Improve inference in vcat (#2559)

Author: timholy

src/abstractdataframe/abstractdataframe.jl

@@ -1023,7 +1023,7 @@ end
 
 _filter_helper(f, cols...)::BitVector = ((x...) -> f(x...)::Bool).(cols...)
 
-@inline function Base.filter((cols, f)::Pair{<:AsTable}, df::AbstractDataFrame;
+@inline function Base.filter((cols, f)::Pair{AsTable}, df::AbstractDataFrame;
                              view::Bool=false)
     df_tmp = select(df, cols.cols, copycols=false)
     if ncol(df_tmp) == 0
@@ -1547,14 +1547,15 @@ Base.vcat(dfs::AbstractDataFrame...;
                       AbstractVector{<:AbstractString}}=:setequal) =
     reduce(vcat, dfs; cols=cols)
 
-Base.reduce(::typeof(vcat),
-            dfs::Union{AbstractVector{<:AbstractDataFrame},
-                       Tuple{Vararg{AbstractDataFrame}}};
-            cols::Union{Symbol, AbstractVector{Symbol},
-                        AbstractVector{<:AbstractString}}=:setequal) =
-    _vcat([df for df in dfs if ncol(df) != 0]; cols=cols)
+function Base.reduce(::typeof(vcat),
+                     dfs::Union{AbstractVector{<:AbstractDataFrame},
+                                Tuple{AbstractDataFrame, Vararg{AbstractDataFrame}}};
+                     cols::Union{Symbol, AbstractVector{Symbol},
+                     AbstractVector{<:AbstractString}}=:setequal)
+    return _vcat(AbstractDataFrame[df for df in dfs if ncol(df) != 0]; cols=cols)
+end
 
-function _vcat(dfs::AbstractVector{<:AbstractDataFrame};
+function _vcat(dfs::AbstractVector{AbstractDataFrame};
                cols::Union{Symbol, AbstractVector{Symbol},
                            AbstractVector{<:AbstractString}}=:setequal)
 
@@ -1586,13 +1587,15 @@ function _vcat(dfs::AbstractVector{<:AbstractDataFrame};
 
         if !isempty(coldiff)
             # if any DataFrames are a full superset of names, skip them
-            filter!(u -> !issetequal(u, header), uniqueheaders)
+            let header=header     # julia #15276
+                filter!(u -> !issetequal(u, header), uniqueheaders)
+            end
             estrings = map(enumerate(uniqueheaders)) do (i, head)
                 matching = findall(h -> head == h, allheaders)
                 headerdiff = setdiff(coldiff, head)
-                cols = join(headerdiff, ", ", " and ")
+                badcols = join(headerdiff, ", ", " and ")
                 args = join(matching, ", ", " and ")
-                return "column(s) $cols are missing from argument(s) $args"
+                return "column(s) $badcols are missing from argument(s) $args"
             end
             throw(ArgumentError(join(estrings, ", ", ", and ")))
         end

src/groupeddataframe/splitapplycombine.jl

@@ -489,7 +489,7 @@ function prepare_idx_keeprows(idx::AbstractVector{<:Integer},
 end
 
 function _combine(gd::GroupedDataFrame,
-                  @nospecialize(cs_norm::Vector{Any}), optional_transform::Vector{Bool},
+                  cs_norm::Vector{Any}, optional_transform::Vector{Bool},
                   copycols::Bool, keeprows::Bool, renamecols::Bool, nthreads::Int)
     if isempty(cs_norm)
         if keeprows && nrow(parent(gd)) > 0 && minimum(gd.groups) == 0

src/other/index.jl

@@ -422,7 +422,7 @@ Base.@propagate_inbounds SubIndex(parent::AbstractIndex, cols) =
     SubIndex(parent, parent[cols])
 
 Base.length(x::SubIndex) = length(x.cols)
-Base.names(x::SubIndex) = string.(_names(x))
+Base.names(x::SubIndex) = string.(_names(x))::Vector{String}
 _names(x::SubIndex) = view(_names(x.parent), x.cols)
 
 function Base.haskey(x::SubIndex, key::Symbol)