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并发，通过线程和任务之间互相切换的方式实现，但同一时刻，只允许有一个线程或任务执行。而并行，则是指多个进程同时执行。
并发通常用于 I/O 操作频繁的场景，而并行则适用于 CPU heavy 的场景。
例：
import concurrent.futures
import requests
import threading
import time
def download_one(url):
resp = requests.get(url)
print('Read {} from {}'.format(len(resp.content), url))
def download_all(sites):
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
executor.map(download_one, sites)
def main():
sites = [
'https://en.wikipedia.org/wiki/Portal:Arts',
'https://en.wikipedia.org/wiki/Portal:History',
'https://en.wikipedia.org/wiki/Portal:Society',
'https://en.wikipedia.org/wiki/Portal:Biography',
'https://en.wikipedia.org/wiki/Portal:Mathematics',
'https://en.wikipedia.org/wiki/Portal:Technology',
'https://en.wikipedia.org/wiki/Portal:Geography',
'https://en.wikipedia.org/wiki/Portal:Science',
'https://en.wikipedia.org/wiki/Computer_science',
'https://en.wikipedia.org/wiki/Python_(programming_language)',
'https://en.wikipedia.org/wiki/Java_(programming_language)',
'https://en.wikipedia.org/wiki/PHP',
'https://en.wikipedia.org/wiki/Node.js',
'https://en.wikipedia.org/wiki/The_C_Programming_Language',
'https://en.wikipedia.org/wiki/Go_(programming_language)'
]
start_time = time.perf_counter()
download_all(sites)
end_time = time.perf_counter()
print('Download {} sites in {} seconds'.format(len(sites), end_time - start_time))
if __name__ == '__main__':
main()
Read 151021 from https://en.wikipedia.org/wiki/Portal:Mathematics
Read 129886 from https://en.wikipedia.org/wiki/Portal:Arts
Read 107637 from https://en.wikipedia.org/wiki/Portal:Biography
Read 224118 from https://en.wikipedia.org/wiki/Portal:Society
Read 184343 from https://en.wikipedia.org/wiki/Portal:History
Read 167923 from https://en.wikipedia.org/wiki/Portal:Geography
Read 157811 from https://en.wikipedia.org/wiki/Portal:Technology
Read 91533 from https://en.wikipedia.org/wiki/Portal:Science
Read 321352 from https://en.wikipedia.org/wiki/Computer_science
Read 391905 from https://en.wikipedia.org/wiki/Python_(programming_language)
Read 180298 from https://en.wikipedia.org/wiki/Node.js
Read 56765 from https://en.wikipedia.org/wiki/The_C_Programming_Language
Read 468461 from https://en.wikipedia.org/wiki/PHP
Read 321417 from https://en.wikipedia.org/wiki/Java_(programming_language)
Read 324039 from https://en.wikipedia.org/wiki/Go_(programming_language)
Download 15 sites in 0.19936635800002023 seconds
多线程版本和单线程版的主要区别在：
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
executor.map(download_one, sites)
这里创建了一个线程池，总共有 5 个线程可以分配使用。executer.map() 与 Python 内置的 map() 函数类似，表示对 sites 中的每一个元素，并发地调用函数 download_one()。
并行：
with futures.ThreadPoolExecutor(workers) as executor
=>
with futures.ProcessPoolExecutor() as executor:
函数 ProcessPoolExecutor() 表示创建进程池，使用多个进程并行的执行程序。不过，这里通常省略参数 workers，因为系统会自动返回 CPU 的数量作为可以调用的进程数。
Future
Python 中的 Futures 模块，位于 concurrent.futures 和 asyncio 中，它们都表示带有延迟的操作。
Futures 会将处于等待状态的操作包裹起来放到队列中，这些操作的状态随时可以查询，当然，它们的结果或是异常，也能够在操作完成后被获取。
通常来说，作为用户，我们不用考虑如何去创建 Futures，这些 Futures 底层都会帮我们处理好。我们要做的，实际上是去 schedule 这些 Futures 的执行。比如，Futures 中的 Executor 类，当执行 executor.submit(func) 时，它便会安排里面的 func() 函数执行，并返回创建好的 future 实例，以便之后查询调用。
Futures 中的方法 done()，表示相对应的操作是否完成——True 表示完成，False 表示没有完成。不过，要注意，done() 是 non-blocking 的，会立即返回结果。相对应的 add_done_callback(fn)，则表示 Futures 完成后，相对应的参数函数 fn，会被通知并执行调用。
Futures 中还有一个重要的函数 result()，它表示当 future 完成后，返回其对应的结果或异常。而 as_completed(fs)，则是针对给定的 future 迭代器 fs，在其完成后，返回完成后的迭代器。所以，上述例子也可以写成下面的形式：
import concurrent.futures
import requests
import time
def download_one(url):
resp = requests.get(url)
print('Read {} from {}'.format(len(resp.content), url))
def download_all(sites):
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
to_do = []
for site in sites:
future = executor.submit(download_one, site)
to_do.append(future)
for future in concurrent.futures.as_completed(to_do):
future.result()
def main():
sites = [
'https://en.wikipedia.org/wiki/Portal:Arts',
'https://en.wikipedia.org/wiki/Portal:History',
'https://en.wikipedia.org/wiki/Portal:Society',
'https://en.wikipedia.org/wiki/Portal:Biography',
'https://en.wikipedia.org/wiki/Portal:Mathematics',
'https://en.wikipedia.org/wiki/Portal:Technology',
'https://en.wikipedia.org/wiki/Portal:Geography',
'https://en.wikipedia.org/wiki/Portal:Science',
'https://en.wikipedia.org/wiki/Computer_science',
'https://en.wikipedia.org/wiki/Python_(programming_language)',
'https://en.wikipedia.org/wiki/Java_(programming_language)',
'https://en.wikipedia.org/wiki/PHP',
'https://en.wikipedia.org/wiki/Node.js',
'https://en.wikipedia.org/wiki/The_C_Programming_Language',
'https://en.wikipedia.org/wiki/Go_(programming_language)'
]
start_time = time.perf_counter()
download_all(sites)
end_time = time.perf_counter()
print('Download {} sites in {} seconds'.format(len(sites), end_time - start_time))
if __name__ == '__main__':
main()
Read 129886 from https://en.wikipedia.org/wiki/Portal:Arts
Read 107634 from https://en.wikipedia.org/wiki/Portal:Biography
Read 224118 from https://en.wikipedia.org/wiki/Portal:Society
Read 158984 from https://en.wikipedia.org/wiki/Portal:Mathematics
Read 184343 from https://en.wikipedia.org/wiki/Portal:History
Read 157949 from https://en.wikipedia.org/wiki/Portal:Technology
Read 167923 from https://en.wikipedia.org/wiki/Portal:Geography
Read 94228 from https://en.wikipedia.org/wiki/Portal:Science
Read 391905 from https://en.wikipedia.org/wiki/Python_(programming_language)
Read 321352 from https://en.wikipedia.org/wiki/Computer_science
Read 180298 from https://en.wikipedia.org/wiki/Node.js
Read 321417 from https://en.wikipedia.org/wiki/Java_(programming_language)
Read 468421 from https://en.wikipedia.org/wiki/PHP
Read 56765 from https://en.wikipedia.org/wiki/The_C_Programming_Language
Read 324039 from https://en.wikipedia.org/wiki/Go_(programming_language)
Download 15 sites in 0.21698231499976828 seconds
这里首先调用 executor.submit()，将下载每一个网站的内容都放进 future 队列 to_do，等待执行。然后是 as_completed() 函数，在 future 完成后，便输出结果。
不过，这里要注意，future 列表中每个 future 完成的顺序，和它在列表中的顺序并不一定完全一致。到底哪个先完成、哪个后完成，取决于系统的调度和每个 future 的执行时间。
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