Same in Germany, and not just for elementary schools but also secondary schools. At least that's how it was decades ago when I was a student, maybe it's different now.
My relatives live in Germany and in all schools their kids were in school gave out lunches. They were not packing own luch and did not considered sandwitch as a proper lunch.
In German, we use "aufrufen", which means "to call up" if you translate it fragment-by-fragment, and in pre-computer times would (as far as I know) only be understood as "to call somebody up by their name or nummer" (like a teacher asking a student to speak or get up) when used with a direct object (as it is for functions).
It's also separate from the verb for making a phone call, which would be "anrufen".
Interesting! Across the lake in Sweden we do use "anropa" for calling subprograms. I've never heard anyone in that context use "uppropa" which would be the direct translation of aufrufen.
That's assuming the AI owners would tolerate the subsistence farmers on their lands (it's obvious that in this scenario, all the land would be bought up by the AI owners eventually).
I wouldn't believe that any sort of economy or governmental system would actually survive any of this. Ford was right in that sense, without people with well-paying jobs, no one will buy the services of robots and AIs. The only thing that would help would be the massive redistribution of wealth through inheritance taxation and taxation on ownership itself. Plus UBI, though I'm fairly sceptical of what that would do to a society without purpose.
>Though I have wondered about the idea of programming something like Dependabot, but telling it, hey, tell me about known CVEs and security releases, but otherwise, let things cook for 6 months before automatically building a PR for me to update.
Even when the 'spawn' strategy is used (default on Windows, and can be chosen explicitly on Linux), the overhead can largely be avoided. (Why choose it on Linux? Apparently forking can cause problems if you also use threads.) Python imports can be deferred (`import` is a statement, not a compiler or pre-processor directive), and child processes (regardless of the creation strategy) name the main module as `__mp_main__` rather than `__main__`, allowing the programmer to distinguish. (Being able to distinguish is of course necessary here, to avoid making a fork bomb - since the top-level code runs automatically and `if __name__ == '__main__':` is normally top-level code.)
But also keep in mind that cleanup for a Python process also takes time, which is harder to trace.
I really wish Python had a way to annotate things you don't care about cleaning up. I don't know what the API would look like, but I imagine something like:
l = list(cleanup=False)
for i in range(1_000_000_000): l.append(i)
telling the runtime that we don't need to individually GC each of those tiny objects and just let the OS's process model free the whole thing at once.
Sure, close TCP connections before you kill the whole thing. I couldn't care less about most objects, though.
On a 64-core machine, Python code that uses all the cores will be modestly faster than single-threaded C, even if all the inner loops are in Python. If you can move the inner loops to C, for example with Numpy, you can do much better still. (Python is still harder to get right than something like C or OCaml, of course, especially for larger programs, but often the smaller amount of code and quicker feedback loop can compensate for that.)
I strongly doubt this claim. Python is more than 64x slower than C without synchronization overhead in most numeric tasks, with synchronization overhead on those processes it should be much worse.
Python is so much slower than any native or JIT compiled language that it begets things like numpy in the first place.
You'd presumably need to do something involving weakrefs, since it would be really bad if you told Python that the elements can be GCd at all (never mind whether it can be done all at once) but someone else had a reference.
Or completely rearchitect the language to have a model of automatic (in the C sense) allocation. I can't see that ever happening.
I don't think either of those are true. I'm not arguing against cleaning up objects during the normal runtime. What I'd like is something that would avoid GC'ing objects one-at-a-time at program shutdown.
I've had cases where it took Python like 30 seconds to exit after I'd slurped a large CSV with a zillion rows into RAM. At that time, I'd dreamed of a way to tell Python not to bother free()ing any of that, just exit() and let Linux unmap RAM all at once. If you think about it, there probably aren't that many resources you actually care about individually freeing on exit. I'm certain somewill will prove me wrong, but at a first pass, objects that don't define __del__ or __exit__ probably don't care how you destroy them.
Never experienced this. If this is truly a problem, here is a sledgehammer, just beware it will not close your tcp connections gracefully: os.kill(os.getpid(), signal.SIGKILL).
Is there a good way to add __del__() methods or to wrap Context Manager __enter__()/__exit__() methods around objects that never needed them because of the gc?
Also, there's a recent proposal to add explicit resource management to JS: "JavaScript's New Superpower: Explicit Resource Management"
https://news.ycombinator.com/item?id=44012227
