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I mean if you've got a feature set to merge into dev, and it suddenly merges into main after someone merged dev into main then that's very annoying.

I mean a branch is just jamming a flag into a commit with a polite note to move the flag along if you're working on it. You make a long trail, leave several flags and merge the whole thing back.

Of course leaving multiple waypoints only makes sense if merging the earlier parts makes any sense, and if the way you continue actually depends on the previous work.

If you can split it into several small changes made to a central branch it's a lot easier to merge things. Otherwise you risk making a new feature codependent on another even if there was no need to.

Connected, sure, that's table stakes. But why is being non-cyclic a desirable property? (Other than it being the definition of "perfect maze", a term I've come to despise)

But it's an insane move. If anything AI has made it more important than ever to know who authored something and then someone does this to promote AI.

Hanlon's razor is about not assuming malice, which makes no sense when applied to faceless mega-corporations or even random strangers where you know conflicting motives exist.

I still don't assume malice, at least as a default / until strongly indicated otherwise, from any individual employee. Emergent behavior of complex artificial incentive systems is, of course, a whole other matter so I can see what you mean that the razor won't apply there without breaking it down to an individual as in the scenario I mentioned about an ill-meaning employee

That's pretty much the reason why. Raymond Hettinger explains the philosophy well while discussing the `random` standard library module: https://www.youtube.com/watch?v=Uwuv05aZ6ug

I feel like much of this has been forgotten of late, though. From what I've seen, i's really quite hard to get anything added to the standard library unless you're a core dev who's sufficiently well liked among other core devs, in which case you can pretty much just do it. Everyone else will (understandably) be put through a PhD thesis defense, then asked to try the idea out as a PyPI package first (and somehow also popularize the package), and then if it somehow catches on that way, get declined anyway because it's easy for everyone to just get it from PyPI (see e.g. Requests).

I personally was directed to PyPI once when I was proposing new methods for the builtin `str`. Where the entire point was not to have to import or instantiate anything.

    import mmap, codecs

    from collections import Counter

    def word_count(filepath):

        freq = Counter()
    
        decode = codecs.getincrementaldecoder('utf-8')().decode
    
        with open(filepath, 'rb') as f, mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ) as mm:
        
                for chunk in iter(lambda: mm.read(65536), b''):
            
                        freq.update(decode(chunk).split())
            
                    freq.update(decode(b'', final=True).split())
        
                return freq

That's two neat tricks that I'm definitely adding to my bag of python trickery.

... Ah, but I suppose the existing code hasn't avoided that anyway. (It's also creating regex match objects, but those get disposed each time through the loop.) I don't know that there's really a way around that. Given the file is barely a KB, I rather doubt that the illustrated techniques are going to move the needle.

In fact, it looks as though the entire data structure (whether a dict, Counter etc.) should a relatively small part of the total reported memory usage. The rest seems to be internal Python stuff.

If you don't care about efficiency you can just do len(set(text.split())), but that's barely worth making a function for.

Really the one thing that conclusively has changed is that the 'ask it on stackoverflow' has become 'ask it an LLM'. Around 95% of the stackoverflow questions can be answered by an LLM with access to the documentation, not sure what will happen to the other 5%. I don't think stackoverflow will survive a 20-fold reduction in size, if only because their stance on not allowing repeat questions means that exponential growth was the main thing preventing them from becoming stale.

Right.

I don't think you even need cynicism or whatever you felt you were having impolite thoughts about:

I'd expect the top mature libraries to be the most resistant to AI tool use for various reasons. They already have established processes, they don't accept drive-by PR spam, the developers working on them might be the least likely to be early adopters, and -- perhaps most importantly -- the todo list of those projects might need the most human comms, like directional planning rather than the sort of yolo feature impl you can do in a one-man greenfield.

All to further bury signals you might find elsewhere in broader ecosystems.

I'm not sure that is a useful model, or more complete. I don't think you can assign interceptors to undetected missiles, so considering their effect on the value is rather pointless. It's effectively a sunk cost.

Multiplying with the probability also makes no sense from an optimisation point of view. Why would you assign lower value to a target about to be hit simply because you were unlikely to detect the missile?

The tracking probability only shows up in the meta game described at the end, where one side is trying to optimise their ability to hit valuable targets and the other is trying to optimise their ability to prevent that from happening.