A tiny library for monitoring and testing asyncio programs
Project description
This is a tiny library for monitoring and testing asyncio programs. Its monitoring features are meant to be always on in production.
Installation
aiodebug is only compatible with Python 3.8 and higher. There are no plans to support older versions.
aiodebug is available on PyPI and you can install it with:
pip install aiodebug
or
poetry add aiodebug
aiodebug will use logwood if it is installed, otherwise it will default to the standard logging module.
Log warnings when callbacks block the event loop
import aiodebug.log_slow_callbacks
aiodebug.log_slow_callbacks.enable(0.05)
This will produce WARNING-level logs such as
Executing <Task pending coro=<foo() running at /home/.../foo.py:37>
wait_for=<Future pending cb=[Task._wakeup()]>> took 0.069 seconds
asyncio already does this in debug mode, but you probably don’t want to enable full-on debug mode in production.
Track event loop lags in StatsD
import aiodebug.monitor_loop_lag
aiodebug.monitor_loop_lag.enable(statsd_client)
Tracks how much scheduled calls get delayed and sends the lags to StatsD.
Dump stack traces of all threads if the event loop hangs for too long
import aiodebug.hang_inspection
dumper = aiodebug.hang_inspection.start('/path/to/output/directory', interval = 0.25) # 0.25 is the default
...
await aiodebug.hang_inspection.stop_wait(dumper)
Enabling this function may help you in case one of your threads (sometimes) runs a CPU-bound operation that completely stalls the event loop, but you don’t know which thread it is or what it is doing.
Every time the event loop hangs (doesn’t run a scheduled ‘monitoring’ task) for longer than the given interval, aiodebug will create 3 stack traces, 1 second apart, in your output directory. For example:
-rw-r--r-- 1 user group 6.7K 4 Jan 09:41 stacktrace-20220104-094154.197418-0.txt
-rw-r--r-- 1 user group 7.0K 4 Jan 09:41 stacktrace-20220104-094155.206574-1.txt
-rw-r--r-- 1 user group 6.6K 4 Jan 09:41 stacktrace-20220104-094156.211781-2.txt
Each file then contains the Python stack traces of all threads that were running or waiting at the time. You might be able to find your culprit blocking the event loop at the end of one of the traces.
Speed up or slow down time in the event loop
This is mainly useful for testing.
import aiodebug.testing.time_dilated_loop
loop = aiodebug.testing.time_dilated_loop.TimeDilatedLoop()
asyncio.set_event_loop(loop)
loop.time_dilation = 3
await asyncio.sleep(1) # Takes 0.333s of real time
loop.time_dilation = 0.1
await asyncio.sleep(1) # Takes 10s of real time
aiodebug was made by Quantlane, a systematic trading firm. We design, build and run our own stock trading platform.
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