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CC @MasonProtter @drelatgithub I really like the more StructArrays.jl style API in https://github.com/MasonProtter/FieldViews.jl and I think that package can be used to experiment with these ideas, while this package can be marked as stable. Also, interestingly, it seems like the Julia compiler has gotten way better at optimizing BangBang.jl bench_mutate = Trial(2.016 ns)
BenchmarkTools.Trial: 10000 samples with 1000 evaluations per sample.
Range (min … max): 2.016 ns … 65.124 ns ┊ GC (min … max): 0.00% … 0.00%
Time (median): 2.019 ns ┊ GC (median): 0.00%
Time (mean ± σ): 2.063 ns ± 0.950 ns ┊ GC (mean ± σ): 0.00% ± 0.00%
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2.02 ns Histogram: log(frequency) by time 2.06 ns <
Memory estimate: 0 bytes, allocs estimate: 0.
bench_setfield = Trial(2.336 μs)
BenchmarkTools.Trial: 10000 samples with 9 evaluations per sample.
Range (min … max): 2.336 μs … 67.999 μs ┊ GC (min … max): 0.00% … 89.36%
Time (median): 3.214 μs ┊ GC (median): 0.00%
Time (mean ± σ): 4.658 μs ± 5.805 μs ┊ GC (mean ± σ): 18.18% ± 14.18%
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2.34 μs Histogram: log(frequency) by time 33.6 μs <
Memory estimate: 84.45 KiB, allocs estimate: 3.
bench_bangbang = Trial(2.266 ns)
BenchmarkTools.Trial: 10000 samples with 1000 evaluations per sample.
Range (min … max): 2.266 ns … 18.937 ns ┊ GC (min … max): 0.00% … 0.00%
Time (median): 2.270 ns ┊ GC (median): 0.00%
Time (mean ± σ): 2.283 ns ± 0.356 ns ┊ GC (mean ± σ): 0.00% ± 0.00%
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2.27 ns Histogram: frequency by time 2.28 ns <
Memory estimate: 0 bytes, allocs estimate: 0. |
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Mark the API as stable. No breaking changes.