More idiomatic way of phrasing `reduce(\circ, repeated(f, x))(y)`?

General Usage Performance
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21

A bit late to the party, but the closest thing to what you are doing is to use foldl with |> instead of creating the composite function. For instance

val = 1.2
n = 5
foldl(|>, Iterators.repeated(exp, n), init = val)

I haven’t benchmarked it, but I’ve found foldl(|>, fs, init = val) to be a pretty useful pattern to compose a list of functions, but of course the other approach with (y, _) -> exp(y) also works if all the functions are equal.

22

nice, looks like that’s basically the same as the other best ones and is much easier to read:

master:

julia> f(a) = foldl(|>, repeated(exp, 1000); init=a)
f (generic function with 3 methods)

julia> @benchmark f(10.)
BenchmarkTools.Trial: 10000 samples with 999 evaluations per sample.
 Range (min … max):  8.245 ns … 184.536 ns  ┊ GC (min … max): 0.00% … 0.00%
 Time  (median):     9.232 ns               ┊ GC (median):    0.00%
 Time  (mean ± σ):   9.830 ns ±   3.589 ns  ┊ GC (mean ± σ):  0.00% ± 0.00%

  ▃   ▄▇█▇▃         ▅▃    ▂▁                                  ▂
  █▆▄▄██████▇▆▆▄▄▄▆▄███▇▇▆██▇▆▆▆▆▆▆▆▆▆▆▅▆▇▆▇▇▆▆▆▅▅▅▆▆▆▄▅▄▄▅▄▅ █
  8.25 ns      Histogram: log(frequency) by time      16.7 ns <

 Memory estimate: 0 bytes, allocs estimate: 0.

julia> @benchmark f($10.)
BenchmarkTools.Trial: 10000 samples with 5 evaluations per sample.
 Range (min … max):  5.883 μs … 112.796 μs  ┊ GC (min … max): 0.00% … 0.00%
 Time  (median):     7.540 μs               ┊ GC (median):    0.00%
 Time  (mean ± σ):   7.786 μs ±   2.355 μs  ┊ GC (mean ± σ):  0.00% ± 0.00%

  ▂  ▅▅   █▂   ▁▁                  ▂▁                         ▁
  █▅▂██▇▆▇██▇███████▇▇▇▆▆▆▆▄▅▅▅▆▆▅▆██▆▅▅▅▅▃▄▅▅▆▄▃▂▃▂▅▃▃▃▂▂▃▃▅ █
  5.88 μs      Histogram: log(frequency) by time      17.1 μs <

 Memory estimate: 0 bytes, allocs estimate: 0.