Data Structures

Python has four main built-in data structures. Each one is good for different tasks.

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Overview

Structure	Ordered	Mutable	Duplicates	Use Case
list	Yes	Yes	Yes	General collections
tuple	Yes	No	Yes	Fixed data, function returns
set	No	Yes	No	Unique values, fast lookup
dict	Yes	Yes	Keys: No	Key-value mapping

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Lists

A list is an ordered collection that you can change.

fruits = ["apple", "banana", "cherry"]

fruits.append("orange")      # add to end
fruits.insert(0, "mango")   # add at position
fruits.remove("banana")     # remove by value
last = fruits.pop()         # remove and return last item

print(fruits[0])    # first item
print(fruits[-1])   # last item
print(len(fruits))  # number of items

Slicing

numbers = [0, 1, 2, 3, 4, 5]

print(numbers[1:4])   # [1, 2, 3]
print(numbers[:3])    # [0, 1, 2]
print(numbers[3:])    # [3, 4, 5]
print(numbers[::2])   # [0, 2, 4]

Useful List Methods

Method	What It Does
append(x)	Add item to end
extend(list)	Add all items from another list
insert(i, x)	Insert item at position
remove(x)	Remove first occurrence
pop(i)	Remove and return item at position
sort()	Sort the list in place
reverse()	Reverse the list in place
index(x)	Find position of item
count(x)	Count occurrences

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Tuples

A tuple is like a list, but you cannot change it after creation.

point = (10, 20)
rgb = (255, 128, 0)

x, y = point  # unpacking

print(point[0])  # 10
print(len(point))  # 2

When to use tuples

Use tuples for data that should not change, like coordinates or database rows.

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Sets

A set stores unique values only. It has no order.

colors = {"red", "green", "blue"}
colors.add("yellow")
colors.discard("red")

print("green" in colors)  # True — fast lookup

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}

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Dictionaries

A dictionary maps keys to values.

user = {
    "name": "Alice",
    "age": 30,
    "role": "QA Engineer",
}

print(user["name"])          # "Alice"
print(user.get("email", "")) # "" (default if missing)

user["email"] = "alice@example.com"  # add new key
del user["age"]                       # remove key

Useful Dict Methods

Method	What It Does
get(key, default)	Get value safely
keys()	All keys
values()	All values
items()	All key-value pairs
update(dict)	Merge another dict
pop(key)	Remove and return value

Iterating Over a Dict

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

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Choosing the Right Structure

Need	Use
Ordered, changeable collection	list
Fixed, unchangeable data	tuple
Unique values, fast membership check	set
Key-value pairs, fast lookup by key	dict

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Best Practices

• Use lists for ordered collections of the same type
• Use tuples for fixed groups of related values
• Use sets to remove duplicates or check membership
• Use dicts for structured data with named fields
• Prefer dict.get(key, default) over dict[key] to avoid KeyError
• Use type hints for clarity: items: list[str], data: dict[str, int]