Interestingly, the Rust language has very few concurrency features. Almost every concurrency feature we’ve talked about so far in this chapter has been part of the standard library, not the language. Your options for handling concurrency are not limited to the language or the standard library; you can write your own concurrency features or use those written by others.
However, two concurrency concepts are embedded in the language: the
std::marker traits Sync and Send.
Allowing Transference of Ownership Between Threads with Send
The Send marker trait indicates that ownership of values of the type implementing
Send can be transferred between threads. Almost every Rust type is Send,
but there are some exceptions, including Rc<T>: this cannot be Send because
if you cloned an Rc<T> value and tried to transfer ownership of the clone to
another thread, both threads might update the reference count at the same time.
For this reason, Rc<T> is implemented for use in single-threaded situations
where you don’t want to pay the thread-safe performance penalty.
Therefore, Rust’s type system and trait bounds ensure that you can never
accidentally send an Rc<T> value across threads unsafely. When we tried to do
this in Listing 16-14, we got the error the trait Send is not implemented for Rc<Mutex<i32>>. When we switched to Arc<T>, which is Send, the code
compiled.
Any type composed entirely of Send types is automatically marked as Send as
well. Almost all primitive types are Send, aside from raw pointers, which
we’ll discuss in Chapter 19.
Allowing Access from Multiple Threads with Sync
The Sync marker trait indicates that it is safe for the type implementing
Sync to be referenced from multiple threads. In other words, any type T is
Sync if &T (an immutable reference to T) is Send, meaning the reference
can be sent safely to another thread. Similar to Send, primitive types are
Sync, and types composed entirely of types that are Sync are also Sync.
The smart pointer Rc<T> is also not Sync for the same reasons that it’s not
Send. The RefCell<T> type (which we talked about in Chapter 15) and the
family of related Cell<T> types are not Sync. The implementation of borrow
checking that RefCell<T> does at runtime is not thread-safe. The smart
pointer Mutex<T> is Sync and can be used to share access with multiple
threads as you saw in the “Sharing a Mutex<T> Between Multiple
Threads” section.
Implementing Send and Sync Manually Is Unsafe
Because types that are made up of Send and Sync traits are automatically
also Send and Sync, we don’t have to implement those traits manually. As
marker traits, they don’t even have any methods to implement. They’re just
useful for enforcing invariants related to concurrency.
Manually implementing these traits involves implementing unsafe Rust code.
We’ll talk about using unsafe Rust code in Chapter 19; for now, the important
information is that building new concurrent types not made up of Send and
Sync parts requires careful thought to uphold the safety guarantees. “The
Rustonomicon” has more information about these guarantees and how to
uphold them.
Summary
This isn’t the last you’ll see of concurrency in this book: the project in Chapter 20 will use the concepts in this chapter in a more realistic situation than the smaller examples discussed here.
As mentioned earlier, because very little of how Rust handles concurrency is part of the language, many concurrency solutions are implemented as crates. These evolve more quickly than the standard library, so be sure to search online for the current, state-of-the-art crates to use in multithreaded situations.
The Rust standard library provides channels for message passing and smart
pointer types, such as Mutex<T> and Arc<T>, that are safe to use in
concurrent contexts. The type system and the borrow checker ensure that the
code using these solutions won’t end up with data races or invalid references.
Once you get your code to compile, you can rest assured that it will happily
run on multiple threads without the kinds of hard-to-track-down bugs common in
other languages. Concurrent programming is no longer a concept to be afraid of:
go forth and make your programs concurrent, fearlessly!
Next, we’ll talk about idiomatic ways to model problems and structure solutions as your Rust programs get bigger. In addition, we’ll discuss how Rust’s idioms relate to those you might be familiar with from object-oriented programming.