The trick is to break that (on the dots) into three const assignments with descriptive names. Practically self-documenting, easily debuggable.

If you don't use the builtin transformations, you'll just end up re-implementing them, poorly. And adding to the cognitive overhead with new concepts. And I have to read your code with a fine-toothed comb to ensure it's really side-effect free. I don't advocate turning everything into a named function as in your example though, short one-off functions should all be inline IMO.

I feel like the functional code you wrote was written to intentionally obfuscate what is being done. For instance, composing a bunch of methods inline doesn't have any utility for it unless you define what compose(xor, lol, rofl) really means.

Ideally this is how it should be written for maximum readability.

  things
  |> pluck('bar')
  |> map(xor)
  |> map(lol)
  |> map(rofl)
  |> reduce(differenceWith('id')

The code is written equally well without using pipe operator but the proposal to introduce it is in works [1].

Here is it using lodash (not even lodash-fp), and this is going to do a single for loop when executing because this is lazy.

  _.chain(things)
   .pluck('bar')
   .map(_.xor)
   .map(_.lol)
   .map(_.rofl)
   .reduce(_.differenceWith('id'))
   .value();

It's no less readable than the code you'd write using using unfolded transformations.

1. https://github.com/tc39/proposal-pipeline-operator

the nice thing is that you can easily split that line up as much as makes sense, should you decide you need to access some intermediate form of the data. and you can use the variable names as a comment that explains what that chunk of transformations represents.

so someone reading over it can kind of skim down the left side and follow what's happening and scan to the right if they need to understand some part in detail

If only you could still recognize it as a transformation when it is inline