Context aware Python asyncio rust analyzer
capara is a profiler written in Rust that uses ContextVars for storing the profile results.
The main goal is to be able to profile certain asyncio tasks, out of concurrently running ones.
It's written in Rust for performance and safety, and also because I like Rust and it's good FFI and soundness experience.
Currently capara captures all calls, not aggregated data, and each function call has a duration of nanoseconds.
Some functions might have None duration in case the profiler stopped before the stop function was called.
capara doesn't maintain order of call currently, but should be easily achieveable in next versions.
Currently supports Python 3.8-3.9. Support of Python3.7 is achievable by sending a PR to PyO3 (I am lazy at this moment to solve this)
capara heavily relies on Python FFI and is in very early development. Use with caution.
You should use capara if you want to profile certain tasks in your asyncio code. Other profilers would show data of all functions that ran, even if in background or not as part of your task.
from capara.profiler import Profiler
profiler = Profiler()
with profiler:
do_something
profiler.results
## will return all functions profiled, in a list of tuple, each tuple containing an entry - (file_name, func_name, duration)
## duration is in nanoseconds.capara was written by Aviram Hassan [email protected], copyright 2020, licensed under MIT license.
See LICENSE