What do you usually look for after a trace? I know how to trace and I know the general gist of it in terms of looking at % ratio to see which function calls is hogging the resources, but other than that I don't know what other insights one could infer from looking at a trace result.
Can you share your knowledge on this?
How do you relate the output of this back to your code?<p>Like I look up ddot_kernel_8 from the sample sklearn output and I find it’s a function from OpenBLAS but when I try to find how sklearn uses it I don’t see where they use that. How would you make use of this tool?<p>It seems like the output would be useful for writing cython extensions is that the main use case?
Really nice tool to have in the toolbox, thanks for that. For the record I've installed Austin from AUR on Arch and austin-tui was not working (I've pinged the packager about that), and it was not working either with pypi version. It's working if I pipx install directly the git version though.<p>How does it play with async code?