On Monday, February 9, 2015 at 1:50:58 PM UTC+5:30, Ryan Stuart wrote:
> Hi Asad,
>
> Is there any reason why you can't just use profile/cProfile? In particular,
> you could use the api of that module to save out the profile stats to an
> external file with a unique name and then inspect them later with a tool like
> snakeviz. The code to save profile stats might look like the following:
>
>
> pr = cProfile.Profile()
> pr.runcall(your_celery_task_without_async)
> ps = pstats.Stats(pr)
> ps.dump_stats("my_task.profile")
> Obviously you need to call your celery task function directly, not via Celery
> using delay() or any derivative. Alternatively, you could try something like
> line_profiler by again, calling the task directly.
>
>
> If using this method it turn out your actual task code is running quite fast,
> then I'd suggest that the majority of the time is being lost in transferring
> the task to the Celery node.
>
> Cheers
>
>
> On Mon Feb 09 2015 at 5:20:43 AM Asad Dhamani <dhama...@gmail.com> wrote:
> I have a Flask application where I run a specific task asynchronously using
> Celery. Its basically parsing some HTML and inserting data into a Postgres
> database(using SQLAlchemy). However, the task seems to be running very
> slowly, at 1 insert per second.
>
> I'd like to find out where the bottleneck is, and I've been looking for a
> good profiler that'd let me do this, however, I couldn't find anything. Any
> recommendations would be great.
>
> --
>
> https://mail.python.org/mailman/listinfo/python-list
Hi Ryan,
I was looking for something that didn't make me modify my code. It seems like
I'll just use cProfile with snakeviz.
Thanks for the help
--
https://mail.python.org/mailman/listinfo/python-list
