On Thu, Dec 9, 2021 at 11:47 AM David Mertz, Ph.D.
<david.mertz@gmail.com> wrote:
>
> There are tens of concrete examples at the link I gave, and hundreds more you can find easily by searching on Dask Delayed. This feels more like trying to believe a contrary than seeking understanding.
>
> Here's a concrete example that I wrote last summer. I wanted to write a similar program in a bunch of programming languages to learn those languages. From long ago, I had a Python implementation (which I improved quite a lot through the exercise, as well).
>
> https://github.com/DavidMertz/LanguagePractice
>
> What the programs do is identify any duplicate files in a filesystem tree (i.e. perhaps among millions of files, often with different names but same content).
>
> The basic idea is that a hash like SHA1 serves as a fingerprint of contents. However, the main speedup potential is in NOT computing the hash when files are either hardlinks or soft links to the same underlying inode. I/O nowadays is more of a hit than CPU cycles, but the concept applies either way.
>
> Essentially the same technique is used in all the languages. But in the Haskell case, it is NECESSARY to express this as deferred computation. I don't want Python to be like Haskell, which was in most ways the most difficult to work with.
>
> However, it would be interesting and expressive to write a Python version based around Dask Delayed... Or around a generalized "deferred" construct in Python 3.13, maybe. I'm pretty sure it could be shorter and more readable thereby.
>
The basic and obvious way to write that is a simple dictionary lookup.
It's not particularly hard to recognize inode numbers without a
deferred/delayed construct. And this is still arguing for their
benefit in the wider language, with no indication of how it's better
for default arguments. This is a MASSIVE amount of overhead for simple
cases of "x=>[]" or similar.
ChrisA
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