data_jd VS BQN-autograd

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

An example J file because this link doesn't say much:

https://github.com/jsoftware/data_jd/blob/master/csv/csv.ijs

Here's one of the more central files that ties into how a Jd database is laid out:

https://github.com/jsoftware/data_jd/blob/master/base/common...

Not that I claim anyone in particular can read it of course. Jd uses a hierarchy of folder, database, table, column that's handled with an object system to share code between them. A folder is just a place to put databases and hardly needs to add anything, while the other levels have a lot of extra functionality. As an inverted database, Jd stores each column in a file, and accesses it using memory mapping.

https://github.com/jsoftware/data_jd/blob/master/base/folder...

https://github.com/jsoftware/data_jd/blob/master/base/table....

(I designed this system when I did some of the early work to turn JDB into Jd as a summer intern)

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 )

Oh, thanks for clarifying, since it occurred to me that you might mean just the appeal to you, but not that you meant the field of programming! I'm no NN expert, but tinygrad looks very approachable in BQN. You might be interested in some other initial work along those lines: https://github.com/loovjo/BQN-autograd with automatic differentiation, and the smaller https://github.com/bddean/BQNprop using backprop.