Add SciML style formatter to MLDatasets.jl

.JuliaFormatter.toml

@@ -0,0 +1 @@
+style = "sciml"

.github/workflows/FormatCheck.yml

@@ -0,0 +1,43 @@
+name: format-check
+
+on:
+  pull_request:
+    branches:
+      - master
+  push:
+    branches:
+      - master
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - '1.6' # Replace this with the minimum Julia version that your package supports. E.g. if your package requires Julia 1.5 or higher, change this to '1.5'.
+        os:
+          - ubuntu-latest
+        arch:
+          - x64
+    steps:
+      - uses: actions/checkout@v2
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - name: Install JuliaFormatter and Format
+        run: |
+          julia  -e 'using Pkg; Pkg.add(PackageSpec(name="JuliaFormatter"))'
+          julia  -e 'using JuliaFormatter; format(".", verbose=true)'
+      - name: Format check
+        run: |
+          julia -e '
+          out = Cmd(`git diff`) |> read |> String
+          if out == ""
+              exit(0)
+          else
+              @error "Some files have not been formatted !!!"
+              write(stdout, out)
+              exit(1)
+          end'

docs/make.jl

@@ -6,34 +6,24 @@ using Documenter, MLDatasets
 # Build documentation.
 # ====================
 
-makedocs(
-    modules = [MLDatasets],
-    doctest = true,
-    clean = false,
-    sitename = "MLDatasets.jl",
-    format = Documenter.HTML(
-        canonical = "https://juliadata.github.io/MLDatasets.jl/stable/",
-        assets = ["assets/favicon.ico"],
-        prettyurls = get(ENV, "CI", nothing) == "true",
-        collapselevel=3,
-    ),
-
-    authors = "Hiroyuki Shindo, Christof Stocker, Carlo Lucibello",
-
-    pages = Any[
-        "Home" => "index.md",
-        "Datasets" => Any[
-            "Graphs" => "datasets/graphs.md",
-            "Meshes" => "datasets/meshes.md",
-            "Miscellaneous" => "datasets/misc.md",
-            "Text" => "datasets/text.md",
-            "Vision" => "datasets/vision.md",
-        ],
-        "Creating Datasets" => Any["containers/overview.md"], # still experimental
-        "LICENSE.md",
-    ],
-    strict = true,
-    checkdocs = :exports
-)
+makedocs(modules = [MLDatasets],
+         doctest = true,
+         clean = false,
+         sitename = "MLDatasets.jl",
+         format = Documenter.HTML(canonical = "https://juliadata.github.io/MLDatasets.jl/stable/",
+                                  assets = ["assets/favicon.ico"],
+                                  prettyurls = get(ENV, "CI", nothing) == "true",
+                                  collapselevel = 3),
+         authors = "Hiroyuki Shindo, Christof Stocker, Carlo Lucibello",
+         pages = Any["Home" => "index.md",
+                     "Datasets" => Any["Graphs" => "datasets/graphs.md",
+                                       "Meshes" => "datasets/meshes.md",
+                                       "Miscellaneous" => "datasets/misc.md",
+                                       "Text" => "datasets/text.md",
+                                       "Vision" => "datasets/vision.md"],
+                     "Creating Datasets" => Any["containers/overview.md"], # still experimental
+                     "LICENSE.md"],
+         strict = true,
+         checkdocs = :exports)
 
 deploydocs(repo = "github.com/JuliaML/MLDatasets.jl.git")

src/MLDatasets.jl

@@ -21,15 +21,15 @@ include("require.jl") # export @require
 # In the other case instead, use `require import SomePkg` to force
 # the use to manually import.
 
-@require import JSON3="0f8b85d8-7281-11e9-16c2-39a750bddbf1"
-@require import DataFrames="a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-@require import ImageShow="4e3cecfd-b093-5904-9786-8bbb286a6a31"
-@require import Chemfiles="46823bd8-5fb3-5f92-9aa0-96921f3dd015"
+@require import JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
+@require import DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+@require import ImageShow = "4e3cecfd-b093-5904-9786-8bbb286a6a31"
+@require import Chemfiles = "46823bd8-5fb3-5f92-9aa0-96921f3dd015"
 
 # @lazy import NPZ # lazy imported by FileIO
-@lazy import Pickle="fbb45041-c46e-462f-888f-7c521cafbc2c"
-@lazy import MAT="23992714-dd62-5051-b70f-ba57cb901cac"
-@lazy import HDF5="f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
+@lazy import Pickle = "fbb45041-c46e-462f-888f-7c521cafbc2c"
+@lazy import MAT = "23992714-dd62-5051-b70f-ba57cb901cac"
+@lazy import HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
 # @lazy import JLD2
 
 export getobs, numobs # From MLUtils.jl
@@ -93,7 +93,6 @@ export Omniglot
 include("datasets/vision/svhn2.jl")
 export SVHN2
 
-
 ## Text
 
 include("datasets/text/ptblm.jl")

src/abstract_datasets.jl

@@ -9,15 +9,14 @@ Implements the following functionality:
 """
 abstract type AbstractDataset <: AbstractDataContainer end
 
-
 MLUtils.getobs(d::AbstractDataset) = d[:]
 MLUtils.getobs(d::AbstractDataset, i) = d[i]
 
-function Base.show(io::IO, d::D) where D <: AbstractDataset
+function Base.show(io::IO, d::D) where {D <: AbstractDataset}
     print(io, "$(D.name.name)()")
 end
 
-function Base.show(io::IO, ::MIME"text/plain", d::D) where D <: AbstractDataset
+function Base.show(io::IO, ::MIME"text/plain", d::D) where {D <: AbstractDataset}
     recur_io = IOContext(io, :compact => false)
 
     print(io, "dataset $(D.name.name):")  # if the type is parameterized don't print the parameters
@@ -38,7 +37,7 @@ function leftalign(s::AbstractString, n::Int)
     if m > n
         return s[1:n]
     else
-        return s * repeat(" ", n-m)
+        return s * repeat(" ", n - m)
     end
 end
 
@@ -59,19 +58,23 @@ a `features` and a `targets` fields.
 """
 abstract type SupervisedDataset <: AbstractDataset end
 
-
-Base.length(d::SupervisedDataset) = Tables.istable(d.features) ? numobs_table(d.features) :
-                                                                 numobs((d.features, d.targets))
-
+function Base.length(d::SupervisedDataset)
+    Tables.istable(d.features) ? numobs_table(d.features) :
+    numobs((d.features, d.targets))
+end
 
 # We return named tuples
-Base.getindex(d::SupervisedDataset, ::Colon) = Tables.istable(d.features) ?
-    (features = d.features, targets=d.targets) :
+function Base.getindex(d::SupervisedDataset, ::Colon)
+    Tables.istable(d.features) ?
+    (features = d.features, targets = d.targets) :
     getobs((; d.features, d.targets))
+end
 
-Base.getindex(d::SupervisedDataset, i) = Tables.istable(d.features) ?
-    (features = getobs_table(d.features, i), targets=getobs_table(d.targets, i)) :
+function Base.getindex(d::SupervisedDataset, i)
+    Tables.istable(d.features) ?
+    (features = getobs_table(d.features, i), targets = getobs_table(d.targets, i)) :
     getobs((; d.features, d.targets), i)
+end
 
 """
     UnsupervisedDataset <: AbstractDataset
@@ -81,13 +84,11 @@ Concrete dataset types inheriting from it must provide a `features` field.
 """
 abstract type UnsupervisedDataset <: AbstractDataset end
 
-
 Base.length(d::UnsupervisedDataset) = numobs(d.features)
 
 Base.getindex(d::UnsupervisedDataset, ::Colon) = getobs(d.features)
 Base.getindex(d::UnsupervisedDataset, i) = getobs(d.features, i)
 
-
 ### DOCSTRING TEMPLATES ######################
 
 # SUPERVISED TABLE
@@ -110,7 +111,6 @@ const METHODS_SUPERVISED_TABLE = """
 - `length(dataset)`: Number of observations.
 """
 
-
 # SUPERVISED ARRAY DATASET
 
 const ARGUMENTS_SUPERVISED_ARRAY = """

src/containers/cacheddataset.jl

@@ -28,8 +28,9 @@ end
 
 CachedDataset(source, cachesize::Int) = CachedDataset(source, 1:cachesize)
 
-CachedDataset(source, cacheidx::AbstractVector{<:Integer} = 1:numobs(source)) =
+function CachedDataset(source, cacheidx::AbstractVector{<:Integer} = 1:numobs(source))
     CachedDataset(source, collect(cacheidx), make_cache(source, cacheidx))
+end
 
 function Base.getindex(dataset::CachedDataset, i::Integer)
     _i = findfirst(==(i), dataset.cacheidx)

src/containers/filedataset.jl

@@ -17,19 +17,24 @@ Wrap a set of file `paths` as a dataset (traversed in the same order as `paths`)
 Alternatively, specify a `dir` and collect all paths that match a glob `pattern`
 (recursively globbing by `depth`). The glob order determines the traversal order.
 """
-struct FileDataset{F, T<:AbstractString} <: AbstractDataContainer
+struct FileDataset{F, T <: AbstractString} <: AbstractDataContainer
     loadfn::F
     paths::Vector{T}
 end
 
 FileDataset(paths) = FileDataset(FileIO.load, paths)
-FileDataset(loadfn,
-            dir::AbstractString,
-            pattern::AbstractString = "*",
-            depth = 4) = FileDataset(loadfn, rglob(pattern, string(dir), depth))
-FileDataset(dir::AbstractString, pattern::AbstractString = "*", depth = 4) =
+function FileDataset(loadfn,
+                     dir::AbstractString,
+                     pattern::AbstractString = "*",
+                     depth = 4)
+    FileDataset(loadfn, rglob(pattern, string(dir), depth))
+end
+function FileDataset(dir::AbstractString, pattern::AbstractString = "*", depth = 4)
     FileDataset(FileIO.load, dir, pattern, depth)
+end
 
 Base.getindex(dataset::FileDataset, i::Integer) = dataset.loadfn(dataset.paths[i])
-Base.getindex(dataset::FileDataset, is::AbstractVector) = map(Base.Fix1(getobs, dataset), is)
+function Base.getindex(dataset::FileDataset, is::AbstractVector)
+    map(Base.Fix1(getobs, dataset), is)
+end
 Base.length(dataset::FileDataset) = length(dataset.paths)

src/containers/hdf5dataset.jl

@@ -19,12 +19,15 @@ See [`close(::HDF5Dataset)`](@ref) for closing the underlying HDF5 file pointer.
 For array datasets, the last dimension is assumed to be the observation dimension.
 For scalar datasets, the stored value is returned by `getobs` for any index.
 """
-struct HDF5Dataset{T<:Union{HDF5.Dataset, Vector{HDF5.Dataset}}} <: AbstractDataContainer
+struct HDF5Dataset{T <: Union{HDF5.Dataset, Vector{HDF5.Dataset}}} <: AbstractDataContainer
     fid::HDF5.File
     paths::T
     shapes::Vector{Tuple}
 
-    function HDF5Dataset(fid::HDF5.File, paths::T, shapes::Vector) where T<:Union{HDF5.Dataset, Vector{HDF5.Dataset}}
+    function HDF5Dataset(fid::HDF5.File, paths::T,
+                         shapes::Vector) where {
+                                                T <:
+                                                Union{HDF5.Dataset, Vector{HDF5.Dataset}}}
         _check_hdf5_shapes(shapes) ||
             throw(ArgumentError("Cannot create HDF5Dataset for datasets with mismatched number of observations."))
 
@@ -33,11 +36,13 @@ struct HDF5Dataset{T<:Union{HDF5.Dataset, Vector{HDF5.Dataset}}} <: AbstractData
 end
 
 HDF5Dataset(fid::HDF5.File, path::HDF5.Dataset) = HDF5Dataset(fid, path, [size(path)])
-HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset}) =
+function HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset})
     HDF5Dataset(fid, paths, map(size, paths))
+end
 HDF5Dataset(fid::HDF5.File, path::AbstractString) = HDF5Dataset(fid, fid[path])
-HDF5Dataset(fid::HDF5.File, paths::Vector{<:AbstractString}) =
+function HDF5Dataset(fid::HDF5.File, paths::Vector{<:AbstractString})
     HDF5Dataset(fid, map(p -> fid[p], paths))
+end
 HDF5Dataset(file::AbstractString, paths) = HDF5Dataset(h5open(file, "r"), paths)
 
 _getobs_hdf5(dataset::HDF5.Dataset, ::Tuple{}, i) = read(dataset)
@@ -46,10 +51,12 @@ function _getobs_hdf5(dataset::HDF5.Dataset, shape, i)
 
     return dataset[I..., i]
 end
-Base.getindex(dataset::HDF5Dataset{HDF5.Dataset}, i) =
+function Base.getindex(dataset::HDF5Dataset{HDF5.Dataset}, i)
     _getobs_hdf5(dataset.paths, only(dataset.shapes), i)
-Base.getindex(dataset::HDF5Dataset{<:Vector}, i) =
+end
+function Base.getindex(dataset::HDF5Dataset{<:Vector}, i)
     Tuple(map((p, s) -> _getobs_hdf5(p, s, i), dataset.paths, dataset.shapes))
+end
 Base.length(dataset::HDF5Dataset) = last(first(filter(!isempty, dataset.shapes)))
 
 """

src/containers/jld2dataset.jl

@@ -10,7 +10,7 @@ Calling `getobs` on a `JLD2Dataset` is equivalent to mapping `getobs` on
 each dataset in `paths`.
 See [`close(::JLD2Dataset)`](@ref) for closing the underlying JLD2 file pointer.
 """
-struct JLD2Dataset{T<:JLD2.JLDFile, S<:Tuple} <: AbstractDataContainer
+struct JLD2Dataset{T <: JLD2.JLDFile, S <: Tuple} <: AbstractDataContainer
     fid::T
     paths::S
 
@@ -27,7 +27,9 @@ end
 JLD2Dataset(file::JLD2.JLDFile, path::String) = JLD2Dataset(file, (path,))
 JLD2Dataset(file::AbstractString, paths) = JLD2Dataset(jldopen(file, "r"), paths)
 
-Base.getindex(dataset::JLD2Dataset{<:JLD2.JLDFile, <:NTuple{1}}, i) = getobs(only(dataset.paths), i)
+function Base.getindex(dataset::JLD2Dataset{<:JLD2.JLDFile, <:NTuple{1}}, i)
+    getobs(only(dataset.paths), i)
+end
 Base.getindex(dataset::JLD2Dataset, i) = map(Base.Fix2(getobs, i), dataset.paths)
 Base.length(dataset::JLD2Dataset) = numobs(dataset.paths[1])
 

src/containers/tabledataset.jl

@@ -21,7 +21,6 @@ end
 TableDataset(table::T) where {T} = TableDataset{T}(table)
 TableDataset(path::AbstractString) = TableDataset(read_csv(path))
 
-
 # slow accesses based on Tables.jl
 _getobs_row(x, i) = first(Iterators.peel(Iterators.drop(x, i - 1)))
 function _getobs_column(x, i)
@@ -55,7 +54,6 @@ end
 Base.getindex(dataset::TableDataset, i) = getobs_table(dataset.table, i)
 Base.length(dataset::TableDataset) = numobs_table(dataset.table)
 
-
 # fast access for DataFrame
 # Base.getindex(dataset::TableDataset{<:DataFrame}, i) = dataset.table[i, :]
 # Base.length(dataset::TableDataset{<:DataFrame}) = nrow(dataset.table)