Python Concurrent Futures解锁并行化编程的魔法示例

from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor

# 使用ThreadPoolExecutor
with ThreadPoolExecutor() as executor:
    results = executor.map(some_function, data)

# 使用ProcessPoolExecutor
with ProcessPoolExecutor() as executor:
    results = executor.map(some_function, data)

from concurrent.futures import ThreadPoolExecutor
def some_function(data):
    # 一些耗时的操作
    return result
with ThreadPoolExecutor() as executor:
    future = executor.submit(some_function, data)
    result = future.result()

from concurrent.futures import ThreadPoolExecutor
def square(x):
    return x * x
data = [1, 2, 3, 4, 5]
with ThreadPoolExecutor() as executor:
    results = executor.map(square, data)
    for result in results:
        print(result)

from concurrent.futures import ThreadPoolExecutor, as_completed
def square(x):
    return x * x
data = [1, 2, 3, 4, 5]
with ThreadPoolExecutor() as executor:
    futures = [executor.submit(square, x) for x in data]
    for future in as_completed(futures):
        result = future.result()
        print(result)

import asyncio
from concurrent.futures import ThreadPoolExecutor
async def main():
    loop = asyncio.get_event_loop()
    with ThreadPoolExecutor() as executor:
        result = await loop.run_in_executor(executor, some_blocking_function, args)
    print(result)
asyncio.run(main())

from concurrent.futures import ThreadPoolExecutor, TimeoutError
def some_function():
    # 一些可能引发异常的操作
with ThreadPoolExecutor() as executor:
    future = executor.submit(some_function)
    try:
        result = future.result(timeout=1)
    except TimeoutError:
        print("任务超时")
    except Exception as e:
        print(f"发生错误: {e}")

from concurrent.futures import ProcessPoolExecutor
data = get_large_dataset()
with ProcessPoolExecutor() as executor:
    results = executor.map(process_data, data)

import asyncio
from concurrent.futures import ThreadPoolExecutor
async def fetch(url):
    # 异步请求数据
async def main():
    loop = asyncio.get_event_loop()
    with ThreadPoolExecutor() as executor:
        tasks = [loop.run_in_executor(executor, fetch, url) for url in urls]
        await asyncio.gather(*tasks)
asyncio.run(main())