• Which Python System is affected? (Was: What does the Async Detour usua

    From Mild Shock@3:633/280.2 to All on Tue Jun 24 08:48:20 2025
    Subject: 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.

    --- MBSE BBS v1.1.1 (Linux-x86_64)
    * Origin: ---:- FTN<->UseNet Gate -:--- (3:633/280.2@fidonet)
  • From Mild Shock@3:633/280.2 to All on Tue Jun 24 16:53:40 2025
    Subject: Schachner, Joseph was the Big Moron [September 2021 16:30] (Was:
    Which Python System is affected?)

    Hi,

    Everybody who puts me personally on CC: , and
    posts form python-list@python.org . Please note,
    I cannot respond on python-list@python.org .

    Somebody blocked me on python-list@python.org .
    If you want a discussion, post on comp.lang.python .
    And stop spamming me with your CC: .

    Bye

    P.S.: BTW, I got blocked after this moron wrote
    this nonsense. It is complete nonsense, now
    that everybody is talking about AsyncAPI, and

    since Dogelog Player evolved into Async, simply
    by its 2nd target JavaScript. What company was he
    working for? A looser company Teledyne ?

    ------------------- begin moron ---------------------

    Opinion: Anyone who is counting on Python for truly
    fast compute speed is probably using Python for the
    wrong purpose. Here, we use Python to control Test
    Equipment, to set up the equipment and ask for a
    measurement, get it, and proceed to the next measurement;
    and at the end produce a nice formatted report. If we
    wrote the test script in C or Rust or whatever it
    could not run substantially faster because it is
    communicating with the test equipment, setting it up
    and waiting for responses, and that is where the vast
    majority of the time goes. Especially if the measurement
    result requires averaging it can take a while. In my
    opinion this is an ideal use for Python, not just
    because the speed of Python is not important, but also
    because we can easily find people who know Python, who
    like coding in Python, and will join the company
    to program in Python ... and stay with us.
    - --- Joseph S.

    Teledyne Confidential; Commercially Sensitive Business Data

    https://mail.python.org/archives/list/python-list@python.org/thread/RWEKXFW4WED7KNI67QBMDTC32EAEU3ZT/

    ------------------- end moron -----------------------


    Mild Shock schrieb:
    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.


    --- MBSE BBS v1.1.1 (Linux-x86_64)
    * Origin: ---:- FTN<->UseNet Gate -:--- (3:633/280.2@fidonet)