Dictionaries

Dictionaries map keys to values. They keep insertion order, so when you iterate over a dictionary you get keys back in the order they were first added.

Creating dictionaries

counts = {"apples": 2, "bananas": 4}
empty_counts: dict[str, int] = {}

The key type and value type are fixed for a given dictionary. When a dictionary is empty, give it a type if the surrounding code does not make that obvious.

Looking up values

counts = {"apples": 2, "bananas": 4}

print(counts["apples"])
print(counts.get("pears"))
print(counts.get_def("pears", 0))
print("apples" in counts)
print(len(counts))

Direct indexing says the key must already exist. get() returns None when a key is missing. get_def() lets you provide a default value instead of handling None later.

Updating entries

counts = {"apples": 2, "bananas": 4}

counts["bananas"] = 5
counts["pears"] = 1
del counts["apples"]

print(counts)

Assigning to a key adds it if it is new or replaces the old value if it already exists.

Removing entries

counts = {"apples": 2, "bananas": 4, "pears": 1}

print(counts.pop("bananas"))
print(counts.pop_def("missing", 0))
print(counts.popitem())

pop() removes a key and returns its value. pop_def() does the same thing with a fallback when the key is absent. popitem() removes and returns one key/value pair.

Iterating over dictionaries

counts = {"apples": 2, "bananas": 4, "pears": 1}

for key in counts:
    print(key)

for key, value in counts.items():
    print(key, value)

print(list(counts.keys()))
print(list(counts.values()))
print(list(counts.items()))

Iterating over a dictionary yields keys. Use items() when you need both the key and the value.

Updating from other data

counts = {"apples": 2}
more_counts = {"bananas": 4, "pears": 1}

counts.update(more_counts.items())
counts.setdefault("apples", 0)
counts.setdefault("grapes", 3)

update() merges entries from another iterable of key/value pairs. setdefault() is useful when you want to add a missing key only once and keep the existing value otherwise.

Dictionary comprehensions

words = ["hello", "world", "acton"]
lengths = {word: len(word) for word in words}
filtered = {word: len(word) for word in words if len(word) > 4}
indexed = {i: word for (i, word) in enumerate(words)}

Dictionary comprehensions are the concise way to build a dictionary from an iterable. They are useful when the new keys and values come from the old data directly.