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lines changed Original file line number Diff line number Diff line change @@ -2260,7 +2260,7 @@ function hash(A::AbstractArray, h::UInt)
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# hashes will often subsequently be compared by equality -- and equality between arrays
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# works elementwise forwards and is short-circuiting. This means that a collision
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# between arrays that differ by elements at the beginning is cheaper than one where the
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- # difference is towards the end. Furthermore, blindly choosing log(N) entries from a
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+ # difference is towards the end. Furthermore, choosing ` log(N)` arbitrary entries from a
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# sparse array will likely only choose the same element repeatedly (zero in this case).
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# To achieve this, we work backwards, starting by hashing the last element of the
Original file line number Diff line number Diff line change @@ -113,7 +113,7 @@ julia> Base.length(S::Squares) = S.count
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```
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Now, when we ask Julia to [ ` collect ` ] ( @ref ) all the elements into an array it can preallocate a ` Vector{Int} `
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- of the right size instead of blindly [ ` push! ` ] ( @ref ) ing each element into a ` Vector{Any} ` :
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+ of the right size instead of naively [ ` push! ` ] ( @ref ) ing each element into a ` Vector{Any} ` :
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``` jldoctest squaretype
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julia> collect(Squares(4))
Original file line number Diff line number Diff line change @@ -906,7 +906,7 @@ f(x::Int, y::Int) = 3
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```
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This is often the right strategy; however, there are circumstances
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- where following this advice blindly can be counterproductive. In
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+ where following this advice mindlessly can be counterproductive. In
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particular, the more methods a generic function has, the more
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possibilities there are for ambiguities. When your method hierarchies
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get more complicated than this simple example, it can be worth your
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