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.
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