我有下面的代码,从数据库(read_db)读取数据,并将数据写入拼图文件(data.to_parquet)。这两个I/O操作都需要一段时间才能运行。
def main():
while id < 1000:
logging.info(f'reading - id: {id}')
data = read_db(id) # returns a dataframe
logging.info(f'saving - id: {id}')
data.to_parquet(f'{id}.parquet')
logging.info(f'saved - id: {id}')
id += 1它很慢,所以我希望同时运行read_db(n+1)和to_parquet(n)。我需要让id的每一步都按顺序完成(read_db(n+1)需要在read_db(n)之后运行,data.to_parquet(n+1)需要在data.to_parquet(n)之后运行)。下面是异步版本
def async_wrap(f):
@wraps(f)
async def run(*args, loop=None, executor=None, **kwargs):
if loop is None:
loop = asyncio.get_event_loop()
p = partial(f, *args, **kwargs)
return await loop.run_in_executor(executor, p)
return run
async def main():
read_db_async = async_wrap(read_db)
while id < 1000:
logging.info(f'reading - id: {id}')
data = await read_db_async(id) # returns a dataframe
logging.info(f'saving - id: {id}')
to_parquet_async = async_wrap(data.to_parquet)
await data.to_parquet(f'{id}.parquet')
logging.info(f'saved - id: {id}')
id += 1
asyncio.get_event_loop().run_until_complete(main())我希望看到一些乱七八糟的日志:
reading - id: 1
saving - id: 1 (saving 1 and reading 2 run in parallel)
reading - id: 2
saved - id: 1
saving - id: 2
reading - id: 3
saved - id: 2
.....但是,实际上同步代码的日志是相同的吗?
reading - id: 1
saving - id: 1
saved - id: 1
reading - id: 2
saving - id: 2
saved - id: 2
reading - id: 3
.....发布于 2021-01-27 17:31:10
您可以通过使用gather或等效工具来同时运行read_db(n+1)和to_parquet(n):
async def main():
read_db_async = async_wrap(read_db)
prev_to_parquet = asyncio.sleep(0) # no-op
for id in range(1, 1000):
data, _ = await asyncio.gather(read_db_async(id), prev_to_parquet)
to_parquet_async = async_wrap(data.to_parquet)
prev_to_parquet = to_parquet_async(f'{id}.parquet')
await prev_to_parquethttps://stackoverflow.com/questions/65911158
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