# This file is a part of Julia. License is MIT: https://julialang.org/license # generic operations on dictionaries """ KeyError(key) An indexing operation into an `AbstractDict` (`Dict`) or `Set` like object tried to access or delete a non-existent element. """ struct KeyError <: Exception key end const secret_table_token = :__c782dbf1cf4d6a2e5e3865d7e95634f2e09b5902__ haskey(d::AbstractDict, k) = in(k, keys(d)) function in(p::Pair, a::AbstractDict, valcmp=(==)) v = get(a,p[1],secret_table_token) if v !== secret_table_token return valcmp(v, p[2]) end return false end function in(p, a::AbstractDict) error("""AbstractDict collections only contain Pairs; Either look for e.g. A=>B instead, or use the `keys` or `values` function if you are looking for a key or value respectively.""") end function summary(io::IO, t::AbstractDict) n = length(t) showarg(io, t, true) print(io, " with ", n, (n==1 ? " entry" : " entries")) end struct KeySet{K, T <: AbstractDict{K}} <: AbstractSet{K} dict::T end struct ValueIterator{T<:AbstractDict} dict::T end function summary(io::IO, iter::T) where {T<:Union{KeySet,ValueIterator}} print(io, T.name, " for a ") summary(io, iter.dict) end show(io::IO, iter::Union{KeySet,ValueIterator}) = show_vector(io, iter) length(v::Union{KeySet,ValueIterator}) = length(v.dict) isempty(v::Union{KeySet,ValueIterator}) = isempty(v.dict) _tt2(::Type{Pair{A,B}}) where {A,B} = B eltype(::Type{ValueIterator{D}}) where {D} = _tt2(eltype(D)) function iterate(v::Union{KeySet,ValueIterator}, state...) y = iterate(v.dict, state...) y === nothing && return nothing return (y[1][isa(v, KeySet) ? 1 : 2], y[2]) end in(k, v::KeySet) = get(v.dict, k, secret_table_token) !== secret_table_token """ keys(iterator) For an iterator or collection that has keys and values (e.g. arrays and dictionaries), return an iterator over the keys. """ function keys end """ keys(a::AbstractDict) Return an iterator over all keys in a dictionary. `collect(keys(a))` returns an array of keys. When the keys are stored internally in a hash table, as is the case for `Dict`, the order in which they are returned may vary. But `keys(a)` and `values(a)` both iterate `a` and return the elements in the same order. # Examples ```jldoctest julia> D = Dict('a'=>2, 'b'=>3) Dict{Char,Int64} with 2 entries: 'a' => 2 'b' => 3 julia> collect(keys(D)) 2-element Array{Char,1}: 'a' 'b' ``` """ keys(a::AbstractDict) = KeySet(a) """ values(a::AbstractDict) Return an iterator over all values in a collection. `collect(values(a))` returns an array of values. When the values are stored internally in a hash table, as is the case for `Dict`, the order in which they are returned may vary. But `keys(a)` and `values(a)` both iterate `a` and return the elements in the same order. # Examples ```jldoctest julia> D = Dict('a'=>2, 'b'=>3) Dict{Char,Int64} with 2 entries: 'a' => 2 'b' => 3 julia> collect(values(D)) 2-element Array{Int64,1}: 2 3 ``` """ values(a::AbstractDict) = ValueIterator(a) """ pairs(collection) Return an iterator over `key => value` pairs for any collection that maps a set of keys to a set of values. This includes arrays, where the keys are the array indices. """ pairs(collection) = Generator(=>, keys(collection), values(collection)) pairs(a::AbstractDict) = a """ empty(a::AbstractDict, [index_type=keytype(a)], [value_type=valtype(a)]) Create an empty `AbstractDict` container which can accept indices of type `index_type` and values of type `value_type`. The second and third arguments are optional and default to the input's `keytype` and `valtype`, respectively. (If only one of the two types is specified, it is assumed to be the `value_type`, and the `index_type` we default to `keytype(a)`). Custom `AbstractDict` subtypes may choose which specific dictionary type is best suited to return for the given index and value types, by specializing on the three-argument signature. The default is to return an empty `Dict`. """ empty(a::AbstractDict) = empty(a, keytype(a), valtype(a)) empty(a::AbstractDict, ::Type{V}) where {V} = empty(a, keytype(a), V) # Note: this is the form which makes sense for `Vector`. copy(a::AbstractDict) = merge!(empty(a), a) copy!(dst::AbstractDict, src::AbstractDict) = merge!(empty!(dst), src) """ merge!(d::AbstractDict, others::AbstractDict...) Update collection with pairs from the other collections. See also [`merge`](@ref). # Examples ```jldoctest julia> d1 = Dict(1 => 2, 3 => 4); julia> d2 = Dict(1 => 4, 4 => 5); julia> merge!(d1, d2); julia> d1 Dict{Int64,Int64} with 3 entries: 4 => 5 3 => 4 1 => 4 ``` """ function merge!(d::AbstractDict, others::AbstractDict...) for other in others for (k,v) in other d[k] = v end end return d end """ merge!(combine, d::AbstractDict, others::AbstractDict...) Update collection with pairs from the other collections. Values with the same key will be combined using the combiner function. # Examples ```jldoctest julia> d1 = Dict(1 => 2, 3 => 4); julia> d2 = Dict(1 => 4, 4 => 5); julia> merge!(+, d1, d2); julia> d1 Dict{Int64,Int64} with 3 entries: 4 => 5 3 => 4 1 => 6 julia> merge!(-, d1, d1); julia> d1 Dict{Int64,Int64} with 3 entries: 4 => 0 3 => 0 1 => 0 ``` """ function merge!(combine::Function, d::AbstractDict, others::AbstractDict...) for other in others for (k,v) in other d[k] = haskey(d, k) ? combine(d[k], v) : v end end return d end """ keytype(type) Get the key type of an dictionary type. Behaves similarly to [`eltype`](@ref). # Examples ```jldoctest julia> keytype(Dict(Int32(1) => "foo")) Int32 ``` """ keytype(::Type{<:AbstractDict{K,V}}) where {K,V} = K keytype(a::AbstractDict) = keytype(typeof(a)) """ valtype(type) Get the value type of an dictionary type. Behaves similarly to [`eltype`](@ref). # Examples ```jldoctest julia> valtype(Dict(Int32(1) => "foo")) String ``` """ valtype(::Type{<:AbstractDict{K,V}}) where {K,V} = V valtype(a::AbstractDict) = valtype(typeof(a)) """ merge(d::AbstractDict, others::AbstractDict...) Construct a merged collection from the given collections. If necessary, the types of the resulting collection will be promoted to accommodate the types of the merged collections. If the same key is present in another collection, the value for that key will be the value it has in the last collection listed. # Examples ```jldoctest julia> a = Dict("foo" => 0.0, "bar" => 42.0) Dict{String,Float64} with 2 entries: "bar" => 42.0 "foo" => 0.0 julia> b = Dict("baz" => 17, "bar" => 4711) Dict{String,Int64} with 2 entries: "bar" => 4711 "baz" => 17 julia> merge(a, b) Dict{String,Float64} with 3 entries: "bar" => 4711.0 "baz" => 17.0 "foo" => 0.0 julia> merge(b, a) Dict{String,Float64} with 3 entries: "bar" => 42.0 "baz" => 17.0 "foo" => 0.0 ``` """ merge(d::AbstractDict, others::AbstractDict...) = merge!(_typeddict(d, others...), others...) """ merge(combine, d::AbstractDict, others::AbstractDict...) Construct a merged collection from the given collections. If necessary, the types of the resulting collection will be promoted to accommodate the types of the merged collections. Values with the same key will be combined using the combiner function. # Examples ```jldoctest julia> a = Dict("foo" => 0.0, "bar" => 42.0) Dict{String,Float64} with 2 entries: "bar" => 42.0 "foo" => 0.0 julia> b = Dict("baz" => 17, "bar" => 4711) Dict{String,Int64} with 2 entries: "bar" => 4711 "baz" => 17 julia> merge(+, a, b) Dict{String,Float64} with 3 entries: "bar" => 4753.0 "baz" => 17.0 "foo" => 0.0 ``` """ merge(combine::Function, d::AbstractDict, others::AbstractDict...) = merge!(combine, _typeddict(d, others...), others...) promoteK(K) = K promoteV(V) = V promoteK(K, d, ds...) = promoteK(promote_type(K, keytype(d)), ds...) promoteV(V, d, ds...) = promoteV(promote_type(V, valtype(d)), ds...) function _typeddict(d::AbstractDict, others::AbstractDict...) K = promoteK(keytype(d), others...) V = promoteV(valtype(d), others...) Dict{K,V}(d) end """ filter!(f, d::AbstractDict) Update `d`, removing elements for which `f` is `false`. The function `f` is passed `key=>value` pairs. # Example ```jldoctest julia> d = Dict(1=>"a", 2=>"b", 3=>"c") Dict{Int64,String} with 3 entries: 2 => "b" 3 => "c" 1 => "a" julia> filter!(p->isodd(p.first), d) Dict{Int64,String} with 2 entries: 3 => "c" 1 => "a" ``` """ function filter!(f, d::AbstractDict) badkeys = Vector{keytype(d)}() for pair in d # don't delete!(d, k) here, since dictionary types # may not support mutation during iteration f(pair) || push!(badkeys, pair.first) end for k in badkeys delete!(d, k) end return d end function filter_in_one_pass!(f, d::AbstractDict) for pair in d if !f(pair) delete!(d, pair.first) end end return d end """ filter(f, d::AbstractDict) Return a copy of `d`, removing elements for which `f` is `false`. The function `f` is passed `key=>value` pairs. # Examples ```jldoctest julia> d = Dict(1=>"a", 2=>"b") Dict{Int64,String} with 2 entries: 2 => "b" 1 => "a" julia> filter(p->isodd(p.first), d) Dict{Int64,String} with 1 entry: 1 => "a" ``` """ function filter(f, d::AbstractDict) # don't just do filter!(f, copy(d)): avoid making a whole copy of d df = empty(d) try for pair in d if f(pair) df[pair.first] = pair.second end end catch e if isa(e, MethodError) && e.f === f depwarn("In `filter(f, dict)`, `f` is now passed a single pair instead of two arguments.", :filter) for (k, v) in d if f(k, v) df[k] = v end end else rethrow() end end return df end function eltype(::Type{<:AbstractDict{K,V}}) where {K,V} if @isdefined(K) if @isdefined(V) return Pair{K,V} else return Pair{K} end elseif @isdefined(V) return Pair{k,V} where k else return Pair end end function isequal(l::AbstractDict, r::AbstractDict) l === r && return true if isa(l,IdDict) != isa(r,IdDict) return false end if length(l) != length(r) return false end for pair in l if !in(pair, r, isequal) return false end end true end function ==(l::AbstractDict, r::AbstractDict) l === r && return true if isa(l,IdDict) != isa(r,IdDict) return false end length(l) != length(r) && return false anymissing = false for pair in l isin = in(pair, r, ==) if ismissing(isin) anymissing = true elseif !isin return false end end return anymissing ? missing : true end const hasha_seed = UInt === UInt64 ? 0x6d35bb51952d5539 : 0x952d5539 function hash(a::AbstractDict, h::UInt) hv = hasha_seed for (k,v) in a hv ⊻= hash(k, hash(v)) end hash(hv, h) end function getindex(t::AbstractDict, key) v = get(t, key, secret_table_token) if v === secret_table_token throw(KeyError(key)) end return v end # t[k1,k2,ks...] is syntactic sugar for t[(k1,k2,ks...)]. (Note # that we need to avoid dispatch loops if setindex!(t,v,k) is not defined.) getindex(t::AbstractDict, k1, k2, ks...) = getindex(t, tuple(k1,k2,ks...)) setindex!(t::AbstractDict, v, k1, k2, ks...) = setindex!(t, v, tuple(k1,k2,ks...)) push!(t::AbstractDict, p::Pair) = setindex!(t, p.second, p.first) push!(t::AbstractDict, p::Pair, q::Pair) = push!(push!(t, p), q) push!(t::AbstractDict, p::Pair, q::Pair, r::Pair...) = push!(push!(push!(t, p), q), r...) # AbstractDicts are convertible convert(::Type{T}, x::T) where {T<:AbstractDict} = x function convert(::Type{T}, x::AbstractDict) where T<:AbstractDict h = T(x) if length(h) != length(x) error("key collision during dictionary conversion") end return h end # hashing objects by identity _tablesz(x::Integer) = x < 16 ? 16 : one(x)<<((sizeof(x)<<3)-leading_zeros(x-1)) """ IdDict([itr]) `IdDict{K,V}()` constructs a hash table using object-id as hash and `===` as equality with keys of type `K` and values of type `V`. See [`Dict`](@ref) for further help. """ mutable struct IdDict{K,V} <: AbstractDict{K,V} ht::Vector{Any} count::Int ndel::Int IdDict{K,V}() where {K, V} = new{K,V}(Vector{Any}(undef, 32), 0, 0) function IdDict{K,V}(itr) where {K, V} d = IdDict{K,V}() for (k,v) in itr; d[k] = v; end d end function IdDict{K,V}(pairs::Pair...) where {K, V} d = IdDict{K,V}() sizehint!(d, length(pairs)) for (k,v) in pairs; d[k] = v; end d end IdDict{K,V}(d::IdDict{K,V}) where {K, V} = new{K,V}(copy(d.ht), d.count, d.ndel) end IdDict() = IdDict{Any,Any}() IdDict(kv::Tuple{}) = IdDict() IdDict(ps::Pair{K,V}...) where {K,V} = IdDict{K,V}(ps) IdDict(ps::Pair{K}...) where {K} = IdDict{K,Any}(ps) IdDict(ps::(Pair{K,V} where K)...) where {V} = IdDict{Any,V}(ps) IdDict(ps::Pair...) = IdDict{Any,Any}(ps) TP{K,V} = Union{Type{Tuple{K,V}},Type{Pair{K,V}}} dict_with_eltype(DT_apply, kv, ::TP{K,V}) where {K,V} = DT_apply(K, V)(kv) dict_with_eltype(DT_apply, kv::Generator, ::TP{K,V}) where {K,V} = DT_apply(K, V)(kv) dict_with_eltype(DT_apply, ::Type{Pair{K,V}}) where {K,V} = DT_apply(K, V)() dict_with_eltype(DT_apply, ::Type) = DT_apply(Any, Any)() dict_with_eltype(DT_apply::F, kv, t) where {F} = grow_to!(dict_with_eltype(DT_apply, @default_eltype(typeof(kv))), kv) function dict_with_eltype(DT_apply::F, kv::Generator, t) where F T = @default_eltype(kv) if T <: Union{Pair, Tuple{Any, Any}} && isconcretetype(T) return dict_with_eltype(DT_apply, kv, T) end return grow_to!(dict_with_eltype(DT_apply, T), kv) end function IdDict(kv) try dict_with_eltype((K, V) -> IdDict{K, V}, kv, eltype(kv)) catch if !applicable(iterate, kv) || !all(x->isa(x,Union{Tuple,Pair}),kv) throw(ArgumentError( "IdDict(kv): kv needs to be an iterator of tuples or pairs")) else rethrow() end end end empty(d::IdDict, ::Type{K}, ::Type{V}) where {K, V} = IdDict{K,V}() function rehash!(d::IdDict, newsz = length(d.ht)) d.ht = ccall(:jl_idtable_rehash, Vector{Any}, (Any, Csize_t), d.ht, newsz) d end function sizehint!(d::IdDict, newsz) newsz = _tablesz(newsz*2) # *2 for keys and values in same array oldsz = length(d.ht) # grow at least 25% if newsz < (oldsz*5)>>2 return d end rehash!(d, newsz) end function setindex!(d::IdDict{K,V}, @nospecialize(val), @nospecialize(key)) where {K, V} !isa(key, K) && throw(ArgumentError("$(limitrepr(key)) is not a valid key for type $K")) if !(val isa V) # avoid a dynamic call val = convert(V, val) end if d.ndel >= ((3*length(d.ht))>>2) rehash!(d, max(length(d.ht)>>1, 32)) d.ndel = 0 end inserted = RefValue{Cint}(0) d.ht = ccall(:jl_eqtable_put, Array{Any,1}, (Any, Any, Any, Ptr{Cint}), d.ht, key, val, inserted) d.count += inserted[] return d end function get(d::IdDict{K,V}, @nospecialize(key), @nospecialize(default)) where {K, V} val = ccall(:jl_eqtable_get, Any, (Any, Any, Any), d.ht, key, default) val === default ? default : val::V end function getindex(d::IdDict{K,V}, @nospecialize(key)) where {K, V} val = get(d, key, secret_table_token) val === secret_table_token && throw(KeyError(key)) return val::V end function pop!(d::IdDict{K,V}, @nospecialize(key), @nospecialize(default)) where {K, V} found = RefValue{Cint}(0) val = ccall(:jl_eqtable_pop, Any, (Any, Any, Any, Ptr{Cint}), d.ht, key, default, found) if found[] === Cint(0) return default else d.count -= 1 d.ndel += 1 return val::V end end function pop!(d::IdDict{K,V}, @nospecialize(key)) where {K, V} val = pop!(d, key, secret_table_token) val === secret_table_token && throw(KeyError(key)) return val::V end function delete!(d::IdDict{K}, @nospecialize(key)) where K pop!(d, key, secret_table_token) d end function empty!(d::IdDict) resize!(d.ht, 32) ccall(:memset, Ptr{Cvoid}, (Ptr{Cvoid}, Cint, Csize_t), d.ht, 0, sizeof(d.ht)) d.ndel = 0 d.count = 0 return d end _oidd_nextind(a, i) = reinterpret(Int, ccall(:jl_eqtable_nextind, Csize_t, (Any, Csize_t), a, i)) function iterate(d::IdDict{K,V}, idx=0) where {K, V} idx = _oidd_nextind(d.ht, idx) idx == -1 && return nothing return (Pair{K, V}(d.ht[idx + 1]::K, d.ht[idx + 2]::V), idx + 2) end length(d::IdDict) = d.count copy(d::IdDict) = typeof(d)(d) get!(d::IdDict{K,V}, @nospecialize(key), @nospecialize(default)) where {K, V} = (d[key] = get(d, key, default))::V function get(default::Callable, d::IdDict{K,V}, @nospecialize(key)) where {K, V} val = get(d, key, secret_table_token) if val === secret_table_token val = default() end return val end function get!(default::Callable, d::IdDict{K,V}, @nospecialize(key)) where {K, V} val = get(d, key, secret_table_token) if val === secret_table_token val = default() setindex!(d, val, key) end return val end in(@nospecialize(k), v::KeySet{<:Any,<:IdDict}) = get(v.dict, k, secret_table_token) !== secret_table_token # For some AbstractDict types, it is safe to implement filter! # by deleting keys during iteration. filter!(f, d::IdDict) = filter_in_one_pass!(f, d) # Like Set, but using IdDict mutable struct IdSet{T} <: AbstractSet{T} dict::IdDict{T,Nothing} IdSet{T}() where {T} = new(IdDict{T,Nothing}()) IdSet{T}(s::IdSet{T}) where {T} = new(copy(s.dict)) end IdSet{T}(itr) where {T} = union!(IdSet{T}(), itr) IdSet() = IdSet{Any}() copymutable(s::IdSet) = typeof(s)(s) copy(s::IdSet) = typeof(s)(s) isempty(s::IdSet) = isempty(s.dict) length(s::IdSet) = length(s.dict) in(@nospecialize(x), s::IdSet) = haskey(s.dict, x) push!(s::IdSet, @nospecialize(x)) = (s.dict[x] = nothing; s) pop!(s::IdSet, @nospecialize(x)) = (pop!(s.dict, x); x) pop!(s::IdSet, @nospecialize(x), @nospecialize(default)) = (x in s ? pop!(s, x) : default) delete!(s::IdSet, @nospecialize(x)) = (delete!(s.dict, x); s) sizehint!(s::IdSet, newsz) = (sizehint!(s.dict, newsz); s) empty!(s::IdSet) = (empty!(s.dict); s) filter!(f, d::IdSet) = unsafe_filter!(f, d) function iterate(s::IdSet, state...) y = iterate(s.dict, state...) y === nothing && return nothing ((k, _), i) = y return (k, i) end """ map!(f, values(dict::AbstractDict)) Modifies `dict` by transforming each value from `val` to `f(val)`. Note that the type of `dict` cannot be changed: if `f(val)` is not an instance of the key type of `dict` then it will be converted to the key type if possible and otherwise raise an error. # Examples ```jldoctest julia> d = Dict(:a => 1, :b => 2) Dict{Symbol,Int64} with 2 entries: :a => 1 :b => 2 julia> map!(v -> v-1, values(d)) Base.ValueIterator for a Dict{Symbol,Int64} with 2 entries. Values: 0 1 ``` """ function map!(f, iter::ValueIterator) # This is the naive fallback which requires hash evaluations # Contrary to the example Dict has an implementation which does not require hash evaluations dict = iter.dict for (key, val) in pairs(dict) dict[key] = f(val) end return iter end