Which Python System is affected? (Was: What does the Async Detour usually cost)

Hi,
I tested this one:
Python 3.11.11 (0253c85bf5f8, Feb 26 2025, 10:43:25)
[PyPy 7.3.19 with MSC v.1941 64 bit (AMD64)] on win32
I didn't test yet this one, because it is usually slower:
ython 3.14.0b2 (tags/v3.14.0b2:12d3f88, May 26 2025, 13:55:44)
[MSC v.1943 64 bit (AMD64)] on win32
Bye
Mild Shock schrieb:

Hi,
 I have some data what the Async Detour usually
costs. I just compared with another Java Prolog
that didn't do the thread thingy.
 Reported measurement with the async Java Prolog:
  > JDK 24: 50 ms (using Threads, not yet VirtualThreads)
 New additional measurement with an alternative Java Prolog:
 JDK 24: 30 ms (no Threads)
 But already the using Threads version is quite optimized,
it basically reuse its own thread and uses a mutex
somewhere, so it doesn't really create a new secondary
 thread, unless a new task is spawn. Creating a 2nd thread
is silly if task have their own thread. This is the
main potential of virtual threads in upcoming Java,
 just run tasks inside virtual threads.
 Bye
 P.S.: But I should measure with more files, since
the 50 ms and 30 ms are quite small. Also I am using a
warm run, so the files and their meta information is already
 cached in operating system memory. I am trying to only
measure the async overhead, but maybe Python doesn't trust
the operating system memory, and calls some disk
 sync somewhere. I don't know. I don't open and close the
files, and don't call some disk syncing. Only reading
stats to get mtime and doing some comparisons.