Fix method ambiguities in SparseArrays

stdlib/SparseArrays/src/higherorderfns.jl

@@ -973,6 +973,7 @@ function _copy(f, args...)
     parevalf, passedargstup = capturescalars(f, args)
     return _copy(parevalf, passedargstup...)
 end
+_copy(f) = throw(MethodError(_copy, (f,)))  # avoid method ambiguity
 
 function _shapecheckbc(f, args...)
     _aresameshape(args...) ? _noshapecheck_map(f, args...) : _diffshape_broadcast(f, args...)
@@ -1006,10 +1007,6 @@ end
     _copyto!(parevalf, dest, passedsrcargstup...)
 end
 
-struct CapturedScalars{F, Args, Order}
-    args::Args
-end
-
 # capturescalars takes a function (f) and a tuple of mixed sparse vectors/matrices and
 # broadcast scalar arguments (mixedargs), and returns a function (parevalf, i.e. partially
 # evaluated f) and a reduced argument tuple (passedargstup) containing only the sparse
@@ -1024,9 +1021,13 @@ end
 # Work around losing Type{T}s as DataTypes within the tuple that makeargs creates
 @inline capturescalars(f, mixedargs::Tuple{Ref{Type{T}}, Vararg{Any}}) where {T} =
     capturescalars((args...)->f(T, args...), Base.tail(mixedargs))
+@inline capturescalars(f, mixedargs::Tuple{Ref{Type{T}}, Ref{Type{S}}, Vararg{Any}}) where {T, S} =
+    # This definition is identical to the one above and necessary only for
+    # avoiding method ambiguity.
+    capturescalars((args...)->f(T, args...), Base.tail(mixedargs))
 @inline capturescalars(f, mixedargs::Tuple{SparseVecOrMat, Ref{Type{T}}, Vararg{Any}}) where {T} =
     capturescalars((a1, args...)->f(a1, T, args...), (mixedargs[1], Base.tail(Base.tail(mixedargs))...))
-@inline capturescalars(f, mixedargs::Tuple{Union{Ref,AbstractArray{0}}, Ref{Type{T}}, Vararg{Any}}) where {T} =
+@inline capturescalars(f, mixedargs::Tuple{Union{Ref,AbstractArray{<:Any,0}}, Ref{Type{T}}, Vararg{Any}}) where {T} =
     capturescalars((args...)->f(mixedargs[1], T, args...), Base.tail(Base.tail(mixedargs)))
 
 nonscalararg(::SparseVecOrMat) = true

stdlib/SparseArrays/test/ambiguous_exec.jl

@@ -0,0 +1,4 @@
+# This file is a part of Julia. License is MIT: https://julialang.org/license
+
+using Test, SparseArrays
+@test detect_ambiguities(SparseArrays; imported=true, recursive=true) == []

stdlib/SparseArrays/test/higherorderfns.jl

@@ -632,4 +632,28 @@ end
     @test minimum(sparse([1, 2], [1, 2], ones(Int32, 2)), dims = 1) isa Matrix
 end
 
+@testset "Issue #30118" begin
+    @test ((_, x) -> x).(Int, spzeros(3)) == spzeros(3)
+    @test ((_, _, x) -> x).(Int, Int, spzeros(3)) == spzeros(3)
+    @test ((_, _, _, x) -> x).(Int, Int, Int, spzeros(3)) == spzeros(3)
+    @test_broken ((_, _, _, _, x) -> x).(Int, Int, Int, Int, spzeros(3)) == spzeros(3)
+end
+
+using SparseArrays.HigherOrderFns: SparseVecStyle
+
+@testset "Issue #30120: method ambiguity" begin
+    # HigherOrderFns._copy(f) was ambiguous.  It may be impossible to
+    # invoke this from dot notation and it is an error anyway.  But
+    # when someone invokes it by accident, we want it to produce a
+    # meaningful error.
+    err = try
+        copy(Broadcast.Broadcasted{SparseVecStyle}(rand, ()))
+    catch err
+        err
+    end
+    @test err isa MethodError
+    @test !occursin("is ambiguous", sprint(showerror, err))
+    @test occursin("no method matching _copy(::typeof(rand))", sprint(showerror, err))
+end
+
 end # module

stdlib/SparseArrays/test/sparse.jl

@@ -2343,4 +2343,12 @@ end
     @test_throws MethodError sprandn(T, 5, 5, 0.5)
 end
 
+@testset "method ambiguity" begin
+    # Ambiguity test is run inside a clean process.
+    # https://github.com/JuliaLang/julia/issues/28804
+    script = joinpath(@__DIR__, "ambiguous_exec.jl")
+    cmd = `$(Base.julia_cmd()) --startup-file=no $script`
+    @test success(pipeline(cmd; stdout=stdout, stderr=stderr))
+end
+
 end # module