Loops 🔁

What You'll Learn

• ✅ How for loops work and when to use them
• ✅ How while loops work and when to use them
• ✅ range(), enumerate(), zip() and more
• ✅ Nested loops with real examples
• ✅ break, continue, pass, and else on loops
• ✅ List comprehensions as a loop shortcut
• ✅ Common mistakes and infinite loop traps

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📖 Introduction

A loop lets you repeat a block of code multiple times without writing it over and over. Python has two main loop types — for for iterating over sequences, and while for repeating based on a condition.

New to Python?

Start with Basics → Complexity Analysis → Data Structures → Algorithms before jumping into practice problems.

Already know Python?

Jump straight to Data Structures or Algorithms depending on what you're revising.

Keep in mind

Every topic includes real code examples, memory diagrams, and practical use cases — read them carefully, don't just skim the code.

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🔁 for Loop

1️⃣ Basic for Loop

Iterates over any iterable — list, string, tuple, dict, set, range.

Real-Life Example

• For each student in the class → print their name
• For each item in the cart → calculate total

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

for fruit in fruits:
    print(fruit)

Output:

apple
banana
cherry

Memory Visualization

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

Iteration 1:  fruit ──► "apple"   → body runs
Iteration 2:  fruit ──► "banana"  → body runs
Iteration 3:  fruit ──► "cherry"  → body runs
              no more items       → loop ends

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2️⃣ range() Function

Generates a sequence of numbers — perfect for index-based loops.

range(stop)range(start, stop)range(start, stop, step)Reverse

for i in range(5):
    print(i, end=" ")

Output:

0 1 2 3 4

for i in range(1, 6):
    print(i, end=" ")

Output:

1 2 3 4 5

for i in range(0, 10, 2):
    print(i, end=" ")

Output:

0 2 4 6 8

for i in range(5, 0, -1):
    print(i, end=" ")

Output:

5 4 3 2 1

Memory Visualization

range(1, 6):

┌───┬───┬───┬───┬───┐
│ 1 │ 2 │ 3 │ 4 │ 5 │
└───┴───┴───┴───┴───┘

range() does NOT store all values in memory —
it generates them one by one (lazy evaluation) ✅

range() is Memory Efficient

range(1000000) does not create a million numbers in memory. It generates each number on demand — making it very fast and efficient.

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3️⃣ enumerate() — Index + Value

Get both the index and value while looping.

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

# Without enumerate ❌
for i in range(len(fruits)):
    print(i, fruits[i])

# With enumerate ✅
for index, fruit in enumerate(fruits):
    print(f"{index}: {fruit}")

# Start from 1
for index, fruit in enumerate(fruits, start=1):
    print(f"{index}. {fruit}")

Output:

0: apple
1: banana
2: cherry
1. apple
2. banana
3. cherry

Always use enumerate() instead of range(len(...))

It's cleaner, more Pythonic, and less error-prone.

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4️⃣ zip() — Loop Two Lists Together

Iterate over multiple iterables in parallel.

names = ["Alice", "Bob", "Charlie"]
scores = [95, 87, 92]

for name, score in zip(names, scores):
    print(f"{name}: {score}")

Output:

Alice: 95
Bob: 87
Charlie: 92

zip() with unequal lengths

a = [1, 2, 3, 4, 5]
b = ["a", "b", "c"]

for x, y in zip(a, b):
    print(x, y)

Output:

1 a
2 b
3 c

zip() stops at the shortest iterable

Items 4 and 5 from list a are ignored. Use itertools.zip_longest() if you need all elements.

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5️⃣ Looping Over Different Iterables

StringTupleDictionarySet

for char in "Python":
    print(char, end="-")

Output:

P-y-t-h-o-n-

colors = ("red", "green", "blue")
for color in colors:
    print(color)

Output:

red
green
blue

student = {"name": "Alice", "age": 20, "gpa": 3.8}

for key in student:
    print(key)

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

Output:

name
age
gpa
name: Alice
age: 20
gpa: 3.8

unique = {3, 1, 4, 1, 5, 9}
for num in unique:
    print(num, end=" ")

Output:

1 3 4 5 9

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6️⃣ Nested for Loops

A loop inside another loop.

# Multiplication table
for i in range(1, 4):
    for j in range(1, 4):
        print(f"{i}×{j}={i*j}", end="  ")
    print()

Output:

1×1=1  1×2=2  1×3=3
2×1=2  2×2=4  2×3=6
3×1=3  3×2=6  3×3=9

Star Pattern

rows = 5
for i in range(1, rows + 1):
    print("* " * i)

Output:

*
* *
* * *
* * * *
* * * * *

Memory Visualization

for i in range(1, 3):       ← outer loop
    for j in range(1, 3):   ← inner loop

i=1: j=1 → (1,1)
     j=2 → (1,2)
i=2: j=1 → (2,1)
     j=2 → (2,2)

Total iterations = outer × inner = 2 × 2 = 4

Nested Loop Complexity

Every extra level of nesting multiplies the number of iterations. Three nested loops over n items = O(n³) — avoid deep nesting when possible.

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🔄 while Loop

7️⃣ Basic while Loop

Repeats as long as a condition is True. Use when you don't know how many iterations you need.

Real-Life Example

• While ATM has balance → allow withdrawals
• While user hasn't guessed correctly → keep asking

count = 1

while count <= 5:
    print(count, end=" ")
    count += 1

print("\nDone!")

Output:

1 2 3 4 5
Done!

Memory Visualization

count = 1

Check: count <= 5 → 1 <= 5 → True  → print 1, count = 2
Check: count <= 5 → 2 <= 5 → True  → print 2, count = 3
Check: count <= 5 → 3 <= 5 → True  → print 3, count = 4
Check: count <= 5 → 4 <= 5 → True  → print 4, count = 5
Check: count <= 5 → 5 <= 5 → True  → print 5, count = 6
Check: count <= 5 → 6 <= 5 → False → loop ends ✅

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8️⃣ while True + break

An intentional infinite loop that exits on a condition — common for menus and input validation.

while True:
    command = input("Enter command (quit to exit): ")
    if command == "quit":
        print("Goodbye! 👋")
        break
    print(f"Running: {command}")

Output:

Enter command (quit to exit): hello
Running: hello
Enter command (quit to exit): quit
Goodbye! 👋

Practical: Input Validation

while True:
    age = int(input("Enter your age (1-120): "))
    if 1 <= age <= 120:
        print(f"Valid age: {age} ✅")
        break
    print("Invalid! Try again ❌")

Output:

Enter your age (1-120): -5
Invalid! Try again ❌
Enter your age (1-120): 200
Invalid! Try again ❌
Enter your age (1-120): 25
Valid age: 25 ✅

Infinite Loop Trap

# ❌ This runs forever — forgot to update count!
count = 1
while count <= 5:
    print(count)
    # count += 1  ← missing!

# ✅ Always update the variable that controls the condition
count = 1
while count <= 5:
    print(count)
    count += 1

for loopwhile loop

# Known number of iterations
for i in range(10):
    print(i)

# Condition-based — unknown iterations
user_input = ""
while user_input != "quit":
    user_input = input("Enter: ")

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🎛️ Loop Control

9️⃣ break — Exit Loop Early

Stops the loop immediately and jumps out.

numbers = [1, 3, 7, 2, 9, 4]

for num in numbers:
    if num == 2:
        print("Found 2! Stopping.")
        break
    print(num)

Output:

1
3
7
Found 2! Stopping.

Memory Visualization

for num in [1, 3, 7, 2, 9, 4]:

  num=1 → print 1
  num=3 → print 3
  num=7 → print 7
  num=2 → BREAK ──────────────────────────┐
  num=9 → never reached                   │
  num=4 → never reached                   ▼
                                 continues after loop

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🔟 continue — Skip Current Iteration

Skips the rest of the current iteration and moves to the next one.

for i in range(1, 11):
    if i % 2 == 0:
        continue        # skip even numbers
    print(i, end=" ")

Output:

1 3 5 7 9

Practical: Filter Invalid Data

data = [10, -5, 20, -3, 15, 0, 8]
total = 0

for num in data:
    if num <= 0:
        continue
    total += num

print(f"Sum of positives: {total}")

Output:

Sum of positives: 53

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1️⃣1️⃣ pass — Do Nothing

A placeholder for empty blocks. Python requires at least one statement in a block.

for i in range(5):
    pass    # TODO: add logic later

print("No errors! ✅")

Output:

No errors! ✅

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1️⃣2️⃣ else on Loops

The else block runs only if the loop finished without hitting break.

numbers = [1, 3, 5, 7, 9]
target = 6

for num in numbers:
    if num == target:
        print(f"Found {target}!")
        break
else:
    print(f"{target} not found in list.")

Output:

6 not found in list.

With break — else is skipped

numbers = [1, 3, 5, 6, 9]
target = 6

for num in numbers:
    if num == target:
        print(f"Found {target}!")
        break
else:
    print(f"{target} not found.")

Output:

Found 6!

Loop else — Perfect for Search

Avoids the need for a found = False flag variable. Clean and Pythonic.

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⚡ List Comprehensions

A compact, Pythonic way to build lists using a single line instead of a loop.

Basic Comprehension

Traditional LoopList Comprehension ✅

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

Output:

[1, 4, 9, 16, 25]

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

Output:

[1, 4, 9, 16, 25]

With Condition

# Even numbers only
evens = [i for i in range(1, 11) if i % 2 == 0]
print(evens)

# Words longer than 4 chars
words = ["hi", "hello", "Python", "AI", "code"]
long_words = [w for w in words if len(w) > 4]
print(long_words)

Output:

[2, 4, 6, 8, 10]
['hello', 'Python']

Nested Comprehension

# Flatten a 2D list
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [num for row in matrix for num in row]
print(flat)

Output:

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

Don't Overuse Comprehensions

If your comprehension is hard to read in one line — use a regular loop. Readability > cleverness.

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✅ Quick Reference Summary

Loop / Statement	Syntax	Use When
for	for x in iterable:	Known sequence to iterate
while	while condition:	Condition-based repetition
range()	range(start, stop, step)	Numeric loops
enumerate()	for i, v in enumerate(lst):	Need index + value
zip()	for a, b in zip(x, y):	Parallel iteration
break	break	Exit loop early
continue	continue	Skip current iteration
pass	pass	Empty block placeholder
for-else	for ... else:	Detect if break was hit
List comp	[x for x in lst if cond]	Build lists concisely