## Testing the Library's Functionality

Now that we've extracted the logic into src/lib.rs and left all the argument parsing and error handling in src/main.rs, it's much easier for us to write tests for the core functionality of our code. We can call our functions directly with various arguments and check return values without having to call our binary from the command line.

In this section, we're going to follow the Test Driven Development (TDD) process. This is a software development technique that follows this set of 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!

This is just one of many ways to write software, but TDD can help drive the design of code. Writing the test before writing the code that makes the test pass helps to maintain high test coverage throughout the process.

We're going to test drive the implementation of the part of our `greprs` program 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're going to add this functionality in a function called `search`.

### Writing a Failing Test

First, since we don't really need them any more, let's remove the `println!` statements from both src/lib.rs and src/main.rs. Then we'll add a `test` module with a test function, like we did in Chapter 11. The test function specifies the behavior we'd like 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

We've chosen to use "duct" as the string we're looking for in this test. The text we're searching in is three lines, only one of which contains "duct". We assert that the value returned from the `search` function contains only the one line we expect.

We aren't able to run this test and watch it fail though, since this test doesn't even compile yet! We're going to add just enough code to get it to compile: a definition of the `search` function that always returns an empty vector, as shown in Listing 12-16. Once we have this, the test should compile and fail because an empty vector doesn't match a vector containing the one line `"safe, fast, productive."`.

Filename: src/lib.rs

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

    #}

Listing 12-16: Defining just enough of the `search` function that 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. Remember from Chapter 10 that the lifetime parameters specify which argument lifetime is connected to the lifetime of the return value. In this case, we're indicating that the returned vector should contain string slices that reference slices of the argument `contents` (rather than the argument `query`).

In other words, we're telling 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 in order for the reference to be valid; if the compiler assumed we were making string slices of `query` rather than `contents`, it would do its safety checking incorrectly.

If we tried to compile this function without lifetimes, we would get this error:

    error[E0106]: missing lifetime specifier
     --> src/lib.rs:5:47
      |
    5 | 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 this may still feel strange, but will get easier over time. You may want to compare this example with the Lifetime Syntax section in Chapter 10.

Now let's try running our test:

    $ cargo test
    ...warnings...
        Finished debug [unoptimized + debuginfo] target(s) in 0.43 secs
         Running target/debug/deps/greprs-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:16
    note: Run with `RUST_BACKTRACE=1` for a backtrace.

    failures:
        test::one_result

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

    error: test failed

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

### Writing Code that Gets the Test to Pass

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 if 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.
3. Return the list of results that match.

Let's take each step at a time, 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:

Filename: src/lib.rs

    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 be talking about iterators in depth in Chapter 13, but we've already seen this way of using an iterator in Listing 3-6, 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 add functionality to check if the current line contains the query string. Luckily, strings have another helpful method named `contains` that does this for us! Add the `contains` method to the `search` function as shown in Listing 12-18:

Filename: src/lib.rs

    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 if the line contains the string in `query`

#### Storing Matching Lines

Finally, we 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

    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 that we can return them

Now the `search` function should be returning only the lines that contain `query`, and our test should pass. Let's run the tests:

    $ cargo test
    running 1 test
    test test::one_result ... ok

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

         Running target/debug/greprs-2f55ee8cd1721808

    running 0 tests

    test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured

       Doc-tests greprs

    running 0 tests

    test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured

Our test passed, great, it works!

Now that our test is passing, we could consider opportunities for refactoring the implementation of the `search` function while keeping the tests passing in order to maintain the same functionality while we do so. This code isn't bad, but it isn't taking advantage of some useful features of iterators. We'll be coming back to this example in Chapter 13 where we'll explore iterators in detail and see how to improve it.

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

Now that we have the `search` function working and tested, we need to actually call `search` from our `run` function. We need to pass the `config.query` value and the `contents` that `run` read from the file to the `search` function. Then `run` will print out 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 again using a `for` loop to get each line returned from `search`, and the code that we run for each line prints it out.

Now our whole program should be working! 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 greprs v0.1.0 (file:///projects/greprs)
        Finished debug [unoptimized + debuginfo] target(s) in 0.38 secs
         Running `target/debug/greprs frog poem.txt`
    How public, like a frog

Cool! Next, how about a word that will match multiple lines, like "the":

    $ cargo run the poem.txt
        Finished debug [unoptimized + debuginfo] target(s) in 0.0 secs
         Running `target/debug/greprs the poem.txt`
    Then there's a pair of us — don't tell!
    To tell your name the livelong day

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, like "monomorphization":

    $ cargo run monomorphization poem.txt
        Finished debug [unoptimized + debuginfo] target(s) in 0.0 secs
         Running `target/debug/greprs monomorphization poem.txt`

Excellent! We've built our own 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.

Feel free to move on to Chapter 13 if you'd like at this point. To round out this project chapter, though, we're going to briefly demonstrate how to work with environment variables and printing to standard error, both of which are useful when writing command line programs.