SplitApplyCombine.jl has "tools [that] come in the form of high-level functions that operate on iterable or indexable containers in an intuitive and simple way"
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This document was generated with Documenter.jl version 1.4.1 on Wednesday 8 May 2024. Using Julia version 1.8.5.
SplitApplyCombine.jl has "tools [that] come in the form of high-level functions that operate on iterable or indexable containers in an intuitive and simple way"
Settings
This document was generated with Documenter.jl version 1.8.0 on Tuesday 19 November 2024. Using Julia version 1.8.5.
Be aware that if iterating the original has a side-effect it will not be repeated when iterating again, – indeed that is a key feature of the CachedIterator. Be aware also that if the original iterator is nondeterminatistic in its order, when iterating again from the cache it will infact be determinatistic and will be the same order as before – this also is a feature.
Iterate through values skipping over those already encountered.
julia> for i in distinct([1,1,2,1,2,4,1,2,3,4])
+
Be aware that if iterating the original has a side-effect it will not be repeated when iterating again, – indeed that is a key feature of the CachedIterator. Be aware also that if the original iterator is nondeterminatistic in its order, when iterating again from the cache it will infact be determinatistic and will be the same order as before – this also is a feature.
Group consecutive values that share the same result of applying f.
julia> for i in groupby(x -> x[1], ["face", "foo", "bar", "book", "baz", "zzz"])
@show i
end
i = ["face", "foo"]
i = ["bar", "book", "baz"]
-i = ["zzz"]
Iterate over values of a function applied to successive values from one or more iterators. Like Iterators.zip, the iterator is done when any of the input iterators have been exhausted.
julia> for i in imap(+, [1,2,3], [4,5,6])
+i = ["zzz"]
Iterate over values of a function applied to successive values from one or more iterators. Like Iterators.zip, the iterator is done when any of the input iterators have been exhausted.
julia> for i in imap(+, [1,2,3], [4,5,6])
@show i
end
i = 5
i = 7
-i = 9
If the predicate is Base.isless (the default) and both inputs are sorted, this produces the sorted output. If the predicate is a stateful functor that alternates true-false-true-false... then this produces the classic interleave operation as described e.g. in the definition of microkanren.
Iterate over successive applications of f, as in x, f(x), f(f(x)), f(f(f(x))), ...
Use Base.Iterators.take() to obtain the required number of elements.
julia> for i in Iterators.take(iterated(x -> 2x, 1), 5)
+ 6
If the predicate is Base.isless (the default) and both inputs are sorted, this produces the sorted output. If the predicate is a stateful functor that alternates true-false-true-false... then this produces the classic interleave operation as described e.g. in the definition of microkanren.
Iterate over successive applications of f, as in x, f(x), f(f(x)), f(f(f(x))), ...
Use Base.Iterators.take() to obtain the required number of elements.
julia> for i in Iterators.take(iterated(x -> 2x, 1), 5)
@show i
end
i = 1
@@ -62,7 +62,7 @@
i = 3.1622776601683795
i = 1.7782794100389228
i = 1.333521432163324
-i = 1.1547819846894583
Iterate over every subset of the indexable collection xs. You can restrict the subsets to a specific size k.
Giving the subset size in the form Val{k}() allows the compiler to produce code optimized for the particular size requested. This leads to performance comparable to hand-written loops if k is small and known at compile time, but may or may not improve performance otherwise.
julia> for i in subsets([1, 2, 3])
@show i
@@ -173,19 +173,19 @@
i = (1, 4)
i = (2, 3)
i = (2, 4)
-i = (3, 4)
For one or more iterable objects, return an iterable of tuples, where the ith tuple contains the ith component of each input iterable if it is not finished, and default otherwise. default can be a scalar, or a tuple with one default per iterable.
For one or more iterable objects, return an iterable of tuples, where the ith tuple contains the ith component of each input iterable if it is not finished, and default otherwise. default can be a scalar, or a tuple with one default per iterable.
julia> for t in zip_longest(1:2, 5:8)
@show t
end
t = (1, 5)
@@ -200,7 +200,7 @@
t = ('b', 'n')
t = ('c', 'x')
t = ('d', 'x')
-t = ('e', 'x')
If expr evaluates to nothing, equivalent to return nothing, otherwise the macro evaluates to the value of expr. Not exported, useful for implementing iterators.
If expr evaluates to nothing, equivalent to return nothing, otherwise the macro evaluates to the value of expr. Not exported, useful for implementing iterators.
julia> IterTools.@ifsomething iterate(1:2)
(1, 1)
-julia> let elt, state = IterTools.@ifsomething iterate(1:2, 2); println("not reached"); end