Data Structures

Aman's AI Journal • Primers • Python Data Structures and Time Complexities

Python Data Structures Overview

SI	DS	Description	Usage Scenario	Pros	Cons
1	List []	Ordered, mutable, allows duplicates.	Storing and modifying a sequence of items.	1. Dynamic sizing 2. Built-in methods 3. Easy indexing	1. Slower for search operations
2	Tuple ()	Ordered, immutable, allows duplicates.	Returning multiple values from a function.	1. Memory-efficient 2. Safe from unintended changes	1. Cannot modify contents
3	Set {} / set()	Unordered, mutable, no duplicates.	Membership testing, removing duplicates.	1. Fast lookup 2. Ensures uniqueness	1. No indexing
4	Dictionary {key: val}	Key-value pairs, unordered in <3.6, ordered from 3.7+.	Lookups by key, JSON-like data.	1. Fast key access 2. Flexible structure	1. Keys must be hashable
5	Stack [list]	LIFO, often implemented using lists.	Undo functionality, parsing.	1. Simple to implement with lists 2. Built-in methods like append, pop	1. Manual enforcement of LIFO
6	Queue deque([])	FIFO, implemented using collections.deque.	Scheduling tasks, producer-consumer.	1. Fast appends and pops from both ends	1. Not built-in as list
7	namedtuple namedtuple()	Immutable object with named fields.	Replacing simple classes.	1. Improves readability 2. Lightweight and immutable	1. Cannot modify fields
8	Counter Counter()	Dict subclass for counting hashable items.	Word frequency, histogram data.	1. Fast frequency count 2. Built-in operations like most_common()	1. Not suitable for unhashables
9	defaultdict defaultdict()	Dict subclass with a default factory for missing keys.	Grouping values, building indexes.	1. Avoids KeyError 2. Cleaner code	1. Slight overhead due to factory

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Code sample

List

my_list = [1, 2, 3]
my_list.append(4)
print(my_list)  # [1, 2, 3, 4]

Tuple

my_tuple = (1, 2, 3)
print(my_tuple[1])  # 2

# my_tuple[1] = 5  # ❌ Error: 'tuple' object does not support item assignment

Set

my_set = {1, 2, 3, 3}
my_set.add(4)
print(my_set)  # {1, 2, 3, 4}

Dictionary

my_dict = {"name": "Anirudh", "age": 25}
print(my_dict["name"])  # Anirudh

Stack

stack = []
stack.append(1)
stack.append(2)
print(stack.pop())  # 2

Queue

from collections import deque

queue = deque()
queue.append(1)
queue.append(2)
print(queue.popleft())  # 1

namedtuple

from collections import namedtuple

Point = namedtuple("Point", "x y")
pt = Point(1, 2)
print(pt.x, pt.y)  # 1 2

Counter

from collections import Counter

c = Counter("anirudh")
print(c)  # Counter({'a': 1, 'n': 1, 'i': 1, 'r': 1, 'u': 1, 'd': 1, 'h': 1})

defaultdict

from collections import defaultdict

dd = defaultdict(int)
dd["apple"] += 1
print(dd["apple"])  # 1
print(dd["banana"])  # 0 (no error!)