager(environ):
        _requests.request = Request(environ)
        yield
        _requests.request = None
     
    def logic():
        return "Hello " + request.remote_addr
     
    def application(environ, start_response):
        status = '200 OK'
     
        with sessionmanager(environ):
            body = logic()
     
        headers = [
            ('Content-Type', 'text/html')
        ]
     
        start_response(status, headers)
        return [body]
     
    WSGIServer(('', 8000), application).serve_forever()

     子进程

    在gevent 1.0版本中，gevent.subprocess 这个库被添加上。这个库能够让子进程相互协调地执行。

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    import gevent
    from gevent.subprocess import Popen, PIPE
     
    def cron():
        while True:
            print "cron"
            gevent.sleep(0.2)
     
    g = gevent.spawn(cron)
    sub = Popen(['sleep 1; uname'], stdout=PIPE, shell=True)
    out, err = sub.communicate()
    g.kill()
    print out.rstrip()

     执行结果：

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    cron
    cron
    cron
    cron
    cron
    Linux
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  • 原文地址：https://www.cnblogs.com/alan-babyblog/p/5393602.html
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