Singeli VS data_jd

I don't put a lot of stock in the "write-only" accusation. I think it's mostly used by those who don't know APL because, first, it's clever, and second, they can't read the code. However, if I remember I implemented something in J 10 years ago, I will definitely dig out the code because that's the fastest way by far for me to remember how it works.

This project specifically looks to be done in a flat array style similar to Co-dfns[0]. It's not a very common way to use APL. However, I've maintained an array-based compiler [1] for several years, and don't find that reading is a particular difficulty. Debugging is significantly easier than a scalar compiler, because the computation works on arrays drawn from the entire source code, and it's easy to inspect these and figure out what doesn't match expectations. I wrote most of [2] using a more traditional compiler architecture and it's easier to write and extend but feels about the same for reading and small tweaks. See also my review [3] of the denser compiler and precursor Co-dfns.

As for being read by others, short snippets are definitely fine. Taking some from the last week or so in the APL Farm, {⍵÷⍨+/|-/¯9 ¯11+.○?2⍵2⍴0} and {(⍸⍣¯1+\⎕IO,⍺)⊂[⎕IO]⍵} seemed to be easily understood. Forum links at [4]; the APL Orchard is viewable without signup and tends to have a lot of code discussion. There are APL codebases with many programmers, but they tend to be very verbose with long names. Something like the YAML parser here with no comments and single-letter names would be hard to get into. I can recognize, say, that c⌿¨⍨←(∨⍀∧∨⍀U⊖)∘(~⊢∊LF⍪WS⍨)¨c trims leading and trailing whitespace from each string in a few seconds, but in other places there are a lot of magic numbers so I get the "what" but not the "why". Eh, as I look over it things are starting to make sense, could probably get through this in an hour or so. But a lot of APLers don't have experience with the patterns used here.

[0] https://github.com/Co-dfns/Co-dfns

[1] https://github.com/mlochbaum/BQN/blob/master/src/c.bqn

[2] https://github.com/mlochbaum/Singeli/blob/master/singeli.bqn

[3] https://mlochbaum.github.io/BQN/implementation/codfns.html

[4] https://aplwiki.com/wiki/Chat_rooms_and_forums

Here's an AVX-2 implementation that assumes it can read up to 31 bytes past the end of the input: https://godbolt.org/z/P7PP1MnK7

Requires -fno-unroll-loops as otherwise clang gets overly unroll-y; the code is fast enough. Tail is dealt with by blending the originally read value with the new one.

(yes, that's autogenerated; from some https://github.com/mlochbaum/singeli code)

It's not ideal, but I've done this in BQN and it took about 15 lines. I didn't need to handle comments or escapes, which would add a little complexity. See functions ParseXml and ParseAttr here: https://github.com/mlochbaum/Singeli/blob/master/data/iintri...

XML is particularly simple though, dealing with something like JPEG would be an entirely different experience.

I suspect the J package Jd is probably the most non-trivial public codebase. I don’t love the coding style (functions are long and scripted) and it doesn’t make use of newer lambda functions (“direct definitions”) which are easier to read. https://github.com/jsoftware/data_jd

I found this license for jd itself. It is free only for non-commercial use:

https://github.com/jsoftware/data_jd/blob/master/doc/License...

The link you mentioned only applies to the jsource folder: the jengine code.

A longer piece from GitHub: csvreportsummary=: 3 : 0 t=. <;.2 fread PATHLOGLOGFILE b=. (<,LF)=t b=. b+.(<'!')={.each t b=. b+.(<'src: ')=5{.each t b=. b+.(<'snk: ')=5{.each t b=. b+.(<'elapsed: ')=9{.each t b=. b+.(<'rows: ')=6{.each t b=. b+.(<'error: ')=7{.each t ;b#t )