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eventor Build Status Gitter

使用多线程,进程以及协程实现的任务执行器,加快任务执行（针对IO密集型任务）

description

1.Eventor类,初始化参数如下:

  • threadcount: 开启多少个线程
  • taskunitcount: 每个线程处理多少任务
  • func: 实际的处理任务的函数, 自己实现
  • interval: 线程间隔
  • async: 同步异步

2.start_multi_consumer方法, 场景:模拟多个消费者(进程) 消费共享资源, 参数如下:

  • consumercount: 开启的消费者(进程)个数,默认 cput_count()
  • iterable=None: 共享资源
  • consumer_func=None: 具体的消费行为
  • beforecallback=None: 每个消费者开启之前调用
  • aftercallback=None: 每个消费者执行消费行为之后调用(仅当 arsync=True)
  • errorcallback=None: 异常回调(仅当 arsync=True)
  • async=False: 消费方式(同步or异步)
  • timeout=None: 超时时间(仅当 arsync=True)

exmaples

exmaple-1: 直接传递要处理的任务集合

>>> from eventor import Eventor
>>> elelist = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> def func(x):
....    // Get http resource and other IO waiting operations
....    return x + 10    
>>> e = Eventor(threadcount=3, taskunitcount=3, func=func, interval=1)
>>> result = e.run_with_tasklist(elelist)
>>> print(result)
[11, 12, 13, 14, 15, 16, 17, 18, 19, 20]

上述例子是开启3个线程,将任务(共有10个task)分割为每份3个task执行的, 间隔1s

exmaple-2: 处理文件和直接传递任务集合类似

>>> from eventor import Eventor
>>> file = "test/data.txt"
>>> def func(x):
....    // Get http resource and other IO waiting operations
....    return x + 10  
>>> e = Eventor(threadcount=3, taskunitcount=3, func=func, interval=1)
>>> result = e.run_with_file(file)
>>> print(result)
[11, 12, 13, 14, 15, 16, 17, 18, 19, 20]

exmaple-3: 开启 4 个进程, 每个进程打印 当前进程名以及准备消费的 共享数据 (在处理稍微比较繁琐的任务时, 可以和上面结合, 也就是 多进程 + 协程, 这样既能利用多核, 又能利用协程高效执行)

>>> from multiprocessing import cpu_count
>>> from eventor import start_multi_consumer
>>> consumer_count = 4
>>> def confunc(data):
....    print("process[{}] deal with {}".format(multiprocessing.current_process().name, data))
>>> datalist = [1, 2, 5, 3, 6, 8, 23, 'data', 232]
>>> start_multi_consumer(consumercount=consumer_count, iterable=datalist, consumer_func=confunc)
process[ForkPoolWorker-3] deal with 1
process[ForkPoolWorker-2] deal with 2
process[ForkPoolWorker-4] deal with 5
process[ForkPoolWorker-5] deal with 3
process[ForkPoolWorker-3] deal with 6
process[ForkPoolWorker-2] deal with 8
process[ForkPoolWorker-4] deal with 23
process[ForkPoolWorker-5] deal with data
process[ForkPoolWorker-3] deal with 232

Very stupid!