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This release repairs the JuliaCall path of the Julia backend, which
had drifted out of sync with current SymbolicRegression.jl
(tested against 1.13.2) and failed for all users on that path. The
underlying engine was working; the R-side glue was not.
setup_julia_backend() reported the backend
as unavailable even when it was installed. The
installed-package check used an incorrect hard-coded UUID for
SymbolicRegression.jl
(8254be44-1295-4e6a-a16d-e31fe2c4a48b); the correct UUID is
8254be44-1295-4e6a-a16d-46603ac705cb. The check now
succeeds, so setup_julia_backend() returns
TRUE when the package is present.
symbolic_search(backend = "julia") failed
with a single predictor. A one-column predictors
produced a length-1 character vector that JuliaCall transfers to Julia
as a scalar String, while SymbolicRegression’s
variable_names argument requires an
AbstractVector{String}
(TypeError: in keyword argument variable_names ...).
variable_names is now coerced to a
Vector{String} on the Julia side, so single-predictor
searches work.
symbolic_search(backend = "julia") failed
when extracting results. The Hall-of-Fame extraction sent a
multi-statement Julia block through a julia_command call
that parses a single expression, raising
ParseError("extra token after end of expression") after a
successful search. The extraction block is now wrapped in
begin ... end (a single expression), so results are
returned correctly as the Pareto frontier.
These fixes restore end-to-end operation of
symbolic_search(backend = "julia") (both single- and
multi-predictor) and of setup_julia_backend() on the
JuliaCall path. No user-facing API changed.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.