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Add nrow and ncol fallback implementations #343

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Sep 19, 2023
Merged

Add nrow and ncol fallback implementations #343

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4be43d9
Add nrow and ncol fallback implementations
bkamins Sep 7, 2023
2d54a91
improve implementation of nrow and ncol
bkamins Sep 17, 2023
2bdac71
update documentation
bkamins Sep 17, 2023
7f504e9
add tests
bkamins Sep 19, 2023
be0165c
update version
bkamins Sep 19, 2023
d712af5
fix locations of method definitions
bkamins Sep 19, 2023
7c811be
add import
bkamins Sep 19, 2023
ec7fb67
fix implementation
bkamins Sep 19, 2023
88a9a79
fix Julia 1.0 tests
bkamins Sep 19, 2023
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "Tables"
uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
authors = ["quinnj <[email protected]>"]
version = "1.10.1"
version = "1.11.0"

[deps]
DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
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28 changes: 15 additions & 13 deletions docs/src/index.md
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Expand Up @@ -229,19 +229,21 @@ make my custom type valid for Tables.jl consumers?

For a type `MyTable`, the interface to becoming a proper table is straightforward:

| Required Methods | Default Definition | Brief Description |
|----------------------------------------|------------------------------|---------------------------------------------------------------------------------------------------------------------------------|
| `Tables.istable(::Type{MyTable})` | | Declare that your table type implements the interface |
| **One of:** | | |
| `Tables.rowaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.rows(::MyTable)` method |
| `Tables.rows(x::MyTable)` | | Return an `Tables.AbstractRow`-compatible iterator from your table |
| **Or:** | | |
| `Tables.columnaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.columns(::MyTable)` method |
| `Tables.columns(x::MyTable)` | | Return an `Tables.AbstractColumns`-compatible object from your table |
| **Optional methods** | | |
| `Tables.schema(x::MyTable)` | `Tables.schema(x) = nothing` | Return a [`Tables.Schema`](@ref) object from your `Tables.AbstractRow` iterator or `Tables.AbstractColumns` object; or `nothing` for unknown schema |
| `Tables.materializer(::Type{MyTable})` | `Tables.columntable` | Declare a "materializer" sink function for your table type that can construct an instance of your type from any Tables.jl input |
| `Tables.subset(x::MyTable, inds; viewhint)` | | Return a row or a sub-table of the original table
| Required Methods | Default Definition | Brief Description |
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|----------------------------------------------|------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|
| `Tables.istable(::Type{MyTable})` | | Declare that your table type implements the interface |
| **One of:** | | |
| `Tables.rowaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.rows(::MyTable)` method |
| `Tables.rows(x::MyTable)` | | Return an `Tables.AbstractRow`-compatible iterator from your table |
| **Or:** | | |
| `Tables.columnaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.columns(::MyTable)` method |
| `Tables.columns(x::MyTable)` | | Return an `Tables.AbstractColumns`-compatible object from your table |
| **Optional methods** | | |
| `Tables.schema(x::MyTable)` | `Tables.schema(x) = nothing` | Return a [`Tables.Schema`](@ref) object from your `Tables.AbstractRow` iterator or `Tables.AbstractColumns` object; or `nothing` for unknown schema |
| `Tables.materializer(::Type{MyTable})` | `Tables.columntable` | Declare a "materializer" sink function for your table type that can construct an instance of your type from any Tables.jl input |
| `Tables.subset(x::MyTable, inds; viewhint)` | | Return a row or a sub-table of the original table |
| `DataAPI.nrow(x::MyTable)` | | Return number of rows of table `x` |
| `DataAPI.ncol(x::MyTable)` | | Return number of columns of table `x` |

Based on whether your table type has defined `Tables.rows` or `Tables.columns`, you then ensure that the `Tables.AbstractRow` iterator
or `Tables.AbstractColumns` object satisfies the respective interface.
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5 changes: 5 additions & 0 deletions src/dicts.jl
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Expand Up @@ -197,3 +197,8 @@ function dictrowtable(x)
end
return DictRowTable(names, types, out)
end

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::DictRowTable) = length(table)
DataAPI.ncol(table::DictRowTable) = length(getfield(table, :names))
9 changes: 9 additions & 0 deletions src/fallbacks.jl
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Expand Up @@ -275,3 +275,12 @@ columnnames(x::CopiedColumns) = columnnames(source(x))
end
throw(ArgumentError("no default `Tables.columns` implementation for type: $T"))
end

# implement default nrow and ncol methods for DataAPI.jl

# this covers also MatrixTable
DataAPI.nrow(table::AbstractColumns) = rowcount(table)
DataAPI.ncol(table::AbstractColumns) = length(columnnames(table))

DataAPI.nrow(table::AbstractRowTable) = length(table)
DataAPI.ncol(table::AbstractRowTable) = isempty(table) ? 0 : length(columnnames(first(table)))
5 changes: 5 additions & 0 deletions src/matrix.jl
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Expand Up @@ -111,3 +111,8 @@ function matrix(table::MatrixTable; transpose::Bool=false)
return matrix
end
end

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::MatrixRowTable) = length(table)
DataAPI.ncol(table::MatrixRowTable) = size(getfield(table, :matrix), 2) # this is correct even if m is a vector
8 changes: 8 additions & 0 deletions src/namedtuples.jl
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Expand Up @@ -190,3 +190,11 @@ function columntable(itr::T) where {T}
return columntable(schema(cols), cols)
end
columntable(x::ColumnTable) = x

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::ColumnTable) = isempty(table) ? 0 : length(first(table))
DataAPI.ncol(table::ColumnTable) = length(table)

DataAPI.nrow(table::RowTable) = length(table)
DataAPI.ncol(table::RowTable) = isempty(table) ? 0 : length(first(table))
57 changes: 54 additions & 3 deletions test/runtests.jl
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@@ -1,4 +1,4 @@
using Test, Tables, OrderedCollections, TableTraits, DataValues, QueryOperators, IteratorInterfaceExtensions, SparseArrays
using Test, Tables, OrderedCollections, TableTraits, DataValues, QueryOperators, IteratorInterfaceExtensions, SparseArrays, DataAPI

@testset "utils.jl" begin

Expand Down Expand Up @@ -957,7 +957,7 @@ end
@test Tables.istable(Vector{Dict{String}})
@test Tables.istable(Vector{Dict{SubString}})
@test Tables.istable(Vector{Dict{AbstractString}})

@test Set(Tables.columnnames(Dict(:a=>1, :b=>2))) == Set([:a, :b])
@test Set(Tables.columnnames(Dict("a"=>1, "b"=>2))) == Set([:a, :b])
@test Set(Tables.columnnames(Dict("a"=>1, SubString("b")=>2))) == Set([:a, :b])
Expand All @@ -976,4 +976,55 @@ end
@test Tables.getcolumn(Dict("a"=>1, SubString("b")=>2), Int, 1, :a) == 1
@test Tables.getcolumn(Dict(SubString("a")=>1, SubString("b")=>2), Int, 1, :a) == 1
end


@testset "test nrow and ncol" begin
# AbstractColumns
@test DataAPI.nrow(Tables.CopiedColumns(NamedTuple())) == 0
@test DataAPI.ncol(Tables.CopiedColumns(NamedTuple())) == 0
@test DataAPI.nrow(Tables.CopiedColumns((a=1:3, b=2:4))) == 3
@test DataAPI.ncol(Tables.CopiedColumns((a=1:3, b=2:4))) == 2

# ColumnTable
@test DataAPI.nrow(NamedTuple()) == 0
@test DataAPI.ncol(NamedTuple()) == 0
@test DataAPI.nrow((a=1:3, b=2:4)) == 3
@test DataAPI.ncol((a=1:3, b=2:4)) == 2

# AbstractRowTable
@test DataAPI.nrow(collect(Tables.rows(Tables.table(ones(0, 0))))) == 0
@test DataAPI.ncol(collect(Tables.rows(Tables.table(ones(0, 0))))) == 0
@test DataAPI.nrow(collect(Tables.rows(Tables.table(ones(2, 3))))) == 2
@test DataAPI.ncol(collect(Tables.rows(Tables.table(ones(2, 3))))) == 3

# RowTable
@test DataAPI.nrow(NamedTuple[]) == 0
@test DataAPI.ncol(NamedTuple[]) == 0
@test DataAPI.nrow([(a=1,b=2), (a=3, b=4), (a=5, b=6)]) == 3
@test DataAPI.ncol([(a=1, b=2), (a=3, b=4), (a=5, b=6)]) == 2

# MatrixTable
@test DataAPI.nrow(Tables.table(ones(0, 0))) == 0
@test DataAPI.ncol(Tables.table(ones(0, 0))) == 0
@test DataAPI.nrow(Tables.table(ones(2, 3))) == 2
@test DataAPI.ncol(Tables.table(ones(2, 3))) == 3
@test DataAPI.nrow(Tables.table([])) == 0
@test DataAPI.ncol(Tables.table([])) == 1
@test DataAPI.nrow(Tables.table([1, 2])) == 2
@test DataAPI.ncol(Tables.table([1, 2])) == 1

# MatrixRowTable
@test DataAPI.nrow(Tables.rows(Tables.table(ones(0, 0)))) == 0
@test DataAPI.ncol(Tables.rows(Tables.table(ones(0, 0)))) == 0
@test DataAPI.nrow(Tables.rows(Tables.table(ones(2, 3)))) == 2
@test DataAPI.ncol(Tables.rows(Tables.table(ones(2, 3)))) == 3
@test DataAPI.nrow(Tables.rows(Tables.table([]))) == 0
@test DataAPI.ncol(Tables.rows(Tables.table([]))) == 1
@test DataAPI.nrow(Tables.rows(Tables.table([1, 2]))) == 2
@test DataAPI.ncol(Tables.rows(Tables.table([1, 2]))) == 1

# DictRowTable
@test DataAPI.nrow(Tables.dictrowtable(NamedTuple[])) == 0
@test DataAPI.ncol(Tables.dictrowtable(NamedTuple[])) == 0
@test DataAPI.nrow(Tables.dictrowtable([(a=1, b=2), (a=3, b=4), (a=5, b=6)])) == 3
@test DataAPI.ncol(Tables.dictrowtable([(a=1, b=2), (a=3, b=4), (a=5, b=6)])) == 2
end
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