mod.rs.html -- source
Description: Source to the Rust file `/usr/obj/ports/rust-1.16.0/rustc-1.16.0-src/src/libstd/collections/mod.rs`.
Keywords: rust, rustlang, rust-lang

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    // Copyright 2013-2014 The Rust Project Developers. See the COPYRIGHT
    // file at the top-level directory of this distribution and at
    // http://rust-lang.org/COPYRIGHT.
    //
    // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
    // http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
    // <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
    // option. This file may not be copied, modified, or distributed
    // except according to those terms.

    //! Collection types.
    //!
    //! Rust's standard collection library provides efficient implementations of the
    //! most common general purpose programming data structures. By using the
    //! standard implementations, it should be possible for two libraries to
    //! communicate without significant data conversion.
    //!
    //! To get this out of the way: you should probably just use [`Vec`] or [`HashMap`].
    //! These two collections cover most use cases for generic data storage and
    //! processing. They are exceptionally good at doing what they do. All the other
    //! collections in the standard library have specific use cases where they are
    //! the optimal choice, but these cases are borderline *niche* in comparison.
    //! Even when `Vec` and `HashMap` are technically suboptimal, they're probably a
    //! good enough choice to get started.
    //!
    //! Rust's collections can be grouped into four major categories:
    //!
    //! * Sequences: [`Vec`], [`VecDeque`], [`LinkedList`]
    //! * Maps: [`HashMap`], [`BTreeMap`]
    //! * Sets: [`HashSet`], [`BTreeSet`]
    //! * Misc: [`BinaryHeap`]
    //!
    //! # When Should You Use Which Collection?
    //!
    //! These are fairly high-level and quick break-downs of when each collection
    //! should be considered. Detailed discussions of strengths and weaknesses of
    //! individual collections can be found on their own documentation pages.
    //!
    //! ### Use a `Vec` when:
    //! * You want to collect items up to be processed or sent elsewhere later, and
    //!   don't care about any properties of the actual values being stored.
    //! * You want a sequence of elements in a particular order, and will only be
    //!   appending to (or near) the end.
    //! * You want a stack.
    //! * You want a resizable array.
    //! * You want a heap-allocated array.
    //!
    //! ### Use a `VecDeque` when:
    //! * You want a [`Vec`] that supports efficient insertion at both ends of the
    //!   sequence.
    //! * You want a queue.
    //! * You want a double-ended queue (deque).
    //!
    //! ### Use a `LinkedList` when:
    //! * You want a [`Vec`] or [`VecDeque`] of unknown size, and can't tolerate
    //!   amortization.
    //! * You want to efficiently split and append lists.
    //! * You are *absolutely* certain you *really*, *truly*, want a doubly linked
    //!   list.
    //!
    //! ### Use a `HashMap` when:
    //! * You want to associate arbitrary keys with an arbitrary value.
    //! * You want a cache.
    //! * You want a map, with no extra functionality.
    //!
    //! ### Use a `BTreeMap` when:
    //! * You're interested in what the smallest or largest key-value pair is.
    //! * You want to find the largest or smallest key that is smaller or larger
    //!   than something.
    //! * You want to be able to get all of the entries in order on-demand.
    //! * You want a sorted map.
    //!
    //! ### Use the `Set` variant of any of these `Map`s when:
    //! * You just want to remember which keys you've seen.
    //! * There is no meaningful value to associate with your keys.
    //! * You just want a set.
    //!
    //! ### Use a `BinaryHeap` when:
    //!
    //! * You want to store a bunch of elements, but only ever want to process the
    //!   "biggest" or "most important" one at any given time.
    //! * You want a priority queue.
    //!
    //! # Performance
    //!
    //! Choosing the right collection for the job requires an understanding of what
    //! each collection is good at. Here we briefly summarize the performance of
    //! different collections for certain important operations. For further details,
    //! see each type's documentation, and note that the names of actual methods may
    //! differ from the tables below on certain collections.
    //!
    //! Throughout the documentation, we will follow a few conventions. For all
    //! operations, the collection's size is denoted by n. If another collection is
    //! involved in the operation, it contains m elements. Operations which have an
    //! *amortized* cost are suffixed with a `*`. Operations with an *expected*
    //! cost are suffixed with a `~`.
    //!
    //! All amortized costs are for the potential need to resize when capacity is
    //! exhausted. If a resize occurs it will take O(n) time. Our collections never
    //! automatically shrink, so removal operations aren't amortized. Over a
    //! sufficiently large series of operations, the average cost per operation will
    //! deterministically equal the given cost.
    //!
    //! Only [`HashMap`] has expected costs, due to the probabilistic nature of hashing.
    //! It is theoretically possible, though very unlikely, for [`HashMap`] to
    //! experience worse performance.
    //!
    //! ## Sequences
    //!
    //! |                | get(i)         | insert(i)       | remove(i)      | append | split_off(i)   |
    //! |----------------|----------------|-----------------|----------------|--------|----------------|
    //! | [`Vec`]        | O(1)           | O(n-i)*         | O(n-i)         | O(m)*  | O(n-i)         |
    //! | [`VecDeque`]   | O(1)           | O(min(i, n-i))* | O(min(i, n-i)) | O(m)*  | O(min(i, n-i)) |
    //! | [`LinkedList`] | O(min(i, n-i)) | O(min(i, n-i))  | O(min(i, n-i)) | O(1)   | O(min(i, n-i)) |
    //!
    //! Note that where ties occur, [`Vec`] is generally going to be faster than [`VecDeque`], and
    //! [`VecDeque`] is generally going to be faster than [`LinkedList`].
    //!
    //! ## Maps
    //!
    //! For Sets, all operations have the cost of the equivalent Map operation.
    //!
    //! |              | get       | insert   | remove   | predecessor | append |
    //! |--------------|-----------|----------|----------|-------------|--------|
    //! | [`HashMap`]  | O(1)~     | O(1)~*   | O(1)~    | N/A         | N/A    |
    //! | [`BTreeMap`] | O(log n)  | O(log n) | O(log n) | O(log n)    | O(n+m) |
    //!
    //! # Correct and Efficient Usage of Collections
    //!
    //! Of course, knowing which collection is the right one for the job doesn't
    //! instantly permit you to use it correctly. Here are some quick tips for
    //! efficient and correct usage of the standard collections in general. If
    //! you're interested in how to use a specific collection in particular, consult
    //! its documentation for detailed discussion and code examples.
    //!
    //! ## Capacity Management
    //!
    //! Many collections provide several constructors and methods that refer to
    //! "capacity". These collections are generally built on top of an array.
    //! Optimally, this array would be exactly the right size to fit only the
    //! elements stored in the collection, but for the collection to do this would
    //! be very inefficient. If the backing array was exactly the right size at all
    //! times, then every time an element is inserted, the collection would have to
    //! grow the array to fit it. Due to the way memory is allocated and managed on
    //! most computers, this would almost surely require allocating an entirely new
    //! array and copying every single element from the old one into the new one.
    //! Hopefully you can see that this wouldn't be very efficient to do on every
    //! operation.
    //!
    //! Most collections therefore use an *amortized* allocation strategy. They
    //! generally let themselves have a fair amount of unoccupied space so that they
    //! only have to grow on occasion. When they do grow, they allocate a
    //! substantially larger array to move the elements into so that it will take a
    //! while for another grow to be required. While this strategy is great in
    //! general, it would be even better if the collection *never* had to resize its
    //! backing array. Unfortunately, the collection itself doesn't have enough
    //! information to do this itself. Therefore, it is up to us programmers to give
    //! it hints.
    //!
    //! Any `with_capacity()` constructor will instruct the collection to allocate
    //! enough space for the specified number of elements. Ideally this will be for
    //! exactly that many elements, but some implementation details may prevent
    //! this. [`Vec`] and [`VecDeque`] can be relied on to allocate exactly the
    //! requested amount, though. Use `with_capacity()` when you know exactly how many
    //! elements will be inserted, or at least have a reasonable upper-bound on that
    //! number.
    //!
    //! When anticipating a large influx of elements, the `reserve()` family of
    //! methods can be used to hint to the collection how much room it should make
    //! for the coming items. As with `with_capacity()`, the precise behavior of
    //! these methods will be specific to the collection of interest.
    //!
    //! For optimal performance, collections will generally avoid shrinking
    //! themselves. If you believe that a collection will not soon contain any more
    //! elements, or just really need the memory, the `shrink_to_fit()` method prompts
    //! the collection to shrink the backing array to the minimum size capable of
    //! holding its elements.
    //!
    //! Finally, if ever you're interested in what the actual capacity of the
    //! collection is, most collections provide a `capacity()` method to query this
    //! information on demand. This can be useful for debugging purposes, or for
    //! use with the `reserve()` methods.
    //!
    //! ## Iterators
    //!
    //! Iterators are a powerful and robust mechanism used throughout Rust's
    //! standard libraries. Iterators provide a sequence of values in a generic,
    //! safe, efficient and convenient way. The contents of an iterator are usually
    //! *lazily* evaluated, so that only the values that are actually needed are
    //! ever actually produced, and no allocation need be done to temporarily store
    //! them. Iterators are primarily consumed using a `for` loop, although many
    //! functions also take iterators where a collection or sequence of values is
    //! desired.
    //!
    //! All of the standard collections provide several iterators for performing
    //! bulk manipulation of their contents. The three primary iterators almost
    //! every collection should provide are `iter()`, `iter_mut()`, and `into_iter()`.
    //! Some of these are not provided on collections where it would be unsound or
    //! unreasonable to provide them.
    //!
    //! `iter()` provides an iterator of immutable references to all the contents of a
    //! collection in the most "natural" order. For sequence collections like [`Vec`],
    //! this means the items will be yielded in increasing order of index starting
    //! at 0. For ordered collections like [`BTreeMap`], this means that the items
    //! will be yielded in sorted order. For unordered collections like [`HashMap`],
    //! the items will be yielded in whatever order the internal representation made
    //! most convenient. This is great for reading through all the contents of the
    //! collection.
    //!
    //! ```
    //! let vec = vec![1, 2, 3, 4];
    //! for x in vec.iter() {
    //!    println!("vec contained {}", x);
    //! }
    //! ```
    //!
    //! `iter_mut()` provides an iterator of *mutable* references in the same order as
    //! `iter()`. This is great for mutating all the contents of the collection.
    //!
    //! ```
    //! let mut vec = vec![1, 2, 3, 4];
    //! for x in vec.iter_mut() {
    //!    *x += 1;
    //! }
    //! ```
    //!
    //! `into_iter()` transforms the actual collection into an iterator over its
    //! contents by-value. This is great when the collection itself is no longer
    //! needed, and the values are needed elsewhere. Using `extend()` with `into_iter()`
    //! is the main way that contents of one collection are moved into another.
    //! `extend()` automatically calls `into_iter()`, and takes any `T: `[`IntoIterator`].
    //! Calling `collect()` on an iterator itself is also a great way to convert one
    //! collection into another. Both of these methods should internally use the
    //! capacity management tools discussed in the previous section to do this as
    //! efficiently as possible.
    //!
    //! ```
    //! let mut vec1 = vec![1, 2, 3, 4];
    //! let vec2 = vec![10, 20, 30, 40];
    //! vec1.extend(vec2);
    //! ```
    //!
    //! ```
    //! use std::collections::VecDeque;
    //!
    //! let vec = vec![1, 2, 3, 4];
    //! let buf: VecDeque<_> = vec.into_iter().collect();
    //! ```
    //!
    //! Iterators also provide a series of *adapter* methods for performing common
    //! threads to sequences. Among the adapters are functional favorites like `map()`,
    //! `fold()`, `skip()` and `take()`. Of particular interest to collections is the
    //! `rev()` adapter, that reverses any iterator that supports this operation. Most
    //! collections provide reversible iterators as the way to iterate over them in
    //! reverse order.
    //!
    //! ```
    //! let vec = vec![1, 2, 3, 4];
    //! for x in vec.iter().rev() {
    //!    println!("vec contained {}", x);
    //! }
    //! ```
    //!
    //! Several other collection methods also return iterators to yield a sequence
    //! of results but avoid allocating an entire collection to store the result in.
    //! This provides maximum flexibility as `collect()` or `extend()` can be called to
    //! "pipe" the sequence into any collection if desired. Otherwise, the sequence
    //! can be looped over with a `for` loop. The iterator can also be discarded
    //! after partial use, preventing the computation of the unused items.
    //!
    //! ## Entries
    //!
    //! The `entry()` API is intended to provide an efficient mechanism for
    //! manipulating the contents of a map conditionally on the presence of a key or
    //! not. The primary motivating use case for this is to provide efficient
    //! accumulator maps. For instance, if one wishes to maintain a count of the
    //! number of times each key has been seen, they will have to perform some
    //! conditional logic on whether this is the first time the key has been seen or
    //! not. Normally, this would require a `find()` followed by an `insert()`,
    //! effectively duplicating the search effort on each insertion.
    //!
    //! When a user calls `map.entry(&key)`, the map will search for the key and
    //! then yield a variant of the `Entry` enum.
    //!
    //! If a `Vacant(entry)` is yielded, then the key *was not* found. In this case
    //! the only valid operation is to `insert()` a value into the entry. When this is
    //! done, the vacant entry is consumed and converted into a mutable reference to
    //! the value that was inserted. This allows for further manipulation of the
    //! value beyond the lifetime of the search itself. This is useful if complex
    //! logic needs to be performed on the value regardless of whether the value was
    //! just inserted.
    //!
    //! If an `Occupied(entry)` is yielded, then the key *was* found. In this case,
    //! the user has several options: they can `get()`, `insert()` or `remove()` the
    //! value of the occupied entry. Additionally, they can convert the occupied
    //! entry into a mutable reference to its value, providing symmetry to the
    //! vacant `insert()` case.
    //!
    //! ### Examples
    //!
    //! Here are the two primary ways in which `entry()` is used. First, a simple
    //! example where the logic performed on the values is trivial.
    //!
    //! #### Counting the number of times each character in a string occurs
    //!
    //! ```
    //! use std::collections::btree_map::BTreeMap;
    //!
    //! let mut count = BTreeMap::new();
    //! let message = "she sells sea shells by the sea shore";
    //!
    //! for c in message.chars() {
    //!     *count.entry(c).or_insert(0) += 1;
    //! }
    //!
    //! assert_eq!(count.get(&'s'), Some(&8));
    //!
    //! println!("Number of occurrences of each character");
    //! for (char, count) in &count {
    //!     println!("{}: {}", char, count);
    //! }
    //! ```
    //!
    //! When the logic to be performed on the value is more complex, we may simply
    //! use the `entry()` API to ensure that the value is initialized and perform the
    //! logic afterwards.
    //!
    //! #### Tracking the inebriation of customers at a bar
    //!
    //! ```
    //! use std::collections::btree_map::BTreeMap;
    //!
    //! // A client of the bar. They have a blood alcohol level.
    //! struct Person { blood_alcohol: f32 }
    //!
    //! // All the orders made to the bar, by client id.
    //! let orders = vec![1,2,1,2,3,4,1,2,2,3,4,1,1,1];
    //!
    //! // Our clients.
    //! let mut blood_alcohol = BTreeMap::new();
    //!
    //! for id in orders {
    //!     // If this is the first time we've seen this customer, initialize them
    //!     // with no blood alcohol. Otherwise, just retrieve them.
    //!     let person = blood_alcohol.entry(id).or_insert(Person { blood_alcohol: 0.0 });
    //!
    //!     // Reduce their blood alcohol level. It takes time to order and drink a beer!
    //!     person.blood_alcohol *= 0.9;
    //!
    //!     // Check if they're sober enough to have another beer.
    //!     if person.blood_alcohol > 0.3 {
    //!         // Too drunk... for now.
    //!         println!("Sorry {}, I have to cut you off", id);
    //!     } else {
    //!         // Have another!
    //!         person.blood_alcohol += 0.1;
    //!     }
    //! }
    //! ```
    //!
    //! # Insert and complex keys
    //!
    //! If we have a more complex key, calls to `insert()` will
    //! not update the value of the key. For example:
    //!
    //! ```
    //! use std::cmp::Ordering;
    //! use std::collections::BTreeMap;
    //! use std::hash::{Hash, Hasher};
    //!
    //! #[derive(Debug)]
    //! struct Foo {
    //!     a: u32,
    //!     b: &'static str,
    //! }
    //!
    //! // we will compare `Foo`s by their `a` value only.
    //! impl PartialEq for Foo {
    //!     fn eq(&self, other: &Self) -> bool { self.a == other.a }
    //! }
    //!
    //! impl Eq for Foo {}
    //!
    //! // we will hash `Foo`s by their `a` value only.
    //! impl Hash for Foo {
    //!     fn hash<H: Hasher>(&self, h: &mut H) { self.a.hash(h); }
    //! }
    //!
    //! impl PartialOrd for Foo {
    //!     fn partial_cmp(&self, other: &Self) -> Option<Ordering> { self.a.partial_cmp(&other.a) }
    //! }
    //!
    //! impl Ord for Foo {
    //!     fn cmp(&self, other: &Self) -> Ordering { self.a.cmp(&other.a) }
    //! }
    //!
    //! let mut map = BTreeMap::new();
    //! map.insert(Foo { a: 1, b: "baz" }, 99);
    //!
    //! // We already have a Foo with an a of 1, so this will be updating the value.
    //! map.insert(Foo { a: 1, b: "xyz" }, 100);
    //!
    //! // The value has been updated...
    //! assert_eq!(map.values().next().unwrap(), &100);
    //!
    //! // ...but the key hasn't changed. b is still "baz", not "xyz".
    //! assert_eq!(map.keys().next().unwrap().b, "baz");
    //! ```
    //!
    //! [`Vec`]: ../../std/vec/struct.Vec.html
    //! [`HashMap`]: ../../std/collections/struct.HashMap.html
    //! [`VecDeque`]: ../../std/collections/struct.VecDeque.html
    //! [`LinkedList`]: ../../std/collections/struct.LinkedList.html
    //! [`BTreeMap`]: ../../std/collections/struct.BTreeMap.html
    //! [`HashSet`]: ../../std/collections/struct.HashSet.html
    //! [`BTreeSet`]: ../../std/collections/struct.BTreeSet.html
    //! [`BinaryHeap`]: ../../std/collections/struct.BinaryHeap.html
    //! [`IntoIterator`]: ../../std/iter/trait.IntoIterator.html

    #![stable(feature = "rust1", since = "1.0.0")]

    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::Bound;
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::{BinaryHeap, BTreeMap, BTreeSet};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::{LinkedList, VecDeque};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::{binary_heap, btree_map, btree_set};
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::{linked_list, vec_deque};

    #[stable(feature = "rust1", since = "1.0.0")]
    pub use self::hash_map::HashMap;
    #[stable(feature = "rust1", since = "1.0.0")]
    pub use self::hash_set::HashSet;

    #[stable(feature = "rust1", since = "1.0.0")]
    pub use core_collections::range;

    mod hash;

    #[stable(feature = "rust1", since = "1.0.0")]
    pub mod hash_map {
        //! A hash map implementation which uses linear probing with Robin
        //! Hood bucket stealing.
        #[stable(feature = "rust1", since = "1.0.0")]
        pub use super::hash::map::*;
    }

    #[stable(feature = "rust1", since = "1.0.0")]
    pub mod hash_set {
        //! An implementation of a hash set using the underlying representation of a
        //! HashMap where the value is ().
        #[stable(feature = "rust1", since = "1.0.0")]
        pub use super::hash::set::*;
    }

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