add generic vector conversion jlvec() method

so that it is called to convert dataframe column with non-scalar eltype.
Also restrict the first jlvec() method to numeric eltypes.

fixes JuliaData#82

src/convert.jl

@@ -25,7 +25,7 @@ isna(x::ComplexF64) = isna(real(x)) || isna(imag(x))
 # convert R vector into Vector holding elements of type T
 # if force_missing is true, the result is always Vector{Union{T,Missing}},
 # otherwise it's Vector{T} if `rv` doesn't contain NAs
-function jlvec(::Type{T}, rv::RVEC, force_missing::Bool=true) where T
+function jlvec(::Type{T}, rv::RVEC, force_missing::Bool=true) where T <: Number
     anyna = any(isna, rv.data)
     if force_missing || anyna
         res = convert(Vector{Union{T,Missing}}, rv.data)
@@ -154,6 +154,11 @@ function jlvec(::Type{ZonedDateTime}, rv::RVEC, force_missing::Bool=true)
     return datetimes
 end
 
+# generic vector conversion
+function jlvec(::Type{T}, rv::RVEC, force_missing::Bool=true) where T
+    return sexp2julia.(rv.data)
+end
+
 function sexp2julia(rex::RSEXPREC)
     @warn "Conversion of $(typeof(rex)) to Julia is not implemented"
     return nothing
@@ -188,10 +193,10 @@ function sexp2julia(rl::RList)
         DataFrame(Any[isa(col, RAltRep) ? sexp2julia(col) : jlvec(col, false) for col in rl.data],
                   identifier.(names(rl)), makeunique=true)
     elseif hasnames(rl)
-        DictoVec(Any[sexp2julia(item) for item in rl.data], names(rl))
+        DictoVec(jlvec(Any, rl), names(rl))
     else
         # FIXME return DictoVec if forceDictoVec is on
-        map(sexp2julia, rl.data)
+        jlvec(Any, rl)
     end
 end
 

test/RDA.jl

@@ -98,6 +98,16 @@ using RData
         @test f["x"] == f["y"] == ["a", "b", "c"]
     end
 
+    @testset "List of vectors (#82)" begin
+        f = load(joinpath(rdata_path, "list_of_vec.rda"))
+        @test f["listofvec"] isa Vector
+        @test length(f["listofvec"]) == 3
+        @test isequal(f["listofvec"], [[1., 2., missing], [3., 4.], [5., 6., missing]])
+
+        @test f["testdf"] isa DataFrame
+        @test nrow(f["testdf"]) == 3
+        @test isequal(f["testdf"][!, "listascol"], [[1., 2., missing], [3., 4.], [5., 6., missing, 7.]])
+    end
 end # for ver in ...
 
 @testset "Loading AltRep-containing RData files (version=3)" begin

test/generate_rda.R

@@ -124,6 +124,13 @@ altrepnames_df <- as.data.frame(altrepnames_list)
 names(altrepnames_df) <- names(altrepnames_list)
 save(altrepnames_list, altrepnames_df, file=file.path("data_v3", "altrep_names.rda"), version=3)
 
+# list of vectors variable and list of vectors column (for #82)
+listofvec <- list(c(1, 2, NA), c(3, 4), c(5, 6, NA))
+testdf <- data.frame(a = c("a", "b", "c"))
+testdf$listascol <- list(c(1, 2, NA), c(3, 4), c(5, 6, NA, 7))
+save(listofvec, testdf, file=file.path("data_v2", "list_of_vec.rda"), version=2)
+save(listofvec, testdf, file=file.path("data_v3", "list_of_vec.rda"), version=3)
+
 # generate files using each of the supported compression types
 df <- data.frame(num = c(1.1, 2.2))
 rdata_path <- "data_v3"