Trait `Itertools`

trait Itertools: Iterator

An Iterator blanket implementation that provides extra adaptors and methods.

This trait defines a number of methods. They are divided into two groups:

Adaptors take an iterator and parameter as input, and return a new iterator value. These are listed first in the trait. An example of an adaptor is .interleave()
Regular methods are those that don't return iterators and instead return a regular value of some other kind. .next_tuple() is an example and the first regular method in the list.

Provided Methods

fn interleave<J>(self: Self, other: J) -> Interleave<Self, <J as >::IntoIter> where J: IntoIterator<Item = <Self as >::Item>, Self: Sized

Alternate elements from two iterators until both have run out.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

let it = (1..7).interleave(vec![-1, -2]);
itertools::assert_equal(it, vec![1, -1, 2, -2, 3, 4, 5, 6]);

fn interleave_shortest<J>(self: Self, other: J) -> InterleaveShortest<Self, <J as >::IntoIter> where J: IntoIterator<Item = <Self as >::Item>, Self: Sized

Alternate elements from two iterators until at least one of them has run out.

Iterator element type is Self::Item.

use itertools::Itertools;

let it = (1..7).interleave_shortest(vec![-1, -2]);
itertools::assert_equal(it, vec![1, -1, 2, -2, 3]);

fn intersperse(self: Self, element: <Self as >::Item) -> Intersperse<Self> where Self: Sized, <Self as >::Item: Clone

An iterator adaptor to insert a particular value between each element of the adapted iterator.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

itertools::assert_equal((0..3).intersperse(8), vec![0, 8, 1, 8, 2]);

fn intersperse_with<F>(self: Self, element: F) -> IntersperseWith<Self, F> where Self: Sized, F: FnMut() -> <Self as >::Item

An iterator adaptor to insert a particular value created by a function between each element of the adapted iterator.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

let mut i = 10;
itertools::assert_equal((0..3).intersperse_with(|| { i -= 1; i }), vec![0, 9, 1, 8, 2]);
assert_eq!(i, 8);

fn get<R>(self: Self, index: R) -> <R as >::Output where Self: Sized, R: traits::IteratorIndex<Self>

Returns an iterator over a subsection of the iterator.

Works similarly to slice::get.

Panics for ranges ..=usize::MAX and 0..=usize::MAX.

It's a generalisation of Iterator::take and Iterator::skip, and uses these under the hood. Therefore, the resulting iterator is:

ExactSizeIterator if the adapted iterator is ExactSizeIterator.
DoubleEndedIterator if the adapted iterator is DoubleEndedIterator and ExactSizeIterator.

Unspecified Behavior

The result of indexing with an exhausted core::ops::RangeInclusive is unspecified.

Examples

use itertools::Itertools;

let vec = vec![3, 1, 4, 1, 5];

let mut range: Vec<_> =
        vec.iter().get(1..=3).copied().collect();
assert_eq!(&range, &[1, 4, 1]);

// It works with other types of ranges, too
range = vec.iter().get(..2).copied().collect();
assert_eq!(&range, &[3, 1]);

range = vec.iter().get(0..1).copied().collect();
assert_eq!(&range, &[3]);

range = vec.iter().get(2..).copied().collect();
assert_eq!(&range, &[4, 1, 5]);

range = vec.iter().get(..=2).copied().collect();
assert_eq!(&range, &[3, 1, 4]);

range = vec.iter().get(..).copied().collect();
assert_eq!(range, vec);

fn zip_longest<J>(self: Self, other: J) -> ZipLongest<Self, <J as >::IntoIter> where J: IntoIterator, Self: Sized

Create an iterator which iterates over both this and the specified iterator simultaneously, yielding pairs of two optional elements.

This iterator is fused.

As long as neither input iterator is exhausted yet, it yields two values via EitherOrBoth::Both.

When the parameter iterator is exhausted, it only yields a value from the self iterator via EitherOrBoth::Left.

When the self iterator is exhausted, it only yields a value from the parameter iterator via EitherOrBoth::Right.

When both iterators return None, all further invocations of .next() will return None.

Iterator element type is EitherOrBoth<Self::Item, J::Item>.

use itertools::EitherOrBoth::{Both, Right};
use itertools::Itertools;
let it = (0..1).zip_longest(1..3);
itertools::assert_equal(it, vec![Both(0, 1), Right(2)]);

fn zip_eq<J>(self: Self, other: J) -> ZipEq<Self, <J as >::IntoIter> where J: IntoIterator, Self: Sized

Create an iterator which iterates over both this and the specified iterator simultaneously, yielding pairs of elements.

Panics if the iterators reach an end and they are not of equal lengths.

fn batching<B, F>(self: Self, f: F) -> Batching<Self, F> where F: FnMut(&mut Self) -> Option, Self: Sized

A “meta iterator adaptor”. Its closure receives a reference to the iterator and may pick off as many elements as it likes, to produce the next iterator element.

Iterator element type is B.

use itertools::Itertools;

// An adaptor that gathers elements in pairs
let pit = (0..4).batching(|it| {
           match it.next() {
               None => None,
               Some(x) => match it.next() {
                   None => None,
                   Some(y) => Some((x, y)),
               }
           }
       });

itertools::assert_equal(pit, vec![(0, 1), (2, 3)]);

fn chunk_by<K, F>(self: Self, key: F) -> ChunkBy<K, Self, F> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: PartialEq

Return an iterable that can group iterator elements. Consecutive elements that map to the same key (“runs”), are assigned to the same group.

ChunkBy is the storage for the lazy grouping operation.

If the groups are consumed in order, or if each group's iterator is dropped without keeping it around, then ChunkBy uses no allocations. It needs allocations only if several group iterators are alive at the same time.

This type implements IntoIterator (it is not an iterator itself), because the group iterators need to borrow from this value. It should be stored in a local variable or temporary and iterated.

Iterator element type is (K, Group): the group's key and the group iterator.

use itertools::Itertools;

// chunk data into runs of larger than zero or not.
let data = vec![1, 3, -2, -2, 1, 0, 1, 2];
// chunks:     |---->|------>|--------->|

// Note: The `&` is significant here, `ChunkBy` is iterable
// only by reference. You can also call `.into_iter()` explicitly.
let mut data_grouped = Vec::new();
for (key, chunk) in &data.into_iter().chunk_by(|elt| *elt >= 0) {
    data_grouped.push((key, chunk.collect()));
}
assert_eq!(data_grouped, vec![(true, vec![1, 3]), (false, vec![-2, -2]), (true, vec![1, 0, 1, 2])]);

fn group_by<K, F>(self: Self, key: F) -> ChunkBy<K, Self, F> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: PartialEq

See .chunk_by().

fn chunks(self: Self, size: usize) -> IntoChunks<Self> where Self: Sized

Return an iterable that can chunk the iterator.

Yield subiterators (chunks) that each yield a fixed number elements, determined by size. The last chunk will be shorter if there aren't enough elements.

IntoChunks is based on ChunkBy: it is iterable (implements IntoIterator, not Iterator), and it only buffers if several chunk iterators are alive at the same time.

Iterator element type is Chunk, each chunk's iterator.

Panics if size is 0.

use itertools::Itertools;

let data = vec![1, 1, 2, -2, 6, 0, 3, 1];
//chunk size=3 |------->|-------->|--->|

// Note: The `&` is significant here, `IntoChunks` is iterable
// only by reference. You can also call `.into_iter()` explicitly.
for chunk in &data.into_iter().chunks(3) {
    // Check that the sum of each chunk is 4.
    assert_eq!(4, chunk.sum());
}

fn tuple_windows<T>(self: Self) -> TupleWindows<Self, T> where Self: Sized + Iterator<Item = <T as >::Item>, T: traits::HomogeneousTuple, <T as >::Item: Clone

Return an iterator over all contiguous windows producing tuples of a specific size (up to 12).

tuple_windows clones the iterator elements so that they can be part of successive windows, this makes it most suited for iterators of references and other values that are cheap to copy.

use itertools::Itertools;
let mut v = Vec::new();

// pairwise iteration
for (a, b) in (1..5).tuple_windows() {
    v.push((a, b));
}
assert_eq!(v, vec![(1, 2), (2, 3), (3, 4)]);

let mut it = (1..5).tuple_windows();
assert_eq!(Some((1, 2, 3)), it.next());
assert_eq!(Some((2, 3, 4)), it.next());
assert_eq!(None, it.next());

// this requires a type hint
let it = (1..5).tuple_windows::<(_, _, _)>();
itertools::assert_equal(it, vec![(1, 2, 3), (2, 3, 4)]);

// you can also specify the complete type
use itertools::TupleWindows;
use std::ops::Range;

let it: TupleWindows<Range<u32>, (u32, u32, u32)> = (1..5).tuple_windows();
itertools::assert_equal(it, vec![(1, 2, 3), (2, 3, 4)]);

fn circular_tuple_windows<T>(self: Self) -> CircularTupleWindows<Self, T> where Self: Sized + Clone + Iterator<Item = <T as >::Item> + ExactSizeIterator, T: tuple_impl::TupleCollect + Clone, <T as >::Item: Clone

Return an iterator over all windows, wrapping back to the first elements when the window would otherwise exceed the length of the iterator, producing tuples of a specific size (up to 12).

circular_tuple_windows clones the iterator elements so that they can be part of successive windows, this makes it most suited for iterators of references and other values that are cheap to copy.

use itertools::Itertools;
let mut v = Vec::new();
for (a, b) in (1..5).circular_tuple_windows() {
    v.push((a, b));
}
assert_eq!(v, vec![(1, 2), (2, 3), (3, 4), (4, 1)]);

let mut it = (1..5).circular_tuple_windows();
assert_eq!(Some((1, 2, 3)), it.next());
assert_eq!(Some((2, 3, 4)), it.next());
assert_eq!(Some((3, 4, 1)), it.next());
assert_eq!(Some((4, 1, 2)), it.next());
assert_eq!(None, it.next());

// this requires a type hint
let it = (1..5).circular_tuple_windows::<(_, _, _)>();
itertools::assert_equal(it, vec![(1, 2, 3), (2, 3, 4), (3, 4, 1), (4, 1, 2)]);

fn tuples<T>(self: Self) -> Tuples<Self, T> where Self: Sized + Iterator<Item = <T as >::Item>, T: traits::HomogeneousTuple

Return an iterator that groups the items in tuples of a specific size (up to 12).

Example

use itertools::Itertools;

type Item = Result<i32, &'static str>;

let first_values: Vec<Item> = vec![Ok(1), Ok(0), Ok(3)];
let second_values: Vec<Item> = vec![Ok(2), Ok(1), Err("overflow")];

// “Lift” the iterator .max() method to work on the Ok-values.
let first_max = first_values.into_iter().process_results(|iter| iter.max().unwrap_or(0));
let second_max = second_values.into_iter().process_results(|iter| iter.max().unwrap_or(0));

assert_eq!(first_max, Ok(3));
assert!(second_max.is_err());

fn merge<J>(self: Self, other: J) -> Merge<Self, <J as >::IntoIter> where Self: Sized, <Self as >::Item: PartialOrd, J: IntoIterator<Item = <Self as >::Item>

Return an iterator adaptor that merges the two base iterators in ascending order. If both base iterators are sorted (ascending), the result is sorted.

Iterator element type is Self::Item.

use itertools::Itertools;

let a = (0..11).step_by(3);
let b = (0..11).step_by(5);
let it = a.merge(b);
itertools::assert_equal(it, vec![0, 0, 3, 5, 6, 9, 10]);

fn merge_by<J, F>(self: Self, other: J, is_first: F) -> MergeBy<Self, <J as >::IntoIter, F> where Self: Sized, J: IntoIterator<Item = <Self as >::Item>, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> bool

Return an iterator adaptor that merges the two base iterators in order. This is much like .merge() but allows for a custom ordering.

This can be especially useful for sequences of tuples.

Iterator element type is Self::Item.

use itertools::Itertools;

let a = (0..).zip("bc".chars());
let b = (0..).zip("ad".chars());
let it = a.merge_by(b, |x, y| x.1 <= y.1);
itertools::assert_equal(it, vec![(0, 'a'), (0, 'b'), (1, 'c'), (1, 'd')]);

fn merge_join_by<J, F, T>(self: Self, other: J, cmp_fn: F) -> MergeJoinBy<Self, <J as >::IntoIter, F> where J: IntoIterator, F: FnMut(&<Self as >::Item, &<J as >::Item) -> T, Self: Sized

Create an iterator that merges items from both this and the specified iterator in ascending order.

The function can either return an Ordering variant or a boolean.

If cmp_fn returns Ordering, it chooses whether to pair elements based on the Ordering returned by the specified compare function. At any point, inspecting the tip of the iterators I and J as items i of type I::Item and j of type J::Item respectively, the resulting iterator will:

Emit EitherOrBoth::Left(i) when i < j, and remove i from its source iterator
Emit EitherOrBoth::Right(j) when i > j, and remove j from its source iterator
Emit EitherOrBoth::Both(i, j) when i == j, and remove both i and j from their respective source iterators

use itertools::Itertools;
use itertools::EitherOrBoth::{Left, Right, Both};

let a = vec![0, 2, 4, 6, 1].into_iter();
let b = (0..10).step_by(3);

itertools::assert_equal(
    // This performs a diff in the style of the Unix command comm(1),
    // generalized to arbitrary types rather than text.
    a.merge_join_by(b, Ord::cmp),
    vec![Both(0, 0), Left(2), Right(3), Left(4), Both(6, 6), Left(1), Right(9)]
);

If cmp_fn returns bool, it chooses whether to pair elements based on the boolean returned by the specified function. At any point, inspecting the tip of the iterators I and J as items i of type I::Item and j of type J::Item respectively, the resulting iterator will:

Emit Either::Left(i) when true, and remove i from its source iterator
Emit Either::Right(j) when false, and remove j from its source iterator

It is similar to the Ordering case if the first argument is considered "less" than the second argument.

use itertools::Itertools;
use itertools::Either::{Left, Right};

let a = vec![0, 2, 4, 6, 1].into_iter();
let b = (0..10).step_by(3);

itertools::assert_equal(
    a.merge_join_by(b, |i, j| i <= j),
    vec![Left(0), Right(0), Left(2), Right(3), Left(4), Left(6), Left(1), Right(6), Right(9)]
);

fn kmerge(self: Self) -> KMerge<<<Self as >::Item as IntoIterator>::IntoIter> where Self: Sized, <Self as >::Item: IntoIterator, <<Self as >::Item as IntoIterator>::Item: PartialOrd

Return an iterator adaptor that flattens an iterator of iterators by merging them in ascending order.

If all base iterators are sorted (ascending), the result is sorted.

Iterator element type is Self::Item.

use itertools::Itertools;

let a = (0..6).step_by(3);
let b = (1..6).step_by(3);
let c = (2..6).step_by(3);
let it = vec![a, b, c].into_iter().kmerge();
itertools::assert_equal(it, vec![0, 1, 2, 3, 4, 5]);

fn kmerge_by<F>(self: Self, first: F) -> KMergeBy<<<Self as >::Item as IntoIterator>::IntoIter, F> where Self: Sized, <Self as >::Item: IntoIterator, F: FnMut(&<<Self as >::Item as IntoIterator>::Item, &<<Self as >::Item as IntoIterator>::Item) -> bool

Return an iterator adaptor that flattens an iterator of iterators by merging them according to the given closure.

The closure first is called with two elements a, b and should return true if a is ordered before b.

If all base iterators are sorted according to first, the result is sorted.

Iterator element type is Self::Item.

use itertools::Itertools;

let a = vec![-1f64, 2., 3., -5., 6., -7.];
let b = vec![0., 2., -4.];
let mut it = vec![a, b].into_iter().kmerge_by(|a, b| a.abs() < b.abs());
assert_eq!(it.next(), Some(0.));
assert_eq!(it.last(), Some(-7.));

fn cartesian_product<J>(self: Self, other: J) -> Product<Self, <J as >::IntoIter> where Self: Sized, <Self as >::Item: Clone, J: IntoIterator, <J as >::IntoIter: Clone

Return an iterator adaptor that iterates over the cartesian product of the element sets of two iterators self and J.

Iterator element type is (Self::Item, J::Item).

use itertools::Itertools;

let it = (0..2).cartesian_product("αβ".chars());
itertools::assert_equal(it, vec![(0, 'α'), (0, 'β'), (1, 'α'), (1, 'β')]);

fn multi_cartesian_product(self: Self) -> MultiProduct<<<Self as >::Item as IntoIterator>::IntoIter> where Self: Sized, <Self as >::Item: IntoIterator, <<Self as >::Item as IntoIterator>::IntoIter: Clone, <<Self as >::Item as IntoIterator>::Item: Clone

Return an iterator adaptor that iterates over the cartesian product of all subiterators returned by meta-iterator self.

All provided iterators must yield the same Item type. To generate the product of iterators yielding multiple types, use the iproduct macro instead.

The iterator element type is Vec<T>, where T is the iterator element of the subiterators.

Note that the iterator is fused.

use itertools::Itertools;
let mut multi_prod = (0..3).map(|i| (i * 2)..(i * 2 + 2))
    .multi_cartesian_product();
assert_eq!(multi_prod.next(), Some(vec![0, 2, 4]));
assert_eq!(multi_prod.next(), Some(vec![0, 2, 5]));
assert_eq!(multi_prod.next(), Some(vec![0, 3, 4]));
assert_eq!(multi_prod.next(), Some(vec![0, 3, 5]));
assert_eq!(multi_prod.next(), Some(vec![1, 2, 4]));
assert_eq!(multi_prod.next(), Some(vec![1, 2, 5]));
assert_eq!(multi_prod.next(), Some(vec![1, 3, 4]));
assert_eq!(multi_prod.next(), Some(vec![1, 3, 5]));
assert_eq!(multi_prod.next(), None);

If the adapted iterator is empty, the result is an iterator yielding a single empty vector. This is known as the nullary cartesian product.

use itertools::Itertools;
let mut nullary_cartesian_product = (0..0).map(|i| (i * 2)..(i * 2 + 2)).multi_cartesian_product();
assert_eq!(nullary_cartesian_product.next(), Some(vec![]));
assert_eq!(nullary_cartesian_product.next(), None);

fn coalesce<F>(self: Self, f: F) -> Coalesce<Self, F> where Self: Sized, F: FnMut(<Self as >::Item, <Self as >::Item) -> Result<<Self as >::Item, (<Self as >::Item, <Self as >::Item)>

Return an iterator adaptor that uses the passed-in closure to optionally merge together consecutive elements.

The closure f is passed two elements, previous and current and may return either (1) Ok(combined) to merge the two values or (2) Err((previous', current')) to indicate they can't be merged. In (2), the value previous' is emitted by the iterator. Either (1) combined or (2) current' becomes the previous value when coalesce continues with the next pair of elements to merge. The value that remains at the end is also emitted by the iterator.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

// sum same-sign runs together
let data = vec![-1., -2., -3., 3., 1., 0., -1.];
itertools::assert_equal(data.into_iter().coalesce(|x, y|
        if (x >= 0.) == (y >= 0.) {
            Ok(x + y)
        } else {
            Err((x, y))
        }),
        vec![-6., 4., -1.]);

fn dedup(self: Self) -> Dedup<Self> where Self: Sized, <Self as >::Item: PartialEq

Remove duplicates from sections of consecutive identical elements. If the iterator is sorted, all elements will be unique.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

let data = vec![1., 1., 2., 3., 3., 2., 2.];
itertools::assert_equal(data.into_iter().dedup(),
                        vec![1., 2., 3., 2.]);

fn dedup_by<Cmp>(self: Self, cmp: Cmp) -> DedupBy<Self, Cmp> where Self: Sized, Cmp: FnMut(&<Self as >::Item, &<Self as >::Item) -> bool

Remove duplicates from sections of consecutive identical elements, determining equality using a comparison function. If the iterator is sorted, all elements will be unique.

Iterator element type is Self::Item.

This iterator is fused.

use itertools::Itertools;

let data = vec![(0, 1.), (1, 1.), (0, 2.), (0, 3.), (1, 3.), (1, 2.), (2, 2.)];
itertools::assert_equal(data.into_iter().dedup_by(|x, y| x.1 == y.1),
                        vec![(0, 1.), (0, 2.), (0, 3.), (1, 2.)]);

fn dedup_with_count(self: Self) -> DedupWithCount<Self> where Self: Sized

Remove duplicates from sections of consecutive identical elements, while keeping a count of how many repeated elements were present. If the iterator is sorted, all elements will be unique.

Iterator element type is (usize, Self::Item).

This iterator is fused.

use itertools::Itertools;

let data = vec!['a', 'a', 'b', 'c', 'c', 'b', 'b'];
itertools::assert_equal(data.into_iter().dedup_with_count(),
                        vec![(2, 'a'), (1, 'b'), (2, 'c'), (2, 'b')]);

fn dedup_by_with_count<Cmp>(self: Self, cmp: Cmp) -> DedupByWithCount<Self, Cmp> where Self: Sized, Cmp: FnMut(&<Self as >::Item, &<Self as >::Item) -> bool

Remove duplicates from sections of consecutive identical elements, while keeping a count of how many repeated elements were present. This will determine equality using a comparison function. If the iterator is sorted, all elements will be unique.

Iterator element type is (usize, Self::Item).

This iterator is fused.

use itertools::Itertools;

let data = vec![(0, 'a'), (1, 'a'), (0, 'b'), (0, 'c'), (1, 'c'), (1, 'b'), (2, 'b')];
itertools::assert_equal(data.into_iter().dedup_by_with_count(|x, y| x.1 == y.1),
                        vec![(2, (0, 'a')), (1, (0, 'b')), (2, (0, 'c')), (2, (1, 'b'))]);

fn duplicates(self: Self) -> Duplicates<Self> where Self: Sized, <Self as >::Item: Eq + Hash

Return an iterator adaptor that produces elements that appear more than once during the iteration. Duplicates are detected using hash and equality.

The iterator is stable, returning the duplicate items in the order in which they occur in the adapted iterator. Each duplicate item is returned exactly once. If an item appears more than twice, the second item is the item retained and the rest are discarded.

use itertools::Itertools;

let data = vec![10, 20, 30, 20, 40, 10, 50];
itertools::assert_equal(data.into_iter().duplicates(),
                        vec![20, 10]);

fn duplicates_by<V, F>(self: Self, f: F) -> DuplicatesBy<Self, V, F> where Self: Sized, V: Eq + Hash, F: FnMut(&<Self as >::Item) -> V

Return an iterator adaptor that produces elements that appear more than once during the iteration. Duplicates are detected using hash and equality.

Duplicates are detected by comparing the key they map to with the keying function f by hash and equality. The keys are stored in a hash map in the iterator.

use itertools::Itertools;

let data = vec!["a", "bb", "aa", "c", "ccc"];
itertools::assert_equal(data.into_iter().duplicates_by(|s| s.len()),
                        vec!["aa", "c"]);

fn unique(self: Self) -> Unique<Self> where Self: Sized, <Self as >::Item: Clone + Eq + Hash

Return an iterator adaptor that filters out elements that have already been produced once during the iteration. Duplicates are detected using hash and equality.

Clones of visited elements are stored in a hash set in the iterator.

The iterator is stable, returning the non-duplicate items in the order in which they occur in the adapted iterator. In a set of duplicate items, the first item encountered is the item retained.

use itertools::Itertools;

let data = vec![10, 20, 30, 20, 40, 10, 50];
itertools::assert_equal(data.into_iter().unique(),
                        vec![10, 20, 30, 40, 50]);

fn unique_by<V, F>(self: Self, f: F) -> UniqueBy<Self, V, F> where Self: Sized, V: Eq + Hash, F: FnMut(&<Self as >::Item) -> V

Return an iterator adaptor that filters out elements that have already been produced once during the iteration.

Duplicates are detected by comparing the key they map to with the keying function f by hash and equality. The keys are stored in a hash set in the iterator.

The iterator is stable, returning the non-duplicate items in the order in which they occur in the adapted iterator. In a set of duplicate items, the first item encountered is the item retained.

use itertools::Itertools;

let data = vec!["a", "bb", "aa", "c", "ccc"];
itertools::assert_equal(data.into_iter().unique_by(|s| s.len()),
                        vec!["a", "bb", "ccc"]);

fn peeking_take_while<F>(self: &mut Self, accept: F) -> PeekingTakeWhile<'_, Self, F> where Self: Sized + PeekingNext, F: FnMut(&<Self as >::Item) -> bool

Return an iterator adaptor that borrows from this iterator and takes items while the closure accept returns true.

This adaptor can only be used on iterators that implement PeekingNext like .peekable(), put_back and a few other collection iterators.

The last and rejected element (first false) is still available when peeking_take_while is done.

See also .take_while_ref() which is a similar adaptor.

fn take_while_ref<F>(self: &mut Self, accept: F) -> TakeWhileRef<'_, Self, F> where Self: Clone, F: FnMut(&<Self as >::Item) -> bool

Return an iterator adaptor that borrows from a Clone-able iterator to only pick off elements while the predicate accept returns true.

It uses the Clone trait to restore the original iterator so that the last and rejected element (first false) is still available when take_while_ref is done.

use itertools::Itertools;

let mut hexadecimals = "0123456789abcdef".chars();

let decimals = hexadecimals.take_while_ref(|c| c.is_numeric())
                           .collect::<String>();
assert_eq!(decimals, "0123456789");
assert_eq!(hexadecimals.next(), Some('a'));

fn take_while_inclusive<F>(self: Self, accept: F) -> TakeWhileInclusive<Self, F> where Self: Sized, F: FnMut(&<Self as >::Item) -> bool

Returns an iterator adaptor that consumes elements while the given predicate is true, including the element for which the predicate first returned false.

The [.take_while()][std::iter::Iterator::take_while] adaptor is useful when you want items satisfying a predicate, but to know when to stop taking elements, we have to consume that first element that doesn't satisfy the predicate. This adaptor includes that element where [.take_while()][std::iter::Iterator::take_while] would drop it.

The [.take_while_ref()][crate::Itertools::take_while_ref] adaptor serves a similar purpose, but this adaptor doesn't require Cloneing the underlying elements.

# use itertools::Itertools;
let items = vec![1, 2, 3, 4, 5];
let filtered: Vec<_> = items
    .into_iter()
    .take_while_inclusive(|&n| n % 3 != 0)
    .collect();

assert_eq!(filtered, vec![1, 2, 3]);

# use itertools::Itertools;
let items = vec![1, 2, 3, 4, 5];

let take_while_inclusive_result: Vec<_> = items
    .iter()
    .copied()
    .take_while_inclusive(|&n| n % 3 != 0)
    .collect();
let take_while_result: Vec<_> = items
    .into_iter()
    .take_while(|&n| n % 3 != 0)
    .collect();

assert_eq!(take_while_inclusive_result, vec![1, 2, 3]);
assert_eq!(take_while_result, vec![1, 2]);
// both iterators have the same items remaining at this point---the 3
// is lost from the `take_while` vec

# use itertools::Itertools;
#[derive(Debug, PartialEq)]
struct NoCloneImpl(i32);

let non_clonable_items: Vec<_> = vec![1, 2, 3, 4, 5]
    .into_iter()
    .map(NoCloneImpl)
    .collect();
let filtered: Vec<_> = non_clonable_items
    .into_iter()
    .take_while_inclusive(|n| n.0 % 3 != 0)
    .collect();
let expected: Vec<_> = vec![1, 2, 3].into_iter().map(NoCloneImpl).collect();
assert_eq!(filtered, expected);

fn while_some<A>(self: Self) -> WhileSome<Self> where Self: Sized + Iterator<Item = Option<A>>

Return an iterator adaptor that filters Option<A> iterator elements and produces A. Stops on the first None encountered.

Iterator element type is A, the unwrapped element.

use itertools::Itertools;

// List all hexadecimal digits
itertools::assert_equal(
    (0..).map(|i| std::char::from_digit(i, 16)).while_some(),
    "0123456789abcdef".chars());

fn tuple_combinations<T>(self: Self) -> TupleCombinations<Self, T> where Self: Sized + Clone, <Self as >::Item: Clone, T: adaptors::HasCombination<Self>

Return an iterator adaptor that iterates over the combinations of the elements from an iterator.

Iterator element can be any homogeneous tuple of type Self::Item with size up to 12.

Guarantees

If the adapted iterator is deterministic, this iterator adapter yields items in a reliable order.

use itertools::Itertools;

let mut v = Vec::new();
for (a, b) in (1..5).tuple_combinations() {
    v.push((a, b));
}
assert_eq!(v, vec![(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]);

let mut it = (1..5).tuple_combinations();
assert_eq!(Some((1, 2, 3)), it.next());
assert_eq!(Some((1, 2, 4)), it.next());
assert_eq!(Some((1, 3, 4)), it.next());
assert_eq!(Some((2, 3, 4)), it.next());
assert_eq!(None, it.next());

// this requires a type hint
let it = (1..5).tuple_combinations::<(_, _, _)>();
itertools::assert_equal(it, vec![(1, 2, 3), (1, 2, 4), (1, 3, 4), (2, 3, 4)]);

// you can also specify the complete type
use itertools::TupleCombinations;
use std::ops::Range;

let it: TupleCombinations<Range<u32>, (u32, u32, u32)> = (1..5).tuple_combinations();
itertools::assert_equal(it, vec![(1, 2, 3), (1, 2, 4), (1, 3, 4), (2, 3, 4)]);

fn array_combinations<K: usize>(self: Self) -> ArrayCombinations<Self, K> where Self: Sized + Clone, <Self as >::Item: Clone

Return an iterator adaptor that iterates over the combinations of the elements from an iterator.

Iterator element type is [Self::Item; K]. The iterator produces a new array per iteration, and clones the iterator elements.

Guarantees

If the adapted iterator is deterministic, this iterator adapter yields items in a reliable order.

use itertools::Itertools;

let mut v = Vec::new();
for [a, b] in (1..5).array_combinations() {
    v.push([a, b]);
}
assert_eq!(v, vec![[1, 2], [1, 3], [1, 4], [2, 3], [2, 4], [3, 4]]);

let mut it = (1..5).array_combinations();
assert_eq!(Some([1, 2, 3]), it.next());
assert_eq!(Some([1, 2, 4]), it.next());
assert_eq!(Some([1, 3, 4]), it.next());
assert_eq!(Some([2, 3, 4]), it.next());
assert_eq!(None, it.next());

// this requires a type hint
let it = (1..5).array_combinations::<3>();
itertools::assert_equal(it, vec![[1, 2, 3], [1, 2, 4], [1, 3, 4], [2, 3, 4]]);

// you can also specify the complete type
use itertools::ArrayCombinations;
use std::ops::Range;

let it: ArrayCombinations<Range<u32>, 3> = (1..5).array_combinations();
itertools::assert_equal(it, vec![[1, 2, 3], [1, 2, 4], [1, 3, 4], [2, 3, 4]]);

fn combinations(self: Self, k: usize) -> Combinations<Self> where Self: Sized, <Self as >::Item: Clone

Return an iterator adaptor that iterates over the k-length combinations of the elements from an iterator.

Iterator element type is Vec<Self::Item>. The iterator produces a new Vec per iteration, and clones the iterator elements.

Guarantees

If the adapted iterator is deterministic, this iterator adapter yields items in a reliable order.

use itertools::Itertools;

let it = (1..5).combinations(3);
itertools::assert_equal(it, vec![
    vec![1, 2, 3],
    vec![1, 2, 4],
    vec![1, 3, 4],
    vec![2, 3, 4],
]);

Note: Combinations does not take into account the equality of the iterated values.

use itertools::Itertools;

let it = vec![1, 2, 2].into_iter().combinations(2);
itertools::assert_equal(it, vec![
    vec![1, 2], // Note: these are the same
    vec![1, 2], // Note: these are the same
    vec![2, 2],
]);

fn combinations_with_replacement(self: Self, k: usize) -> CombinationsWithReplacement<Self> where Self: Sized, <Self as >::Item: Clone

Return an iterator that iterates over the k-length combinations of the elements from an iterator, with replacement.

Iterator element type is Vec<Self::Item>. The iterator produces a new Vec per iteration, and clones the iterator elements.

use itertools::Itertools;

let it = (1..4).combinations_with_replacement(2);
itertools::assert_equal(it, vec![
    vec![1, 1],
    vec![1, 2],
    vec![1, 3],
    vec![2, 2],
    vec![2, 3],
    vec![3, 3],
]);

fn permutations(self: Self, k: usize) -> Permutations<Self> where Self: Sized, <Self as >::Item: Clone

Return an iterator adaptor that iterates over all k-permutations of the elements from an iterator.

Iterator element type is Vec<Self::Item> with length k. The iterator produces a new Vec per iteration, and clones the iterator elements.

If k is greater than the length of the input iterator, the resultant iterator adaptor will be empty.

If you are looking for permutations with replacements, use repeat_n(iter, k).multi_cartesian_product() instead.

use itertools::Itertools;

let perms = (5..8).permutations(2);
itertools::assert_equal(perms, vec![
    vec![5, 6],
    vec![5, 7],
    vec![6, 5],
    vec![6, 7],
    vec![7, 5],
    vec![7, 6],
]);

Note: Permutations does not take into account the equality of the iterated values.

use itertools::Itertools;

let it = vec![2, 2].into_iter().permutations(2);
itertools::assert_equal(it, vec![
    vec![2, 2], // Note: these are the same
    vec![2, 2], // Note: these are the same
]);

Note: The source iterator is collected lazily, and will not be re-iterated if the permutations adaptor is completed and re-iterated.

fn powerset(self: Self) -> Powerset<Self> where Self: Sized, <Self as >::Item: Clone

Return an iterator that iterates through the powerset of the elements from an iterator.

Iterator element type is Vec<Self::Item>. The iterator produces a new Vec per iteration, and clones the iterator elements.

The powerset of a set contains all subsets including the empty set and the full input set. A powerset has length 2^n where n is the length of the input set.

Each Vec produced by this iterator represents a subset of the elements produced by the source iterator.

use itertools::Itertools;

let sets = (1..4).powerset().collect::<Vec<_>>();
itertools::assert_equal(sets, vec![
    vec![],
    vec![1],
    vec![2],
    vec![3],
    vec![1, 2],
    vec![1, 3],
    vec![2, 3],
    vec![1, 2, 3],
]);

fn pad_using<F>(self: Self, min: usize, f: F) -> PadUsing<Self, F> where Self: Sized, F: FnMut(usize) -> <Self as >::Item

Return an iterator adaptor that pads the sequence to a minimum length of min by filling missing elements using a closure f.

Iterator element type is Self::Item.

use itertools::Itertools;

let it = (0..5).pad_using(10, |i| 2*i);
itertools::assert_equal(it, vec![0, 1, 2, 3, 4, 10, 12, 14, 16, 18]);

let it = (0..10).pad_using(5, |i| 2*i);
itertools::assert_equal(it, vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);

let it = (0..5).pad_using(10, |i| 2*i).rev();
itertools::assert_equal(it, vec![18, 16, 14, 12, 10, 4, 3, 2, 1, 0]);

fn with_position(self: Self) -> WithPosition<Self> where Self: Sized

Return an iterator adaptor that combines each element with a Position to ease special-case handling of the first or last elements.

Iterator element type is (Position, Self::Item)

use itertools::{Itertools, Position};

let it = (0..4).with_position();
itertools::assert_equal(it,
                        vec![(Position::First, 0),
                             (Position::Middle, 1),
                             (Position::Middle, 2),
                             (Position::Last, 3)]);

let it = (0..1).with_position();
itertools::assert_equal(it, vec![(Position::Only, 0)]);

fn positions(self: Self, predicate: P) -> Positions<Self, P> where Self: Sized, P: FnMut(<Self as >::Item) -> bool

Return an iterator adaptor that yields the indices of all elements satisfying a predicate, counted from the start of the iterator.

Equivalent to iter.enumerate().filter(|(_, v)| predicate(*v)).map(|(i, _)| i).

use itertools::Itertools;

let data = vec![1, 2, 3, 3, 4, 6, 7, 9];
itertools::assert_equal(data.iter().positions(|v| v % 2 == 0), vec![1, 4, 5]);

itertools::assert_equal(data.iter().positions(|v| v % 2 == 1).rev(), vec![7, 6, 3, 2, 0]);

fn update<F>(self: Self, updater: F) -> Update<Self, F> where Self: Sized, F: FnMut(&mut <Self as >::Item)

Return an iterator adaptor that applies a mutating function to each element before yielding it.

use itertools::Itertools;

let input = vec![vec![1], vec![3, 2, 1]];
let it = input.into_iter().update(|v| v.push(0));
itertools::assert_equal(it, vec![vec![1, 0], vec![3, 2, 1, 0]]);

fn next_array<N: usize>(self: &mut Self) -> Option<[<Self as >::Item; N]> where Self: Sized

Advances the iterator and returns the next items grouped in an array of a specific size.

If there are enough elements to be grouped in an array, then the array is returned inside Some, otherwise None is returned.

use itertools::Itertools;

let mut iter = 1..5;

assert_eq!(Some([1, 2]), iter.next_array());

fn collect_array<N: usize>(self: Self) -> Option<[<Self as >::Item; N]> where Self: Sized

Collects all items from the iterator into an array of a specific size.

If the number of elements inside the iterator is exactly equal to the array size, then the array is returned inside Some, otherwise None is returned.

use itertools::Itertools;

let iter = 1..3;

if let Some([x, y]) = iter.collect_array() {
    assert_eq!([x, y], [1, 2])
} else {
    panic!("Expected two elements")
}

fn next_tuple<T>(self: &mut Self) -> Option<T> where Self: Sized + Iterator<Item = <T as >::Item>, T: traits::HomogeneousTuple

Advances the iterator and returns the next items grouped in a tuple of a specific size (up to 12).

If there are enough elements to be grouped in a tuple, then the tuple is returned inside Some, otherwise None is returned.

use itertools::Itertools;

let mut iter = 1..5;

assert_eq!(Some((1, 2)), iter.next_tuple());

fn collect_tuple<T>(self: Self) -> Option<T> where Self: Sized + Iterator<Item = <T as >::Item>, T: traits::HomogeneousTuple

Collects all items from the iterator into a tuple of a specific size (up to 12).

If the number of elements inside the iterator is exactly equal to the tuple size, then the tuple is returned inside Some, otherwise None is returned.

use itertools::Itertools;

let iter = 1..3;

if let Some((x, y)) = iter.collect_tuple() {
    assert_eq!((x, y), (1, 2))
} else {
    panic!("Expected two elements")
}

fn find_position(self: &mut Self, pred: P) -> Option<(usize, <Self as >::Item)> where P: FnMut(&<Self as >::Item) -> bool

Find the position and value of the first element satisfying a predicate.

The iterator is not advanced past the first element found.

use itertools::Itertools;

let text = "Hα";
assert_eq!(text.chars().find_position(|ch| ch.is_lowercase()), Some((1, 'α')));

fn find_or_last(self: Self, predicate: P) -> Option<<Self as >::Item> where Self: Sized, P: FnMut(&<Self as >::Item) -> bool

Find the value of the first element satisfying a predicate or return the last element, if any.

The iterator is not advanced past the first element found.

use itertools::Itertools;

let numbers = [1, 2, 3, 4];
assert_eq!(numbers.iter().find_or_last(|&&x| x > 5), Some(&4));
assert_eq!(numbers.iter().find_or_last(|&&x| x > 2), Some(&3));
assert_eq!(std::iter::empty::<i32>().find_or_last(|&x| x > 5), None);

// An iterator of Results can return the first Ok or the last Err:
let input = vec![Err(()), Ok(11), Err(()), Ok(22)];
assert_eq!(input.into_iter().find_or_last(Result::is_ok), Some(Ok(11)));

let input: Vec<Result<(), i32>> = vec![Err(11), Err(22)];
assert_eq!(input.into_iter().find_or_last(Result::is_ok), Some(Err(22)));

assert_eq!(std::iter::empty::<Result<(), i32>>().find_or_last(Result::is_ok), None);

fn find_or_first(self: Self, predicate: P) -> Option<<Self as >::Item> where Self: Sized, P: FnMut(&<Self as >::Item) -> bool

Find the value of the first element satisfying a predicate or return the first element, if any.

The iterator is not advanced past the first element found.

use itertools::Itertools;

let numbers = [1, 2, 3, 4];
assert_eq!(numbers.iter().find_or_first(|&&x| x > 5), Some(&1));
assert_eq!(numbers.iter().find_or_first(|&&x| x > 2), Some(&3));
assert_eq!(std::iter::empty::<i32>().find_or_first(|&x| x > 5), None);

// An iterator of Results can return the first Ok or the first Err:
let input = vec![Err(()), Ok(11), Err(()), Ok(22)];
assert_eq!(input.into_iter().find_or_first(Result::is_ok), Some(Ok(11)));

let input: Vec<Result<(), i32>> = vec![Err(11), Err(22)];
assert_eq!(input.into_iter().find_or_first(Result::is_ok), Some(Err(11)));

assert_eq!(std::iter::empty::<Result<(), i32>>().find_or_first(Result::is_ok), None);

fn contains<Q>(self: &mut Self, query: &Q) -> bool where Self: Sized, <Self as >::Item: Borrow<Q>, Q: PartialEq + ?Sized

Returns true if the given item is present in this iterator.

This method is short-circuiting. If the given item is present in this iterator, this method will consume the iterator up-to-and-including the item. If the given item is not present in this iterator, the iterator will be exhausted.

use itertools::Itertools;

#[derive(PartialEq, Debug)]
enum Enum { A, B, C, D, E, }

let mut iter = vec![Enum::A, Enum::B, Enum::C, Enum::D].into_iter();

// search `iter` for `B`
assert_eq!(iter.contains(&Enum::B), true);
// `B` was found, so the iterator now rests at the item after `B` (i.e, `C`).
assert_eq!(iter.next(), Some(Enum::C));

// search `iter` for `E`
assert_eq!(iter.contains(&Enum::E), false);
// `E` wasn't found, so `iter` is now exhausted
assert_eq!(iter.next(), None);

fn all_equal(self: &mut Self) -> bool where Self: Sized, <Self as >::Item: PartialEq

Check whether all elements compare equal.

Empty iterators are considered to have equal elements:

use itertools::Itertools;

let data = vec![1, 1, 1, 2, 2, 3, 3, 3, 4, 5, 5];
assert!(!data.iter().all_equal());
assert!(data[0..3].iter().all_equal());
assert!(data[3..5].iter().all_equal());
assert!(data[5..8].iter().all_equal());

let data : Option<usize> = None;
assert!(data.into_iter().all_equal());

fn all_equal_value(self: &mut Self) -> Result<<Self as >::Item, Option<(<Self as >::Item, <Self as >::Item)>> where Self: Sized, <Self as >::Item: PartialEq

If there are elements and they are all equal, return a single copy of that element. If there are no elements, return an Error containing None. If there are elements and they are not all equal, return a tuple containing the first two non-equal elements found.

use itertools::Itertools;

let data = vec![1, 1, 1, 2, 2, 3, 3, 3, 4, 5, 5];
assert_eq!(data.iter().all_equal_value(), Err(Some((&1, &2))));
assert_eq!(data[0..3].iter().all_equal_value(), Ok(&1));
assert_eq!(data[3..5].iter().all_equal_value(), Ok(&2));
assert_eq!(data[5..8].iter().all_equal_value(), Ok(&3));

let data : Option<usize> = None;
assert_eq!(data.into_iter().all_equal_value(), Err(None));

fn all_unique(self: &mut Self) -> bool where Self: Sized, <Self as >::Item: Eq + Hash

Check whether all elements are unique (non equal).

Empty iterators are considered to have unique elements:

use itertools::Itertools;

let data = vec![1, 2, 3, 4, 1, 5];
assert!(!data.iter().all_unique());
assert!(data[0..4].iter().all_unique());
assert!(data[1..6].iter().all_unique());

let data : Option<usize> = None;
assert!(data.into_iter().all_unique());

fn dropping(self: Self, n: usize) -> Self where Self: Sized

Consume the first n elements from the iterator eagerly, and return the same iterator again.

It works similarly to .skip(n) except it is eager and preserves the iterator type.

use itertools::Itertools;

let iter = "αβγ".chars().dropping(2);
itertools::assert_equal(iter, "γ".chars());

Fusing notes: if the iterator is exhausted by dropping, the result of calling .next() again depends on the iterator implementation.

fn dropping_back(self: Self, n: usize) -> Self where Self: Sized + DoubleEndedIterator

Consume the last n elements from the iterator eagerly, and return the same iterator again.

This is only possible on double ended iterators. n may be larger than the number of elements.

Note: This method is eager, dropping the back elements immediately and preserves the iterator type.

use itertools::Itertools;

let init = vec![0, 3, 6, 9].into_iter().dropping_back(1);
itertools::assert_equal(init, vec![0, 3, 6]);

fn concat(self: Self) -> <Self as >::Item where Self: Sized, <Self as >::Item: Extend<<<Self as Iterator>::Item as IntoIterator>::Item> + IntoIterator + Default

Combine all an iterator's elements into one element by using Extend.

This combinator will extend the first item with each of the rest of the items of the iterator. If the iterator is empty, the default value of I::Item is returned.

use itertools::Itertools;

let input = vec![vec![1], vec![2, 3], vec![4, 5, 6]];
assert_eq!(input.into_iter().concat(),
           vec![1, 2, 3, 4, 5, 6]);

fn collect_vec(self: Self) -> Vec<<Self as >::Item> where Self: Sized

.collect_vec() is simply a type specialization of Iterator::collect, for convenience.

fn try_collect<T, U, E>(self: Self) -> Result<U, E> where Self: Sized + Iterator<Item = Result<T, E>>, Result<U, E>: FromIterator<Result<T, E>>

.try_collect() is more convenient way of writing .collect::<Result<_, _>>()

Example

use std::{fs, io};
use itertools::Itertools;

fn process_dir_entries(entries: &[fs::DirEntry]) {
    // ...
    # let _ = entries;
}

fn do_stuff() -> io::Result<()> {
    let entries: Vec<_> = fs::read_dir(".")?.try_collect()?;
    process_dir_entries(&entries);

    Ok(())
}

# let _ = do_stuff;

fn set_from<'a, A: 'a, J>(self: &mut Self, from: J) -> usize where Self: Iterator<Item = &'a mut A>, J: IntoIterator<Item = A>

Assign to each reference in self from the from iterator, stopping at the shortest of the two iterators.

The from iterator is queried for its next element before the self iterator, and if either is exhausted the method is done.

Return the number of elements written.

use itertools::Itertools;

let mut xs = [0; 4];
xs.iter_mut().set_from(1..);
assert_eq!(xs, [1, 2, 3, 4]);

fn join(self: &mut Self, sep: &str) -> String where <Self as >::Item: std::fmt::Display

Combine all iterator elements into one String, separated by sep.

Use the Display implementation of each element.

use itertools::Itertools;

assert_eq!(["a", "b", "c"].iter().join(", "), "a, b, c");
assert_eq!([1, 2, 3].iter().join(", "), "1, 2, 3");

fn format(self: Self, sep: &str) -> Format<'_, Self> where Self: Sized

Format all iterator elements, separated by sep.

All elements are formatted (any formatting trait) with sep inserted between each element.

Panics if the formatter helper is formatted more than once.

use itertools::Itertools;

let data = [1.1, 2.71828, -3.];
assert_eq!(
    format!("{:.2}", data.iter().format(", ")),
           "1.10, 2.72, -3.00");

fn format_with<F>(self: Self, sep: &str, format: F) -> FormatWith<'_, Self, F> where Self: Sized, F: FnMut(<Self as >::Item, &mut dyn FnMut(&dyn fmt::Display) -> fmt::Result) -> fmt::Result

Format all iterator elements, separated by sep.

This is a customizable version of .format().

The supplied closure format is called once per iterator element, with two arguments: the element and a callback that takes a &Display value, i.e. any reference to type that implements Display.

Using &format_args!(...) is the most versatile way to apply custom element formatting. The callback can be called multiple times if needed.

Panics if the formatter helper is formatted more than once.

use itertools::Itertools;

let data = [1.1, 2.71828, -3.];
let data_formatter = data.iter().format_with(", ", |elt, f| f(&format_args!("{:.2}", elt)));
assert_eq!(format!("{}", data_formatter),
           "1.10, 2.72, -3.00");

// .format_with() is recursively composable
let matrix = [[1., 2., 3.],
              [4., 5., 6.]];
let matrix_formatter = matrix.iter().format_with("\n", |row, f| {
                                f(&row.iter().format_with(", ", |elt, g| g(&elt)))
                             });
assert_eq!(format!("{}", matrix_formatter),
           "1, 2, 3\n4, 5, 6");

fn fold_ok<A, E, B, F>(self: &mut Self, start: B, f: F) -> Result<B, E> where Self: Iterator<Item = Result<A, E>>, F: FnMut(B, A) -> B

Fold Result values from an iterator.

Only Ok values are folded. If no error is encountered, the folded value is returned inside Ok. Otherwise, the operation terminates and returns the first Err value it encounters. No iterator elements are consumed after the first error.

The first accumulator value is the start parameter. Each iteration passes the accumulator value and the next value inside Ok to the fold function f and its return value becomes the new accumulator value.

For example the sequence Ok(1), Ok(2), Ok(3) will result in a computation like this:

# let start = 0;
# let f = |x, y| x + y;
let mut accum = start;
accum = f(accum, 1);
accum = f(accum, 2);
accum = f(accum, 3);
# let _ = accum;

With a start value of 0 and an addition as folding function, this effectively results in ((0 + 1) + 2) + 3

use std::ops::Add;
use itertools::Itertools;

let values = [1, 2, -2, -1, 2, 1];
assert_eq!(
    values.iter()
          .map(Ok::<_, ()>)
          .fold_ok(0, Add::add),
    Ok(3)
);
assert!(
    values.iter()
          .map(|&x| if x >= 0 { Ok(x) } else { Err("Negative number") })
          .fold_ok(0, Add::add)
          .is_err()
);

fn fold_options<A, B, F>(self: &mut Self, start: B, f: F) -> Option where Self: Iterator<Item = Option<A>>, F: FnMut(B, A) -> B

Fold Option values from an iterator.

Only Some values are folded. If no None is encountered, the folded value is returned inside Some. Otherwise, the operation terminates and returns None. No iterator elements are consumed after the None.

This is the Option equivalent to fold_ok.

use std::ops::Add;
use itertools::Itertools;

let mut values = vec![Some(1), Some(2), Some(-2)].into_iter();
assert_eq!(values.fold_options(5, Add::add), Some(5 + 1 + 2 - 2));

let mut more_values = vec![Some(2), None, Some(0)].into_iter();
assert!(more_values.fold_options(0, Add::add).is_none());
assert_eq!(more_values.next().unwrap(), Some(0));

fn fold1<F>(self: Self, f: F) -> Option<<Self as >::Item> where F: FnMut(<Self as >::Item, <Self as >::Item) -> <Self as >::Item, Self: Sized

Accumulator of the elements in the iterator.

Like .fold(), without a base case. If the iterator is empty, return None. With just one element, return it. Otherwise elements are accumulated in sequence using the closure f.

use itertools::Itertools;

assert_eq!((0..10).fold1(|x, y| x + y).unwrap_or(0), 45);
assert_eq!((0..0).fold1(|x, y| x * y), None);

fn tree_reduce<F>(self: Self, f: F) -> Option<<Self as >::Item> where F: FnMut(<Self as >::Item, <Self as >::Item) -> <Self as >::Item, Self: Sized

Accumulate the elements in the iterator in a tree-like manner.

You can think of it as, while there's more than one item, repeatedly combining adjacent items. It does so in bottom-up-merge-sort order, however, so that it needs only logarithmic stack space.

This produces a call tree like the following (where the calls under an item are done after reading that item):

1 2 3 4 5 6 7
│ │ │ │ │ │ │
└─f └─f └─f │
  │   │   │ │
  └───f   └─f
      │     │
      └─────f

Which, for non-associative functions, will typically produce a different result than the linear call tree used by [Iterator::reduce]:

1 2 3 4 5 6 7
│ │ │ │ │ │ │
└─f─f─f─f─f─f

If f is associative you should also decide carefully:

For an iterator producing n elements, both Iterator::reduce and tree_reduce will call f n - 1 times. However, tree_reduce will call f on earlier intermediate results, which is beneficial for f that allocate and produce longer results for longer arguments. For example if f combines arguments using format!, then tree_reduce will operate on average on shorter arguments resulting in less bytes being allocated overall.

Moreover, the output of tree_reduce is preferable to that of Iterator::reduce in certain cases. For example, building a binary search tree using tree_reduce will result in a balanced tree with height O(ln(n)), while Iterator::reduce will output a tree with height O(n), essentially a linked list.

If f does not benefit from such a reordering, like u32::wrapping_add, prefer the normal Iterator::reduce instead since it will most likely result in the generation of simpler code because the compiler is able to optimize it.

use itertools::Itertools;

let f = |a: String, b: String| {
    format!("f({a}, {b})")
};

// The same tree as above
assert_eq!((1..8).map(|x| x.to_string()).tree_reduce(f),
           Some(String::from("f(f(f(1, 2), f(3, 4)), f(f(5, 6), 7))")));

// Like reduce, an empty iterator produces None
assert_eq!((0..0).tree_reduce(|x, y| x * y), None);

// tree_reduce matches reduce for associative operations...
assert_eq!((0..10).tree_reduce(|x, y| x + y),
    (0..10).reduce(|x, y| x + y));

// ...but not for non-associative ones
assert_ne!((0..10).tree_reduce(|x, y| x - y),
    (0..10).reduce(|x, y| x - y));

let mut total_len_reduce = 0;
let reduce_res = (1..100).map(|x| x.to_string())
    .reduce(|a, b| {
        let r = f(a, b);
        total_len_reduce += r.len();
        r
    })
    .unwrap();

let mut total_len_tree_reduce = 0;
let tree_reduce_res = (1..100).map(|x| x.to_string())
    .tree_reduce(|a, b| {
        let r = f(a, b);
        total_len_tree_reduce += r.len();
        r
    })
    .unwrap();

assert_eq!(total_len_reduce, 33299);
assert_eq!(total_len_tree_reduce, 4228);
assert_eq!(reduce_res.len(), tree_reduce_res.len());

fn tree_fold1<F>(self: Self, f: F) -> Option<<Self as >::Item> where F: FnMut(<Self as >::Item, <Self as >::Item) -> <Self as >::Item, Self: Sized

See .tree_reduce().

fn fold_while<B, F>(self: &mut Self, init: B, f: F) -> FoldWhile where Self: Sized, F: FnMut(B, <Self as >::Item) -> FoldWhile

An iterator method that applies a function, producing a single, final value.

fold_while() is basically equivalent to Iterator::fold but with additional support for early exit via short-circuiting.

use itertools::Itertools;
use itertools::FoldWhile::{Continue, Done};

let numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];

let mut result = 0;

// for loop:
for i in &numbers {
    if *i > 5 {
        break;
    }
    result = result + i;
}

// fold:
let result2 = numbers.iter().fold(0, |acc, x| {
    if *x > 5 { acc } else { acc + x }
});

// fold_while:
let result3 = numbers.iter().fold_while(0, |acc, x| {
    if *x > 5 { Done(acc) } else { Continue(acc + x) }
}).into_inner();

// they're the same
assert_eq!(result, result2);
assert_eq!(result2, result3);

The big difference between the computations of result2 and result3 is that while fold() called the provided closure for every item of the callee iterator, fold_while() actually stopped iterating as soon as it encountered Fold::Done(_).

fn sum1<S>(self: Self) -> Option<S> where Self: Sized, S: std::iter::Sum<<Self as >::Item>

Iterate over the entire iterator and add all the elements.

An empty iterator returns None, otherwise Some(sum).

Panics

When calling sum1() and a primitive integer type is being returned, this method will panic if the computation overflows and debug assertions are enabled.

Examples

use itertools::Itertools;

let empty_sum = (1..1).sum1::<i32>();
assert_eq!(empty_sum, None);

let nonempty_sum = (1..11).sum1::<i32>();
assert_eq!(nonempty_sum, Some(55));

fn product1(self: Self) -> Option where Self: Sized, P: std::iter::Product<<Self as >::Item>

Iterate over the entire iterator and multiply all the elements.

An empty iterator returns None, otherwise Some(product).

Panics

When calling product1() and a primitive integer type is being returned, method will panic if the computation overflows and debug assertions are enabled.

Examples

use itertools::Itertools;

let empty_product = (1..1).product1::<i32>();
assert_eq!(empty_product, None);

let nonempty_product = (1..11).product1::<i32>();
assert_eq!(nonempty_product, Some(3628800));

fn sorted_unstable(self: Self) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort_unstable method and returns the result as a new iterator that owns its elements.

This sort is unstable (i.e., may reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort the letters of the text in ascending order
let text = "bdacfe";
itertools::assert_equal(text.chars().sorted_unstable(),
                        "abcdef".chars());

fn sorted_unstable_by<F>(self: Self, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort_unstable_by method and returns the result as a new iterator that owns its elements.

This sort is unstable (i.e., may reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort people in descending order by age
let people = vec![("Jane", 20), ("John", 18), ("Jill", 30), ("Jack", 27)];

let oldest_people_first = people
    .into_iter()
    .sorted_unstable_by(|a, b| Ord::cmp(&b.1, &a.1))
    .map(|(person, _age)| person);

itertools::assert_equal(oldest_people_first,
                        vec!["Jill", "Jack", "Jane", "John"]);

fn sorted_unstable_by_key<K, F>(self: Self, f: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort_unstable_by_key method and returns the result as a new iterator that owns its elements.

This sort is unstable (i.e., may reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort people in descending order by age
let people = vec![("Jane", 20), ("John", 18), ("Jill", 30), ("Jack", 27)];

let oldest_people_first = people
    .into_iter()
    .sorted_unstable_by_key(|x| -x.1)
    .map(|(person, _age)| person);

itertools::assert_equal(oldest_people_first,
                        vec!["Jill", "Jack", "Jane", "John"]);

fn sorted(self: Self) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort method and returns the result as a new iterator that owns its elements.

This sort is stable (i.e., does not reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort the letters of the text in ascending order
let text = "bdacfe";
itertools::assert_equal(text.chars().sorted(),
                        "abcdef".chars());

fn sorted_by<F>(self: Self, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort_by method and returns the result as a new iterator that owns its elements.

This sort is stable (i.e., does not reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort people in descending order by age
let people = vec![("Jane", 20), ("John", 18), ("Jill", 30), ("Jack", 30)];

let oldest_people_first = people
    .into_iter()
    .sorted_by(|a, b| Ord::cmp(&b.1, &a.1))
    .map(|(person, _age)| person);

itertools::assert_equal(oldest_people_first,
                        vec!["Jill", "Jack", "Jane", "John"]);

fn sorted_by_key<K, F>(self: Self, f: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Sort all iterator elements into a new iterator in ascending order.

Note: This consumes the entire iterator, uses the slice::sort_by_key method and returns the result as a new iterator that owns its elements.

This sort is stable (i.e., does not reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort people in descending order by age
let people = vec![("Jane", 20), ("John", 18), ("Jill", 30), ("Jack", 30)];

let oldest_people_first = people
    .into_iter()
    .sorted_by_key(|x| -x.1)
    .map(|(person, _age)| person);

itertools::assert_equal(oldest_people_first,
                        vec!["Jill", "Jack", "Jane", "John"]);

fn sorted_by_cached_key<K, F>(self: Self, f: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Sort all iterator elements into a new iterator in ascending order. The key function is called exactly once per key.

Note: This consumes the entire iterator, uses the slice::sort_by_cached_key method and returns the result as a new iterator that owns its elements.

This sort is stable (i.e., does not reorder equal elements).

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

use itertools::Itertools;

// sort people in descending order by age
let people = vec![("Jane", 20), ("John", 18), ("Jill", 30), ("Jack", 30)];

let oldest_people_first = people
    .into_iter()
    .sorted_by_cached_key(|x| -x.1)
    .map(|(person, _age)| person);

itertools::assert_equal(oldest_people_first,
                        vec!["Jill", "Jack", "Jane", "John"]);

fn k_smallest(self: Self, k: usize) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort the k smallest elements into a new iterator, in ascending order.

Note: This consumes the entire iterator, and returns the result as a new iterator that owns its elements. If the input contains less than k elements, the result is equivalent to self.sorted().

This is guaranteed to use k * sizeof(Self::Item) + O(1) memory and O(n log k) time, with n the number of elements in the input.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Note: This is functionally-equivalent to self.sorted().take(k) but much more efficient.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest(5);

itertools::assert_equal(five_smallest, 0..5);

fn k_smallest_by<F>(self: Self, k: usize, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort the k smallest elements into a new iterator using the provided comparison.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

This corresponds to self.sorted_by(cmp).take(k) in the same way that k_smallest corresponds to self.sorted().take(k), in both semantics and complexity.

Particularly, a custom heap implementation ensures the comparison is not cloned.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest_by(5, |a, b| (a % 7).cmp(&(b % 7)).then(a.cmp(b)));

itertools::assert_equal(five_smallest, vec![0, 7, 14, 1, 8]);

fn k_smallest_by_key<F, K>(self: Self, k: usize, key: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: Ord

Return the elements producing the k smallest outputs of the provided function.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

This corresponds to self.sorted_by_key(key).take(k) in the same way that k_smallest corresponds to self.sorted().take(k), in both semantics and complexity.

Particularly, a custom heap implementation ensures the comparison is not cloned.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest_by_key(5, |n| (n % 7, *n));

itertools::assert_equal(five_smallest, vec![0, 7, 14, 1, 8]);

fn k_smallest_relaxed(self: Self, k: usize) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort the k smallest elements into a new iterator, in ascending order, relaxing the amount of memory required.

Note: This consumes the entire iterator, and returns the result as a new iterator that owns its elements. If the input contains less than k elements, the result is equivalent to self.sorted().

This is guaranteed to use 2 * k * sizeof(Self::Item) + O(1) memory and O(n + k log k) time, with n the number of elements in the input, meaning it uses more memory than the minimum obtained by k_smallest but achieves linear time in the number of elements.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Note: This is functionally-equivalent to self.sorted().take(k) but much more efficient.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest_relaxed(5);

itertools::assert_equal(five_smallest, 0..5);

fn k_smallest_relaxed_by<F>(self: Self, k: usize, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort the k smallest elements into a new iterator using the provided comparison, relaxing the amount of memory required.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

This corresponds to self.sorted_by(cmp).take(k) in the same way that k_smallest_relaxed corresponds to self.sorted().take(k), in both semantics and complexity.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest_relaxed_by(5, |a, b| (a % 7).cmp(&(b % 7)).then(a.cmp(b)));

itertools::assert_equal(five_smallest, vec![0, 7, 14, 1, 8]);

fn k_smallest_relaxed_by_key<F, K>(self: Self, k: usize, key: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: Ord

Return the elements producing the k smallest outputs of the provided function, relaxing the amount of memory required.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

This corresponds to self.sorted_by_key(key).take(k) in the same way that k_smallest_relaxed corresponds to self.sorted().take(k), in both semantics and complexity.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_smallest = numbers
    .into_iter()
    .k_smallest_relaxed_by_key(5, |n| (n % 7, *n));

itertools::assert_equal(five_smallest, vec![0, 7, 14, 1, 8]);

fn k_largest(self: Self, k: usize) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort the k largest elements into a new iterator, in descending order.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

It is semantically equivalent to k_smallest with a reversed Ord. However, this is implemented with a custom binary heap which does not have the same performance characteristics for very large Self::Item.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest(5);

itertools::assert_equal(five_largest, vec![14, 13, 12, 11, 10]);

fn k_largest_by<F>(self: Self, k: usize, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort the k largest elements into a new iterator using the provided comparison.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Functionally equivalent to k_smallest_by with a reversed Ord.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest_by(5, |a, b| (a % 7).cmp(&(b % 7)).then(a.cmp(b)));

itertools::assert_equal(five_largest, vec![13, 6, 12, 5, 11]);

fn k_largest_by_key<F, K>(self: Self, k: usize, key: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: Ord

Return the elements producing the k largest outputs of the provided function.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Functionally equivalent to k_smallest_by_key with a reversed Ord.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest_by_key(5, |n| (n % 7, *n));

itertools::assert_equal(five_largest, vec![13, 6, 12, 5, 11]);

fn k_largest_relaxed(self: Self, k: usize) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Sort the k largest elements into a new iterator, in descending order, relaxing the amount of memory required.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

It is semantically equivalent to k_smallest_relaxed with a reversed Ord.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest_relaxed(5);

itertools::assert_equal(five_largest, vec![14, 13, 12, 11, 10]);

fn k_largest_relaxed_by<F>(self: Self, k: usize, cmp: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Sort the k largest elements into a new iterator using the provided comparison, relaxing the amount of memory required.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Functionally equivalent to k_smallest_relaxed_by with a reversed Ord.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest_relaxed_by(5, |a, b| (a % 7).cmp(&(b % 7)).then(a.cmp(b)));

itertools::assert_equal(five_largest, vec![13, 6, 12, 5, 11]);

fn k_largest_relaxed_by_key<F, K>(self: Self, k: usize, key: F) -> alloc::vec::IntoIter<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item) -> K, K: Ord

Return the elements producing the k largest outputs of the provided function, relaxing the amount of memory required.

The sorted iterator, if directly collected to a Vec, is converted without any extra copying or allocation cost.

Functionally equivalent to k_smallest_relaxed_by_key with a reversed Ord.

use itertools::Itertools;

// A random permutation of 0..15
let numbers = vec![6, 9, 1, 14, 0, 4, 8, 7, 11, 2, 10, 3, 13, 12, 5];

let five_largest = numbers
    .into_iter()
    .k_largest_relaxed_by_key(5, |n| (n % 7, *n));

itertools::assert_equal(five_largest, vec![13, 6, 12, 5, 11]);

fn tail(self: Self, n: usize) -> alloc::collections::vec_deque::IntoIter<<Self as >::Item> where Self: Sized

Consumes the iterator and return an iterator of the last n elements.

The iterator, if directly collected to a VecDeque, is converted without any extra copying or allocation cost. If directly collected to a Vec, it may need some data movement but no re-allocation.

use itertools::{assert_equal, Itertools};

let v = vec![5, 9, 8, 4, 2, 12, 0];
assert_equal(v.iter().tail(3), &[2, 12, 0]);
assert_equal(v.iter().tail(10), &v);

assert_equal(v.iter().tail(1), v.iter().last());

assert_equal((0..100).tail(10), 90..100);

assert_equal((0..100).filter(|x| x % 3 == 0).tail(10), (72..100).step_by(3));

For double ended iterators without side-effects, you might prefer .rev().take(n).rev() to have a similar result (lazy and non-allocating) without consuming the entire iterator.

fn partition_map<A, B, F, L, R>(self: Self, predicate: F) -> (A, B) where Self: Sized, F: FnMut(<Self as >::Item) -> Either<L, R>, A: Default + Extend<L>, B: Default + Extend<R>

Collect all iterator elements into one of two partitions. Unlike Iterator::partition, each partition may have a distinct type.

use itertools::{Itertools, Either};

let successes_and_failures = vec![Ok(1), Err(false), Err(true), Ok(2)];

let (successes, failures): (Vec<_>, Vec<_>) = successes_and_failures
    .into_iter()
    .partition_map(|r| {
        match r {
            Ok(v) => Either::Left(v),
            Err(v) => Either::Right(v),
        }
    });

assert_eq!(successes, [1, 2]);
assert_eq!(failures, [false, true]);

fn partition_result<A, B, T, E>(self: Self) -> (A, B) where Self: Iterator<Item = Result<T, E>> + Sized, A: Default + Extend<T>, B: Default + Extend<E>

Partition a sequence of Results into one list of all the Ok elements and another list of all the Err elements.

use itertools::Itertools;

let successes_and_failures = vec![Ok(1), Err(false), Err(true), Ok(2)];

let (successes, failures): (Vec<_>, Vec<_>) = successes_and_failures
    .into_iter()
    .partition_result();

assert_eq!(successes, [1, 2]);
assert_eq!(failures, [false, true]);

fn into_group_map<K, V>(self: Self) -> HashMap<K, Vec<V>> where Self: Iterator<Item = (K, V)> + Sized, K: Hash + Eq

Return a HashMap of keys mapped to Vecs of values. Keys and values are taken from (Key, Value) tuple pairs yielded by the input iterator.

Essentially a shorthand for .into_grouping_map().collect::<Vec<_>>().

use itertools::Itertools;

let data = vec![(0, 10), (2, 12), (3, 13), (0, 20), (3, 33), (2, 42)];
let lookup = data.into_iter().into_group_map();

assert_eq!(lookup[&0], vec![10, 20]);
assert_eq!(lookup.get(&1), None);
assert_eq!(lookup[&2], vec![12, 42]);
assert_eq!(lookup[&3], vec![13, 33]);

fn into_group_map_by<K, V, F>(self: Self, f: F) -> HashMap<K, Vec<V>> where Self: Iterator<Item = V> + Sized, K: Hash + Eq, F: FnMut(&V) -> K

Return a HashMap of keys mapped to Vecs of values. The key is specified in the closure. The values are taken from the input iterator.

Essentially a shorthand for .into_grouping_map_by(f).collect::<Vec<_>>().

use itertools::Itertools;
use std::collections::HashMap;

let data = vec![(0, 10), (2, 12), (3, 13), (0, 20), (3, 33), (2, 42)];
let lookup: HashMap<u32,Vec<(u32, u32)>> =
    data.clone().into_iter().into_group_map_by(|a| a.0);

assert_eq!(lookup[&0], vec![(0,10), (0,20)]);
assert_eq!(lookup.get(&1), None);
assert_eq!(lookup[&2], vec![(2,12), (2,42)]);
assert_eq!(lookup[&3], vec![(3,13), (3,33)]);

assert_eq!(
    data.into_iter()
        .into_group_map_by(|x| x.0)
        .into_iter()
        .map(|(key, values)| (key, values.into_iter().fold(0,|acc, (_,v)| acc + v )))
        .collect::<HashMap<u32,u32>>()[&0],
    30,
);

fn into_grouping_map<K, V>(self: Self) -> GroupingMap<Self> where Self: Iterator<Item = (K, V)> + Sized, K: Hash + Eq

Constructs a GroupingMap to be used later with one of the efficient group-and-fold operations it allows to perform.

The input iterator must yield item in the form of (K, V) where the value of type K will be used as key to identify the groups and the value of type V as value for the folding operation.

See GroupingMap for more informations on what operations are available.

fn into_grouping_map_by<K, V, F>(self: Self, key_mapper: F) -> GroupingMapBy<Self, F> where Self: Iterator<Item = V> + Sized, K: Hash + Eq, F: FnMut(&V) -> K

Constructs a GroupingMap to be used later with one of the efficient group-and-fold operations it allows to perform.

The values from this iterator will be used as values for the folding operation while the keys will be obtained from the values by calling key_mapper.

See GroupingMap for more informations on what operations are available.

fn min_set(self: Self) -> Vec<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Return all minimum elements of an iterator.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().min_set(), Vec::<&i32>::new());

let a = [1];
assert_eq!(a.iter().min_set(), vec![&1]);

let a = [1, 2, 3, 4, 5];
assert_eq!(a.iter().min_set(), vec![&1]);

let a = [1, 1, 1, 1];
assert_eq!(a.iter().min_set(), vec![&1, &1, &1, &1]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn min_set_by<F>(self: Self, compare: F) -> Vec<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return all minimum elements of an iterator, as determined by the specified function.

Examples

# use std::cmp::Ordering;
use itertools::Itertools;

let a: [(i32, i32); 0] = [];
assert_eq!(a.iter().min_set_by(|_, _| Ordering::Equal), Vec::<&(i32, i32)>::new());

let a = [(1, 2)];
assert_eq!(a.iter().min_set_by(|&&(k1,_), &&(k2, _)| k1.cmp(&k2)), vec![&(1, 2)]);

let a = [(1, 2), (2, 2), (3, 9), (4, 8), (5, 9)];
assert_eq!(a.iter().min_set_by(|&&(_,k1), &&(_,k2)| k1.cmp(&k2)), vec![&(1, 2), &(2, 2)]);

let a = [(1, 2), (1, 3), (1, 4), (1, 5)];
assert_eq!(a.iter().min_set_by(|&&(k1,_), &&(k2, _)| k1.cmp(&k2)), vec![&(1, 2), &(1, 3), &(1, 4), &(1, 5)]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn min_set_by_key<K, F>(self: Self, key: F) -> Vec<<Self as >::Item> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Return all minimum elements of an iterator, as determined by the specified function.

Examples

use itertools::Itertools;

let a: [(i32, i32); 0] = [];
assert_eq!(a.iter().min_set_by_key(|_| ()), Vec::<&(i32, i32)>::new());

let a = [(1, 2)];
assert_eq!(a.iter().min_set_by_key(|&&(k,_)| k), vec![&(1, 2)]);

let a = [(1, 2), (2, 2), (3, 9), (4, 8), (5, 9)];
assert_eq!(a.iter().min_set_by_key(|&&(_, k)| k), vec![&(1, 2), &(2, 2)]);

let a = [(1, 2), (1, 3), (1, 4), (1, 5)];
assert_eq!(a.iter().min_set_by_key(|&&(k, _)| k), vec![&(1, 2), &(1, 3), &(1, 4), &(1, 5)]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn max_set(self: Self) -> Vec<<Self as >::Item> where Self: Sized, <Self as >::Item: Ord

Return all maximum elements of an iterator.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().max_set(), Vec::<&i32>::new());

let a = [1];
assert_eq!(a.iter().max_set(), vec![&1]);

let a = [1, 2, 3, 4, 5];
assert_eq!(a.iter().max_set(), vec![&5]);

let a = [1, 1, 1, 1];
assert_eq!(a.iter().max_set(), vec![&1, &1, &1, &1]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn max_set_by<F>(self: Self, compare: F) -> Vec<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return all maximum elements of an iterator, as determined by the specified function.

Examples

# use std::cmp::Ordering;
use itertools::Itertools;

let a: [(i32, i32); 0] = [];
assert_eq!(a.iter().max_set_by(|_, _| Ordering::Equal), Vec::<&(i32, i32)>::new());

let a = [(1, 2)];
assert_eq!(a.iter().max_set_by(|&&(k1,_), &&(k2, _)| k1.cmp(&k2)), vec![&(1, 2)]);

let a = [(1, 2), (2, 2), (3, 9), (4, 8), (5, 9)];
assert_eq!(a.iter().max_set_by(|&&(_,k1), &&(_,k2)| k1.cmp(&k2)), vec![&(3, 9), &(5, 9)]);

let a = [(1, 2), (1, 3), (1, 4), (1, 5)];
assert_eq!(a.iter().max_set_by(|&&(k1,_), &&(k2, _)| k1.cmp(&k2)), vec![&(1, 2), &(1, 3), &(1, 4), &(1, 5)]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn max_set_by_key<K, F>(self: Self, key: F) -> Vec<<Self as >::Item> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Return all maximum elements of an iterator, as determined by the specified function.

Examples

use itertools::Itertools;

let a: [(i32, i32); 0] = [];
assert_eq!(a.iter().max_set_by_key(|_| ()), Vec::<&(i32, i32)>::new());

let a = [(1, 2)];
assert_eq!(a.iter().max_set_by_key(|&&(k,_)| k), vec![&(1, 2)]);

let a = [(1, 2), (2, 2), (3, 9), (4, 8), (5, 9)];
assert_eq!(a.iter().max_set_by_key(|&&(_, k)| k), vec![&(3, 9), &(5, 9)]);

let a = [(1, 2), (1, 3), (1, 4), (1, 5)];
assert_eq!(a.iter().max_set_by_key(|&&(k, _)| k), vec![&(1, 2), &(1, 3), &(1, 4), &(1, 5)]);

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn minmax(self: Self) -> MinMaxResult<<Self as >::Item> where Self: Sized, <Self as >::Item: PartialOrd

Return the minimum and maximum elements in the iterator.

The return type MinMaxResult is an enum of three variants:

NoElements if the iterator is empty.
OneElement(x) if the iterator has exactly one element.
MinMax(x, y) is returned otherwise, where x <= y. Two values are equal if and only if there is more than one element in the iterator and all elements are equal.

On an iterator of length n, minmax does 1.5 * n comparisons, and so is faster than calling min and max separately which does 2 * n comparisons.

Examples

use itertools::Itertools;
use itertools::MinMaxResult::{NoElements, OneElement, MinMax};

let a: [i32; 0] = [];
assert_eq!(a.iter().minmax(), NoElements);

let a = [1];
assert_eq!(a.iter().minmax(), OneElement(&1));

let a = [1, 2, 3, 4, 5];
assert_eq!(a.iter().minmax(), MinMax(&1, &5));

let a = [1, 1, 1, 1];
assert_eq!(a.iter().minmax(), MinMax(&1, &1));

The elements can be floats but no particular result is guaranteed if an element is NaN.

fn minmax_by_key<K, F>(self: Self, key: F) -> MinMaxResult<<Self as >::Item> where Self: Sized, K: PartialOrd, F: FnMut(&<Self as >::Item) -> K

Return the minimum and maximum element of an iterator, as determined by the specified function.

The return value is a variant of MinMaxResult like for .minmax().

For the minimum, the first minimal element is returned. For the maximum, the last maximal element wins. This matches the behavior of the standard Iterator::min and Iterator::max methods.

The keys can be floats but no particular result is guaranteed if a key is NaN.

fn minmax_by<F>(self: Self, compare: F) -> MinMaxResult<<Self as >::Item> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return the minimum and maximum element of an iterator, as determined by the specified comparison function.

The return value is a variant of MinMaxResult like for .minmax().

For the minimum, the first minimal element is returned. For the maximum, the last maximal element wins. This matches the behavior of the standard Iterator::min and Iterator::max methods.

fn position_max(self: Self) -> Option<usize> where Self: Sized, <Self as >::Item: Ord

Return the position of the maximum element in the iterator.

If several elements are equally maximum, the position of the last of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_max(), None);

let a = [-3, 0, 1, 5, -10];
assert_eq!(a.iter().position_max(), Some(3));

let a = [1, 1, -1, -1];
assert_eq!(a.iter().position_max(), Some(1));

fn position_max_by_key<K, F>(self: Self, key: F) -> Option<usize> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Return the position of the maximum element in the iterator, as determined by the specified function.

If several elements are equally maximum, the position of the last of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_max_by_key(|x| x.abs()), None);

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_max_by_key(|x| x.abs()), Some(4));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_max_by_key(|x| x.abs()), Some(3));

fn position_max_by<F>(self: Self, compare: F) -> Option<usize> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return the position of the maximum element in the iterator, as determined by the specified comparison function.

If several elements are equally maximum, the position of the last of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_max_by(|x, y| x.cmp(y)), None);

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_max_by(|x, y| x.cmp(y)), Some(3));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_max_by(|x, y| x.cmp(y)), Some(1));

fn position_min(self: Self) -> Option<usize> where Self: Sized, <Self as >::Item: Ord

Return the position of the minimum element in the iterator.

If several elements are equally minimum, the position of the first of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_min(), None);

let a = [-3, 0, 1, 5, -10];
assert_eq!(a.iter().position_min(), Some(4));

let a = [1, 1, -1, -1];
assert_eq!(a.iter().position_min(), Some(2));

fn position_min_by_key<K, F>(self: Self, key: F) -> Option<usize> where Self: Sized, K: Ord, F: FnMut(&<Self as >::Item) -> K

Return the position of the minimum element in the iterator, as determined by the specified function.

If several elements are equally minimum, the position of the first of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_min_by_key(|x| x.abs()), None);

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_min_by_key(|x| x.abs()), Some(1));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_min_by_key(|x| x.abs()), Some(0));

fn position_min_by<F>(self: Self, compare: F) -> Option<usize> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return the position of the minimum element in the iterator, as determined by the specified comparison function.

If several elements are equally minimum, the position of the first of them is returned.

Examples

use itertools::Itertools;

let a: [i32; 0] = [];
assert_eq!(a.iter().position_min_by(|x, y| x.cmp(y)), None);

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_min_by(|x, y| x.cmp(y)), Some(4));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_min_by(|x, y| x.cmp(y)), Some(2));

fn position_minmax(self: Self) -> MinMaxResult<usize> where Self: Sized, <Self as >::Item: PartialOrd

Return the positions of the minimum and maximum elements in the iterator.

The return type MinMaxResult is an enum of three variants:

NoElements if the iterator is empty.
OneElement(xpos) if the iterator has exactly one element.
MinMax(xpos, ypos) is returned otherwise, where the element at xpos ≤ the element at ypos. While the referenced elements themselves may be equal, xpos cannot be equal to ypos.

On an iterator of length n, position_minmax does 1.5 * n comparisons, and so is faster than calling position_min and position_max separately which does 2 * n comparisons.

For the minimum, if several elements are equally minimum, the position of the first of them is returned. For the maximum, if several elements are equally maximum, the position of the last of them is returned.

The elements can be floats but no particular result is guaranteed if an element is NaN.

Examples

use itertools::Itertools;
use itertools::MinMaxResult::{NoElements, OneElement, MinMax};

let a: [i32; 0] = [];
assert_eq!(a.iter().position_minmax(), NoElements);

let a = [10];
assert_eq!(a.iter().position_minmax(), OneElement(0));

let a = [-3, 0, 1, 5, -10];
assert_eq!(a.iter().position_minmax(), MinMax(4, 3));

let a = [1, 1, -1, -1];
assert_eq!(a.iter().position_minmax(), MinMax(2, 1));

fn position_minmax_by_key<K, F>(self: Self, key: F) -> MinMaxResult<usize> where Self: Sized, K: PartialOrd, F: FnMut(&<Self as >::Item) -> K

Return the postions of the minimum and maximum elements of an iterator, as determined by the specified function.

The return value is a variant of MinMaxResult like for position_minmax.

The keys can be floats but no particular result is guaranteed if a key is NaN.

Examples

use itertools::Itertools;
use itertools::MinMaxResult::{NoElements, OneElement, MinMax};

let a: [i32; 0] = [];
assert_eq!(a.iter().position_minmax_by_key(|x| x.abs()), NoElements);

let a = [10_i32];
assert_eq!(a.iter().position_minmax_by_key(|x| x.abs()), OneElement(0));

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_minmax_by_key(|x| x.abs()), MinMax(1, 4));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_minmax_by_key(|x| x.abs()), MinMax(0, 3));

fn position_minmax_by<F>(self: Self, compare: F) -> MinMaxResult<usize> where Self: Sized, F: FnMut(&<Self as >::Item, &<Self as >::Item) -> Ordering

Return the postions of the minimum and maximum elements of an iterator, as determined by the specified comparison function.

The return value is a variant of MinMaxResult like for position_minmax.

Examples

use itertools::Itertools;
use itertools::MinMaxResult::{NoElements, OneElement, MinMax};

let a: [i32; 0] = [];
assert_eq!(a.iter().position_minmax_by(|x, y| x.cmp(y)), NoElements);

let a = [10_i32];
assert_eq!(a.iter().position_minmax_by(|x, y| x.cmp(y)), OneElement(0));

let a = [-3_i32, 0, 1, 5, -10];
assert_eq!(a.iter().position_minmax_by(|x, y| x.cmp(y)), MinMax(4, 3));

let a = [1_i32, 1, -1, -1];
assert_eq!(a.iter().position_minmax_by(|x, y| x.cmp(y)), MinMax(2, 1));

fn exactly_one(self: Self) -> Result<<Self as >::Item, ExactlyOneError<Self>> where Self: Sized

If the iterator yields exactly one element, that element will be returned, otherwise an error will be returned containing an iterator that has the same output as the input iterator.

This provides an additional layer of validation over just calling Iterator::next(). If your assumption that there should only be one element yielded is false this provides the opportunity to detect and handle that, preventing errors at a distance.

Examples

use itertools::Itertools;

assert_eq!((0..10).filter(|&x| x == 2).exactly_one().unwrap(), 2);
assert!((0..10).filter(|&x| x > 1 && x < 4).exactly_one().unwrap_err().eq(2..4));
assert!((0..10).filter(|&x| x > 1 && x < 5).exactly_one().unwrap_err().eq(2..5));
assert!((0..10).filter(|&_| false).exactly_one().unwrap_err().eq(0..0));

fn at_most_one(self: Self) -> Result<Option<<Self as >::Item>, ExactlyOneError<Self>> where Self: Sized

If the iterator yields no elements, Ok(None) will be returned. If the iterator yields exactly one element, that element will be returned, otherwise an error will be returned containing an iterator that has the same output as the input iterator.

This provides an additional layer of validation over just calling Iterator::next(). If your assumption that there should be at most one element yielded is false this provides the opportunity to detect and handle that, preventing errors at a distance.

Examples

use itertools::Itertools;

assert_eq!((0..10).filter(|&x| x == 2).at_most_one().unwrap(), Some(2));
assert!((0..10).filter(|&x| x > 1 && x < 4).at_most_one().unwrap_err().eq(2..4));
assert!((0..10).filter(|&x| x > 1 && x < 5).at_most_one().unwrap_err().eq(2..5));
assert_eq!((0..10).filter(|&_| false).at_most_one().unwrap(), None);

fn multipeek(self: Self) -> MultiPeek<Self> where Self: Sized

An iterator adaptor that allows the user to peek at multiple .next() values without advancing the base iterator.

Examples

use itertools::Itertools;

let mut iter = (0..10).multipeek();
assert_eq!(iter.peek(), Some(&0));
assert_eq!(iter.peek(), Some(&1));
assert_eq!(iter.peek(), Some(&2));
assert_eq!(iter.next(), Some(0));
assert_eq!(iter.peek(), Some(&1));

fn counts(self: Self) -> HashMap<<Self as >::Item, usize> where Self: Sized, <Self as >::Item: Eq + Hash

Collect the items in this iterator and return a HashMap which contains each item that appears in the iterator and the number of times it appears.

Examples

# use itertools::Itertools;
let counts = [1, 1, 1, 3, 3, 5].iter().counts();
assert_eq!(counts[&1], 3);
assert_eq!(counts[&3], 2);
assert_eq!(counts[&5], 1);
assert_eq!(counts.get(&0), None);

fn counts_by<K, F>(self: Self, f: F) -> HashMap<K, usize> where Self: Sized, K: Eq + Hash, F: FnMut(<Self as >::Item) -> K

Collect the items in this iterator and return a HashMap which contains each item that appears in the iterator and the number of times it appears, determining identity using a keying function.

# use itertools::Itertools;
struct Character {
  first_name: &'static str,
  # #[allow(dead_code)]
  last_name:  &'static str,
}

let characters =
    vec![
        Character { first_name: "Amy",   last_name: "Pond"      },
        Character { first_name: "Amy",   last_name: "Wong"      },
        Character { first_name: "Amy",   last_name: "Santiago"  },
        Character { first_name: "James", last_name: "Bond"      },
        Character { first_name: "James", last_name: "Sullivan"  },
        Character { first_name: "James", last_name: "Norington" },
        Character { first_name: "James", last_name: "Kirk"      },
    ];

let first_name_frequency =
    characters
        .into_iter()
        .counts_by(|c| c.first_name);

assert_eq!(first_name_frequency["Amy"], 3);
assert_eq!(first_name_frequency["James"], 4);
assert_eq!(first_name_frequency.contains_key("Asha"), false);

fn multiunzip<FromI>(self: Self) -> FromI where Self: Sized + MultiUnzip<FromI>

Converts an iterator of tuples into a tuple of containers.

It consumes an entire iterator of n-ary tuples, producing n collections, one for each column.

This function is, in some sense, the opposite of multizip.

use itertools::Itertools;

let inputs = vec![(1, 2, 3), (4, 5, 6), (7, 8, 9)];

let (a, b, c): (Vec<_>, Vec<_>, Vec<_>) = inputs
    .into_iter()
    .multiunzip();

assert_eq!(a, vec![1, 4, 7]);
assert_eq!(b, vec![2, 5, 8]);
assert_eq!(c, vec![3, 6, 9]);

fn try_len(self: &Self) -> Result<usize, (usize, Option<usize>)>

Returns the length of the iterator if one exists. Otherwise return self.size_hint().

Fallible ExactSizeIterator::len.

Inherits guarantees and restrictions from Iterator::size_hint.

use itertools::Itertools;

assert_eq!([0; 10].iter().try_len(), Ok(10));
assert_eq!((10..15).try_len(), Ok(5));
assert_eq!((15..10).try_len(), Ok(0));
assert_eq!((10..).try_len(), Err((usize::MAX, None)));
assert_eq!((10..15).filter(|x| x % 2 == 0).try_len(), Err((0, Some(5))));

Implementors

impl<T> Itertools for RcIter
impl<T> Itertools for Powerset
impl<T> Itertools for TakeWhileRef<'a, I, F>
impl<T> Itertools for Iterate<St, F>
impl<T> Itertools for Update<I, F>
impl<T> Itertools for Groups<'a, K, I, F>
impl<T> Itertools for KMergeBy<I, F>
impl<T> Itertools for CircularTupleWindows<I, T>
impl<T> Itertools for PutBack
impl<T> Itertools for FilterMapOk<I, F>
impl<T> Itertools for Group<'a, K, I, F>
impl<T> Itertools for ZipEq<I, J>
impl<T> Itertools for TupleBuffer<T>
impl<T> Itertools for MultiPeek
impl<T> Itertools for TakeWhileInclusive<I, F>
impl<T> Itertools for Positions<I, F>
impl<T> Itertools for Zip<T>
impl<T> Itertools for TupleCombinations<I, T>
impl<T> Itertools for TupleWindows<I, T>
impl<T> Itertools for PeekNth
impl<T> Itertools for T
impl<T> Itertools for Unique
impl<T> Itertools for UniqueBy<I, V, F>
impl<T> Itertools for MultiProduct
impl<T> Itertools for Tee
impl<T> Itertools for WithPosition
impl<T> Itertools for RepeatN<A>
impl<T> Itertools for InterleaveShortest<I, J>
impl<T> Itertools for PeekingTakeWhile<'a, I, F>
impl<T> Itertools for WhileSome
impl<T> Itertools for ProcessResults<'a, I, E>
impl<T> Itertools for FilterOk<I, F>
impl<T> Itertools for PadUsing<I, F>
impl<T> Itertools for ZipLongest<T, U>
impl<T> Itertools for Batching<I, F>
impl<T> Itertools for Unfold<St, F>
impl<T> Itertools for Product<I, J>
impl<T> Itertools for Chunk<'a, I>
impl<T> Itertools for MergeBy<I, J, F>
impl<T> Itertools for IntersperseWith<I, ElemF>
impl<T> Itertools for Permutations
impl<T> Itertools for FlattenOk<I, T, E>
impl<T> Itertools for Tuples<I, T>
impl<T> Itertools for Chunks<'a, I>
impl<T> Itertools for PutBackN
impl<T> Itertools for CombinationsWithReplacement
impl<T> Itertools for Interleave<I, J>
impl<T> Itertools for ExactlyOneError