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julia> using FixedSizeArrays
julia> FixedSizeArrays.collect_as(FixedSizeVector, (n*n for n ∈1:0))
0-element FixedSizeVector{Any, Memory{Any}}
julia> collect((n*n for n ∈1:0))
Int64[]
We return an empty array with eltype of Any, while collect from Base returns an empty array with an element type of Int. Neither of these is ideal:
Any is obviously suboptimal
Int seems nice at first, but necessitates the use of return type inference. This is quite undesirable:
It inhibits compiler optimization AFAIK
in particular, the :foldable effect requires :nortcall
It makes the behavior depend on type inference, which makes for a terrible programming and debugging experience.
Unlike Base, we're not yet constrained by compatibility considerations, so I think we should:
avoid making our behavior depend on type inference (in particular, I think this means not doing things like map(identity, some_array) in the implementation of collect_as)
for empty input, we could do something like this::
set the output element type to Union{}, for an input element type equal to Any
set the output element type to the input element type, when it's not equal to Any
The text was updated successfully, but these errors were encountered:
Current behavior:
We return an empty array with
eltype
ofAny
, whilecollect
fromBase
returns an empty array with an element type ofInt
. Neither of these is ideal:Any
is obviously suboptimalInt
seems nice at first, but necessitates the use of return type inference. This is quite undesirable::foldable
effect requires:nortcall
Unlike
Base
, we're not yet constrained by compatibility considerations, so I think we should:map(identity, some_array)
in the implementation ofcollect_as
)Union{}
, for an input element type equal toAny
Any
The text was updated successfully, but these errors were encountered: