I agree with the poster you're replying to - the naming is not intuitive or approachable without that previous body of knowledge. It's enough that I would call it bad - I would flag the crap out of it in a code review.

I'm glad you linked to the style guide - i've often wondered where certain names come from.

It's not all bad. K for key, V for value, i for index... no disagreement. But the seeming aversion to any variable name longer than 2-3 characters might be great in mathematics, but makes for a nightmare of code which is focused more on writing. It doesn't need to go the extreme of UIMutableUserNotificationAction; but at least use words.

AI is already clever enough; it doesn't need to be made more cryptic with poor naming conventions. I get that for people in the industry it may be fine - but for it to break out into general use it'll need to be more social; which means simpler & clearer verbage.

> It's fine if you don't like it (although it may be you're just not quite used to it yet), but I'm not sure it's fair to call it "bad".

It is totally fair to call a naming convention where all variables are 2 or 3 letter acronyms bad, at the very least un-pythonic, and certainly not suitable for an educational tool. If you think that it's good practice to make your code shorter at the expense your users needing an abbreviation guide, you're going to make adoption a much harder sell, especially if you're pitching at python devs. Unlike the last few decades, we now live in an age of autocomplete, there is absolutely no need for this.

Here is a few lines from the imdb ipython notebook (https://github.com/fastai/fastai/blob/master/courses/dl2/imd...), that gave me a headache just to look at -

trn_dl = LanguageModelLoader(np.concatenate(trn_lm), bs, bptt)

val_dl = LanguageModelLoader(np.concatenate(val_lm), bs, bptt)

md = LanguageModelData(PATH, 1, vs, trn_dl, val_dl, bs=bs, bptt=bptt)

The cognitive load put on someone unfamiliar with your code is not acceptable:

LanguageModelData takes two LanguageModelLoaders as arguments, and then later in the code it produces a model? Surely these two classes are named the wrong way round? You haven't explained what 'bs', or '1' are supposed to be. To figure out/ remember what the other variables are, you need to chase up and down the notebook, which would easily be avoided if you just gave them descriptive names. You only use these variables once or twice, so I don't even understand what is gained by making their names so terse.

Regarding the short variables names, I actually like it a lot. It's nice because you don't have to read as much.

Once you are familiar enough with the abbreviations, it becomes much easier to read. Just from looking at this code, I can already tell you bs is batch size, bptt is back-projection through time. And then probably dl is data loader, lm is language model, md is model data. No idea what vs or 1 is but I can just look at the docs for LanguageModelData, which takes what? less than 30 seconds to read?

I think it's worth it because you can just look at one line of code and know what's going on. Instead of parsing through a paragraph of code that does the same thing.

fast.ai is great and I also want to love it but I find the coding style extremely unconventional and uninviting to the point that I only use the library when there is really no better alternative (ex for the lr finding features). Variable naming and wildcard imports would be my main complains. But thanks a lot Jeremy for the course and for posting the style guide.