Storing Keys with Associated Values in Hash Maps

The last of our common collections is the hash map. The type HashMap<K, V> stores a mapping of keys of type K to values of type V. It does this via a hashing function, which determines how it places these keys and values into memory. Many programming languages support this kind of data structure, but they often use a different name, such as hash, map, object, hash table, dictionary, or associative array, just to name a few.

Hash maps are useful when you want to look up data not by using an index, as you can with vectors, but by using a key that can be of any type. For example, in a game, you could keep track of each team’s score in a hash map in which each key is a team’s name and the values are each team’s score. Given a team name, you can retrieve its score.

We’ll go over the basic API of hash maps in this section, but many more goodies are hiding in the functions defined on HashMap<K, V> by the standard library. As always, check the standard library documentation for more information.

Creating a New Hash Map

You can create an empty hash map with new and add elements with insert. In Listing 8-20, we’re keeping track of the scores of two teams whose names are Blue and Yellow. The Blue team starts with 10 points, and the Yellow team starts with 50.

fn main() {
    use std::collections::HashMap;
    let mut scores = HashMap::new();
    scores.insert(String::from("Blue"), 10);
    scores.insert(String::from("Yellow"), 50);
}

Listing 8-20: Creating a new hash map and inserting some keys and values

Note that we need to first use the HashMap from the collections portion of the standard library. Of our three common collections, this one is the least often used, so it’s not included in the features brought into scope automatically in the prelude. Hash maps also have less support from the standard library; there’s no built-in macro to construct them, for example.

Just like vectors, hash maps store their data on the heap. This HashMap has keys of type String and values of type i32. Like vectors, hash maps are homogeneous: all of the keys must have the same type, and all of the values must have the same type.

Another way of constructing a hash map is by using iterators and the collect method on a vector of tuples, where each tuple consists of a key and its value. We’ll be going into more detail about iterators and their associated methods in the ”Processing a Series of Items with Iterators” section of Chapter 13. The collect method gathers data into a number of collection types, including HashMap. For example, if we had the team names and initial scores in two separate vectors, we could use the zip method to create an iterator of tuples where “Blue” is paired with 10, and so forth. Then we could use the collect method to turn that iterator of tuples into a hash map, as shown in Listing 8-21.

fn main() {
    use std::collections::HashMap;
    let teams = vec![String::from("Blue"), String::from("Yellow")];
    let initial_scores = vec![10, 50];
    let mut scores: HashMap<_, _> =
        teams.into_iter().zip(initial_scores.into_iter()).collect();
}

Listing 8-21: Creating a hash map from a list of teams and a list of scores

The type annotation HashMap<_, _> is needed here because it’s possible to collect into many different data structures and Rust doesn’t know which you want unless you specify. For the parameters for the key and value types, however, we use underscores, and Rust can infer the types that the hash map contains based on the types of the data in the vectors. In Listing 8-21, the key type will be String and the value type will be i32, just as the types were in Listing 8-20.

Hash Maps and Ownership

For types that implement the Copy trait, like i32, the values are copied into the hash map. For owned values like String, the values will be moved and the hash map will be the owner of those values, as demonstrated in Listing 8-22.

fn main() {
    use std::collections::HashMap;
    let field_name = String::from("Favorite color");
    let field_value = String::from("Blue");
    let mut map = HashMap::new();
    map.insert(field_name, field_value);
    // field_name and field_value are invalid at this point, try using them and
    // see what compiler error you get!
}

Listing 8-22: Showing that keys and values are owned by the hash map once they’re inserted

We aren’t able to use the variables field_name and field_value after they’ve been moved into the hash map with the call to insert.

If we insert references to values into the hash map, the values won’t be moved into the hash map. The values that the references point to must be valid for at least as long as the hash map is valid. We’ll talk more about these issues in the “Validating References with Lifetimes” section in Chapter 10.

Accessing Values in a Hash Map

We can get a value out of the hash map by providing its key to the get method, as shown in Listing 8-23.

fn main() {
    use std::collections::HashMap;
    let mut scores = HashMap::new();
    scores.insert(String::from("Blue"), 10);
    scores.insert(String::from("Yellow"), 50);
    let team_name = String::from("Blue");
    let score = scores.get(&team_name);
}

Listing 8-23: Accessing the score for the Blue team stored in the hash map

Here, score will have the value that’s associated with the Blue team, and the result will be Some(&10). The result is wrapped in Some because get returns an Option<&V>; if there’s no value for that key in the hash map, get will return None. The program will need to handle the Option in one of the ways that we covered in Chapter 6.

We can iterate over each key/value pair in a hash map in a similar manner as we do with vectors, using a for loop:

fn main() {
    use std::collections::HashMap;
    let mut scores = HashMap::new();
    scores.insert(String::from("Blue"), 10);
    scores.insert(String::from("Yellow"), 50);
    for (key, value) in &scores {
        println!("{}: {}", key, value);
    }
}

This code will print each pair in an arbitrary order:

Yellow: 50 Blue: 10

Updating a Hash Map

Although the number of keys and values is growable, each key can only have one value associated with it at a time. When you want to change the data in a hash map, you have to decide how to handle the case when a key already has a value assigned. You could replace the old value with the new value, completely disregarding the old value. You could keep the old value and ignore the new value, only adding the new value if the key doesn’t already have a value. Or you could combine the old value and the new value. Let’s look at how to do each of these!

Overwriting a Value

If we insert a key and a value into a hash map and then insert that same key with a different value, the value associated with that key will be replaced. Even though the code in Listing 8-24 calls insert twice, the hash map will only contain one key/value pair because we’re inserting the value for the Blue team’s key both times.

fn main() {
    use std::collections::HashMap;
    let mut scores = HashMap::new();
    scores.insert(String::from("Blue"), 10);
    scores.insert(String::from("Blue"), 25);
    println!("{:?}", scores);
}

Listing 8-24: Replacing a value stored with a particular key

This code will print {"Blue": 25}. The original value of 10 has been overwritten.

Only Inserting a Value If the Key Has No Value

It’s common to check whether a particular key has a value and, if it doesn’t, insert a value for it. Hash maps have a special API for this called entry that takes the key you want to check as a parameter. The return value of the entry method is an enum called Entry that represents a value that might or might not exist. Let’s say we want to check whether the key for the Yellow team has a value associated with it. If it doesn’t, we want to insert the value 50, and the same for the Blue team. Using the entry API, the code looks like Listing 8-25.

fn main() {
    use std::collections::HashMap;
    let mut scores = HashMap::new();
    scores.insert(String::from("Blue"), 10);
    scores.entry(String::from("Yellow")).or_insert(50);
    scores.entry(String::from("Blue")).or_insert(50);
    println!("{:?}", scores);
}

Listing 8-25: Using the entry method to only insert if the key does not already have a value

The or_insert method on Entry is defined to return a mutable reference to the value for the corresponding Entry key if that key exists, and if not, inserts the parameter as the new value for this key and returns a mutable reference to the new value. This technique is much cleaner than writing the logic ourselves and, in addition, plays more nicely with the borrow checker.

Running the code in Listing 8-25 will print {"Yellow": 50, "Blue": 10}. The first call to entry will insert the key for the Yellow team with the value 50 because the Yellow team doesn’t have a value already. The second call to entry will not change the hash map because the Blue team already has the value 10.

Updating a Value Based on the Old Value

Another common use case for hash maps is to look up a key’s value and then update it based on the old value. For instance, Listing 8-26 shows code that counts how many times each word appears in some text. We use a hash map with the words as keys and increment the value to keep track of how many times we’ve seen that word. If it’s the first time we’ve seen a word, we’ll first insert the value 0.

fn main() {
    use std::collections::HashMap;
    let text = "hello world wonderful world";
    let mut map = HashMap::new();
    for word in text.split_whitespace() {
        let count = map.entry(word).or_insert(0);
        *count += 1;
    }
    println!("{:?}", map);
}

Listing 8-26: Counting occurrences of words using a hash map that stores words and counts

This code will print {"world": 2, "hello": 1, "wonderful": 1}. The or_insert method actually returns a mutable reference (&mut V) to the value for this key. Here we store that mutable reference in the count variable, so in order to assign to that value, we must first dereference count using the asterisk (*). The mutable reference goes out of scope at the end of the for loop, so all of these changes are safe and allowed by the borrowing rules.

Hashing Functions

By default, HashMap uses a hashing function called SipHash that can provide resistance to Denial of Service (DoS) attacks involving hash tables1. This is not the fastest hashing algorithm available, but the trade-off for better security that comes with the drop in performance is worth it. If you profile your code and find that the default hash function is too slow for your purposes, you can switch to another function by specifying a different hasher. A hasher is a type that implements the BuildHasher trait. We’ll talk about traits and how to implement them in Chapter 10. You don’t necessarily have to implement your own hasher from scratch; crates.io has libraries shared by other Rust users that provide hashers implementing many common hashing algorithms.

1

https://en.wikipedia.org/wiki/SipHash

Summary

Vectors, strings, and hash maps will provide a large amount of functionality necessary in programs when you need to store, access, and modify data. Here are some exercises you should now be equipped to solve:

• Given a list of integers, use a vector and return the mean (the average value), median (when sorted, the value in the middle position), and mode (the value that occurs most often; a hash map will be helpful here) of the list.
• Convert strings to pig latin. The first consonant of each word is moved to the end of the word and “ay” is added, so “first” becomes “irst-fay.” Words that start with a vowel have “hay” added to the end instead (“apple” becomes “apple-hay”). Keep in mind the details about UTF-8 encoding!
• Using a hash map and vectors, create a text interface to allow a user to add employee names to a department in a company. For example, “Add Sally to Engineering” or “Add Amir to Sales.” Then let the user retrieve a list of all people in a department or all people in the company by department, sorted alphabetically.

The standard library API documentation describes methods that vectors, strings, and hash maps have that will be helpful for these exercises!

We’re getting into more complex programs in which operations can fail, so, it’s a perfect time to discuss error handling. We’ll do that next!