Update TableTraits.jl integration

REQUIRE

@@ -2,6 +2,7 @@ julia 1.0
 PyCall 1.7.2
 Lazy 0.11.4
 Compat 0.17
-TableTraits 0.0.1
-TableTraitsUtils 0.0.1
-DataValues 0.0.1
+IteratorInterfaceExtensions 0.1.1
+TableTraits 0.3.1
+TableTraitsUtils 0.3.0
+DataValues 0.4.4

src/Pandas.jl

@@ -420,10 +420,11 @@ end
 include("tabletraits.jl")
 
 function DataFrame(obj)
-    if TableTraits.isiterabletable(obj)
-        _construct_pandas_from_iterabletable(obj)
+    y = _construct_pandas_from_iterabletable(obj)
+    if y===nothing
+        return invoke(DataFrame, Tuple{Vararg{Any}}, obj)
     else
-        invoke(DataFrame, Tuple{Vararg{Any}}, obj)
+        return y
     end
 end
 

src/tabletraits.jl

@@ -1,7 +1,8 @@
+using IteratorInterfaceExtensions
 using TableTraitsUtils
 import DataValues
 
-TableTraits.isiterable(x::DataFrame) = true
+IteratorInterfaceExtensions.isiterable(x::DataFrame) = true
 TableTraits.isiterabletable(x::DataFrame) = true
 
 function TableTraits.getiterator(df::DataFrame)
@@ -13,16 +14,18 @@ function TableTraits.getiterator(df::DataFrame)
 end
 
 function _construct_pandas_from_iterabletable(source)
-    columns, column_names = create_columns_from_iterabletable(source)
-    cols = Dict(i[1]=>i[2] for i in zip(column_names, columns))
+    y = create_columns_from_iterabletable(source, errorhandling=:returnvalue)
+    y===nothing && return nothing
+    columns, column_names = y[1], y[2]
+    cols = Dict{Symbol,Any}(i[1]=>i[2] for i in zip(column_names, columns))
 
-    for (k,v) in cols
+    for (k,v) in pairs(cols)
         if eltype(v)<:DataValues.DataValue
             T = eltype(eltype(v))
             if T<:AbstractFloat
                 cols[k] = T[get(i, NaN) for i in v]
             elseif T<:Integer
-                cols[k] = Float64[isnull(i) ? NaN : Float64(get(i)) for i in v]
+                cols[k] = Float64[DataValues.isna(i) ? NaN : Float64(get(i)) for i in v]
             else
                 throw(ArgumentError("Can't create a Pandas.DataFrame from a source that has missing data."))
             end

test/runtests.jl

@@ -12,9 +12,7 @@ df = read_csv(joinpath(dirname(@__FILE__), "test.csv"))
 typeof(df)
 @test isa(df, Pandas.DataFrame)
 
-# Disabling this test until the 'queryverse' is fully
-# 1.0-compatible.
-# include("test_tabletraits.jl")
+include("test_tabletraits.jl")
 
 @test !isempty(df)
 empty!(df)

test/test_tabletraits.jl

@@ -1,11 +1,12 @@
 using Pandas
-using NamedTuples
+using IteratorInterfaceExtensions
+using TableTraits
 using DataValues
-using Base.Test
+using Test
 
 @testset "TableTraits" begin
 
-table_array = [@NT(a=1, b="John", c=3.2), @NT(a=2, b="Sally", c=5.8)]
+table_array = [(a=1, b="John", c=3.2), (a=2, b="Sally", c=5.8)]
 
 df = DataFrame(table_array)
 
@@ -16,26 +17,26 @@ df = DataFrame(table_array)
 
 @test TableTraits.isiterabletable(df) == true
 
-it = TableTraits.getiterator(df)
+it = IteratorInterfaceExtensions.getiterator(df)
 
-@test eltype(it) == @NT(a::Int, b::String, c::Float64)
+@test eltype(it) == NamedTuple{(:a,:b,:c),Tuple{Int,String,Float64}}
 
 it_collected = collect(it)
 
-@test eltype(it_collected) == @NT(a::Int, b::String, c::Float64)
+@test eltype(it_collected) == NamedTuple{(:a,:b,:c),Tuple{Int,String,Float64}}
 @test length(it_collected) == 2
-@test it_collected[1] == @NT(a=1, b="John", c=3.2)
-@test it_collected[2] == @NT(a=2, b="Sally", c=5.8)
+@test it_collected[1] == (a=1, b="John", c=3.2)
+@test it_collected[2] == (a=2, b="Sally", c=5.8)
 
-table_array2 = [@NT(a=1, b=DataValue("John"), c=3.2), @NT(a=2, b=DataValue("Sally"), c=5.8)]
+table_array2 = [(a=1, b=DataValue("John"), c=3.2), (a=2, b=DataValue("Sally"), c=5.8)]
 
 @test_throws ArgumentError DataFrame(table_array2)
 
-table_array3 = [@NT(a=DataValue{Int}(), b="John", c=DataValue(3.2)), @NT(a=DataValue(2), b="Sally", c=DataValue{Float64}())]
+table_array3 = [(a=DataValue{Int}(), b="John", c=DataValue(3.2)), (a=DataValue(2), b="Sally", c=DataValue{Float64}())]
 
 df3 = DataFrame(table_array3)
 
-it3_collected = collect(TableTraits.getiterator(df3))
+it3_collected = collect(IteratorInterfaceExtensions.getiterator(df3))
 
 @test length(it3_collected) == 2
 @test isnan(it3_collected[1].a)