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python concurrency

python多线程多进程

因为GIL的原因，多线程只能并发的跑，不能并行，多进程可多核并行

import threading
threads = []
for i in range(4):
    thread = threading.Thread(target=task, args=(param,))
    thread.start()
    threads.append(thread)
for thread in threads:
    thread.join()

线程（进程）池

from concurrent.futures import ThreadPoolExecutor
# from concurrent.futures import ProcessPoolExecutor

with ThreadPoolExecutor(max_workers=2) as executor:
    #task1 = executor.submit(someTask, (param1, param2))
    tasks = executor.map(someTask, params)
    results = [task for task in tasks]

using as_completed

from concurrent.futures import as_completed
...
tasks = [executor.submit(checkStatus, (url)) for url in urls]
for result in as_completed(tasks)
    print(result)

chaining callbacks

future = executor.submit(task, (param))
future.add_done_callback(task_done)
future.add_done_callback(second_task_done)

future object

future_obj.result(timeout=None)
future_obj.running()
future_obj.cancel()
future_obj.exception()
future_obj.done()

Multiprocessing

Multiprocessing pools 比 ProcessPoolExecutor 更强大

from multiprocessing import Pool
with Pool(processes=2, maxtasksperchild=2) as p:
    p.apply(...)
    #p.apply_async(...)
    #p.map(...)
    #p.map_async(...)
    # return iterable
    #p.imap(...)
    # allow to submit a list of tuples(multi variables)
    #p.starmap(...)
    #p.starmap_async(...)

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