Crash on 1.12 when showing `diff(P).args[2]`

[DanielVandH]

I'm not sure if this is just on my machine or not. On 1.12 in a fresh environment:

julia> using SemiclassicalOrthogonalPolynomials

julia> P = SemiclassicalJacobi(2, 0, 0, 0)
SemiclassicalJacobi with weight x^0.0 * (1-x)^0.0 * (2.0-x)^0.0 on 0..1

julia> diff(P); # works fine

julia> diff(P).args[2]
ℵ₀×ℵ₀ adjoint(::BandedMatrices.BandedMatrix{Float64, ApplyArray{Float64, 2, typeof(vcat), Tuple{LinearAlgebra.Adjoint{Float64, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, Accumulate{Float64, 1, typeof(*), Vector{Float64}, AbstractVector{Float64}}}}}, LinearAlgebra.Adjoint{Float64, BroadcastVector{Float64, typeof(*), Tuple{BroadcastVector{Float64, typeof(-), Tuple{BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, BroadcastVector{Float64, typeof(+), Tuple{Cumsum{Float64, 1, AbstractVector{Float64}}, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(-), Tuple{BroadcastVector{Float64, typeof(/), Tuple{SubArray{Float64, 1, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(-), Tuple{BroadcastVector{Float64, typeof(/), Tuple{Int64, BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, FillArrays.Fill{Float64, 1, Tuple{InfiniteArrays.OneToInf{Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}, BroadcastVector{Float64, typeof(sqrt), Tuple{BroadcastVector{Float64, typeof(*), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}, SubArray{Float64, 1, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}}}}}}}}}, BroadcastVector{Float64, typeof(inv), Tuple{BroadcastVector{Float64, typeof(sqrt), Tuple{BroadcastVector{Float64, typeof(*), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}, SubArray{Float64, 1, ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}}}}}}}}}}}}}, BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, BroadcastVector{Float64, typeof(+), Tuple{BroadcastVector{Float64, typeof(*), Tuple{BroadcastVector{Float64, typeof(inv), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}, SemiclassicalOrthogonalPolynomials.MulAddAccumulate{Float64}}}, BroadcastVector{Float64, typeof(/), Tuple{BroadcastVector{Float64, typeof(-), Tuple{BroadcastVector{Float64, typeof(/), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}, InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}}}, BroadcastVector{Float64, typeof(inv), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}}}}}}}}}, Accumulate{Float64, 1, typeof(*), Vector{Float64}, AbstractVector{Float64}}}}}}}, InfiniteArrays.OneToInf{Int64}}) with eltype Float64 with indices OneToInf()×OneToInf():

Please submit a bug report with steps to reproduce this fault, and any error messages that follow (in their entirety). Thanks.
Exception: EXCEPTION_ACCESS_VIOLATION at 0x7ffaa078e720 -- gc_mark_outrefs at C:/workdir/src\gc-stock.c:2362 [inlined]
gc_mark_loop_serial_ at C:/workdir/src\gc-stock.c:2517
in expression starting at REPL[7]:1
gc_mark_outrefs at C:/workdir/src\gc-stock.c:2362 [inlined]
gc_mark_loop_serial_ at C:/workdir/src\gc-stock.c:2517
gc_mark_loop_serial at C:/workdir/src\gc-stock.c:2540
gc_mark_loop at C:/workdir/src\gc-stock.c:2728 [inlined]
_jl_gc_collect at C:/workdir/src\gc-stock.c:3073
ijl_gc_collect at C:/workdir/src\gc-stock.c:3461
maybe_collect at C:/workdir/src\gc-stock.c:349 [inlined]
jl_gc_small_alloc_inner at C:/workdir/src\gc-stock.c:725 [inlined]
jl_gc_small_alloc_noinline at C:/workdir/src\gc-stock.c:783 [inlined]
jl_gc_alloc_ at C:/workdir/src\gc-stock.c:797
jl_alloc_genericmemory_unchecked at C:/workdir/src\genericmemory.c:41
GenericMemory at .\boot.jl:588 [inlined]
array_new_memory at .\array.jl:1067 [inlined]
#_growend!##0 at .\array.jl:1148
jfptr_YY._growendNOT.YY.YY.0_15739.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
tojlinvoke85464.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
j_YY._growendNOT.YY.YY.0_80409.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
_growend! at .\array.jl:1131 [inlined]
_push! at .\array.jl:1289 [inlined]
push! at .\array.jl:1286 [inlined]
cfg_inline_item! at .\../usr/share/julia/Compiler/src/ssair\inlining.jl:164
batch_inline! at .\../usr/share/julia/Compiler/src/ssair\inlining.jl:630
ssa_inlining_pass! at .\../usr/share/julia/Compiler/src/ssair\inlining.jl:79 [inlined]
run_passes_ipo_safe at .\../usr/share/julia/Compiler/src\optimize.jl:1013
run_passes_ipo_safe at .\../usr/share/julia/Compiler/src\optimize.jl:1027 [inlined]
optimize at .\../usr/share/julia/Compiler/src\optimize.jl:1002
jfptr_optimize_83077.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
finish_nocycle at .\../usr/share/julia/Compiler/src\typeinfer.jl:202
jfptr_finish_nocycle_84273.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
typeinf at .\../usr/share/julia/Compiler/src\abstractinterpretation.jl:4507
typeinf_ext at .\../usr/share/julia/Compiler/src\typeinfer.jl:1259
typeinf_ext_toplevel at .\../usr/share/julia/Compiler/src\typeinfer.jl:1442 [inlined]
typeinf_ext_toplevel at .\../usr/share/julia/Compiler/src\typeinfer.jl:1451
jfptr_typeinf_ext_toplevel_84114.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
jl_apply at C:/workdir/src\julia.h:2391 [inlined]
jl_type_infer at C:/workdir/src\gf.c:462
jl_compile_method_internal at C:/workdir/src\gf.c:3512
_jl_invoke at C:/workdir/src\gf.c:4002 [inlined]
ijl_apply_generic at C:/workdir/src\gf.c:4210
getindex at .\broadcast.jl:616 [inlined]
getindex at C:\Users\djv23\.julia\packages\LazyArrays\gHXdm\src\lazybroadcasting.jl:113
unknown function (ip: 0000018afccb9814) at (unknown file)
getindex at C:\workdir\usr\share\julia\stdlib\v1.12\LinearAlgebra\src\adjtrans.jl:342
unknown function (ip: 0000018afccb9314) at (unknown file)
_getindex at .\abstractarray.jl:1371 [inlined]
getindex at .\abstractarray.jl:1342 [inlined]
vcat_getindex_recursive at C:\Users\djv23\.julia\packages\LazyArrays\gHXdm\src\lazyconcat.jl:70 [inlined]
vcat_getindex_recursive at C:\Users\djv23\.julia\packages\LazyArrays\gHXdm\src\lazyconcat.jl:71 [inlined]
vcat_getindex at C:\Users\djv23\.julia\packages\LazyArrays\gHXdm\src\lazyconcat.jl:53 [inlined]
getindex at C:\Users\djv23\.julia\packages\LazyArrays\gHXdm\src\lazyconcat.jl:86 [inlined]
inbands_getindex at C:\Users\djv23\.julia\packages\BandedMatrices\Vz6Ql\src\banded\BandedMatrix.jl:396 [inlined]
banded_getindex at C:\Users\djv23\.julia\packages\BandedMatrices\Vz6Ql\src\banded\BandedMatrix.jl:414 [inlined]
getindex at C:\Users\djv23\.julia\packages\BandedMatrices\Vz6Ql\src\banded\BandedMatrix.jl:424 [inlined]
isassigned at .\multidimensional.jl:1653 [inlined]
isassigned at C:\workdir\usr\share\julia\stdlib\v1.12\LinearAlgebra\src\adjtrans.jl:341
unknown function (ip: 0000018afccb4304) at (unknown file)
alignment at .\arrayshow.jl:68
_print_matrix at .\arrayshow.jl:207
unknown function (ip: 0000018afccb1b9e) at (unknown file)
print_matrix at .\arrayshow.jl:171
print_matrix at .\arrayshow.jl:171 [inlined]
print_array at .\arrayshow.jl:358 [inlined]
show at .\arrayshow.jl:399
unknown function (ip: 0000018afccaeeb1) at (unknown file)
show_repl at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:548
show_limited at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:517
#display##0 at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:540
jfptr_YY.displayYY.YY.0_18749.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\share\julia\compiled\v1.12\REPL\u0gqU_hz07T.dll (unknown line)
with_repl_linfo at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:833
jfptr_with_repl_linfo_18330.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\share\julia\compiled\v1.12\REPL\u0gqU_hz07T.dll (unknown line)
display at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:526
display at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:546 [inlined]
display at .\multimedia.jl:340
jfptr_display_15715.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\share\julia\compiled\v1.12\REPL\u0gqU_hz07T.dll (unknown line)
jl_apply at C:/workdir/src\julia.h:2391 [inlined]
jl_f_invokelatest at C:/workdir/src\builtins.c:881
#print_response##2 at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:590
jfptr_YY.print_responseYY.YY.2_19630.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\share\julia\compiled\v1.12\REPL\u0gqU_hz07T.dll (unknown line)
repl_backend_loop at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:445
#start_repl_backend#41 at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:427
start_repl_backend at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:424 [inlined]
#run_repl#50 at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:653
run_repl at C:\workdir\usr\share\julia\stdlib\v1.12\REPL\src\REPL.jl:639
jfptr_run_repl_19573.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\share\julia\compiled\v1.12\REPL\u0gqU_hz07T.dll (unknown line)
run_std_repl at .\client.jl:478
jfptr_run_std_repl_59774.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
jl_apply at C:/workdir/src\julia.h:2391 [inlined]
jl_f_invokelatest at C:/workdir/src\builtins.c:881
run_main_repl at .\client.jl:499
repl_main at .\client.jl:586 [inlined]
_start at .\client.jl:561
jfptr__start_40651.1 at C:\Users\djv23\.julia\juliaup\julia-1.12.1+0.x64.w64.mingw32\lib\julia\sys.dll (unknown line)
jl_apply at C:/workdir/src\julia.h:2391 [inlined]
true_main at C:/workdir/src\jlapi.c:971
jl_repl_entrypoint at C:/workdir/src\jlapi.c:1139
mainCRTStartup at C:/workdir/cli\loader_exe.c:58
BaseThreadInitThunk at C:\Windows\System32\KERNEL32.DLL (unknown line)
RtlUserThreadStart at C:\Windows\SYSTEM32\ntdll.dll (unknown line)
Allocations: 56831860 (Pool: 56828717; Big: 3143); GC: 32

If I instead go on 1.11, it's fine:

julia> using SemiclassicalOrthogonalPolynomials

julia> P = SemiclassicalJacobi(2, 0, 0, 0);

julia> diff(P).args[2]
ℵ₀×ℵ₀ adjoint(::BandedMatrices.BandedMatrix{Float64, LazyArrays.ApplyArray{Float64, 2, typeof(vcat), Tuple{LinearAlgebra.Adjoint{Float64, LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, LazyArrays.Accumulate{Float64, 1, typeof(*), Vector{Float64}, AbstractVector{Float64}}}}}, LinearAlgebra.Adjoint{Float64, LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{LazyArrays.BroadcastVector{Float64, typeof(-), Tuple{LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, LazyArrays.BroadcastVector{Float64, typeof(+), Tuple{LazyArrays.Cumsum{Float64, 1, AbstractVector{Float64}}, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(-), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{SubArray{Float64, 1, LazyArrays.ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(-), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{Int64, LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, FillArrays.Fill{Float64, 1, Tuple{InfiniteArrays.OneToInf{Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}, LazyArrays.BroadcastVector{Float64, typeof(sqrt), Tuple{LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}, SubArray{Float64, 1, LazyArrays.ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}}}}}}}}}, LazyArrays.BroadcastVector{Float64, typeof(inv), Tuple{LazyArrays.BroadcastVector{Float64, typeof(sqrt), Tuple{LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}, SubArray{Float64, 1, LazyArrays.ApplyArray{Float64, 1, typeof(vcat), Tuple{Float64, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfUnitRange{Int64}}}, LazyArrays.BroadcastVector{Int64, typeof(*), Tuple{InfiniteArrays.InfStepRange{Int64, Int64}, InfiniteArrays.InfStepRange{Int64, Int64}}}}}, Float64}}}}, Tuple{InfiniteArrays.InfUnitRange{Int64}}, true}}}}}}}}}}}}}, LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{InfiniteArrays.InfUnitRange{Int64}, LazyArrays.BroadcastVector{Float64, typeof(+), Tuple{LazyArrays.BroadcastVector{Float64, typeof(*), Tuple{LazyArrays.BroadcastVector{Float64, typeof(inv), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}, SemiclassicalOrthogonalPolynomials.MulAddAccumulate{Float64}}}, LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{LazyArrays.BroadcastVector{Float64, typeof(-), Tuple{LazyArrays.BroadcastVector{Float64, typeof(/), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}, InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}}}, LazyArrays.BroadcastVector{Float64, typeof(inv), Tuple{InfiniteLinearAlgebra.TridiagonalConjugationBand{Float64}}}}}}}}}}}, LazyArrays.Accumulate{Float64, 1, typeof(*), Vector{Float64}, AbstractVector{Float64}}}}}}}, InfiniteArrays.OneToInf{Int64}}) with eltype Float64 with indices OneToInf()×OneToInf():
  ⋅   3.4641  -0.894427    ⋅         ⋅         ⋅       …
  ⋅    ⋅       5.93296   -1.36753    ⋅         ⋅
  ⋅    ⋅        ⋅         8.37436  -1.80534    ⋅
  ⋅    ⋅        ⋅          ⋅       10.8047   -2.23245
  ⋅    ⋅        ⋅          ⋅         ⋅       13.2294
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅       …
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅       …
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
  ⋅    ⋅        ⋅          ⋅         ⋅         ⋅
 ⋮                                            ⋮        ⋱

The tests on 1.12 have a versioninfo():

julia> versioninfo()
Julia Version 1.12.1
Commit ba1e628ee4 (2025-10-17 13:02 UTC)
Build Info:
  Official https://julialang.org release
Platform Info:
  OS: Windows (x86_64-w64-mingw32)
  CPU: 24 × AMD Ryzen Threadripper PRO 7945WX 12-Cores
  WORD_SIZE: 64
  LLVM: libLLVM-18.1.7 (ORCJIT, znver4)
  GC: Built with stock GC
Threads: 1 default, 1 interactive, 1 GC (on 24 virtual cores)

[DanielVandH]

A similar error when building diff(P).args[2] directly (it's a screenshot since VSCode just crashes before I can copy it - I don't get this same crash report in the command prompt directly...)

The code I'm pasting here is

using SemiclassicalOrthogonalPolynomials, ClassicalOrthogonalPolynomials, LazyArrays, Test
import ClassicalOrthogonalPolynomials: recurrencecoefficients, _BandedMatrix, _p0, Weighted
import LazyArrays: Accumulate, AccumulateAbstractVector
import SemiclassicalOrthogonalPolynomials: MulAddAccumulate, HalfWeighted, toclassical
import LinearAlgebra: norm, triu
        P = SemiclassicalJacobi(2,0,0,0);
        Q = SemiclassicalJacobi(2,1,1,1,P);
        D = SemiclassicalOrthogonalPolynomials.divdiff(P,Q);
        A,B,_ = recurrencecoefficients(P);
        α,β,_ = recurrencecoefficients(Q);
        d = AccumulateAbstractVector(*, A ./ Vcat(1,α));
        v1 = AccumulateAbstractVector(+, B ./ A);
        v2 = MulAddAccumulate(Vcat(0,0,α[2:∞]) ./ α, Vcat(0,β ./ α) ./ α);
        v3 = AccumulateAbstractVector(*, Vcat(A[1]A[2], A[3:∞] ./ α));
        D2 = _BandedMatrix(Vcat(((1:∞) .* d)', (((1:∞) .* (v1 .+ B[2:end]./A[2:end]) .- (2:∞) .* (α .* v2 .+ β ./ α)) .* v3)'), ∞, 2,-1)';

Any thoughts on what may be happening here (if it's not just unique to my machine)?

[dlfivefifty]

This is definitely a Julia bug... jl_compile_method_internal is a red flag

[DanielVandH]

I'll submit an issue at the Julia repo soon then