集合和数据结构

被转换成

next = iterate(iter)
while next !== nothing
    (i, state) = next
    # body
    next = iterate(iter, state)
end

state 对象可以是任何对象，并且对于每个可迭代类型应该选择合适的 state 对象。请参照来获取关于定义一个常见迭代类型的更多细节。

Base.iterate — Function

iterate(iter [, state]) -> Union{Nothing, Tuple{Any, Any}}

Advance the iterator to obtain the next element. If no elements remain, nothing should be returned. Otherwise, a 2-tuple of the next element and the new iteration state should be returned.

Base.IteratorSize — Type

IteratorSize(itertype::Type) -> IteratorSize

Given the type of an iterator, return one of the following values:

SizeUnknown() if the length (number of elements) cannot be determined in advance.
HasLength() if there is a fixed, finite length.
HasShape{N}() if there is a known length plus a notion of multidimensional shape (as for an array). In this case N should give the number of dimensions, and the function is valid for the iterator.
IsInfinite() if the iterator yields values forever.

The default value (for iterators that do not define this function) is HasLength(). This means that most iterators are assumed to implement length.

This trait is generally used to select between algorithms that pre-allocate space for their result, and algorithms that resize their result incrementally.

julia> Base.IteratorSize(1:5)
Base.HasShape{1}()
julia> Base.IteratorSize((2,3))
Base.HasLength()

Base.IteratorEltype — Type

IteratorEltype(itertype::Type) -> IteratorEltype

Given the type of an iterator, return one of the following values:

EltypeUnknown() if the type of elements yielded by the iterator is not known in advance.
HasEltype() if the element type is known, and would return a meaningful value.

HasEltype() is the default, since iterators are assumed to implement eltype.

This trait is generally used to select between algorithms that pre-allocate a specific type of result, and algorithms that pick a result type based on the types of yielded values.

julia> Base.IteratorEltype(1:5)
Base.HasEltype()

以下类型均完全实现了上述函数：

AbstractRange
Tuple
Number
AbstractArray
IdDict
WeakKeyDict
EachLine
AbstractString
Pair

Base.AbstractRange — Type

AbstractRange{T}

Supertype for ranges with elements of type T. and other types are subtypes of this.

source

— Type

OrdinalRange{T, S} <: AbstractRange{T}

Supertype for ordinal ranges with elements of type T with spacing(s) of type S. The steps should be always-exact multiples of oneunit, and T should be a “discrete” type, which cannot have values smaller than oneunit. For example, Integer or Date types would qualify, whereas Float64 would not (since this type can represent values smaller than oneunit(Float64). , StepRange, and other types are subtypes of this.

Base.AbstractUnitRange — Type

AbstractUnitRange{T} <: OrdinalRange{T, T}

Supertype for ranges with a step size of with elements of type T. UnitRange and other types are subtypes of this.

Base.StepRange — Type

StepRange{T, S} <: OrdinalRange{T, S}

Ranges with elements of type T with spacing of type S. The step between each element is constant, and the range is defined in terms of a start and stop of type T and a step of type S. Neither T nor S should be floating point types. The syntax a:b:c with b > 1 and a, b, and c all integers creates a StepRange.

Examples

julia> collect(StepRange(1, Int8(2), 10))
5-element Vector{Int64}:
 1
 3
 5
 7
 9
julia> typeof(StepRange(1, Int8(2), 10))
StepRange{Int64, Int8}
julia> typeof(1:3:6)
StepRange{Int64, Int64}

Base.UnitRange — Type

UnitRange{T<:Real}

A range parameterized by a start and stop of type T, filled with elements spaced by 1 from start until stop is exceeded. The syntax a:b with a and b both Integers creates a UnitRange.

Examples

julia> collect(UnitRange(2.3, 5.2))
3-element Vector{Float64}:
 2.3
 3.3
 4.3
julia> typeof(1:10)
UnitRange{Int64}

Base.LinRange — Type

LinRange{T,L}

A range with len linearly spaced elements between its start and stop. The size of the spacing is controlled by len, which must be an Integer.

Examples

julia> LinRange(1.5, 5.5, 9)
9-element LinRange{Float64, Int64}:
 1.5,2.0,2.5,3.0,3.5,4.0,4.5,5.0,5.5

Compared to using , directly constructing a LinRange should have less overhead but won’t try to correct for floating point errors:

julia> collect(range(-0.1, 0.3, length=5))
5-element Array{Float64,1}:
 -0.1
  0.0
  0.1
  0.2
  0.3
julia> collect(LinRange(-0.1, 0.3, 5))
5-element Array{Float64,1}:
 -0.1
 -1.3877787807814457e-17
  0.09999999999999999
  0.19999999999999998
  0.3

source

通用集合

— Function

isempty(collection) -> Bool

Determine whether a collection is empty (has no elements).

Examples

julia> isempty([])
true
julia> isempty([1 2 3])
false

source

isempty(condition)

Return true if no tasks are waiting on the condition, false otherwise.

Base.empty! — Function

empty!(collection) -> collection

Remove all elements from a collection.

Examples

julia> A = Dict("a" => 1, "b" => 2)
Dict{String, Int64} with 2 entries:
  "b" => 2
  "a" => 1
julia> empty!(A);
julia> A
Dict{String, Int64}()

Base.length — Function

length(collection) -> Integer

Return the number of elements in the collection.

Use to get the last valid index of an indexable collection.