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I like it, but isn't the approach a little overkill? If you'd design a declarative systems where you declare your datasets and how they transform into each oth
by rix0r 16y ago
I like it, but isn't the approach a little overkill?
If you'd design a declarative systems where you declare your datasets and how they transform into each other, then you could analyze the dependency chain and do the same thing as a library instead of a separate interpreter.
Sprinkle some transparent pickling, hashing and timestamping in there and you get all of the benefits but much more reusable.
Am I underestimating the problem?
- zerothehero 16y agoYeah I fail to understand why a separate interpreter is desirable for this problem. Seems like something for a Python library.
- scott_s 16y agoIf you'd design a declarative systems where you declare your datasets and how they transform into each other, then you could analyze the dependency chain and do the same thing as a library instead of a separate interpreter. That sounds like a lot of effort on the part of the programmer. The author's approach - which I like - is to require as little intervention from the programmer as possible. Don't confuse the author's research implementation with how it should look in practice. I imagine the author implemented a light-weight interpreter that does the memoization on top of CPython. That's far easier than hacking CPython itself, which gives him a faster path to proof-of-concept implementation and publishing evaluations of the idea. If the research gives good results, then maybe this approach could get implemented as a VM optimization - you wouldn't know it's happening, your programs just run faster.