如何监控Python事件循环的繁忙程度? [英] How do I monitor how busy a Python event loop is?
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问题描述
我有一个异步应用程序,它通过aiohttp服务请求并执行其他异步任务(作为HTTP客户端与数据库交互、处理消息、发出请求)。我想监视事件循环的繁忙程度,比如它执行代码所花费的时间与等待select
完成相比所花费的时间。select
。
有没有办法用标准库事件循环或其他第三方循环(Uvloop)来衡量这一点?
具体地说,我想要一个持续的饱和度百分比度量,而不仅仅是this question似乎要解决的二进制"是否繁忙"。
推荐答案
挖源代码如下:
- 事件循环基本上是executing
_run_once
在while True
循环中 _run_once
是否所有工作都在等待select
完成includingtimeout
等待select
isn't存储在_run_once
之外的任何位置
没有什么能阻止我们重新实现_run_once
,这样我们就可以为我们需要的东西计时。
我们不复制整个_run_once
实现,而是正好在select
开始之前计时(因为在select
之前没有耗时)和select
is when_process_events
开始后计时。
从言语到行动:
import asyncio
class MeasuredEventLoop(asyncio.SelectorEventLoop):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._total_time = 0
self._select_time = 0
self._before_select = None
# TOTAL TIME:
def run_forever(self):
started = self.time()
try:
super().run_forever()
finally:
finished = self.time()
self._total_time = finished - started
# SELECT TIME:
def _run_once(self):
self._before_select = self.time()
super()._run_once()
def _process_events(self, *args, **kwargs):
after_select = self.time()
self._select_time += after_select - self._before_select
super()._process_events(*args, **kwargs)
# REPORT:
def close(self, *args, **kwargs):
super().close(*args, **kwargs)
select = self._select_time
cpu = self._total_time - self._select_time
total = self._total_time
print(f'Waited for select: {select:.{3}f}')
print(f'Did other stuff: {cpu:.{3}f}')
print(f'Total time: {total:.{3}f}')
让我们测试一下:
import time
async def main():
await asyncio.sleep(1) # simulate I/O, will be handled by selectors
time.sleep(0.01) # CPU job, executed here, outside event loop
await asyncio.sleep(1)
time.sleep(0.01)
loop = MeasuredEventLoop()
asyncio.set_event_loop(loop)
try:
loop.run_until_complete(main())
finally:
loop.close()
结果:
Waited for select: 2.000
Did other stuff: 0.032
Total time: 2.032
让我们对照具有实际I/O的代码测试它:
import aiohttp
async def io_operation(delay):
async with aiohttp.ClientSession() as session:
async with session.get(f'http://httpbin.org/delay/{delay}') as resp:
await resp.text()
async def main():
await asyncio.gather(*[
io_operation(delay=1),
io_operation(delay=2),
io_operation(delay=3),
])
结果:
Waited for select: 3.250
Did other stuff: 0.016
Total time: 3.266
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