Collections

The collections module in Python provides specialized data structures that extend the built-in types like lists, tuples, and dictionaries. These data structures offer enhanced functionality and efficiency.

Counter

A Counter is a dictionary subclass used to count occurrences of elements.

from collections import Counter

# Example: Counting letters in a word
word = "mississippi"
counter = Counter(word)

print(counter)

Output:

{'i': 4, 's': 4, 'p': 2, 'm': 1}

Useful Methods:

• .most_common(n): Returns the n most common elements.
• .elements(): Returns an iterator repeating each element as per count.

print(counter.most_common(2))  # [('i', 4), ('s', 4)]

defaultdict

A defaultdict is a dictionary that assigns default values to keys that don’t exist.

from collections import defaultdict

# Default value type is list
students = defaultdict(list)

students["Math"].append("Jasmeet")
students["Science"].append("Chris")

print(students)  

Output:

{'Math': ['Jasmeet'], 'Science': ['Chris']}

Why Use defaultdict?

• Avoids KeyError
• Automatically initializes missing keys

deque

A deque (pronounced "deck") is a faster list optimized for insertion and deletion from both ends.

from collections import deque

queue = deque(["Jasmeet", "Chris", "Charlie"])

queue.append("David")  # Add to the right
queue.appendleft("Eve")  # Add to the left

print(queue)

Output:

deque(['Eve', 'Jasmeet', 'Chris', 'Charlie', 'David'])

Useful Methods:

• .pop(): Removes from the right
• .popleft(): Removes from the left
• .extend(iterable): Extends from the right

namedtuple

A namedtuple is an immutable tuple where elements have meaningful names.

from collections import namedtuple

# Define a named tuple
Person = namedtuple("Person", ["name", "age", "city"])

# Create an instance
p1 = Person(name="Jasmeet", age=25, city="New York")

print(p1.name, p1.age, p1.city)

Output:

Jasmeet 25 New York

Why Use namedtuple?

• Improves code readability
• Memory-efficient

OrderedDict

An OrderedDict remembers the order in which items were added (from Python 3.7+, regular dictionaries do this too).

from collections import OrderedDict

ordered_dict = OrderedDict()
ordered_dict["a"] = 1
ordered_dict["b"] = 2
ordered_dict["c"] = 3

print(ordered_dict)

Output:

OrderedDict([('a', 1), ('b', 2), ('c', 3)])

Why Use OrderedDict?
Useful when maintaining order is essential.

Why Use Collections Module?

✅ More efficient than built-in data types
✅ Provides advanced functionality
✅ Reduces code complexity