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 using 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.
One way to create an empty hash map is to use new and to 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.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-20/src/main.rs:here}}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.
We can get a value out of the hash map by providing its key to the get
method, as shown in Listing 8-21.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-21/src/main.rs:here}}Here, score will have the value that’s associated with the Blue team, and the
result will be 10. The get method returns an Option<&V>; if there’s no
value for that key in the hash map, get will return None. This program
handles the Option by calling copied to get an Option<i32> rather than an
Option<&i32>, then unwrap_or to set score to zero if scores doesn’t
have an entry for the key.
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:
{{#rustdoc_include ../listings/ch08-common-collections/no-listing-03-iterate-over-hashmap/src/main.rs:here}}This code will print each pair in an arbitrary order:
Yellow: 50
Blue: 10
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.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-22/src/main.rs:here}}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.
Although the number of key and value pairs is growable, each unique key can
only have one value associated with it at a time (but not vice versa: for
example, both the Blue team and the Yellow team could have the value 10
stored in the scores hash map).
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!
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 8-23 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.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-23/src/main.rs:here}}This code will print {"Blue": 25}. The original value of 10 has been
overwritten.
It’s common to check whether a particular key already exists in the hash map with a value and then to take the following actions: if the key does exist in the hash map, the existing value should remain the way it is; if the key doesn’t exist, insert it and 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 8-24.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-24/src/main.rs:here}}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, it
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 8-24 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.
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 8-25 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.
{{#rustdoc_include ../listings/ch08-common-collections/listing-08-25/src/main.rs:here}}This code will print {"world": 2, "hello": 1, "wonderful": 1}. You might see
the same key–value pairs printed in a different order: recall from the
“Accessing Values in a Hash Map” section that
iterating over a hash map happens in an arbitrary order.
The split_whitespace method returns an iterator over subslices, separated by
whitespace, of the value in text. The or_insert method returns a mutable
reference (&mut V) to the value for the specified 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.
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.
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 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!