This is the core method in terms of which the other methods (fold, all, any, find, position, nth, ...) can be implemented, allowing Iterator implementors to get the full goodness of internal iteration by only overriding one method (per direction).
Improve wording for StepBy
No other iterator makes the distinction between an iterator and an iterator adapter
in its summary line, so change it to be consistent with all other adapters.
Add more custom folding to `core::iter` adaptors
Many of the iterator adaptors will perform faster folds if they forward
to their inner iterator's folds, especially for inner types like `Chain`
which are optimized too. The following types are newly specialized:
| Type | `fold` | `rfold` |
| ----------- | ------ | ------- |
| `Enumerate` | ✓ | ✓ |
| `Filter` | ✓ | ✓ |
| `FilterMap` | ✓ | ✓ |
| `FlatMap` | exists | ✓ |
| `Fuse` | ✓ | ✓ |
| `Inspect` | ✓ | ✓ |
| `Peekable` | ✓ | N/A¹ |
| `Skip` | ✓ | N/A² |
| `SkipWhile` | ✓ | N/A¹ |
¹ not a `DoubleEndedIterator`
² `Skip::next_back` doesn't pull skipped items at all, but this couldn't
be avoided if `Skip::rfold` were to call its inner iterator's `rfold`.
Benchmarks
----------
In the following results, plain `_sum` computes the sum of a million
integers -- note that `sum()` is implemented with `fold()`. The
`_ref_sum` variants do the same on a `by_ref()` iterator, which is
limited to calling `next()` one by one, without specialized `fold`.
The `chain` variants perform the same tests on two iterators chained
together, to show a greater benefit of forwarding `fold` internally.
test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228)
test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676)
test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110)
test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334)
test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051)
test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013)
test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188)
test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894)
test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440)
test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972)
test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507)
test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472)
test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395)
test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341)
test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748)
test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616)
test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371)
test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928)
test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702)
test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320)
test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186)
test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712)
test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480)
test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309)
test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198)
test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645)
test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252)
test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054)
test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845)
test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892)
test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804)
test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
Many of the iterator adaptors will perform faster folds if they forward
to their inner iterator's folds, especially for inner types like `Chain`
which are optimized too. The following types are newly specialized:
| Type | `fold` | `rfold` |
| ----------- | ------ | ------- |
| `Enumerate` | ✓ | ✓ |
| `Filter` | ✓ | ✓ |
| `FilterMap` | ✓ | ✓ |
| `FlatMap` | exists | ✓ |
| `Fuse` | ✓ | ✓ |
| `Inspect` | ✓ | ✓ |
| `Peekable` | ✓ | N/A¹ |
| `Skip` | ✓ | N/A² |
| `SkipWhile` | ✓ | N/A¹ |
¹ not a `DoubleEndedIterator`
² `Skip::next_back` doesn't pull skipped items at all, but this couldn't
be avoided if `Skip::rfold` were to call its inner iterator's `rfold`.
Benchmarks
----------
In the following results, plain `_sum` computes the sum of a million
integers -- note that `sum()` is implemented with `fold()`. The
`_ref_sum` variants do the same on a `by_ref()` iterator, which is
limited to calling `next()` one by one, without specialized `fold`.
The `chain` variants perform the same tests on two iterators chained
together, to show a greater benefit of forwarding `fold` internally.
test iter::bench_enumerate_chain_ref_sum ... bench: 2,216,264 ns/iter (+/- 29,228)
test iter::bench_enumerate_chain_sum ... bench: 922,380 ns/iter (+/- 2,676)
test iter::bench_enumerate_ref_sum ... bench: 476,094 ns/iter (+/- 7,110)
test iter::bench_enumerate_sum ... bench: 476,438 ns/iter (+/- 3,334)
test iter::bench_filter_chain_ref_sum ... bench: 2,266,095 ns/iter (+/- 6,051)
test iter::bench_filter_chain_sum ... bench: 745,594 ns/iter (+/- 2,013)
test iter::bench_filter_ref_sum ... bench: 889,696 ns/iter (+/- 1,188)
test iter::bench_filter_sum ... bench: 667,325 ns/iter (+/- 1,894)
test iter::bench_filter_map_chain_ref_sum ... bench: 2,259,195 ns/iter (+/- 353,440)
test iter::bench_filter_map_chain_sum ... bench: 1,223,280 ns/iter (+/- 1,972)
test iter::bench_filter_map_ref_sum ... bench: 611,607 ns/iter (+/- 2,507)
test iter::bench_filter_map_sum ... bench: 611,610 ns/iter (+/- 472)
test iter::bench_fuse_chain_ref_sum ... bench: 2,246,106 ns/iter (+/- 22,395)
test iter::bench_fuse_chain_sum ... bench: 634,887 ns/iter (+/- 1,341)
test iter::bench_fuse_ref_sum ... bench: 444,816 ns/iter (+/- 1,748)
test iter::bench_fuse_sum ... bench: 316,954 ns/iter (+/- 2,616)
test iter::bench_inspect_chain_ref_sum ... bench: 2,245,431 ns/iter (+/- 21,371)
test iter::bench_inspect_chain_sum ... bench: 631,645 ns/iter (+/- 4,928)
test iter::bench_inspect_ref_sum ... bench: 317,437 ns/iter (+/- 702)
test iter::bench_inspect_sum ... bench: 315,942 ns/iter (+/- 4,320)
test iter::bench_peekable_chain_ref_sum ... bench: 2,243,585 ns/iter (+/- 12,186)
test iter::bench_peekable_chain_sum ... bench: 634,848 ns/iter (+/- 1,712)
test iter::bench_peekable_ref_sum ... bench: 444,808 ns/iter (+/- 480)
test iter::bench_peekable_sum ... bench: 317,133 ns/iter (+/- 3,309)
test iter::bench_skip_chain_ref_sum ... bench: 1,778,734 ns/iter (+/- 2,198)
test iter::bench_skip_chain_sum ... bench: 761,850 ns/iter (+/- 1,645)
test iter::bench_skip_ref_sum ... bench: 478,207 ns/iter (+/- 119,252)
test iter::bench_skip_sum ... bench: 315,614 ns/iter (+/- 3,054)
test iter::bench_skip_while_chain_ref_sum ... bench: 2,486,370 ns/iter (+/- 4,845)
test iter::bench_skip_while_chain_sum ... bench: 633,915 ns/iter (+/- 5,892)
test iter::bench_skip_while_ref_sum ... bench: 666,926 ns/iter (+/- 804)
test iter::bench_skip_while_sum ... bench: 444,405 ns/iter (+/- 571)
No other iterator makes the distinction between an iterator and an iterator adapter
in its summary line, so change it to be consistent with all other adapters.
This verifies that TrustedRandomAccess has no side effects when the
iterator item implements Copy. This also implements TrustedLen and
TrustedRandomAccess for str::Bytes.
Add iterator method .rfold(init, function); the reverse of fold
rfold is the reverse version of fold.
Fold allows iterators to implement a different (non-resumable) internal
iteration when it is more efficient than the external iteration implemented
through the next method. (Common examples are VecDeque and .chain()).
Introduce rfold() so that the same customization is available for reverse
iteration. This is achieved by both adding the method, and by having the
Rev\<I> adaptor connect Rev::rfold → I::fold and Rev::fold → I::rfold.
On the surface, rfold(..) is just .rev().fold(..), but the special case
implementations allow a data structure specific fold to be used through for
example .iter().rev(); we thus have gains even for users never calling exactly
rfold themselves.
`FlatMap` can use internal iteration for its `fold`, which shows a
performance advantage in the new benchmarks:
test iter::bench_flat_map_chain_ref_sum ... bench: 4,354,111 ns/iter (+/- 108,871)
test iter::bench_flat_map_chain_sum ... bench: 468,167 ns/iter (+/- 2,274)
test iter::bench_flat_map_ref_sum ... bench: 449,616 ns/iter (+/- 6,257)
test iter::bench_flat_map_sum ... bench: 348,010 ns/iter (+/- 1,227)
... where the "ref" benches are using `by_ref()` that isn't optimized.
So this change shows a decent advantage on its own, but much more when
combined with a `chain` iterator that also optimizes `fold`.
Replaced by adding extra imports, adding hidden code (`# ...`), modifying
examples to be runnable (sorry Homura), specifying non-Rust code, and
converting to should_panic, no_run, or compile_fail.
Remaining "```ignore"s received an explanation why they are being ignored.
Change for-loop desugar to not borrow the iterator during the loop
This is enables the use of suspend points inside for-loops in movable generators. This is illegal in the current desugaring as `iter` is borrowed across the body.
Override size_hint and propagate ExactSizeIterator for iter::StepBy
Generally useful, but also a prerequisite for moving a bunch of unit tests off `Range*::step_by`.
A small non-breaking subset of https://github.com/rust-lang/rust/pull/42110 (which I closed).
Includes two small documentation changes @ivandardi requested on that PR.
r? @alexcrichton
Correct some stability versions
These were found by running tidy on stable versions of rust and finding
features stabilised with the wrong version numbers.
Fix two small issues in iterator docs
- `collect()` is a regular method, not an adaptor (does not return an Iterator). I just randomly picked `filter` as a third common adaptor to mention instead.
- Fix example in `Map`'s docs so that it uses the DoubleEndedIterator implementation
Forward ExactSizeIterator::len and is_empty for important iterator adaptors
Forward ExactSizeIterator::len and is_empty for important iterator adaptors
Because some iterators will provide improved version of len and/or is_empty,
adaptors should forward to those implementations if possible.
Peekable must remember if a None has been seen in the `.peek()` method.
It ensures that `.peek(); .peek();` or `.peek(); .next();` only advances the
underlying iterator at most once. This does not by itself make the iterator
fused.
Add Iterator trait TrustedLen to enable better FromIterator / Extend
This trait attempts to improve FromIterator / Extend code by enabling it to trust the iterator to produce an exact number of elements, which means that reallocation needs to happen only once and is moved out of the loop.
`TrustedLen` differs from `ExactSizeIterator` in that it attempts to include _more_ iterators by allowing for the case that the iterator's len does not fit in `usize`. Consumers must check for this case (for example they could panic, since they can't allocate a collection of that size).
For example, chain can be TrustedLen and all numerical ranges can be TrustedLen. All they need to do is to report an exact size if it fits in `usize`, and `None` as the upper bound otherwise.
The trait describes its contract like this:
```
An iterator that reports an accurate length using size_hint.
The iterator reports a size hint where it is either exact
(lower bound is equal to upper bound), or the upper bound is `None`.
The upper bound must only be `None` if the actual iterator length is
larger than `usize::MAX`.
The iterator must produce exactly the number of elements it reported.
This trait must only be implemented when the contract is upheld.
Consumers of this trait must inspect `.size_hint()`’s upper bound.
```
Fixes#37232
