Common functional iterator patterns. DEPRECATED in favour of IterTools.jl
Common functional iterator patterns.
Iterators.jl has been deprecated in favour of IterTools.jl. Please update your package dependencies: Iterators 0.3.1 maps to IterTools 0.1.0.
See #104 for more information.
Install this package with Pkg.add("Iterators")
takestrict(xs, n)
Equivalent to take
, but will throw an exception if fewer than n
items
are encountered in xs
.
repeatedly(f, [n])
Call a function n
times, or infinitely if n
is omitted.
Example:
for t in repeatedly(time_ns, 3)
@show t
end
t = 0x0000592ff83caf87
t = 0x0000592ff83d8cf4
t = 0x0000592ff83dd11e
chain(xs...)
Iterate through any number of iterators in sequence.
Example:
for i in chain(1:3, ['a', 'b', 'c'])
@show i
end
i = 1
i = 2
i = 3
i = 'a'
i = 'b'
i = 'c'
product(xs...)
Iterate over all combinations in the cartesian product of the inputs.
Example:
for p in product(1:3,1:2)
@show p
end
yields
p = (1,1)
p = (2,1)
p = (3,1)
p = (1,2)
p = (2,2)
p = (3,2)
distinct(xs)
Iterate through values skipping over those already encountered.
Example:
for i in distinct([1,1,2,1,2,4,1,2,3,4])
@show i
end
i = 1
i = 2
i = 4
i = 3
nth(xs, n)
Return the n'th element of xs
. Mostly useful for non indexable collections.
Example:
nth(1:3, 3)
3
takenth(xs, n)
Iterate through every n'th element of xs
Example:
collect(takenth(5:15,3))
3-element Array{Int32,1}:
7
10
13
partition(xs, n, [step])
Group values into n
-tuples.
Example:
for i in partition(1:9, 3)
@show i
end
i = (1,2,3)
i = (4,5,6)
i = (7,8,9)
If the step
parameter is set, each tuple is separated by step
values.
Example:
for i in partition(1:9, 3, 2)
@show i
end
i = (1,2,3)
i = (3,4,5)
i = (5,6,7)
i = (7,8,9)
groupby(f, xs)
Group consecutive values that share the same result of applying f
.
Example:
for i in groupby(x -> x[1], ["face", "foo", "bar", "book", "baz", "zzz"])
@show i
end
i = ASCIIString["face","foo"]
i = ASCIIString["bar","book","baz"]
i = ASCIIString["zzz"]
imap(f, xs1, [xs2, ...])
Iterate over values of a function applied to successive values from one or more iterators.
Example:
for i in imap(+, [1,2,3], [4,5,6])
@show i
end
i = 5
i = 7
i = 9
subsets(xs)
Iterate over every subset of a collection xs
.
Example:
for i in subsets([1,2,3])
@show i
end
i = []
i = [1]
i = [2]
i = [1,2]
i = [3]
i = [1,3]
i = [2,3]
i = [1,2,3]
subsets(xs, k)
Iterate over every subset of size k
from a collection xs
.
Example:
for i in subsets([1,2,3],2)
@show i
end
i = [1,2]
i = [1,3]
i = [2,3]
peekiter(xs)
Add possibility to peek head element of an iterator without updating the state.
Example:
it = peekiter(["face", "foo", "bar", "book", "baz", "zzz"])
s = start(it)
@show peek(it, s)
@show peek(it, s)
x, s = next(it, s)
@show x
@show peek(it, s)
peek(it,s) = Nullable("face")
peek(it,s) = Nullable("face") # no change
x = "face"
peek(it,s) = Nullable("foo")
ncycle(xs,n)
Cycles through an iterator n
times
Example:
for i in ncycle(1:3, 2)
@show i
end
i = 1
i = 2
i = 3
i = 1
i = 2
i = 3
iterate(f, x)
Iterate over successive applications of f
, as in f(x), f(f(x)), f(f(f(x))), ...
.
Example:
for i in take(iterate(x -> 2x, 1), 5)
@show i
end
i = 1
i = 2
i = 4
i = 8
i = 16
@itr
macro for automatic inlining in for
loopsUsing functional iterators is powerful and concise, but may incur in some
overhead, and manually inlining the operations can typically improve
performance in critical parts of the code. The @itr
macro is provided to do
that automatically in some cases. Its usage is trivial: for example, given this code:
for (x,y) in zip(a,b)
@show x,y
end
the automatically inlined version can be obtained by simply doing:
@itr for (x,y) in zip(a,b)
@show x,y
end
This typically results in faster code, but its applicability has limitations:
for
loops;Tuple
is expected, an
explicit tuple must be provided, a tuple variable won't be accepted);for x in a, y in b
) are
not supportedThe @itr
macro can be used with the following supported iterators: