Dictionaries and Sets

Dictionaries and sets are two more essential Python data structures. Dictionaries map keys to values; sets store unique values with no duplicates.

Dictionaries

A dictionary stores key-value pairs, defined with curly braces:

person = {
    "name": "Alice",
    "age": 30,
    "city": "London"
}

Keys must be immutable (strings, numbers, tuples). Values can be anything.

Accessing Values

print(person["name"])            # Alice
print(person.get("age"))         # 30
print(person.get("email", "N/A")) # N/A — default if key missing

Using get() is safer than bracket notation — it returns None (or a default) instead of raising a KeyError if the key does not exist.

Modifying Dictionaries

person["age"] = 31               # update existing key
person["email"] = "alice@example.com"  # add new key
del person["city"]               # remove a key
removed = person.pop("age")      # remove and return value

Iterating Over Dictionaries

inventory = {"apples": 5, "bananas": 12, "cherries": 3}

for key in inventory:
    print(key)

for value in inventory.values():
    print(value)

for key, value in inventory.items():
    print(f"{key}: {value}")

Useful Dictionary Methods

d = {"a": 1, "b": 2}
print(d.keys())     # dict_keys(['a', 'b'])
print(d.values())   # dict_values([1, 2])
print(d.items())    # dict_items([('a', 1), ('b', 2)])
print(len(d))       # 2
print("a" in d)     # True — checks keys

Dictionary Comprehensions

squares = {x: x ** 2 for x in range(1, 6)}
print(squares)   # {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

Sets

A set is an unordered collection of unique items:

colors = {"red", "green", "blue"}
numbers = {1, 2, 3, 2, 1}   # duplicates removed automatically
print(numbers)               # {1, 2, 3}
empty_set = set()            # must use set(), not {} (that's an empty dict)

Set Operations

a = {1, 2, 3, 4}
b = {3, 4, 5, 6}

print(a | b)   # union: {1, 2, 3, 4, 5, 6}
print(a & b)   # intersection: {3, 4}
print(a - b)   # difference: {1, 2}
print(a ^ b)   # symmetric difference: {1, 2, 5, 6}

Modifying Sets

s = {1, 2, 3}
s.add(4)
s.remove(2)      # raises KeyError if not present
s.discard(10)    # no error if not present
print(s)         # {1, 3, 4}

Sets are ideal for membership testing (much faster than lists for large collections) and for removing duplicates. Dictionaries are the go-to structure for storing structured data with named fields.