Practice Generators and Generator Functions - 3.3 | Chapter 3: Generators and Iterators | Python Advance
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a generator in Python?

πŸ’‘ Hint: Think about iterators and how they work.

Question 2

Easy

How do you start executing a generator function?

πŸ’‘ Hint: What does 'next()' do in general?

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the purpose of the 'yield' keyword in Python?

  • To exit a function
  • To return a value and pause execution
  • To create a class

πŸ’‘ Hint: Think about what happens when a function uses 'yield' versus 'return'.

Question 2

True or False: Generators are memory-efficient because they compute all values at once.

  • True
  • False

πŸ’‘ Hint: How does a traditional list differ from a generator?

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a generator that yields the Fibonacci sequence indefinitely. How would you modify it to stop if the number exceeds a certain limit?

πŸ’‘ Hint: Consider the logic of the Fibonacci sequence and how to use two previous values to create the next.

Question 2

Write a generator that takes a list and yields only the even numbers. How would you then use 'yield from' to handle a second list of numbers?

πŸ’‘ Hint: Think about how you can create stages in your data processing pipelines.

Challenge and get performance evaluation