Python標準モジュール--concurrent.futuresモジュール(ThreadPoolExecutor:スレッドプール、非同期呼び出し、ProcessPoolExecutor:プロセスプール、非同期呼び出し)

目次
ProcessPoolExecutor:プロセスプール
ThreadPoolExecutor:スレッドプール
mapの使い方
コールバック関数
https://docs.python.org/dev/library/concurrent.futures.html
1.concurrent.futuresモジュールは高度にカプセル化された非同期呼び出しインターフェースThreadPoolExecutor:スレッドプール、非同期呼び出しProcessPoolExecutor:プロセスプール、非同期呼び出しBoth implement the same interface、which is defined by the abstract Executor classを提供する.
2基本方法●submit(fn,*args,**kwargs)非同期コミットタスク
●map(func,*iterables,timeout=None,chunksize=1)forサイクルsubmitの動作に取って代わる
●shutdown(wait=True)はプロセスプールのpoolに相当する.close()+pool.join()はwait=Trueを操作し、プール内のすべてのタスクの実行が完了してリソースが回収されるのを待ってからwait=Falseを継続し、すぐに戻ります.プール内のタスクの実行が完了するのを待つことはありませんが、waitパラメータの値にかかわらず、プログラム全体はすべてのタスクの実行が完了するまでsubmitとmapがshutdownの前に必要です.
●result(timeout=None)取得結果
●add_done_callback(fn)コールバック関数
ProcessPoolExecutor:プロセスプール

#  
The ProcessPoolExecutor class is an Executor subclass that uses a pool of processes to execute calls asynchronously. ProcessPoolExecutor uses the multiprocessing module, which allows it to side-step the Global Interpreter Lock but also means that only picklable objects can be executed and returned.

class concurrent.futures.ProcessPoolExecutor(max_workers=None, mp_context=None)
An Executor subclass that executes calls asynchronously using a pool of at most max_workers processes. If max_workers is None or not given, it will default to the number of processors on the machine. If max_workers is lower or equal to 0, then a ValueError will be raised.


#  
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor

import os,time,random
def task(n):
    print('%s is runing' %os.getpid())
    time.sleep(random.randint(1,3))
    return n**2

if __name__ == '__main__':

    executor=ProcessPoolExecutor(max_workers=3)

    futures=[]
    for i in range(11):
        future=executor.submit(task,i)
        futures.append(future)
    executor.shutdown(True)
    print('+++>')
    for future in futures:
        print(future.result())

ThreadPoolExecutor:スレッドプール

#  
ThreadPoolExecutor is an Executor subclass that uses a pool of threads to execute calls asynchronously.
class concurrent.futures.ThreadPoolExecutor(max_workers=None, thread_name_prefix='')
An Executor subclass that uses a pool of at most max_workers threads to execute calls asynchronously.

Changed in version 3.5: If max_workers is None or not given, it will default to the number of processors on the machine, multiplied by 5, assuming that ThreadPoolExecutor is often used to overlap I/O instead of CPU work and the number of workers should be higher than the number of workers for ProcessPoolExecutor.

New in version 3.6: The thread_name_prefix argument was added to allow users to control the threading.Thread names for worker threads created by the pool for easier debugging.

#  
 ProcessPoolExecutor  

ThreadPoolExecutor

mapの使い方

from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor

import os,time,random
def task(n):
    print('%s is runing' %os.getpid())
    time.sleep(random.randint(1,3))
    return n**2

if __name__ == '__main__':

    executor=ThreadPoolExecutor(max_workers=3)

    # for i in range(11):
    #     future=executor.submit(task,i)

    executor.map(task,range(1,12)) #map   for+submit

コールバック関数

from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
from multiprocessing import Pool
import requests
import json
import os

def get_page(url):
    print(' get %s' %(os.getpid(),url))
    respone=requests.get(url)
    if respone.status_code == 200:
        return {'url':url,'text':respone.text}

def parse_page(res):
    res=res.result()
    print(' parse %s' %(os.getpid(),res['url']))
    parse_res='url: size:[%s]
' %(res['url'],len(res['text']))
    with open('db.txt','a') as f:
        f.write(parse_res)


if __name__ == '__main__':
    urls=[
        'https://www.baidu.com',
        'https://www.python.org',
        'https://www.openstack.org',
        'https://help.github.com/',
        'http://www.sina.com.cn/'
    ]

    # p=Pool(3)
    # for url in urls:
    #     p.apply_async(get_page,args=(url,),callback=pasrse_page)
    # p.close()
    # p.join()

    p=ProcessPoolExecutor(3)
    for url in urls:
        p.submit(get_page,url).add_done_callback(parse_page) #parse_page      future  obj，   obj.result()