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Merge pull request #16 from FenrirWolf/collections

ctr-std: add collections module
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Ronald Kinard 8 years ago committed by GitHub
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d5af9faac9
  1. 458
      ctr-std/src/collections/mod.rs
  2. 3
      ctr-std/src/lib.rs

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ctr-std/src/collections/mod.rs

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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};
#[cfg(feature = "not_yet_implemented")]
pub use self::hash_map::HashMap;
#[cfg(feature = "not_yet_implemented")]
pub use self::hash_set::HashSet;
#[stable(feature = "rust1", since = "1.0.0")]
pub use core_collections::range;
#[cfg(feature = "not_yet_implemented")]
mod hash;
#[cfg(feature = "not_yet_implemented")]
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::*;
}
#[cfg(feature = "not_yet_implemented")]
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::*;
}

3
ctr-std/src/lib.rs

@ -2,6 +2,8 @@ @@ -2,6 +2,8 @@
#![feature(allow_internal_unstable)]
#![feature(box_syntax)]
#![feature(collections)]
#![feature(collections_bound)]
#![feature(collections_range)]
#![feature(const_fn)]
#![feature(compiler_builtins_lib)]
#![feature(core_intrinsics)]
@ -135,6 +137,7 @@ pub mod f32; @@ -135,6 +137,7 @@ pub mod f32;
pub mod f64;
pub mod ascii;
pub mod collections;
pub mod error;
pub mod ffi;
pub mod io;

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