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:
- Write a test that fails, and run it to make sure it fails for the reason you expected.
- Write or modify just enough code to make the new test pass.
- Refactor the code you just added or changed, and make sure the tests continue to pass.
- 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, which won't compile yet:
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) ); } } #}
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![] } #}
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 the “Validating References with Lifetimes” section in Chapter 10.
Now let’s run the test:
$ cargo test
Compiling minigrep v0.1.0 (file:///projects/minigrep)
--warnings--
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
}
}
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
}
}
}
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
}
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.