`Leaves` optic about accessors.jl

[jw3126]

Nice! Accessing the leaves of a tree is certainly an important task. As I understand, this assumes that the tree structure is encoded using Tuples and NamedTuples. There are many other possible choices, however. What if I have a tree like this:

["some", ["tree", [["encoded", "using"], "vectors"]

Is there a way to let the user supply the tree structure?

[cscherrer]

Hmm, good question. It's not clear to me in this case even what we'd want the result to look like. Julia infers the type as Array{Any, 1}, so that doesn't help.

OTOH, if we instead had some nested structs, that should be manageable. StructArrays has some nice tricks for recasting a struct as a named tuple, and after that it reduces to the previous case.

My interest here was to just work with the part that can be manipulated very quickly. So one approach could be to use this as an "outer optic" and pass to something else for each resolved component.

Then I guess part of the question is whether the current results should be considered "leaves". Maybe TupleLeaves or something is a better name?

[jw3126]

Hmm, good question. It's not clear to me in this case even what we'd want the result to look like. Julia infers the type as Array{Any, 1}, so that doesn't help.

I would expect bad performance in this case, but the semantics would be:

tree = ["some", ["tree", [["encoded", "using"], "vectors"]
modify(uppercase, tree, Leaves(...)) == ["SOME", ["TREE", [["ENCODED", "USING"], "VECTORS"]

My point was that there are many ways trees are encoded and instead of only supporting one somewhat arbitrary way (descent into Tuples and NamedTuples) I would prefer if Accessors.jl could be helpful for all these cases.

My interest here was to just work with the part that can be manipulated very quickly. So one approach could be to use this as an "outer optic" and pass to something else for each resolved component.

I think Recursive goes in this direction. Let's hope inference can handle it 😄

[jw3126]

using Accessors
x = (a = [1, 2], b = (c = ([3, 4], [5, 6]), d = [7, 8]));
optic = Recursive(x -> x isa Union{Tuple, NamedTuple}, Elements())
@test modify(sum, x, optic, ) === (a = 3, b = (c = (7, 11), d = 15))

But sadly

@code_warntype modify(sum, x, optic, )

Variables
  #self#::Core.Compiler.Const(Accessors.modify, false)
  f::Core.Compiler.Const(sum, false)
  obj::NamedTuple{(:a, :b),Tuple{Array{Int64,1},NamedTuple{(:c, :d),Tuple{Tuple{Array{Int64,1},Array{Int64,1}},Array{Int64,1}}}}}
  optic::Core.Compiler.Const(Recursive{var"#3#4",Elements}(var"#3#4"(), Elements()), false)

Body::NamedTuple{(:a, :b),_A} where _A<:Tuple
1 ─      nothing
│   %2 = Accessors.OpticStyle(optic)::Core.Compiler.Const(Accessors.ModifyBased(), false)
│   %3 = Accessors._modify(f, obj, optic, %2)::NamedTuple{(:a, :b),_A} where _A<:Tuple
└──      return %3

[cscherrer]

Yeah, the reason I started down this path was that statically-typed things should have better performance than I was able to get out of Recursive. But maybe there's a way to fix that more directly, I'm not sure

[aplavin]

You may find RecursiveOfType recently added to AccessorsExtra helpful:

julia> x = (a = (1, 2), b = (c = ((3, 4), (5, 6)), d = (7, 8)));
julia> o = RecursiveOfType(Tuple{Vararg{Number}})

julia> @btime modify($sum, $x, $o)
  2.903 ns (0 allocations: 0 bytes)
(a = 3, b = (c = (7, 11), d = 15))

julia> @btime getall($x, $o)
  3.272 ns (0 allocations: 0 bytes)
((1, 2), (3, 4), (5, 6), (7, 8))