Automatically call eachrow for DataFrames

src/Transducers.jl

@@ -81,6 +81,9 @@ function __init__()
     @require OnlineStatsBase="925886fa-5bf2-5e8e-b522-a9147a512338" begin
         include("interop/onlinestats.jl")
     end
+    @require DataFrames="a93c6f00-e57d-5684-b7b6-d8193f3e46c0" begin
+        include("interop/dataframes.jl")
+    end
 end
 
 end # module

src/core.jl

@@ -657,6 +657,7 @@ identityof(::typeof(right), ::Any) = nothing
 
 abstract type Reducible end
 abstract type Foldable <: Reducible end
+asfoldable(x) = x
 
 abstract type AbstractInitializer end
 

src/interop/dataframes.jl

@@ -0,0 +1,3 @@
+asfoldable(df::DataFrames.AbstractDataFrame) = DataFrames.eachrow(df)
+# We can't use `Compat.eachrow` here.  See:
+# https://github.com/JuliaData/DataFrames.jl/pull/2067

src/processes.jl

@@ -345,7 +345,8 @@ _unreduced__foldl__(rf, step, coll) = unreduced(__foldl__(rf, step, coll))
     # `darkritual` below to work.
     rf = maybe_usesimd(rf0, simd)
     state = _start_init(rf, init)
-    result = __foldl__(rf, state, coll)
+    foldable = asfoldable(coll)
+    result = __foldl__(rf, state, foldable)
     if unreduced(result) isa DefaultInit
         throw(EmptyResultError(rf0))
         # Should I check if `init` is a `MissingInit`?
@@ -366,7 +367,7 @@ _unreduced__foldl__(rf, step, coll) = unreduced(__foldl__(rf, step, coll))
         # not change the return type.
         realtype = _nonidtype(Core.Compiler.return_type(
             _unreduced__foldl__,
-            typeof((rf0, state, coll)),
+            typeof((rf0, state, foldable)),
         ))
         if realtype isa Type
             realvalue = convert(realtype, ur_result)
@@ -633,7 +634,13 @@ julia> @assert copy(Map(x -> (a=x, b=x^2)), Table, 1:1) == Table(a=[1], b=[1])
 julia> using StructArrays
 
 julia> @assert copy(Map(x -> (a=x, b=x^2)), StructVector, 1:1) == StructVector(a=[1], b=[1])
-```
+
+julia> using DataFrames
+
+julia> @assert copy(
+           Map(x -> (A = x.a + 1, B = x.b + 1)),
+           DataFrame(a = [1], b = [2]),
+       ) == DataFrame(A = [2], B = [3])
 """
 Base.copy(xf::Transducer, ::Type{T}, foldable) where {T} = append!!(xf, Empty(T), foldable)
 Base.copy(xf::Transducer, foldable) = copy(xf, _materializer(foldable), foldable)

test/test_copy.jl

@@ -1,7 +1,7 @@
 module TestCopy
 
 include("preamble.jl")
-using DataFrames: DataFrame
+using DataFrames: DataFrame, eachrow
 using StructArrays: StructVector
 using TypedTables: Table
 
@@ -14,7 +14,7 @@ end
 
 @testset "$copy" for copy in [copy, tcopy, dcopy]
     @testset "$copy(_, ::$(prettytypeof(src)))" for src in Any[
-        # DataFrame(a=[1], b=[2]),
+        DataFrame(a=[1], b=[2]),
         StructVector(a=[1:4;], b=[5:8;]),
         Table(a=[1:4;], b=[5:8;]),
     ]
@@ -26,7 +26,6 @@ end
     @testset "$copy(_, eachrow(df))" begin
         df = DataFrame(a=[1:4;], b=[5:8;])
         @test_broken copy(Map(identity), eachrow(df)) ==ₜ df
-        # requires https://github.com/JuliaData/DataFrames.jl/pull/2055
     end
 end