[AUTO] Format files using DocumentFormat

docs/make.jl

@@ -1,14 +1,14 @@
 using Documenter, FeatherLib
 
 makedocs(
-	modules = [FeatherLib],
-	sitename = "FeatherLib.jl",
+	modules=[FeatherLib],
+	sitename="FeatherLib.jl",
 	analytics="UA-132838790-1",
-	pages = [
+	pages=[
         "Introduction" => "index.md"
     ]
 )
 
 deploydocs(
-    repo = "github.com/queryverse/FeatherLib.jl.git"
+    repo="github.com/queryverse/FeatherLib.jl.git"
 )

src/loadfile.jl

@@ -6,7 +6,7 @@ function validatefile(filename::AbstractString, data::AbstractVector{UInt8})
         throw(ArgumentError("'$file' is not in feather format: total length of file: $(length(data))"))
     end    
     header = data[1:4]
-    footer = data[(end-3):end]
+    footer = data[(end - 3):end]
     if header ≠ FEATHER_MAGIC_BYTES || footer ≠ FEATHER_MAGIC_BYTES
         throw(ArgumentError(string("'$filename' is not in feather format: header = $header, ",
             "footer = $footer.")))
@@ -21,15 +21,15 @@ function loadfile(filename::AbstractString; use_mmap::Bool=true)
 end
 
 function metalength(data::AbstractVector{UInt8})
-    read(IOBuffer(data[(length(data)-7):(length(data)-4)]), Int32)
+    read(IOBuffer(data[(length(data) - 7):(length(data) - 4)]), Int32)
 end
 
 function metaposition(data::AbstractVector{UInt8}, metalen::Integer=metalength(data))
-    length(data) - (metalen+7)
+    length(data) - (metalen + 7)
 end
 
 function rootposition(data::AbstractVector{UInt8}, mpos::Integer=metaposition(data))
-    read(IOBuffer(data[mpos:(mpos+4)]), Int32)
+    read(IOBuffer(data[mpos:(mpos + 4)]), Int32)
 end
 
 function getctable(data::AbstractVector{UInt8})

src/metadata.jl

@@ -29,7 +29,7 @@ mutable struct CategoryMetadata
     ordered::Bool
 end
 
-@DEFAULT CategoryMetadata ordered=false
+@DEFAULT CategoryMetadata ordered = false
 
 mutable struct TimestampMetadata
     unit::TimeUnit
@@ -43,7 +43,7 @@ mutable struct TimeMetadata
     unit::TimeUnit
 end
 
-@UNION TypeMetadata (Nothing,CategoryMetadata,TimestampMetadata,DateMetadata,TimeMetadata)
+@UNION TypeMetadata (Nothing, CategoryMetadata, TimestampMetadata, DateMetadata, TimeMetadata)
 
 mutable struct Column
     name::String
@@ -119,7 +119,7 @@ const JULIA_TIME_DICT = Dict{Metadata.TimeUnit,DataType}(
     Metadata.MICROSECOND => Dates.Microsecond,
     Metadata.NANOSECOND => Dates.Nanosecond
 )
-const METADATA_TIME_DICT = Dict{DataType,Metadata.TimeUnit}(v=>k for (k,v) in JULIA_TIME_DICT)
+const METADATA_TIME_DICT = Dict{DataType,Metadata.TimeUnit}(v => k for (k, v) in JULIA_TIME_DICT)
 
 
 isprimitivetype(t::Metadata.DType) = t ∉ NON_PRIMITIVE_TYPES
@@ -171,4 +171,4 @@ function getmetadata(io::IO, ::Type{T}, A::DictEncoding) where T
     Metadata.CategoryMetadata(vals, true)
 end
 
-getmetadata(io::IO, ::Type{Union{Missing, T}}, A::DictEncoding) where T = getmetadata(io, T, A)
+getmetadata(io::IO, ::Type{Union{Missing,T}}, A::DictEncoding) where T = getmetadata(io, T, A)

src/read.jl

@@ -15,12 +15,12 @@ function featherread(filename::AbstractString; use_mmap=true)
     return ResultSet(columns, colnames, ctable.description, ctable.metadata)
 end
 
-#=====================================================================================================
+#= ====================================================================================================
     new column construction stuff
-=====================================================================================================#
+==================================================================================================== =#
 Base.length(p::Metadata.PrimitiveArray) = p.length
 
-startloc(p::Metadata.PrimitiveArray) = p.offset+1
+startloc(p::Metadata.PrimitiveArray) = p.offset + 1
 
 Arrow.nullcount(p::Metadata.PrimitiveArray) = p.null_count
 
@@ -29,7 +29,7 @@ function bitmasklength(p::Metadata.PrimitiveArray)
 end
 
 function offsetslength(p::Metadata.PrimitiveArray)
-    isprimitivetype(p.dtype) ? 0 : padding((length(p)+1)*sizeof(Int32))
+    isprimitivetype(p.dtype) ? 0 : padding((length(p) + 1) * sizeof(Int32))
 end
 
 valueslength(p::Metadata.PrimitiveArray) = p.total_bytes - offsetslength(p) - bitmasklength(p)

src/write.jl

@@ -43,7 +43,7 @@ function writecontents(::Type{Metadata.PrimitiveArray}, io::IO, A::ArrowVector)
     a = position(io)
     writecontents(io, A)
     b = position(io)
-    Metadata.PrimitiveArray(A, a, b-a)
+    Metadata.PrimitiveArray(A, a, b - a)
 end
 
 
@@ -55,7 +55,7 @@ end
 
 function writemetadata(io::IO, ctable::Metadata.CTable)
     meta = FlatBuffers.build!(ctable)
-    rng = (meta.head+1):length(meta.bytes)
+    rng = (meta.head + 1):length(meta.bytes)
     writepadded(io, view(meta.bytes, rng))
     Int32(length(rng))
 end

test/runtests.jl

@@ -5,21 +5,21 @@ temps = []
 
 @testset "FeatherLib" begin
 
-include("test_readwrite.jl")
-include("test_arrow.jl")
+    include("test_readwrite.jl")
+    include("test_arrow.jl")
 
-GC.gc(); GC.gc()
-for t in temps
-    try
-        rm(t)
-    catch
-        GC.gc()
+    GC.gc(); GC.gc()
+    for t in temps
         try
             rm(t)
         catch
+            GC.gc()
+            try
+                rm(t)
+            catch
+            end
         end
     end
-end
 
 # issue #34
 # data = DataFrame(A=Union{Missing, String}[randstring(10) for i ∈ 1:100], B=rand(100))

test/test_arrow.jl

@@ -13,18 +13,18 @@ randdate() = Date(rand(0:4000), rand(1:12), rand(1:27))
 randtime() = Dates.Time(rand(0:23), rand(0:59), rand(0:59))
 randdatetime() = randdate() + randtime()
 
-randstrings() = String[[randstring(rand(0:20)) for i ∈ 1:(NROWS-1)]; "a"]
+randstrings() = String[[randstring(rand(0:20)) for i ∈ 1:(NROWS - 1)]; "a"]
 function randstrings(::Missing)
-    Union{String,Missing}[[rand(Bool) ? missing : randstring(rand(0:20)) for i ∈ 1:(NROWS-1)]; "a"]
+    Union{String,Missing}[[rand(Bool) ? missing : randstring(rand(0:20)) for i ∈ 1:(NROWS - 1)]; "a"]
 end
 
 convstring(str::AbstractString) = String(str)
 convstring(::Missing) = missing
 
 @testset "ArrowTests" begin
 
-cols = [rand(Int32,NROWS),
-    rand(Float64,NROWS),
+    cols = [rand(Int32, NROWS),
+    rand(Float64, NROWS),
     Date[randdate() for i ∈ 1:NROWS],
     DateTime[randdatetime() for i ∈ 1:NROWS],
     Dates.Time[randtime() for i ∈ 1:NROWS],
@@ -34,55 +34,53 @@ cols = [rand(Int32,NROWS),
     CategoricalArrays.categorical(randstrings()),
     CategoricalArrays.categorical(randstrings(missing))]
 
-colnames = [:ints,:floats,:dates,:datetimes,:times,:missingints,:strings,
+    colnames = [:ints,:floats,:dates,:datetimes,:times,:missingints,:strings,
     :missingstrings,:catstrings,:catstringsmissing]
 
-featherwrite(arrow_tempname, cols, colnames)
+    featherwrite(arrow_tempname, cols, colnames)
 
-ndf = featherread(arrow_tempname)
+    ndf = featherread(arrow_tempname)
 
-@test ndf.names == colnames
+    @test ndf.names == colnames
 
-@test typeof(ndf.columns[1]) == Arrow.Primitive{Int32}
-@test typeof(ndf.columns[2]) == Arrow.Primitive{Float64}
-@test typeof(ndf.columns[3]) == Arrow.Primitive{Arrow.Datestamp}
-@test typeof(ndf.columns[4]) == Arrow.Primitive{Arrow.Timestamp{Dates.Millisecond}}
-@test typeof(ndf.columns[5]) == Arrow.Primitive{Arrow.TimeOfDay{Dates.Nanosecond,Int64}}
-@test typeof(ndf.columns[6]) == Arrow.NullablePrimitive{Int64}
-@test typeof(ndf.columns[7]) == Arrow.List{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}
-@test typeof(ndf.columns[8]) == Arrow.NullableList{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}
-@test typeof(ndf.columns[9]) == Arrow.DictEncoding{String,Arrow.Primitive{Int32},
-    Arrow.List{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}}
-@test typeof(ndf.columns[10]) ==
-        Arrow.DictEncoding{Union{String,Missing},Arrow.NullablePrimitive{Int32},Arrow.List{String,Arrow.DefaultOffset,
-        Arrow.Primitive{UInt8}}}
+    @test typeof(ndf.columns[1]) == Arrow.Primitive{Int32}
+    @test typeof(ndf.columns[2]) == Arrow.Primitive{Float64}
+    @test typeof(ndf.columns[3]) == Arrow.Primitive{Arrow.Datestamp}
+    @test typeof(ndf.columns[4]) == Arrow.Primitive{Arrow.Timestamp{Dates.Millisecond}}
+    @test typeof(ndf.columns[5]) == Arrow.Primitive{Arrow.TimeOfDay{Dates.Nanosecond,Int64}}
+    @test typeof(ndf.columns[6]) == Arrow.NullablePrimitive{Int64}
+    @test typeof(ndf.columns[7]) == Arrow.List{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}
+    @test typeof(ndf.columns[8]) == Arrow.NullableList{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}
+    @test typeof(ndf.columns[9]) == Arrow.DictEncoding{String,Arrow.Primitive{Int32},Arrow.List{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}}
+    @test typeof(ndf.columns[10]) ==
+        Arrow.DictEncoding{Union{String,Missing},Arrow.NullablePrimitive{Int32},Arrow.List{String,Arrow.DefaultOffset,Arrow.Primitive{UInt8}}}
 
-for j ∈ 1:N_IDX_TESTS
-    i = rand(1:NROWS)
-    @test cols[1][i] == ndf.columns[1][i]
-    @test cols[2][i] == ndf.columns[2][i]
-    @test cols[3][i] == convert(Date, ndf.columns[3][i])
-    @test cols[4][i] == convert(DateTime, ndf.columns[4][i])
-    @test cols[5][i] == convert(Dates.Time, ndf.columns[5][i])
-    @test isequal(cols[6][i], ndf.columns[6][i])
-    @test cols[7][i] == ndf.columns[7][i]
-    @test isequal(cols[8][i], ndf.columns[8][i])
-    @test cols[9][i] == String(ndf.columns[9][i])
-    @test isequal(cols[10][i], convstring(ndf.columns[10][i]))
-end
-for j ∈ 1:N_IDX_TESTS
-    a, b = extrema(rand(1:NROWS, 2))
-    i = a:b
-    @test cols[1][i] == ndf.columns[1][i]
-    @test cols[2][i] == ndf.columns[2][i]
-    @test cols[3][i] == convert.(Date, ndf.columns[3][i])
-    @test cols[4][i] == convert.(DateTime, ndf.columns[4][i])
-    @test cols[5][i] == convert.(Dates.Time, ndf.columns[5][i])
-    @test isequal(cols[6][i], ndf.columns[6][i])
-    @test cols[7][i] == ndf.columns[7][i]
-    @test isequal(cols[8][i], ndf.columns[8][i])
-    @test cols[9][i] == String.(ndf.columns[9][i])
-    @test isequal(cols[10][i], convstring.(ndf.columns[10][i]))
-end
+    for j ∈ 1:N_IDX_TESTS
+        i = rand(1:NROWS)
+        @test cols[1][i] == ndf.columns[1][i]
+        @test cols[2][i] == ndf.columns[2][i]
+        @test cols[3][i] == convert(Date, ndf.columns[3][i])
+        @test cols[4][i] == convert(DateTime, ndf.columns[4][i])
+        @test cols[5][i] == convert(Dates.Time, ndf.columns[5][i])
+        @test isequal(cols[6][i], ndf.columns[6][i])
+        @test cols[7][i] == ndf.columns[7][i]
+        @test isequal(cols[8][i], ndf.columns[8][i])
+        @test cols[9][i] == String(ndf.columns[9][i])
+        @test isequal(cols[10][i], convstring(ndf.columns[10][i]))
+    end
+    for j ∈ 1:N_IDX_TESTS
+        a, b = extrema(rand(1:NROWS, 2))
+        i = a:b
+        @test cols[1][i] == ndf.columns[1][i]
+        @test cols[2][i] == ndf.columns[2][i]
+        @test cols[3][i] == convert.(Date, ndf.columns[3][i])
+        @test cols[4][i] == convert.(DateTime, ndf.columns[4][i])
+        @test cols[5][i] == convert.(Dates.Time, ndf.columns[5][i])
+        @test isequal(cols[6][i], ndf.columns[6][i])
+        @test cols[7][i] == ndf.columns[7][i]
+        @test isequal(cols[8][i], ndf.columns[8][i])
+        @test cols[9][i] == String.(ndf.columns[9][i])
+        @test isequal(cols[10][i], convstring.(ndf.columns[10][i]))
+    end
 
 end

test/test_readwrite.jl

@@ -4,8 +4,8 @@
     files = map(x -> joinpath(testdir, x), readdir(testdir))
 
     for f in files
-         res = featherread(f)
-         columns, headers = res.columns, res.names
+        res = featherread(f)
+        columns, headers = res.columns, res.names
 
         ncols = length(columns)
         nrows = length(columns[1])
@@ -15,23 +15,23 @@
 
         featherwrite(temp, columns, headers, description=res.description, metadata=res.metadata)
 
-         res2 = featherread(temp)
-         columns2, headers2 = res2.columns, res2.names
+        res2 = featherread(temp)
+        columns2, headers2 = res2.columns, res2.names
 
         @test length(columns2) == ncols
 
-        @test headers==headers2
+        @test headers == headers2
 
-        for (c1,c2) in zip(columns, columns2)
-            @test length(c1)==nrows
-            @test length(c2)==nrows
+        for (c1, c2) in zip(columns, columns2)
+            @test length(c1) == nrows
+            @test length(c2) == nrows
             for i = 1:nrows
                 @test isequal(c1[i], c2[i])
             end
         end
 
-    @test res.description == res2.description
-    @test res.metadata == res2.metadata
+        @test res.description == res2.description
+        @test res.metadata == res2.metadata
     # for (col1,col2) in zip(source.ctable.columns,sink.ctable.columns)
     #     @test col1.name == col2.name
     #     @test col1.metadata_type == col2.metadata_type