What portion of this is due to the fact that you're using a functional pattern on an imperative language? For example, none of those attempts can take advantage of any underlying purely functional data structures (see: Erlang/OTP/Elixir, or Clojure)
More fuel for the pyre: async Iterables cannot be consumed as a piped stream. You must use the for await construct, which is a shame considering the FP niceties that the Array type already provides for more traditional lists. Once again, one is forced by the API to use an imperative construct unless they specifically want to invite trouble by converting it into an Array (... and potentially choking in the process)
Go with a generator, and watch that list be more kind to the resources.
This is a micro-optimization and it's not always true. Generators usually use less memory, but list comprehensions can actually be faster because the memory gets allocated all at once and the loop is performed internally inside the interpreter, instead of the generator possibly being consumed as a slow top-level loop.
I was talking about examples like making a copy of a list/dict/object instead of replacing elements in-place, or using a stack of map/filter operations instead of a single-pass for-loop with dynamic programming.