返回首页返回书籍《The Rust Programming Language》
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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 73 / 111 节

第 73 节 · SECTION 73

Reference Cycles Can Leak Memory

Reference Cycles Can Leak Memory

Rust’s memory safety guarantees make it difficult, but not impossible, to accidentally create memory that is never cleaned up (known as a memory leak). Preventing memory leaks entirely is not one of Rust’s guarantees, meaning memory leaks are memory safe in Rust. We can see that Rust allows memory leaks by using Rc<T> and RefCell<T>: It’s possible to create references where items refer to each other in a cycle. This creates memory leaks because the reference count of each item in the cycle will never reach 0, and the values will never be dropped.

Creating a Reference Cycle

Let’s look at how a reference cycle might happen and how to prevent it, starting with the definition of the List enum and a tail method in Listing 15-25.

Listing 15-25: A cons list definition that holds a RefCell<T> so that we can modify what a Cons variant is referring to Filename: src/main.rs

use crate::List::{Cons, Nil};
use std::cell::RefCell;
use std::rc::Rc;

#[derive(Debug)]
enum List {
    Cons(i32, RefCell<Rc<List>>),
    Nil,
}

impl List {
    fn tail(&self) -> Option<&RefCell<Rc<List>>> {
        match self {
            Cons(_, item) => Some(item),
            Nil => None,
        }
    }
}

We’re using another variation of the List definition from Listing 15-5. The second element in the Cons variant is now RefCell<Rc<List>>, meaning that instead of having the ability to modify the i32 value as we did in Listing 15-24, we want to modify the List value a Cons variant is pointing to. We’re also adding a tail method to make it convenient for us to access the second item if we have a Cons variant.

In Listing 15-26, we’re adding a main function that uses the definitions in Listing 15-25. This code creates a list in a and a list in b that points to the list in a. Then, it modifies the list in a to point to b, creating a reference cycle. There are println! statements along the way to show what the reference counts are at various points in this process.

Listing 15-26: Creating a reference cycle of two List values pointing to each other Filename: src/main.rs

fn main() {
    let a = Rc::new(Cons(5, RefCell::new(Rc::new(Nil))));

    println!("a initial rc count = {}", Rc::strong_count(&a));
    println!("a next item = {:?}", a.tail());

    let b = Rc::new(Cons(10, RefCell::new(Rc::clone(&a))));

    println!("a rc count after b creation = {}", Rc::strong_count(&a));
    println!("b initial rc count = {}", Rc::strong_count(&b));
    println!("b next item = {:?}", b.tail());

    if let Some(link) = a.tail() {
        *link.borrow_mut() = Rc::clone(&b);
    }

    println!("b rc count after changing a = {}", Rc::strong_count(&b));
    println!("a rc count after changing a = {}", Rc::strong_count(&a));

    // Uncomment the next line to see that we have a cycle;
    // it will overflow the stack.
    // println!("a next item = {:?}", a.tail());
}

We create an Rc<List> instance holding a List value in the variable a with an initial list of 5, Nil. We then create an Rc<List> instance holding another List value in the variable b that contains the value 10 and points to the list in a.

We modify a so that it points to b instead of Nil, creating a cycle. We do that by using the tail method to get a reference to the RefCell<Rc<List>> in a, which we put in the variable link. Then, we use the borrow_mut method on the RefCell<Rc<List>> to change the value inside from an Rc<List> that holds a Nil value to the Rc<List> in b.

When we run this code, keeping the last println! commented out for the moment, we’ll get this output:

$ cargo run
   Compiling cons-list v0.1.0 (file:///projects/cons-list)
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.53s
     Running `target/debug/cons-list`
a initial rc count = 1
a next item = Some(RefCell { value: Nil })
a rc count after b creation = 2
b initial rc count = 1
b next item = Some(RefCell { value: Cons(5, RefCell { value: Nil }) })
b rc count after changing a = 2
a rc count after changing a = 2

The reference count of the Rc<List> instances in both a and b is 2 after we change the list in a to point to b. At the end of main, Rust drops the variable b, which decreases the reference count of the b Rc<List> instance from 2 to 1. The memory that Rc<List> has on the heap won’t be dropped at this point because its reference count is 1, not 0. Then, Rust drops a, which decreases the reference count of the a Rc<List> instance from 2 to 1 as well. This instance’s memory can’t be dropped either, because the other Rc<List> instance still refers to it. The memory allocated to the list will remain uncollected forever. To visualize this reference cycle, we’ve created the diagram in Figure 15-4.

A rectangle labeled 'a' that points to a rectangle containing the integer 5. A rectangle labeled 'b' that points to a rectangle containing the integer 10. The rectangle containing 5 points to the rectangle containing 10, and the rectangle containing 10 points back to the rectangle containing 5, creating a cycle.

Figure 15-4: A reference cycle of lists a and b pointing to each other

If you uncomment the last println! and run the program, Rust will try to print this cycle with a pointing to b pointing to a and so forth until it overflows the stack.

Compared to a real-world program, the consequences of creating a reference cycle in this example aren’t very dire: Right after we create the reference cycle, the program ends. However, if a more complex program allocated lots of memory in a cycle and held onto it for a long time, the program would use more memory than it needed and might overwhelm the system, causing it to run out of available memory.

Creating reference cycles is not easily done, but it’s not impossible either. If you have RefCell<T> values that contain Rc<T> values or similar nested combinations of types with interior mutability and reference counting, you must ensure that you don’t create cycles; you can’t rely on Rust to catch them. Creating a reference cycle would be a logic bug in your program that you should use automated tests, code reviews, and other software development practices to minimize.

Another solution for avoiding reference cycles is reorganizing your data structures so that some references express ownership and some references don’t. As a result, you can have cycles made up of some ownership relationships and some non-ownership relationships, and only the ownership relationships affect whether or not a value can be dropped. In Listing 15-25, we always want Cons variants to own their list, so reorganizing the data structure isn’t possible. Let’s look at an example using graphs made up of parent nodes and child nodes to see when non-ownership relationships are an appropriate way to prevent reference cycles.

Preventing Reference Cycles Using Weak<T>

So far, we’ve demonstrated that calling Rc::clone increases the strong_count of an Rc<T> instance, and an Rc<T> instance is only cleaned up if its strong_count is 0. You can also create a weak reference to the value within an Rc<T> instance by calling Rc::downgrade and passing a reference to the Rc<T>. Strong references are how you can share ownership of an Rc<T> instance. Weak references don’t express an ownership relationship, and their count doesn’t affect when an Rc<T> instance is cleaned up. They won’t cause a reference cycle, because any cycle involving some weak references will be broken once the strong reference count of values involved is 0.

When you call Rc::downgrade, you get a smart pointer of type Weak<T>. Instead of increasing the strong_count in the Rc<T> instance by 1, calling Rc::downgrade increases the weak_count by 1. The Rc<T> type uses weak_count to keep track of how many Weak<T> references exist, similar to strong_count. The difference is the weak_count doesn’t need to be 0 for the Rc<T> instance to be cleaned up.

Because the value that Weak<T> references might have been dropped, to do anything with the value that a Weak<T> is pointing to you must make sure the value still exists. Do this by calling the upgrade method on a Weak<T> instance, which will return an Option<Rc<T>>. You’ll get a result of Some if the Rc<T> value has not been dropped yet and a result of None if the Rc<T> value has been dropped. Because upgrade returns an Option<Rc<T>>, Rust will ensure that the Some case and the None case are handled, and there won’t be an invalid pointer.

As an example, rather than using a list whose items know only about the next item, we’ll create a tree whose items know about their child items and their parent items.

Creating a Tree Data Structure

To start, we’ll build a tree with nodes that know about their child nodes. We’ll create a struct named Node that holds its own i32 value as well as references to its child Node values:

Filename: src/main.rs

use std::cell::RefCell;
use std::rc::Rc;

#[derive(Debug)]
struct Node {
    value: i32,
    children: RefCell<Vec<Rc<Node>>>,
}

We want a Node to own its children, and we want to share that ownership with variables so that we can access each Node in the tree directly. To do this, we define the Vec<T> items to be values of type Rc<Node>. We also want to modify which nodes are children of another node, so we have a RefCell<T> in children around the Vec<Rc<Node>>.

Next, we’ll use our struct definition and create one Node instance named leaf with the value 3 and no children, and another instance named branch with the value 5 and leaf as one of its children, as shown in Listing 15-27.

Listing 15-27: Creating a leaf node with no children and a branch node with leaf as one of its children Filename: src/main.rs

fn main() {
    let leaf = Rc::new(Node {
        value: 3,
        children: RefCell::new(vec![]),
    });

    let branch = Rc::new(Node {
        value: 5,
        children: RefCell::new(vec![Rc::clone(&leaf)]),
    });
}

We clone the Rc<Node> in leaf and store that in branch, meaning the Node in leaf now has two owners: leaf and branch. We can get from branch to leaf through branch.children, but there’s no way to get from leaf to branch. The reason is that leaf has no reference to branch and doesn’t know they’re related. We want leaf to know that branch is its parent. We’ll do that next.

Adding a Reference from a Child to Its Parent

To make the child node aware of its parent, we need to add a parent field to our Node struct definition. The trouble is in deciding what the type of parent should be. We know it can’t contain an Rc<T>, because that would create a reference cycle with leaf.parent pointing to branch and branch.children pointing to leaf, which would cause their strong_count values to never be 0.

Thinking about the relationships another way, a parent node should own its children: If a parent node is dropped, its child nodes should be dropped as well. However, a child should not own its parent: If we drop a child node, the parent should still exist. This is a case for weak references!

So, instead of Rc<T>, we’ll make the type of parent use Weak<T>, specifically a RefCell<Weak<Node>>. Now our Node struct definition looks like this:

Filename: src/main.rs

use std::cell::RefCell;
use std::rc::{Rc, Weak};

#[derive(Debug)]
struct Node {
    value: i32,
    parent: RefCell<Weak<Node>>,
    children: RefCell<Vec<Rc<Node>>>,
}

A node will be able to refer to its parent node but doesn’t own its parent. In Listing 15-28, we update main to use this new definition so that the leaf node will have a way to refer to its parent, branch.

Listing 15-28: A leaf node with a weak reference to its parent node, branch Filename: src/main.rs

fn main() {
    let leaf = Rc::new(Node {
        value: 3,
        parent: RefCell::new(Weak::new()),
        children: RefCell::new(vec![]),
    });

    println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());

    let branch = Rc::new(Node {
        value: 5,
        parent: RefCell::new(Weak::new()),
        children: RefCell::new(vec![Rc::clone(&leaf)]),
    });

    *leaf.parent.borrow_mut() = Rc::downgrade(&branch);

    println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());
}

Creating the leaf node looks similar to Listing 15-27 with the exception of the parent field: leaf starts out without a parent, so we create a new, empty Weak<Node> reference instance.

At this point, when we try to get a reference to the parent of leaf by using the upgrade method, we get a None value. We see this in the output from the first println! statement:

leaf parent = None

When we create the branch node, it will also have a new Weak<Node> reference in the parent field because branch doesn’t have a parent node. We still have leaf as one of the children of branch. Once we have the Node instance in branch, we can modify leaf to give it a Weak<Node> reference to its parent. We use the borrow_mut method on the RefCell<Weak<Node>> in the parent field of leaf, and then we use the Rc::downgrade function to create a Weak<Node> reference to branch from the Rc<Node> in branch.

When we print the parent of leaf again, this time we’ll get a Some variant holding branch: Now leaf can access its parent! When we print leaf, we also avoid the cycle that eventually ended in a stack overflow like we had in Listing 15-26; the Weak<Node> references are printed as (Weak):

leaf parent = Some(Node { value: 5, parent: RefCell { value: (Weak) },
children: RefCell { value: [Node { value: 3, parent: RefCell { value: (Weak) },
children: RefCell { value: [] } }] } })

The lack of infinite output indicates that this code didn’t create a reference cycle. We can also tell this by looking at the values we get from calling Rc::strong_count and Rc::weak_count.

Visualizing Changes to strong_count and weak_count

Let’s look at how the strong_count and weak_count values of the Rc<Node> instances change by creating a new inner scope and moving the creation of branch into that scope. By doing so, we can see what happens when branch is created and then dropped when it goes out of scope. The modifications are shown in Listing 15-29.

Listing 15-29: Creating branch in an inner scope and examining strong and weak reference counts Filename: src/main.rs

fn main() {
    let leaf = Rc::new(Node {
        value: 3,
        parent: RefCell::new(Weak::new()),
        children: RefCell::new(vec![]),
    });

    println!(
        "leaf strong = {}, weak = {}",
        Rc::strong_count(&leaf),
        Rc::weak_count(&leaf),
    );

    {
        let branch = Rc::new(Node {
            value: 5,
            parent: RefCell::new(Weak::new()),
            children: RefCell::new(vec![Rc::clone(&leaf)]),
        });

        *leaf.parent.borrow_mut() = Rc::downgrade(&branch);

        println!(
            "branch strong = {}, weak = {}",
            Rc::strong_count(&branch),
            Rc::weak_count(&branch),
        );

        println!(
            "leaf strong = {}, weak = {}",
            Rc::strong_count(&leaf),
            Rc::weak_count(&leaf),
        );
    }

    println!("leaf parent = {:?}", leaf.parent.borrow().upgrade());
    println!(
        "leaf strong = {}, weak = {}",
        Rc::strong_count(&leaf),
        Rc::weak_count(&leaf),
    );
}

After leaf is created, its Rc<Node> has a strong count of 1 and a weak count of 0. In the inner scope, we create branch and associate it with leaf, at which point when we print the counts, the Rc<Node> in branch will have a strong count of 1 and a weak count of 1 (for leaf.parent pointing to branch with a Weak<Node>). When we print the counts in leaf, we’ll see it will have a strong count of 2 because branch now has a clone of the Rc<Node> of leaf stored in branch.children but will still have a weak count of 0.

When the inner scope ends, branch goes out of scope and the strong count of the Rc<Node> decreases to 0, so its Node is dropped. The weak count of 1 from leaf.parent has no bearing on whether or not Node is dropped, so we don’t get any memory leaks!

If we try to access the parent of leaf after the end of the scope, we’ll get None again. At the end of the program, the Rc<Node> in leaf has a strong count of 1 and a weak count of 0 because the variable leaf is now the only reference to the Rc<Node> again.

All of the logic that manages the counts and value dropping is built into Rc<T> and Weak<T> and their implementations of the Drop trait. By specifying that the relationship from a child to its parent should be a Weak<T> reference in the definition of Node, you’re able to have parent nodes point to child nodes and vice versa without creating a reference cycle and memory leaks.

Summary

This chapter covered how to use smart pointers to make different guarantees and trade-offs from those Rust makes by default with regular references. The Box<T> type has a known size and points to data allocated on the heap. The Rc<T> type keeps track of the number of references to data on the heap so that the data can have multiple owners. The RefCell<T> type with its interior mutability gives us a type that we can use when we need an immutable type but need to change an inner value of that type; it also enforces the borrowing rules at runtime instead of at compile time.

Also discussed were the Deref and Drop traits, which enable a lot of the functionality of smart pointers. We explored reference cycles that can cause memory leaks and how to prevent them using Weak<T>.

If this chapter has piqued your interest and you want to implement your own smart pointers, check out “The Rustonomicon” for more useful information.

Next, we’ll talk about concurrency in Rust. You’ll even learn about a few new smart pointers.