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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What module would you use for running CPU-bound tasks in Python?
💡 Hint: Think about parallel execution of processes.
Question 2
Easy
What does GIL stand for?
💡 Hint: Is it related to threading or multiprocessing?
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 does the multiprocessing module help achieve?
- True parallelism
- Thread safety
- Memory sharing
💡 Hint: Focus on the nature of CPU-bound tasks.
Question 2
True or False: The GIL allows multiple threads in Python to run bytecode simultaneously.
- True
- False
💡 Hint: Remember the limitation posed by GIL.
Solve 3 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Implement a multiprocessing solution for computing the factorial of numbers from 1 to 10, using the multiprocessing module to parallelize the computation.
💡 Hint: Recall how to define functions and invoke processes.
Question 2
Discuss the limitations of using multiprocessing in a high-throughput application where latency is a concern. Suggest alternative approaches.
💡 Hint: Think about trade-offs related to performance and application needs.
Challenge and get performance evaluation