The try block in Rust

I wrote previously about libs for error management in Rust. This week, I want to write about the try block, an experimental feature.

The limit of the ? operator

Please check the above article for a complete refresher on error management in general and the ? operator in particular. In short, ? allows to hook into a function call that returns a Result:

• If the Result contains a value, it continues normally
• If it contains an error, it short-circuits and returns the Result to the calling function.

fn add(str1: &str, str2: &str) -> Result<i8, ParseIntError> {
  Ok(str1.parse::<i8>()? + str2.parse::<i8>()?)
}

fn main() {
    print!("{:?}", add("1", "2"));
    print!("{:?}", add("1", "a"));
}

The output is the following:

Ok(3)
Err(ParseIntError { kind: InvalidDigit })

Note that the defining function's signature must return a Result or an Option. The following block doesn't compile:

fn add(str1: &str, str2: &str) -> i8 {
  str1.parse::<i8>()? + str2.parse::<i8>()?
}

the `?` operator can only be used in a function that returns `Result` or `Option`

The verbose alternative

We must manually unwrap to return a non-wrapper type, e.g., i8 instead of Option.

fn add(str1: &str, str2: &str) -> i8 {
  let int1 = str1.parse::<i8>();                  //1
  let int2 = str2.parse::<i8>();                  //1
  if int1.is_err() || int2.is_err() { -1 }        //2-3
  else { int1.unwrap() + int2.unwrap() }          //4
}

1. Define Result variables
2. Manually checks if any of the variables contains an error, i.e., the parsing failed
3. Return a default value since we cannot get a Result. In this case, it's not a great idea, but it's for explanation's sake
4. Unwrap with confidence

The try block to the rescue

The sample above works but is quite lengthy. The try block is an experimental approach to make it more elegant. It allows "compacting" all the checks for errors in a single block:

#![feature(try_blocks)]                           //1

fn add(str1: &str, str2: &str) -> i8 {
  let result = try {
    let int1 = str1.parse::<i8>();
    let int2 = str2.parse::<i8>();
    int1.unwrap()? + int2.unwrap()?               //2
  };
  if result.is_err() { -1 }                       //3
  else { result.unwrap() }                        //4
}

1. Enable the experimental feature
2. Use the ? operator though the defining function doesn't return Result
3. Check for errors only once
4. Unwrap confidently

Alas, the code doesn't compile:

the `?` operator can only be applied to values that implement `Try`

i8 doesn't implement Try. Neither i8 nor Try belong to our crate; a custom implementation would require the use of the wrapper-type pattern. Fortunately, a couple of types already implement Try: Result, Option, Poll, and ControlFlow.

fn add(str1: &str, str2: &str) -> i8 {
  let result: Result<i8, ParseIntError> = try {   //1
    str1.parse::<i8>()? + str2.parse::<i8>()?     //2
  };
  if result.is_err() { -1 }
  else { result.unwrap() }
}

1. The compiler cannot infer the type
2. Using ? on Result inside the try block is now allowed

Conclusion

I learned about the try block in Java over twenty years ago. Java needs it because exceptions are at the root of its error-handling system; Rust doesn't because it uses Functional Programming for its error handling - mainly Result.

The ? operator builds upon the Result type to allow short-circuiting in functions that return Result themselves. If the function doesn't, you need a lot of boilerplate code. The experimental try block relieves some of it.

To go further:

• Error management in Rust, and libs that support it
• "The Rust Unstable Book: try_blocks"
• The Rust RFC Book
• Extending Rust's Effect System

Originally published at A Java Geek on April 21^st, 2024

• Research

Nicolas Frankel

Author

Technologist focusing on cloud-native technologies, DevOps, CI/CD pipelines, and system observability. His focus revolves around creating technical content, delivering talks, and engaging with developer communities to promote the adoption of modern software practices. With a strong background in software, he has worked extensively with the JVM, applying his expertise across various industries. In addition to his technical work, he is the author of several books and regularly shares insights through his blog and open-source contributions.