proposal for BTreeMap/Set min/max, #62924
- Which pair of names: #62924 lists the existing possibilities min/max, first/last, (EDIT) front/back, peek(/peek_back?). Iterators have next/next_back or next/last. I'm slightly in favour of first/last because min/max might suggest they search over the entire map, and front/back pretends they are only about position.
- Return key only instead of pair like iterator does?
- If not, then keep the _key_value suffix? ~~Also provide variant with mutable value? But there is no such variant for get_key_value.~~
- Look for and upgrade more usages of `.iter().next()` and such in the libraries? I only upgraded the ones I contributed myself, all very recently.
Implement ordered/sorted iterators on BinaryHeap as per #59278
I've implemented the ordered version of iterator on BinaryHeap as per #59278.
# Added methods:
* `.into_iter_sorted()`
* like `.into_iter()`; but returns elements in heap order
* `.drain_sorted()`
* like `.drain()`; but returns elements in heap order
* It's a bit _lazy_; elements are removed on drop. (Edit: it’s similar to vec::Drain)
For `DrainSorted` struct, I implemented `Drop` trait following @scottmcm 's [suggestion](https://github.com/rust-lang/rust/issues/59278#issuecomment-537306925)
# ~TODO~ DONE
* ~I think I need to add more tests other than doctest.~
# **Notes:**
* we renamed `_ordered` to `_sorted`, because the latter is more common in rust libs. (as suggested by @KodrAus )
This commit deletes the `alloc_system` crate from the standard
distribution. This unstable crate is no longer needed in the modern
stable global allocator world, but rather its functionality is folded
directly into the standard library. The standard library was already the
only stable location to access this crate, and as a result this should
not affect any stable code.
Incorporate a stray test
`liballoc/repeat-generic-slice.rs` doesn't seem to be tested (I think it was intended to be placed in `run-pass`). This PR incorporates the test into `liballoc/tests`.
Add slice::sort_by_cached_key as a memoised sort_by_key
At present, `slice::sort_by_key` calls its key function twice for each comparison that is made. When the key function is expensive (which can often be the case when `sort_by_key` is chosen over `sort_by`), this can lead to very suboptimal behaviour.
To address this, I've introduced a new slice method, `sort_by_cached_key`, which has identical semantic behaviour to `sort_by_key`, except that it guarantees the key function will only be called once per element.
Where there are `n` elements and the key function is `O(m)`:
- `slice::sort_by_cached_key` time complexity is `O(m n log m n)`, compared to `slice::sort_by_key`'s `O(m n + n log n)`.
- `slice::sort_by_cached_key` space complexity remains at `O(n + m)`. (Technically, it now reserves a slice of size `n`, whereas before it reserved a slice of size `n/2`.)
`slice::sort_unstable_by_key` has not been given an analogue, as it is important that unstable sorts are in-place, which is not a property that is guaranteed here. However, this also means that `slice::sort_unstable_by_key` is likely to be slower than `slice::sort_by_cached_key` when the key function does not have negligible complexity. We might want to explore this trade-off further in the future.
Benchmarks (for a vector of 100 `i32`s):
```
# Lexicographic: `|x| x.to_string()`
test bench_sort_by_key ... bench: 112,638 ns/iter (+/- 19,563)
test bench_sort_by_cached_key ... bench: 15,038 ns/iter (+/- 4,814)
# Identity: `|x| *x`
test bench_sort_by_key ... bench: 1,346 ns/iter (+/- 238)
test bench_sort_by_cached_key ... bench: 1,839 ns/iter (+/- 765)
# Power: `|x| x.pow(31)`
test bench_sort_by_key ... bench: 3,624 ns/iter (+/- 738)
test bench_sort_by_cached_key ... bench: 1,997 ns/iter (+/- 311)
# Abs: `|x| x.abs()`
test bench_sort_by_key ... bench: 1,546 ns/iter (+/- 174)
test bench_sort_by_cached_key ... bench: 1,668 ns/iter (+/- 790)
```
(So it seems functions that are single operations do perform slightly worse with this method, but for pretty much any more complex key, you're better off with this optimisation.)
I've definitely found myself using expensive keys in the past and wishing this optimisation was made (e.g. for https://github.com/rust-lang/rust/pull/47415). This feels like both desirable and expected behaviour, at the small cost of slightly more stack allocation and minute degradation in performance for extremely trivial keys.
Resolves#34447.
Stabilize inclusive range (`..=`)
Stabilize the followings:
* `inclusive_range` — The `std::ops::RangeInclusive` and `std::ops::RangeInclusiveTo` types, except its fields (tracked by #49022 separately).
* `inclusive_range_syntax` — The `a..=b` and `..=b` expression syntax
* `dotdoteq_in_patterns` — Using `a..=b` in a pattern
cc #28237
r? @rust-lang/lang
