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Python3での非同期処理まとめ

Last updated at Posted at 2017-11-07

1.シンプルなパターン


import asyncio

# 時間がかかる処理を含む関数
async def compute(x, y):
    print("Compute %s + %s ..." % (x, y))
    # 時間がかかる処理にはawaitつける
    await asyncio.sleep(1.0)
    return x + y

async def print_sum(x, y):
    result = await compute(x, y)
    print("%s + %s = %s" % (x, y, result))

loop = asyncio.get_event_loop()
# async関数の実行
loop.run_until_complete(print_sum(1, 2))

結果
Compute 1 + 2 ...
1 + 2 = 3

2.並列で実行するパターン


import asyncio

# 時間がかかる処理を含む関数
async def factorial(name, number):
    f = 1
    for i in range(2, number+1):
        print("Task %s: Compute factorial(%s)..." % (name, i))
        await asyncio.sleep(1)
        f *= i
        
    print("Task %s: factorial(%s) = %s" % (name, number, f))

loop = asyncio.get_event_loop()
# 並列で実行 -> tupleで返す
result = loop.run_until_complete(asyncio.gather(
    factorial("A", 2),
    factorial("B", 3),
    factorial("C", 4),
))

結果
Task C: Compute factorial(2)...
Task B: Compute factorial(2)...
Task A: Compute factorial(2)...
Task C: Compute factorial(3)...
Task B: Compute factorial(3)...
Task A: factorial(2) = 2
Task C: Compute factorial(4)...
Task B: factorial(3) = 6
Task C: factorial(4) = 24

TaskA,B,Cが並列で実行されていることがわかる。

3.ちょっと綺麗に

gatherの中を綺麗に表現するためには以下のようにできる。やっていることは2と全く同じ

loop = asyncio.get_event_loop()
name_number_list = [("A",2),("B", 3),("C", 4)]

parallel_tasks = tuple(map(lambda name_num: factorial(*name_num), name_number_list))
    
result = loop.run_until_complete(asyncio.gather(*parallel_tasks))

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