Lab 04: Lists, Tuples & Sets

🎯 Objective

Master Python's three sequence/collection types: lists (mutable sequences), tuples (immutable sequences), and sets (unique unordered collections).

📚 Background

Python has rich built-in collection types. Lists store ordered mutable sequences. Tuples store ordered immutable sequences (faster, safer for fixed data). Sets store unique unordered items with O(1) membership tests. Each excels in different scenarios.

⏱️ Estimated Time

30 minutes

📋 Prerequisites

• Lab 3: Strings

🛠️ Tools Used

• Python 3.12

🔬 Lab Instructions

Step 1: List Basics

fruits = ["apple", "banana", "cherry"]
print(fruits)
print(fruits[0])     # First: apple
print(fruits[-1])    # Last: cherry
print(fruits[1:3])   # Slice
print(len(fruits))   # 3
print(type(fruits))

📸 Verified Output:

['apple', 'banana', 'cherry']
apple
cherry
['banana', 'cherry']
3
<class 'list'>

Step 2: Modifying Lists

fruits = ["apple", "banana"]
fruits.append("cherry")
fruits.insert(1, "blueberry")
fruits.extend(["date", "fig"])
print(fruits)

fruits.remove("banana")
last = fruits.pop()
print(fruits)
print(f"Popped: {last}")

📸 Verified Output:

['apple', 'blueberry', 'banana', 'cherry', 'date', 'fig']
['apple', 'blueberry', 'cherry', 'date']
Popped: fig

Step 3: List Operations

nums = [3, 1, 4, 1, 5, 9, 2, 6]
print(f"sorted:  {sorted(nums)}")
print(f"min: {min(nums)}, max: {max(nums)}, sum: {sum(nums)}")
print(f"count 1: {nums.count(1)}")

nums.sort()
print(f"in-place: {nums}")
nums.reverse()
print(f"reversed: {nums}")

📸 Verified Output:

sorted:  [1, 1, 2, 3, 4, 5, 6, 9]
min: 1, max: 9, sum: 31
count 1: 2
in-place: [1, 1, 2, 3, 4, 5, 6, 9]
reversed: [9, 6, 5, 4, 3, 2, 1, 1]

Step 4: Tuples (Immutable)

point = (3, 4)
rgb = (255, 128, 0)
single = (42,)   # Comma makes it a tuple

print(point)
x, y = point     # Unpacking
print(f"x={x}, y={y}")

try:
    point[0] = 99
except TypeError as e:
    print(f"TypeError: {e}")

# Tuples in collections
coords = [(0, 0), (1, 2), (3, 4)]
print(coords)

📸 Verified Output:

(3, 4)
x=3, y=4
TypeError: 'tuple' object does not support item assignment
[(0, 0), (1, 2), (3, 4)]

💡 Tuples are immutable — safer for data that shouldn't change (coordinates, RGB values, database records). They're also ~30% faster than lists for iteration.

Step 5: Sets

s1 = {1, 2, 3, 4, 5}
s2 = {4, 5, 6, 7, 8}

print(f"union:        {sorted(s1 | s2)}")
print(f"intersection: {sorted(s1 & s2)}")
print(f"difference:   {sorted(s1 - s2)}")
print(f"symmetric:    {sorted(s1 ^ s2)}")

dupes = [1, 2, 2, 3, 3, 3, 4]
unique = sorted(set(dupes))
print(f"unique: {unique}")

print(999 in set(range(1000)))  # O(1) membership

📸 Verified Output:

union:        [1, 2, 3, 4, 5, 6, 7, 8]
intersection: [4, 5]
difference:   [1, 2, 3]
symmetric:    [1, 2, 3, 6, 7, 8]
unique: [1, 2, 3, 4]
True

Step 6: List Comprehensions

# Traditional
squares = []
for i in range(1, 6):
    squares.append(i ** 2)
print(squares)

# Comprehension (Pythonic)
squares = [i**2 for i in range(1, 6)]
print(squares)

# With filter
evens = [i for i in range(20) if i % 2 == 0]
print(evens)

words = ["hello", "world", "python"]
print([w.upper() for w in words])

📸 Verified Output:

[1, 4, 9, 16, 25]
[1, 4, 9, 16, 25]
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
['HELLO', 'WORLD', 'PYTHON']

Step 7: Nested Lists (Matrix)

matrix = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]
print(matrix[1][2])   # Row 1, Col 2: 6

# Transpose
transposed = [[row[i] for row in matrix] for i in range(3)]
for row in transposed:
    print(row)

📸 Verified Output:

6
[1, 4, 7]
[2, 5, 8]
[3, 6, 9]

Step 8: When to Use Each

# List: ordered, mutable, allows duplicates
cart = ["apple", "banana", "apple"]
cart.append("cherry")

# Tuple: fixed/immutable data
point = (10.5, 20.3)
color = (255, 0, 128)

# Set: unique items, fast membership
visited = {"google.com", "python.org"}
visited.add("github.com")

print(f"Cart: {cart}")
print(f"Point: {point}")
print(f"Visited {len(visited)} sites")
print(f"python.org visited: {'python.org' in visited}")

📸 Verified Output:

Cart: ['apple', 'banana', 'apple', 'cherry']
Point: (10.5, 20.3)
Visited 3 sites
python.org visited: True

✅ Verification

data = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
unique_sorted = sorted(set(data))
squares = [x**2 for x in unique_sorted]
print(f"Unique: {unique_sorted}")
print(f"Squares: {squares}")
print("Lab 4 verified ✅")

Expected output:

Unique: [1, 2, 3, 4, 5, 6, 9]
Squares: [1, 4, 9, 16, 25, 36, 81]
Lab 4 verified ✅

🚨 Common Mistakes

• (42) is just 42 — use (42,) for single-element tuple

• list.sort() returns None; sorted() returns new list

• Sets are unordered — don't rely on order

• b = a makes alias; use b = a.copy() or b = list(a) to copy

📝 Summary

• List []: ordered, mutable, duplicates allowed — for sequences

• Tuple (): ordered, immutable — for fixed records, function returns

• Set {}: unordered, unique, O(1) membership — for deduplication

• List comprehensions are concise and Pythonic

• sorted() returns new list; .sort() modifies in place

🔗 Further Reading

• Python Docs: Data Structures

• Real Python: Lists vs Tuples