返回首页返回书籍《The Rust Programming Language》
目录

目录 · CONTENTS

  1. 01The Rust Programming Language
  2. 02Foreword
  3. 03Introduction
  4. 04Getting Started
  5. 05Installation
  6. 06Hello, World!
  7. 07Hello, Cargo!
  8. 08Programming a Guessing Game
  9. 09Common Programming Concepts
  10. 10Variables and Mutability
  11. 11Data Types
  12. 12Functions
  13. 13Comments
  14. 14Control Flow
  15. 15Understanding Ownership
  16. 16What is Ownership?
  17. 17References and Borrowing
  18. 18The Slice Type
  19. 19Using Structs to Structure Related Data
  20. 20Defining and Instantiating Structs
  21. 21An Example Program Using Structs
  22. 22Methods
  23. 23Enums and Pattern Matching
  24. 24Defining an Enum
  25. 25The `match` Control Flow Construct
  26. 26Concise Control Flow with `if let` and `let...else`
  27. 27Packages, Crates, and Modules
  28. 28Packages and Crates
  29. 29Control Scope and Privacy with Modules
  30. 30Paths for Referring to an Item in the Module Tree
  31. 31Bringing Paths Into Scope with the `use` Keyword
  32. 32Separating Modules into Different Files
  33. 33Common Collections
  34. 34Storing Lists of Values with Vectors
  35. 35Storing UTF-8 Encoded Text with Strings
  36. 36Storing Keys with Associated Values in Hash Maps
  37. 37Error Handling
  38. 38Unrecoverable Errors with `panic!`
  39. 39Recoverable Errors with `Result`
  40. 40To `panic!` or Not to `panic!`
  41. 41Generic Types, Traits, and Lifetimes
  42. 42Generic Data Types
  43. 43Defining Shared Behavior with Traits
  44. 44Validating References with Lifetimes
  45. 45Writing Automated Tests
  46. 46How to Write Tests
  47. 47Controlling How Tests Are Run
  48. 48Test Organization
  49. 49An I/O Project: Building a Command Line Program
  50. 50Accepting Command Line Arguments
  51. 51Reading a File
  52. 52Refactoring to Improve Modularity and Error Handling
  53. 53Adding Functionality with Test Driven Development
  54. 54Working with Environment Variables
  55. 55Redirecting Errors to Standard Error
  56. 56Functional Language Features: Iterators and Closures
  57. 57Closures
  58. 58Processing a Series of Items with Iterators
  59. 59Improving Our I/O Project
  60. 60Performance in Loops vs. Iterators
  61. 61More About Cargo and Crates.io
  62. 62Customizing Builds with Release Profiles
  63. 63Publishing a Crate to Crates.io
  64. 64Cargo Workspaces
  65. 65Installing Binaries with `cargo install`
  66. 66Extending Cargo with Custom Commands
  67. 67Smart Pointers
  68. 68Using `Box<T>` to Point to Data on the Heap
  69. 69Treating Smart Pointers Like Regular References
  70. 70Running Code on Cleanup with the `Drop` Trait
  71. 71`Rc<T>`, the Reference Counted Smart Pointer
  72. 72`RefCell<T>` and the Interior Mutability Pattern
  73. 73Reference Cycles Can Leak Memory
  74. 74Fearless Concurrency
  75. 75Using Threads to Run Code Simultaneously
  76. 76Transfer Data Between Threads with Message Passing
  77. 77Shared-State Concurrency
  78. 78Extensible Concurrency with `Send` and `Sync`
  79. 79Fundamentals of Asynchronous Programming: Async, Await, Futures, and Streams
  80. 80extern crate trpl; // required for mdbook test
  81. 81Applying Concurrency with Async
  82. 82Working With Any Number of Futures
  83. 83Streams: Futures in Sequence
  84. 84A Closer Look at the Traits for Async
  85. 85Futures, Tasks, and Threads
  86. 86Object-Oriented Programming Features
  87. 87Characteristics of Object-Oriented Languages
  88. 88Using Trait Objects to Abstract over Shared Behavior
  89. 89Implementing an Object-Oriented Design Pattern
  90. 90Patterns and Matching
  91. 91All the Places Patterns Can Be Used
  92. 92Refutability: Whether a Pattern Might Fail to Match
  93. 93Pattern Syntax
  94. 94Advanced Features
  95. 95Unsafe Rust
  96. 96Advanced Traits
  97. 97Advanced Types
  98. 98Advanced Functions and Closures
  99. 99Macros
  100. 100Final Project: Building a Multithreaded Web Server
  101. 101Building a Single-Threaded Web Server
  102. 102From Single-Threaded to Multithreaded Server
  103. 103Graceful Shutdown and Cleanup
  104. 104Appendix
  105. 105A - Keywords
  106. 106B - Operators and Symbols
  107. 107C - Derivable Traits
  108. 108D - Useful Development Tools
  109. 109E - Editions
  110. 110F - Translations of the Book
  111. 111G - How Rust is Made and “Nightly Rust”
第 58 / 111 节

第 58 节 · SECTION 58

Processing a Series of Items with Iterators

Processing a Series of Items with Iterators

The iterator pattern allows you to perform some task on a sequence of items in turn. An iterator is responsible for the logic of iterating over each item and determining when the sequence has finished. When you use iterators, you don’t have to reimplement that logic yourself.

In Rust, iterators are lazy, meaning they have no effect until you call methods that consume the iterator to use it up. For example, the code in Listing 13-10 creates an iterator over the items in the vector v1 by calling the iter method defined on Vec<T>. This code by itself doesn’t do anything useful.

Listing 13-10: Creating an iterator Filename: src/main.rs

    let v1 = vec![1, 2, 3];

    let v1_iter = v1.iter();

The iterator is stored in the v1_iter variable. Once we’ve created an iterator, we can use it in a variety of ways. In Listing 3-5, we iterated over an array using a for loop to execute some code on each of its items. Under the hood, this implicitly created and then consumed an iterator, but we glossed over how exactly that works until now.

In the example in Listing 13-11, we separate the creation of the iterator from the use of the iterator in the for loop. When the for loop is called using the iterator in v1_iter, each element in the iterator is used in one iteration of the loop, which prints out each value.

Listing 13-11: Using an iterator in a for loop Filename: src/main.rs

    let v1 = vec![1, 2, 3];

    let v1_iter = v1.iter();

    for val in v1_iter {
        println!("Got: {val}");
    }

In languages that don’t have iterators provided by their standard libraries, you would likely write this same functionality by starting a variable at index 0, using that variable to index into the vector to get a value, and incrementing the variable value in a loop until it reached the total number of items in the vector.

Iterators handle all of that logic for you, cutting down on repetitive code you could potentially mess up. Iterators give you more flexibility to use the same logic with many different kinds of sequences, not just data structures you can index into, like vectors. Let’s examine how iterators do that.

The Iterator Trait and the next Method

All iterators implement a trait named Iterator that is defined in the standard library. The definition of the trait looks like this:

pub trait Iterator {
    type Item;

    fn next(&mut self) -> Option<Self::Item>;

    // methods with default implementations elided
}

Notice that this definition uses some new syntax: type Item and Self::Item, which are defining an associated type with this trait. We’ll talk about associated types in depth in Chapter 20. For now, all you need to know is that this code says implementing the Iterator trait requires that you also define an Item type, and this Item type is used in the return type of the next method. In other words, the Item type will be the type returned from the iterator.

The Iterator trait only requires implementors to define one method: the next method, which returns one item of the iterator at a time, wrapped in Some, and, when iteration is over, returns None.

We can call the next method on iterators directly; Listing 13-12 demonstrates what values are returned from repeated calls to next on the iterator created from the vector.

Listing 13-12: Calling the next method on an iterator Filename: src/lib.rs

    #[test]
    fn iterator_demonstration() {
        let v1 = vec![1, 2, 3];

        let mut v1_iter = v1.iter();

        assert_eq!(v1_iter.next(), Some(&1));
        assert_eq!(v1_iter.next(), Some(&2));
        assert_eq!(v1_iter.next(), Some(&3));
        assert_eq!(v1_iter.next(), None);
    }

Note that we needed to make v1_iter mutable: Calling the next method on an iterator changes internal state that the iterator uses to keep track of where it is in the sequence. In other words, this code consumes, or uses up, the iterator. Each call to next eats up an item from the iterator. We didn’t need to make v1_iter mutable when we used a for loop, because the loop took ownership of v1_iter and made it mutable behind the scenes.

Also note that the values we get from the calls to next are immutable references to the values in the vector. The iter method produces an iterator over immutable references. If we want to create an iterator that takes ownership of v1 and returns owned values, we can call into_iter instead of iter. Similarly, if we want to iterate over mutable references, we can call iter_mut instead of iter.

Methods That Consume the Iterator

The Iterator trait has a number of different methods with default implementations provided by the standard library; you can find out about these methods by looking in the standard library API documentation for the Iterator trait. Some of these methods call the next method in their definition, which is why you’re required to implement the next method when implementing the Iterator trait.

Methods that call next are called consuming adapters because calling them uses up the iterator. One example is the sum method, which takes ownership of the iterator and iterates through the items by repeatedly calling next, thus consuming the iterator. As it iterates through, it adds each item to a running total and returns the total when iteration is complete. Listing 13-13 has a test illustrating a use of the sum method.

Listing 13-13: Calling the sum method to get the total of all items in the iterator Filename: src/lib.rs

    #[test]
    fn iterator_sum() {
        let v1 = vec![1, 2, 3];

        let v1_iter = v1.iter();

        let total: i32 = v1_iter.sum();

        assert_eq!(total, 6);
    }

We aren’t allowed to use v1_iter after the call to sum, because sum takes ownership of the iterator we call it on.

Methods That Produce Other Iterators

Iterator adapters are methods defined on the Iterator trait that don’t consume the iterator. Instead, they produce different iterators by changing some aspect of the original iterator.

Listing 13-14 shows an example of calling the iterator adapter method map, which takes a closure to call on each item as the items are iterated through. The map method returns a new iterator that produces the modified items. The closure here creates a new iterator in which each item from the vector will be incremented by 1.

Listing 13-14: Calling the iterator adapter map to create a new iterator Filename: src/main.rs

    let v1: Vec<i32> = vec![1, 2, 3];

    v1.iter().map(|x| x + 1);

However, this code produces a warning:

$ cargo run
   Compiling iterators v0.1.0 (file:///projects/iterators)
warning: unused `Map` that must be used
 --> src/main.rs:4:5
  |
4 |     v1.iter().map(|x| x + 1);
  |     ^^^^^^^^^^^^^^^^^^^^^^^^
  |
  = note: iterators are lazy and do nothing unless consumed
  = note: `#[warn(unused_must_use)]` (part of `#[warn(unused)]`) on by default
help: use `let _ = ...` to ignore the resulting value
  |
4 |     let _ = v1.iter().map(|x| x + 1);
  |     +++++++

warning: `iterators` (bin "iterators") generated 1 warning
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.47s
     Running `target/debug/iterators`

The code in Listing 13-14 doesn’t do anything; the closure we’ve specified never gets called. The warning reminds us why: Iterator adapters are lazy, and we need to consume the iterator here.

To fix this warning and consume the iterator, we’ll use the collect method, which we used with env::args in Listing 12-1. This method consumes the iterator and collects the resultant values into a collection data type.

In Listing 13-15, we collect the results of iterating over the iterator that’s returned from the call to map into a vector. This vector will end up containing each item from the original vector, incremented by 1.

Listing 13-15: Calling the map method to create a new iterator, and then calling the collect method to consume the new iterator and create a vector Filename: src/main.rs

    let v1: Vec<i32> = vec![1, 2, 3];

    let v2: Vec<_> = v1.iter().map(|x| x + 1).collect();

    assert_eq!(v2, vec![2, 3, 4]);

Because map takes a closure, we can specify any operation we want to perform on each item. This is a great example of how closures let you customize some behavior while reusing the iteration behavior that the Iterator trait provides.

You can chain multiple calls to iterator adapters to perform complex actions in a readable way. But because all iterators are lazy, you have to call one of the consuming adapter methods to get results from calls to iterator adapters.

Closures That Capture Their Environment

Many iterator adapters take closures as arguments, and commonly the closures we’ll specify as arguments to iterator adapters will be closures that capture their environment.

For this example, we’ll use the filter method that takes a closure. The closure gets an item from the iterator and returns a bool. If the closure returns true, the value will be included in the iterator produced by filter. If the closure returns false, the value won’t be included.

In Listing 13-16, we use filter with a closure that captures the shoe_size variable from its environment to iterate over a collection of Shoe struct instances. It will return only shoes that are the specified size.

Listing 13-16: Using the filter method with a closure that captures shoe_size Filename: src/lib.rs

#[derive(PartialEq, Debug)]
struct Shoe {
    size: u32,
    style: String,
}

fn shoes_in_size(shoes: Vec<Shoe>, shoe_size: u32) -> Vec<Shoe> {
    shoes.into_iter().filter(|s| s.size == shoe_size).collect()
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn filters_by_size() {
        let shoes = vec![
            Shoe {
                size: 10,
                style: String::from("sneaker"),
            },
            Shoe {
                size: 13,
                style: String::from("sandal"),
            },
            Shoe {
                size: 10,
                style: String::from("boot"),
            },
        ];

        let in_my_size = shoes_in_size(shoes, 10);

        assert_eq!(
            in_my_size,
            vec![
                Shoe {
                    size: 10,
                    style: String::from("sneaker")
                },
                Shoe {
                    size: 10,
                    style: String::from("boot")
                },
            ]
        );
    }
}

The shoes_in_size function takes ownership of a vector of shoes and a shoe size as parameters. It returns a vector containing only shoes of the specified size.

In the body of shoes_in_size, we call into_iter to create an iterator that takes ownership of the vector. Then, we call filter to adapt that iterator into a new iterator that only contains elements for which the closure returns true.

The closure captures the shoe_size parameter from the environment and compares the value with each shoe’s size, keeping only shoes of the size specified. Finally, calling collect gathers the values returned by the adapted iterator into a vector that’s returned by the function.

The test shows that when we call shoes_in_size, we get back only shoes that have the same size as the value we specified.