How do I find the shadow price of anonymous constraints?

Hello! I have a model in which I need to create constraints for the non-zero elements of a sparse matrix (a parameter). I create them as anonymous constraints, but I do not know how to find their dual values after the model runs to optimality. Any help will be appreciated!
I am using Julia 1.04 and JuMP 0.20.
Leonardo Rivera.

You need to use the constraint references returned by the @constraint macro, e.g.

con_refs = Dict{Tuple{Int, Int}, JuMP.ConstraintRef}()
for col in 1:size(A, 2)
    for k in nzrange(A, col)
        row = rowvals(A)[k]
        val = nonzeros(A)[k]
        con_refs[(row, col)] = @constraint(model, val == 0)
duals = Dict(key => dual(value) for (key, value) in con_refs)

Thanks a lot. Your answer worked perfectly!

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