Developing the Library’s Functionality with Test Driven Development - Developing the Library’s Functionality with Test Driven Development - The Rust Programming Language

## Developing the Library’s Functionality with Test Driven Development

Now that we’ve extracted the logic into src/lib.rs and left the argument collecting and error handling in src/main.rs, 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. Feel free to write some tests for the functionality in the `Config::new` and `run` functions on your own.

In this section, we’ll add the searching logic to the `minigrep` program by using the Test Driven Development (TDD) process. This software development technique follows these steps:

1. Write a test that fails, and run it to make sure it fails for the reason you expected.
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!

This process is just one of many ways to write software, but TDD can help drive code design as well. Writing the test before you write the code that makes the test pass helps to 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

Because we don’t need them anymore, let’s remove the `println!` statements from src/lib.rs and src/main.rs that we used to check the program’s behavior. Then, in src/lib.rs, we’ll add a `test` 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 for the query in, and will return only the lines from the text that contain the query. Listing 12-15 shows this test:

Filename: src/lib.rs

    # #![allow(unused_variables)]
    #fn main() {
    # fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
    #      vec![]
    # }
    #
    #[cfg(test)]
    mod test {
        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 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.” We assert that the value returned from the `search` function contains only the line we expect.

We aren’t able to run this test and watch it fail because the test doesn’t even compile: the `search` function doesn’t exist yet! So now we’ll add just enough code to get the test to compile and run by adding a definition of the `search` function that always returns 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

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

Listing 12-16: Defining just enough of the `search` function so our test will compile

Notice that we need an explicit lifetime `'a` defined in the signature of `search` and used 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:

    error[E0106]: missing lifetime specifier
     --> src/lib.rs:5:51
      |
    5 | pub fn search(query: &str, contents: &str) -> Vec<&str> {
      |                                                   ^ expected 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`

Rust can’t possibly know which of the two arguments we need, so we need to tell it. Because `contents` is the argument that contains all of our text and we want to return the parts of that text that match, we know `contents` is the argument 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, so although this might seem strange, it will get easier over time. You might want to compare this example with “Validating References with Lifetimes” in Chapter 10 on page XX.

Now let’s run the test:

    $ cargo test
    --warnings--
       Compiling minigrep v0.1.0 (file:///projects/minigrep)
        Finished dev [unoptimized + debuginfo] target(s) in 0.43 secs
         Running target/debug/deps/minigrep-abcabcabc

    running 1 test
    test test::one_result ... FAILED

    failures:

    ---- test::one_result stdout ----
            thread 'test::one_result' panicked at 'assertion failed: `(left ==
    right)`
    left: `["safe, fast, productive."]`,
    right: `[]`)', src/lib.rs:48:8
    note: Run with `RUST_BACKTRACE=1` for a backtrace.

    failures:
        test::one_result

    test result: FAILED. 0 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out

    error: test failed, to rerun pass '--lib'

Great, the test fails, exactly as we expected. Let’s get the test to pass!

### 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:

- Iterate through each line of the contents.
- Check whether the line contains our query string.
- If it does, add it to the list of values we’re returning.
- If it doesn’t, do nothing.
- 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 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
        }
    }

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 3-4, 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 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
            }
        }
    }

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

#### Storing Matching Lines

We also need a way to store the lines that contain our query string. 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
    }

Listing 12-19: Storing the lines that match so 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
    --snip--
    running 1 test
    test test::one_result ... ok

    test result: ok. 1 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out

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.

#### Using the `search` Function in the `run` Function

Now that the `search` function is working and tested, we need to call `search` from our `run` function. We need to pass the `config.query` value and the `contents` that `run` reads from the file to the `search` function. Then `run` will print each line returned from `search`:

Filename: src/lib.rs

    pub fn run(config: Config) -> Result<(), Box<Error>> {
        let mut f = File::open(config.filename)?;

        let mut contents = String::new();
        f.read_to_string(&mut contents)?;

        for line in search(&config.query, &contents) {
            println!("{}", line);
        }

        Ok(())
    }

We’re still using a `for` loop to return each line from `search` and print 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 [unoptimized + debuginfo] target(s) in 0.38 secs
         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
        Finished dev [unoptimized + debuginfo] target(s) in 0.0 secs
         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
        Finished dev [unoptimized + debuginfo] target(s) in 0.0 secs
         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.