Practice When to Use What? - 5.5 | Chapter 7: Concurrency and Parallelism in Python | Python Advance
K12 Students

Academics

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

Professionals

Professional Courses

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

Games

Interactive Games

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

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What type of task is best suited for threading?

💡 Hint: Think about tasks that involve waiting for input or output operations.

Question 2

Easy

What does GIL stand for?

💡 Hint: It’s a term related to Python and concurrency.

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 an advantage of using threading for I/O-bound tasks?

  • Faster execution
  • Utilizes multiple CPU cores
  • Simplifies task management

💡 Hint: Think about why concurrency is beneficial for tasks waiting for input.

Question 2

Using multiprocessing allows us to bypass which limitation of Python?

  • True
  • False

💡 Hint: Consider what limits execution in Python.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are tasked with developing a web scraper that fetches multiple pages at once to collect data. Would you use threads or multiprocessing, and why?

💡 Hint: Look for evidence of waiting for data rather than processing.

Question 2

You are designing a program that performs large scale matrix multiplications. What concurrency model would be appropriate, and how would you implement it?

💡 Hint: Assess the load on the CPU during heavy computations.

Challenge and get performance evaluation