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Loops

Loops in Python

Loops are used to execute a block of code repeatedly. Python offers two primary loop constructs: for and while.

For Loop

The for loop iterates over a sequence (like a list, tuple, or string).

Python

fruits = ["apple", "banana", "cherry"]
for fruit in fruits:
  print(fruit)

While Loop

The while loop executes a block of code as long as a specified condition is true.

Python

count = 0
while count < 5:
  print(count)
  count += 1

Key points:

  • Indentation: Crucial for defining the loop body.
  • Iterables: Objects that can be iterated over, like lists, tuples, strings, and dictionaries.
  • Loop control statements: break to exit the loop, continue to skip the current iteration.
  • Infinite loops: Be cautious with while loops to avoid infinite loops.

Example with else clause

Python uniquely supports an else clause with loops. It executes if the loop completes normally (without encountering a break statement).

Python

for num in range(2, 10):
  for i in range(2, num):
    if (num % i) == 0:
      print(num, "is not a prime number")
      break
  else:
    print(num, "is a prime number")

What are the two main types of loops in Python?

for and while loops.

What is an iterable?

An iterable is an object that can be iterated over, such as lists, tuples, strings, and dictionaries.

Can I use a for loop with a range object?

Yes, the range() function generates a sequence of numbers.

How does a while loop work?

A while loop continues to execute as long as a given condition is true.

What is an infinite loop?

An infinite loop occurs when the loop condition never becomes false.

What is the break statement?

The break statement terminates the loop immediately.

What is the continue statement?

The continue statement skips the current iteration and moves to the next.

Can I nest loops?

Yes, you can nest loops to create complex iterations.

Are there performance implications for loops?

Looping can be computationally expensive, especially for large datasets. Consider list comprehensions or generator expressions for efficiency.

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