Many functions--e.g. mean, variance, etc.--could be made parallelizable, faster, shorter, and more general--by accepting Transducers.jl as a dependency, and it would substantially simplify the implementation of some features. I find myself reaching for it but having to use clumsier iterators or broadcasting methods often.

Luckily, Transducers.jl is now being maintained by Mason Protter and the rest of the people working on the JuliaFolds ecosystem.

The package and its dependencies have been pared down substantially over time and should not be a major contributor to StatsBase.jl's loading time. Transducers is now lightweight, with only about 80ms load time for all dependencies (including indirect dependencies) on v1.10.

julia> @time_imports using Transducers
      0.2 ms  Adapt
      6.1 ms  MacroTools
      0.5 ms  StaticArraysCore
      0.3 ms  ConstructionBase
      6.4 ms  Setfield
      0.3 ms  ArgCheck
      0.1 ms  Compat
      0.1 ms  Compat → CompatLinearAlgebraExt
      6.4 ms  InitialValues
               ┌ 0.0 ms Requires.__init__() 
     32.5 ms  Requires 98.74% compilation time
               ┌ 0.0 ms BangBang.__init__() 
      4.7 ms  BangBang
      9.5 ms  Baselet
      0.2 ms  CompositionsBase
      0.2 ms  DefineSingletons
      2.9 ms  MicroCollections
     30.2 ms  Test
      4.5 ms  SplittablesBase
     14.2 ms  Transducers

The primary advantage would be to simplify the implementation of many features, enable in-place algorithms that can be substantially faster and more memory-efficient, and to use a more generic interface than the iterator interface (as transducers can operate on collections that are not themselves iterators).