ba402312fe
Allow a few specific ones but otherwise this helps ensure that our examples are squeaky clean! Closes #18199
416 lines
18 KiB
Rust
416 lines
18 KiB
Rust
// Copyright 2013-2014 The Rust Project Developers. See the COPYRIGHT
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// file at the top-level directory of this distribution and at
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// http://rust-lang.org/COPYRIGHT.
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//
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// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
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// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
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// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
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// option. This file may not be copied, modified, or distributed
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// except according to those terms.
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//! Collection types.
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//!
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//! Rust's standard collection library provides efficient implementations of the
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//! most common general purpose programming data structures. By using the
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//! standard implementations, it should be possible for two libraries to
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//! communicate without significant data conversion.
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//!
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//! To get this out of the way: you should probably just use `Vec` or `HashMap`.
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//! These two collections cover most use cases for generic data storage and
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//! processing. They are exceptionally good at doing what they do. All the other
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//! collections in the standard library have specific use cases where they are
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//! the optimal choice, but these cases are borderline *niche* in comparison.
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//! Even when `Vec` and `HashMap` are technically suboptimal, they're probably a
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//! good enough choice to get started.
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//!
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//! Rust's collections can be grouped into four major categories:
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//!
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//! * Sequences: `Vec`, `VecDeque`, `LinkedList`, `BitVec`
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//! * Maps: `HashMap`, `BTreeMap`, `VecMap`
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//! * Sets: `HashSet`, `BTreeSet`, `BitSet`
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//! * Misc: `BinaryHeap`
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//!
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//! # When Should You Use Which Collection?
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//!
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//! These are fairly high-level and quick break-downs of when each collection
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//! should be considered. Detailed discussions of strengths and weaknesses of
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//! individual collections can be found on their own documentation pages.
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//!
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//! ### Use a `Vec` when:
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//! * You want to collect items up to be processed or sent elsewhere later, and
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//! don't care about any properties of the actual values being stored.
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//! * You want a sequence of elements in a particular order, and will only be
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//! appending to (or near) the end.
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//! * You want a stack.
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//! * You want a resizable array.
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//! * You want a heap-allocated array.
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//!
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//! ### Use a `VecDeque` when:
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//! * You want a `Vec` that supports efficient insertion at both ends of the
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//! sequence.
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//! * You want a queue.
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//! * You want a double-ended queue (deque).
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//!
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//! ### Use a `LinkedList` when:
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//! * You want a `Vec` or `VecDeque` of unknown size, and can't tolerate
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//! amortization.
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//! * You want to efficiently split and append lists.
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//! * You are *absolutely* certain you *really*, *truly*, want a doubly linked
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//! list.
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//!
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//! ### Use a `HashMap` when:
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//! * You want to associate arbitrary keys with an arbitrary value.
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//! * You want a cache.
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//! * You want a map, with no extra functionality.
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//!
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//! ### Use a `BTreeMap` when:
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//! * You're interested in what the smallest or largest key-value pair is.
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//! * You want to find the largest or smallest key that is smaller or larger
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//! than something
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//! * You want to be able to get all of the entries in order on-demand.
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//! * You want a sorted map.
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//!
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//! ### Use a `VecMap` when:
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//! * You want a `HashMap` but with known to be small `usize` keys.
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//! * You want a `BTreeMap`, but with known to be small `usize` keys.
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//!
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//! ### Use the `Set` variant of any of these `Map`s when:
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//! * You just want to remember which keys you've seen.
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//! * There is no meaningful value to associate with your keys.
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//! * You just want a set.
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//!
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//! ### Use a `BitVec` when:
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//! * You want to store an unbounded number of booleans in a small space.
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//! * You want a bit vector.
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//!
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//! ### Use a `BitSet` when:
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//! * You want a `BitVec`, but want `Set` properties
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//!
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//! ### Use a `BinaryHeap` when:
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//!
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//! * You want to store a bunch of elements, but only ever want to process the
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//! "biggest" or "most important" one at any given time.
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//! * You want a priority queue.
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//!
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//! # Performance
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//!
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//! Choosing the right collection for the job requires an understanding of what
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//! each collection is good at. Here we briefly summarize the performance of
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//! different collections for certain important operations. For further details,
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//! see each type's documentation, and note that the names of actual methods may
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//! differ from the tables below on certain collections.
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//!
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//! Throughout the documentation, we will follow a few conventions. For all
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//! operations, the collection's size is denoted by n. If another collection is
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//! involved in the operation, it contains m elements. Operations which have an
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//! *amortized* cost are suffixed with a `*`. Operations with an *expected*
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//! cost are suffixed with a `~`.
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//!
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//! All amortized costs are for the potential need to resize when capacity is
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//! exhausted. If a resize occurs it will take O(n) time. Our collections never
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//! automatically shrink, so removal operations aren't amortized. Over a
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//! sufficiently large series of operations, the average cost per operation will
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//! deterministically equal the given cost.
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//!
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//! Only HashMap has expected costs, due to the probabilistic nature of hashing.
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//! It is theoretically possible, though very unlikely, for HashMap to
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//! experience worse performance.
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//!
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//! ## Sequences
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//!
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//! | | get(i) | insert(i) | remove(i) | append | split_off(i) |
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//! |--------------|----------------|-----------------|----------------|--------|----------------|
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//! | Vec | O(1) | O(n-i)* | O(n-i) | O(m)* | O(n-i) |
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//! | VecDeque | O(1) | O(min(i, n-i))* | O(min(i, n-i)) | O(m)* | O(min(i, n-i)) |
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//! | LinkedList | O(min(i, n-i)) | O(min(i, n-i)) | O(min(i, n-i)) | O(1) | O(min(i, n-i)) |
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//! | BitVec | O(1) | O(n-i)* | O(n-i) | O(m)* | O(n-i) |
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//!
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//! Note that where ties occur, Vec is generally going to be faster than VecDeque, and VecDeque
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//! is generally going to be faster than LinkedList. BitVec is not a general purpose collection, and
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//! therefore cannot reasonably be compared.
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//!
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//! ## Maps
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//!
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//! For Sets, all operations have the cost of the equivalent Map operation. For
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//! BitSet,
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//! refer to VecMap.
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//!
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//! | | get | insert | remove | predecessor |
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//! |----------|-----------|----------|----------|-------------|
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//! | HashMap | O(1)~ | O(1)~* | O(1)~ | N/A |
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//! | BTreeMap | O(log n) | O(log n) | O(log n) | O(log n) |
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//! | VecMap | O(1) | O(1)? | O(1) | O(n) |
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//!
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//! Note that VecMap is *incredibly* inefficient in terms of space. The O(1)
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//! insertion time assumes space for the element is already allocated.
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//! Otherwise, a large key may require a massive reallocation, with no direct
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//! relation to the number of elements in the collection. VecMap should only be
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//! seriously considered for small keys.
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//!
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//! Note also that BTreeMap's precise preformance depends on the value of B.
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//!
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//! # Correct and Efficient Usage of Collections
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//!
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//! Of course, knowing which collection is the right one for the job doesn't
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//! instantly permit you to use it correctly. Here are some quick tips for
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//! efficient and correct usage of the standard collections in general. If
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//! you're interested in how to use a specific collection in particular, consult
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//! its documentation for detailed discussion and code examples.
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//!
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//! ## Capacity Management
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//!
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//! Many collections provide several constructors and methods that refer to
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//! "capacity". These collections are generally built on top of an array.
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//! Optimally, this array would be exactly the right size to fit only the
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//! elements stored in the collection, but for the collection to do this would
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//! be very inefficient. If the backing array was exactly the right size at all
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//! times, then every time an element is inserted, the collection would have to
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//! grow the array to fit it. Due to the way memory is allocated and managed on
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//! most computers, this would almost surely require allocating an entirely new
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//! array and copying every single element from the old one into the new one.
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//! Hopefully you can see that this wouldn't be very efficient to do on every
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//! operation.
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//!
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//! Most collections therefore use an *amortized* allocation strategy. They
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//! generally let themselves have a fair amount of unoccupied space so that they
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//! only have to grow on occasion. When they do grow, they allocate a
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//! substantially larger array to move the elements into so that it will take a
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//! while for another grow to be required. While this strategy is great in
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//! general, it would be even better if the collection *never* had to resize its
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//! backing array. Unfortunately, the collection itself doesn't have enough
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//! information to do this itself. Therefore, it is up to us programmers to give
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//! it hints.
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//!
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//! Any `with_capacity` constructor will instruct the collection to allocate
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//! enough space for the specified number of elements. Ideally this will be for
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//! exactly that many elements, but some implementation details may prevent
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//! this. `Vec` and `VecDeque` can be relied on to allocate exactly the
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//! requested amount, though. Use `with_capacity` when you know exactly how many
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//! elements will be inserted, or at least have a reasonable upper-bound on that
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//! number.
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//!
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//! When anticipating a large influx of elements, the `reserve` family of
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//! methods can be used to hint to the collection how much room it should make
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//! for the coming items. As with `with_capacity`, the precise behavior of
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//! these methods will be specific to the collection of interest.
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//!
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//! For optimal performance, collections will generally avoid shrinking
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//! themselves. If you believe that a collection will not soon contain any more
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//! elements, or just really need the memory, the `shrink_to_fit` method prompts
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//! the collection to shrink the backing array to the minimum size capable of
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//! holding its elements.
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//!
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//! Finally, if ever you're interested in what the actual capacity of the
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//! collection is, most collections provide a `capacity` method to query this
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//! information on demand. This can be useful for debugging purposes, or for
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//! use with the `reserve` methods.
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//!
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//! ## Iterators
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//!
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//! Iterators are a powerful and robust mechanism used throughout Rust's
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//! standard libraries. Iterators provide a sequence of values in a generic,
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//! safe, efficient and convenient way. The contents of an iterator are usually
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//! *lazily* evaluated, so that only the values that are actually needed are
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//! ever actually produced, and no allocation need be done to temporarily store
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//! them. Iterators are primarily consumed using a `for` loop, although many
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//! functions also take iterators where a collection or sequence of values is
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//! desired.
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//!
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//! All of the standard collections provide several iterators for performing
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//! bulk manipulation of their contents. The three primary iterators almost
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//! every collection should provide are `iter`, `iter_mut`, and `into_iter`.
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//! Some of these are not provided on collections where it would be unsound or
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//! unreasonable to provide them.
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//!
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//! `iter` provides an iterator of immutable references to all the contents of a
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//! collection in the most "natural" order. For sequence collections like `Vec`,
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//! this means the items will be yielded in increasing order of index starting
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//! at 0. For ordered collections like `BTreeMap`, this means that the items
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//! will be yielded in sorted order. For unordered collections like `HashMap`,
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//! the items will be yielded in whatever order the internal representation made
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//! most convenient. This is great for reading through all the contents of the
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//! collection.
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//!
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//! ```
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//! let vec = vec![1, 2, 3, 4];
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//! for x in vec.iter() {
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//! println!("vec contained {}", x);
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//! }
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//! ```
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//!
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//! `iter_mut` provides an iterator of *mutable* references in the same order as
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//! `iter`. This is great for mutating all the contents of the collection.
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//!
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//! ```
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//! let mut vec = vec![1, 2, 3, 4];
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//! for x in vec.iter_mut() {
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//! *x += 1;
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//! }
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//! ```
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//!
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//! `into_iter` transforms the actual collection into an iterator over its
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//! contents by-value. This is great when the collection itself is no longer
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//! needed, and the values are needed elsewhere. Using `extend` with `into_iter`
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//! is the main way that contents of one collection are moved into another.
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//! Calling `collect` on an iterator itself is also a great way to convert one
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//! collection into another. Both of these methods should internally use the
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//! capacity management tools discussed in the previous section to do this as
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//! efficiently as possible.
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//!
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//! ```
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//! let mut vec1 = vec![1, 2, 3, 4];
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//! let vec2 = vec![10, 20, 30, 40];
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//! vec1.extend(vec2.into_iter());
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//! ```
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//!
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//! ```
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//! use std::collections::VecDeque;
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//!
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//! let vec = vec![1, 2, 3, 4];
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//! let buf: VecDeque<_> = vec.into_iter().collect();
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//! ```
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//!
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//! Iterators also provide a series of *adapter* methods for performing common
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//! tasks to sequences. Among the adapters are functional favorites like `map`,
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//! `fold`, `skip`, and `take`. Of particular interest to collections is the
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//! `rev` adapter, that reverses any iterator that supports this operation. Most
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//! collections provide reversible iterators as the way to iterate over them in
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//! reverse order.
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//!
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//! ```
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//! let vec = vec![1, 2, 3, 4];
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//! for x in vec.iter().rev() {
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//! println!("vec contained {}", x);
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//! }
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//! ```
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//!
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//! Several other collection methods also return iterators to yield a sequence
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//! of results but avoid allocating an entire collection to store the result in.
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//! This provides maximum flexibility as `collect` or `extend` can be called to
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//! "pipe" the sequence into any collection if desired. Otherwise, the sequence
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//! can be looped over with a `for` loop. The iterator can also be discarded
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//! after partial use, preventing the computation of the unused items.
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//!
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//! ## Entries
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//!
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//! The `entry` API is intended to provide an efficient mechanism for
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//! manipulating the contents of a map conditionally on the presence of a key or
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//! not. The primary motivating use case for this is to provide efficient
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//! accumulator maps. For instance, if one wishes to maintain a count of the
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//! number of times each key has been seen, they will have to perform some
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//! conditional logic on whether this is the first time the key has been seen or
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//! not. Normally, this would require a `find` followed by an `insert`,
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//! effectively duplicating the search effort on each insertion.
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//!
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//! When a user calls `map.entry(&key)`, the map will search for the key and
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//! then yield a variant of the `Entry` enum.
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//!
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//! If a `Vacant(entry)` is yielded, then the key *was not* found. In this case
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//! the only valid operation is to `insert` a value into the entry. When this is
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//! done, the vacant entry is consumed and converted into a mutable reference to
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//! the the value that was inserted. This allows for further manipulation of the
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//! value beyond the lifetime of the search itself. This is useful if complex
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//! logic needs to be performed on the value regardless of whether the value was
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//! just inserted.
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//!
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//! If an `Occupied(entry)` is yielded, then the key *was* found. In this case,
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//! the user has several options: they can `get`, `insert`, or `remove` the
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//! value of the occupied entry. Additionally, they can convert the occupied
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//! entry into a mutable reference to its value, providing symmetry to the
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//! vacant `insert` case.
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//!
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//! ### Examples
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//!
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//! Here are the two primary ways in which `entry` is used. First, a simple
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//! example where the logic performed on the values is trivial.
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//!
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//! #### Counting the number of times each character in a string occurs
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//!
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//! ```
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//! use std::collections::btree_map::BTreeMap;
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//!
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//! let mut count = BTreeMap::new();
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//! let message = "she sells sea shells by the sea shore";
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//!
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//! for c in message.chars() {
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//! *count.entry(c).or_insert(0) += 1;
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//! }
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//!
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//! assert_eq!(count.get(&'s'), Some(&8));
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//!
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//! println!("Number of occurrences of each character");
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//! for (char, count) in count.iter() {
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//! println!("{}: {}", char, count);
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//! }
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//! ```
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//!
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//! When the logic to be performed on the value is more complex, we may simply
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//! use the `entry` API to ensure that the value is initialized, and perform the
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//! logic afterwards.
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//!
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//! #### Tracking the inebriation of customers at a bar
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//!
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//! ```
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//! use std::collections::btree_map::BTreeMap;
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//!
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//! // A client of the bar. They have an id and a blood alcohol level.
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//! struct Person { id: u32, blood_alcohol: f32 }
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//!
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//! // All the orders made to the bar, by client id.
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//! let orders = vec![1,2,1,2,3,4,1,2,2,3,4,1,1,1];
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//!
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//! // Our clients.
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//! let mut blood_alcohol = BTreeMap::new();
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//!
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//! for id in orders.into_iter() {
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//! // If this is the first time we've seen this customer, initialize them
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//! // with no blood alcohol. Otherwise, just retrieve them.
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//! let person = blood_alcohol.entry(id).or_insert(Person{id: id, blood_alcohol: 0.0});
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//!
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//! // Reduce their blood alcohol level. It takes time to order and drink a beer!
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//! person.blood_alcohol *= 0.9;
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//!
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//! // Check if they're sober enough to have another beer.
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//! if person.blood_alcohol > 0.3 {
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//! // Too drunk... for now.
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//! println!("Sorry {}, I have to cut you off", person.id);
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//! } else {
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//! // Have another!
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//! person.blood_alcohol += 0.1;
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//! }
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//! }
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//! ```
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#![stable(feature = "rust1", since = "1.0.0")]
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pub use core_collections::Bound;
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pub use core_collections::{BinaryHeap, BitVec, BitSet, BTreeMap, BTreeSet};
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pub use core_collections::{LinkedList, VecDeque, VecMap};
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pub use core_collections::{binary_heap, bit_vec, bit_set, btree_map, btree_set};
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pub use core_collections::{linked_list, vec_deque, vec_map};
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pub use self::hash_map::HashMap;
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pub use self::hash_set::HashSet;
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mod hash;
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#[stable(feature = "rust1", since = "1.0.0")]
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pub mod hash_map {
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//! A hashmap
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pub use super::hash::map::*;
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}
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#[stable(feature = "rust1", since = "1.0.0")]
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pub mod hash_set {
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//! A hashset
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pub use super::hash::set::*;
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}
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/// Experimental support for providing custom hash algorithms to a HashMap and
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/// HashSet.
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#[unstable(feature = "std_misc", reason = "module was recently added")]
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pub mod hash_state {
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pub use super::hash::state::*;
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}
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