Python中并发future模块的介绍（代码）
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本篇文章给大家带来的内容是关于Python中并发future模块的介绍（代码） ，有一定的参考价值，有需要的朋友可以参考一下，希望对你有所帮助。concurrent.futures模块
该模块主要特色在于ThreadPoolExecutor 和 ProcessPoolExecutor 类，这两个类都继承自concurrent.futures._base.Executor类，它们实现的接口能分别在不同的线程或进程中执行可调用的对象，它们都在内部维护着一个工作线程或者进程池。
ThreadPoolExecutor 和 ProcessPoolExecutor 类是高级类，大部分情况下只要学会使用即可，无需关注其实现细节。
####ProcessPoolExecutor 类
>class ThreadPoolExecutor(concurrent.futures._base.Executor) >| This is an abstract base class for concrete asynchronous executors. >| Method resolution order: >| ThreadPoolExecutor | concurrent.futures._base.Executor | builtins.object | | Methods defined here: | | init(self, max_workers=None, thread_name_prefix='') | Initializes a new ThreadPoolExecutor instance. | | Args: | max_workers: The maximum number of threads that can be used to | execute the given calls. | thread_name_prefix: An optional name prefix to give our threads. | | shutdown(self, wait=True) | Clean-up the resources associated with the Executor. | | It is safe to call this method several times. Otherwise, no other | methods can be called after this one. | | Args: | wait: If True then shutdown will not return until all running | futures have finished executing and the resources used by the | executor have been reclaimed. | | submit(self, fn, *args, **kwargs) | Submits a callable to be executed with the given arguments. | | Schedules the callable to be executed as fn(*args, **kwargs) and returns | a Future instance representing the execution of the callable. | | Returns: | A Future representing the given call. | | ---------------------------------------------------------------------- | Methods inherited from concurrent.futures._base.Executor: | | enter(self) | | exit(self, exc_type, exc_val, exc_tb) | | map(self, fn, *iterables, timeout=None, chunksize=1) | Returns an iterator equivalent to map(fn, iter). | | Args: | fn: A callable that will take as many arguments as there are | passed iterables. | timeout: The maximum number of seconds to wait. If None, then there | is no limit on the wait time. | chunksize: The size of the chunks the iterable will be broken into | before being passed to a child process. This argument is only | used by ProcessPoolExecutor; it is ignored by | ThreadPoolExecutor. | | Returns: | An iterator equivalent to: map(func, *iterables) but the calls may | be evaluated out-of-order. | | Raises: | TimeoutError: If the entire result iterator could not be generated | before the given timeout. | Exception: If fn(*args) raises for any values.
初始化可以指定一个最大进程数作为其参数 max_workers 的值，该值一般无需指定，默认为当前运行机器的核心数，可以由os.cpu_count()获取；类中含有方法：
map()方法，与python内置方法map() 功能类似，也就是映射，参数为：
一个可调用函数 fn
一个迭代器 iterables
超时时长 timeout
块数chuncksize 如果大于1, 迭代器会被分块处理
---->> 该函数有一个特性：其返回结果与调用开始的顺序是一致的；在调用过程中不会产生阻塞，也就是说可能前者被调用执行结束之前，后者被调用已经执行结束了。
如果一定要获取到所有结果后再处理，可以选择采用submit()方法和futures.as_completed函数结合使用。
shutdown()方法，清理所有与当前执行器（executor)相关的资源
submit() 方法，提交一个可调用对象给fn使用
从concurrent.futures._base.Executor继承了__enter__() 和 __exit__()方法，这意味着ProcessPoolExecutor 对象可以用于with 语句。
from concurrent import futures
with futures.ProcessPoolExecutor(max_works=3) as executor:
executor.map()ThreadPoolExecutor类
class ThreadPoolExecutor(concurrent.futures._base.Executor) | This is an abstract base class for concrete asynchronous executors. | | Method resolution order: | ThreadPoolExecutor | concurrent.futures._base.Executor | builtins.object | | Methods defined here: | | init(self, max_workers=None, thread_name_prefix='') | Initializes a new ThreadPoolExecutor instance. | | Args: | max_workers: The maximum number of threads that can be used to | execute the given calls. | thread_name_prefix: An optional name prefix to give our threads. | | shutdown(self, wait=True) | Clean-up the resources associated with the Executor. | | It is safe to call this method several times. Otherwise, no other | methods can be called after this one. | | Args: | wait: If True then shutdown will not return until all running | futures have finished executing and the resources used by the | executor have been reclaimed. | | submit(self, fn, *args, **kwargs) | Submits a callable to be executed with the given arguments. | | Schedules the callable to be executed as fn(*args, **kwargs) and returns | a Future instance representing the execution of the callable. | | Returns: | A Future representing the given call. | | ---------------------------------------------------------------------- | Methods inherited from concurrent.futures._base.Executor: | | enter(self) | | exit(self, exc_type, exc_val, exc_tb) | | map(self, fn, *iterables, timeout=None, chunksize=1) | Returns an iterator equivalent to map(fn, iter). | | Args: | fn: A callable that will take as many arguments as there are | passed iterables. | timeout: The maximum number of seconds to wait. If None, then there | is no limit on the wait time. | chunksize: The size of the chunks the iterable will be broken into | before being passed to a child process. This argument is only | used by ProcessPoolExecutor; it is ignored by | ThreadPoolExecutor. | | Returns: | An iterator equivalent to: map(func, *iterables) but the calls may | be evaluated out-of-order. | | Raises: | TimeoutError: If the entire result iterator could not be generated | before the given timeout. | Exception: If fn(*args) raises for any values.
与ProcessPoolExecutor 类十分相似，只不过一个是处理进程，一个是处理线程，可根据实际需要选择。
示例
from time import sleep, strftime
from concurrent import futures
def display(*args):
print(strftime('[%H:%M:%S]'), end="")
print(*args)
def loiter(n):
msg = '{}loiter({}): doing nothing for {}s'
display(msg.format('\t'*n, n, n))
sleep(n)
msg = '{}loiter({}): done.'
display(msg.format('\t'*n, n))
return n*10
def main():
display('Script starting')
executor = futures.ThreadPoolExecutor(max_workers=3)
results = executor.map(loiter, range(5))
display('results:', results)
display('Waiting for inpidual results:')
for i, result in enumerate(results):
display('result {} : {}'.format(i, result))
if __name__ == '__main__':
main()运行结果：
[20:32:12]Script starting [20:32:12]loiter(0): doing nothing for 0s [20:32:12]loiter(0): done. [20:32:12] loiter(1): doing nothing for 1s [20:32:12] loiter(2): doing nothing for 2s [20:32:12]results: <generator object Executor.map.<locals>.result_iterator at 0x00000246DB21BC50> [20:32:12]Waiting for inpidual results: [20:32:12] loiter(3): doing nothing for 3s [20:32:12]result 0 : 0 [20:32:13] loiter(1): done. [20:32:13] loiter(4): doing nothing for 4s [20:32:13]result 1 : 10 [20:32:14] loiter(2): done. [20:32:14]result 2 : 20 [20:32:15] loiter(3): done. [20:32:15]result 3 : 30 [20:32:17] loiter(4): done. [20:32:17]result 4 : 40
不同机器运行结果可能不同。
示例中设置max_workers=3，所以代码一开始运行，则有三个对象（0,1,2）被执行loiter() 操作; 三秒后，对象0运行结束，得到结果result 0之后，对象3才开始被执行，同理，对象4的执行时间在对象1执行结果result 1打印结束之后。
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