Adding Functionality with Test Driven Development - The Rust Programming Language

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## Adding Functionality with Test-Driven Development

Now that we have the search logic in src/lib.rs separate from the `main` function, it’s much easier to write tests for the core functionality of our code. We can call functions directly with various arguments and check return values without having to call our binary from the command line.

In this section, we’ll add the searching logic to the `minigrep` program using the test-driven development (TDD) process with the following steps:

1. Write a test that fails and run it to make sure it fails for the reason you expect.
2. Write or modify just enough code to make the new test pass.
3. Refactor the code you just added or changed and make sure the tests continue to pass.
4. Repeat from step 1!

Though it’s just one of many ways to write software, TDD can help drive code design. Writing the test before you write the code that makes the test pass helps maintain high test coverage throughout the process.

We’ll test-drive the implementation of the functionality that will actually do the searching for the query string in the file contents and produce a list of lines that match the query. We’ll add this functionality in a function called `search`.

### Writing a Failing Test

In src/lib.rs, we’ll add a `tests` module with a test function, as we did in Chapter 11. The test function specifies the behavior we want the `search` function to have: It will take a query and the text to search, and it will return only the lines from the text that contain the query. Listing 12-15 shows this test.

Filename: src/lib.rs

    pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
        unimplemented!();
    }

    // --snip--

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

        #[test]
        fn one_result() {
            let query = "duct";
            let contents = "\
    Rust:
    safe, fast, productive.
    Pick three.";

            assert_eq!(vec!["safe, fast, productive."], search(query, contents));
        }
    }

Listing 12-15: Creating a failing test for the `search` function for the functionality we wish we had

This test searches for the string `"duct"`. The text we’re searching is three lines, only one of which contains `"duct"` (note that the backslash after the opening double quote tells Rust not to put a newline character at the beginning of the contents of this string literal). We assert that the value returned from the `search` function contains only the line we expect.

If we run this test, it will currently fail because the `unimplemented!` macro panics with the message “not implemented”. In accordance with TDD principles, we’ll take a small step of adding just enough code to get the test to not panic when calling the function by defining the `search` function to always return an empty vector, as shown in Listing 12-16. Then, the test should compile and fail because an empty vector doesn’t match a vector containing the line `"safe, fast, productive."`.

Filename: src/lib.rs

    pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
        vec![]
    }

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

        #[test]
        fn one_result() {
            let query = "duct";
            let contents = "\
    Rust:
    safe, fast, productive.
    Pick three.";

            assert_eq!(vec!["safe, fast, productive."], search(query, contents));
        }
    }

Listing 12-16: Defining just enough of the `search` function so that calling it won’t panic

Now let’s discuss why we need to define an explicit lifetime `'a` in the signature of `search` and use that lifetime with the `contents` argument and the return value. Recall in Chapter 10 that the lifetime parameters specify which argument lifetime is connected to the lifetime of the return value. In this case, we indicate that the returned vector should contain string slices that reference slices of the argument `contents` (rather than the argument `query`).

In other words, we tell Rust that the data returned by the `search` function will live as long as the data passed into the `search` function in the `contents` argument. This is important! The data referenced by a slice needs to be valid for the reference to be valid; if the compiler assumes we’re making string slices of `query` rather than `contents`, it will do its safety checking incorrectly.

If we forget the lifetime annotations and try to compile this function, we’ll get this error:

    $ cargo build
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
    error[E0106]: missing lifetime specifier
     --> src/lib.rs:1:51
      |
    1 | pub fn search(query: &str, contents: &str) -> Vec<&str> {
      |                      ----            ----         ^ expected named lifetime parameter
      |
      = help: this function's return type contains a borrowed value, but the signature does not say whether it is borrowed from `query` or `contents`
    help: consider introducing a named lifetime parameter
      |
    1 | pub fn search<'a>(query: &'a str, contents: &'a str) -> Vec<&'a str> {
      |              ++++         ++                 ++              ++

    For more information about this error, try `rustc --explain E0106`.
    error: could not compile `minigrep` (lib) due to 1 previous error

Rust can’t know which of the two parameters we need for the output, so we need to tell it explicitly. Note that the help text suggests specifying the same lifetime parameter for all the parameters and the output type, which is incorrect! Because `contents` is the parameter that contains all of our text and we want to return the parts of that text that match, we know `contents` is the only parameter that should be connected to the return value using the lifetime syntax.

Other programming languages don’t require you to connect arguments to return values in the signature, but this practice will get easier over time. You might want to compare this example with the examples in the “Validating References with Lifetimes” section in Chapter 10.

### Writing Code to Pass the Test

Currently, our test is failing because we always return an empty vector. To fix that and implement `search`, our program needs to follow these steps:

1. Iterate through each line of the contents.
2. Check whether the line contains our query string.
3. If it does, add it to the list of values we’re returning.
4. If it doesn’t, do nothing.
5. Return the list of results that match.

Let’s work through each step, starting with iterating through lines.

#### Iterating Through Lines with the `lines` Method

Rust has a helpful method to handle line-by-line iteration of strings, conveniently named `lines`, that works as shown in Listing 12-17. Note that this won’t compile yet.

Filename: src/lib.rs

    pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
        for line in contents.lines() {
            // do something with line
        }
    }

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

        #[test]
        fn one_result() {
            let query = "duct";
            let contents = "\
    Rust:
    safe, fast, productive.
    Pick three.";

            assert_eq!(vec!["safe, fast, productive."], search(query, contents));
        }
    }

Listing 12-17: Iterating through each line in `contents`

The `lines` method returns an iterator. We’ll talk about iterators in depth in Chapter 13. But recall that you saw this way of using an iterator in Listing 3-5, where we used a `for` loop with an iterator to run some code on each item in a collection.

#### Searching Each Line for the Query

Next, we’ll check whether the current line contains our query string. Fortunately, strings have a helpful method named `contains` that does this for us! Add a call to the `contains` method in the `search` function, as shown in Listing 12-18. Note that this still won’t compile yet.

Filename: src/lib.rs

    pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
        for line in contents.lines() {
            if line.contains(query) {
                // do something with line
            }
        }
    }

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

        #[test]
        fn one_result() {
            let query = "duct";
            let contents = "\
    Rust:
    safe, fast, productive.
    Pick three.";

            assert_eq!(vec!["safe, fast, productive."], search(query, contents));
        }
    }

Listing 12-18: Adding functionality to see whether the line contains the string in `query`

At the moment, we’re building up functionality. To get the code to compile, we need to return a value from the body as we indicated we would in the function signature.

#### Storing Matching Lines

To finish this function, we need a way to store the matching lines that we want to return. For that, we can make a mutable vector before the `for` loop and call the `push` method to store a `line` in the vector. After the `for` loop, we return the vector, as shown in Listing 12-19.

Filename: src/lib.rs

    pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
        let mut results = Vec::new();

        for line in contents.lines() {
            if line.contains(query) {
                results.push(line);
            }
        }

        results
    }

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

        #[test]
        fn one_result() {
            let query = "duct";
            let contents = "\
    Rust:
    safe, fast, productive.
    Pick three.";

            assert_eq!(vec!["safe, fast, productive."], search(query, contents));
        }
    }

Listing 12-19: Storing the lines that match so that we can return them

Now the `search` function should return only the lines that contain `query`, and our test should pass. Let’s run the test:

    $ cargo test
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
        Finished `test` profile [unoptimized + debuginfo] target(s) in 1.22s
         Running unittests src/lib.rs (target/debug/deps/minigrep-9cd200e5fac0fc94)

    running 1 test
    test tests::one_result ... ok

    test result: ok. 1 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s

         Running unittests src/main.rs (target/debug/deps/minigrep-9cd200e5fac0fc94)

    running 0 tests

    test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s

       Doc-tests minigrep

    running 0 tests

    test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s

Our test passed, so we know it works!

At this point, we could consider opportunities for refactoring the implementation of the search function while keeping the tests passing to maintain the same functionality. The code in the search function isn’t too bad, but it doesn’t take advantage of some useful features of iterators. We’ll return to this example in Chapter 13, where we’ll explore iterators in detail, and look at how to improve it.

Now the entire program should work! Let’s try it out, first with a word that should return exactly one line from the Emily Dickinson poem: frog.

    $ cargo run -- frog poem.txt
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
        Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.38s
         Running `target/debug/minigrep frog poem.txt`
    How public, like a frog

Cool! Now let’s try a word that will match multiple lines, like body:

    $ cargo run -- body poem.txt
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
        Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.0s
         Running `target/debug/minigrep body poem.txt`
    I'm nobody! Who are you?
    Are you nobody, too?
    How dreary to be somebody!

And finally, let’s make sure that we don’t get any lines when we search for a word that isn’t anywhere in the poem, such as monomorphization:

    $ cargo run -- monomorphization poem.txt
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
        Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.0s
         Running `target/debug/minigrep monomorphization poem.txt`

Excellent! We’ve built our own mini version of a classic tool and learned a lot about how to structure applications. We’ve also learned a bit about file input and output, lifetimes, testing, and command line parsing.

To round out this project, we’ll briefly demonstrate how to work with environment variables and how to print to standard error, both of which are useful when you’re writing command line programs.