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auto merge of #17802 : Gankro/rust/collection-docs-redux, r=aturon

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Adds a high-level discussion of "what collection should you use for what", as well as some general discussion of correct/efficient usage of the capacity, iterator, and entry APIs.

Still building docs to confirm this renders right and the examples are good, but the content can be reviewed now.
This commit is contained in:
bors 2014-10-07 09:42:06 +00:00
commit a3786db706
3 changed files with 322 additions and 3 deletions
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2
src/libcollections/btree/mod.rs
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@ -15,6 +15,8 @@ pub use self::map::MoveEntries;
pub use self::map::Keys;
pub use self::map::Values;
pub use self::map::Entry;
pub use self::map::Occupied;
pub use self::map::Vacant;
pub use self::map::OccupiedEntry;
pub use self::map::VacantEntry;

3
src/libcollections/lib.rs
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@ -9,6 +9,9 @@
// except according to those terms.
//! Collection types.
//!
//! See [../std/collections](std::collections) for a detailed discussion of collections in Rust.
#![crate_name = "collections"]
#![experimental]

320
src/libstd/collections/mod.rs
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@ -8,9 +8,323 @@
// option. This file may not be copied, modified, or distributed
// except according to those terms.
/*!
* Collection types.
*/
//! 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`, `RingBuf`, `DList`, `BitV`
//! * Maps: `HashMap`, `BTreeMap`, `TreeMap`, `TrieMap`, `SmallIntMap`, `LruCache`
//! * Sets: `HashSet`, `BTreeSet`, `TreeSet`, `TrieSet`, `BitVSet`, `EnumSet`
//! * Misc: `PriorityQueue`
//!
//! # 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 `RingBuf` 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 `DList` when:
//! * You want a `Vec` or `RingBuf` of unknown size, and can't tolerate inconsistent
//! performance during insertions.
//! * 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 a `TreeMap` when:
//! * You want a `BTreeMap`, but can't tolerate inconsistent performance.
//! * You want a `BTreeMap`, but have *very large* keys or values.
//! * You want a `BTreeMap`, but have keys that are expensive to compare.
//! * You want a `BTreeMap`, but you accept arbitrary untrusted inputs.
//!
//! ### Use a `TrieMap` when:
//! * You want a `HashMap`, but with many potentially large `uint` keys.
//! * You want a `BTreeMap`, but with potentially large `uint` keys.
//!
//! ### Use a `SmallIntMap` when:
//! * You want a `HashMap` but with known to be small `uint` keys.
//! * You want a `BTreeMap`, but with known to be small `uint` keys.
//!
//! ### 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 `BitV` when:
//! * You want to store an unbounded number of booleans in a small space.
//! * You want a bitvector.
//!
//! ### Use a `BitVSet` when:
//! * You want a `SmallIntSet`.
//!
//! ### Use an `EnumSet` when:
//! * You want a C-like enum, stored in a single `uint`.
//!
//! ### Use a `PriorityQueue` 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.
//!
//! ### Use an `LruCache` when:
//! * You want a cache that discards infrequently used items when it becomes full.
//! * You want a least-recently-used cache.
//!
//! # 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 `RingBuf` 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![1u, 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![1u, 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. 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![1u, 2, 3, 4];
//! let vec2 = vec![10u, 20, 30, 40];
//! vec1.extend(vec2.into_iter());
//! ```
//!
//! ```
//! use std::collections::RingBuf;
//!
//! let vec = vec![1u, 2, 3, 4];
//! let buf: RingBuf<uint> = vec.into_iter().collect();
//! ```
//!
//! Iterators also provide a series of *adapter* methods for performing common tasks 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![1u, 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 `set` the value of the entry. When this is done,
//! the vacant entry is consumed and converted into a mutable reference to the
//! 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`, `set`, or `take` 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 `set` 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::{BTreeMap, Occupied, Vacant};
//!
//! let mut count = BTreeMap::new();
//! let message = "she sells sea shells by the sea shore";
//!
//! for c in message.chars() {
//! match count.entry(c) {
//! Vacant(entry) => { entry.set(1u); },
//! Occupied(mut entry) => *entry.get_mut() += 1,
//! }
//! }
//!
//! assert_eq!(count.find(&'s'), Some(&8));
//!
//! println!("Number of occurences of each character");
//! for (char, count) in count.iter() {
//! 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::{BTreeMap, Occupied, Vacant};
//!
//! // A client of the bar. They have an id and a blood alcohol level.
//! struct Person { id: u32, 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.into_iter() {
//! // If this is the first time we've seen this customer, initialize them
//! // with no blood alcohol. Otherwise, just retrieve them.
//! let person = match blood_alcohol.entry(id) {
//! Vacant(entry) => entry.set(Person{id: id, blood_alcohol: 0.0}),
//! Occupied(entry) => entry.into_mut(),
//! };
//!
//! // 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", person.id);
//! } else {
//! // Have another!
//! person.blood_alcohol += 0.1;
//! }
//! }
//! ```
#![experimental]