Practice When To Use What? (5.5) - Chapter 7: Concurrency and Parallelism in Python

Practice: When to Use What?

Lesson 5.5Concurrency and Parallelism in Python

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9 questions

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2 cards from this section. Quick, good the night before a test.
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6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What type of task is best suited for threading?
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Think about tasks that involve waiting for input or output operations.
Question 2.
What does GIL stand for?
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It’s a term related to Python and concurrency.
3Question 3.
What is an advantage of using threading for I/O-bound tasks?
- Faster execution
- Utilizes multiple CPU cores
- Simplifies task management
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Think about why concurrency is beneficial for tasks waiting for input.
4Question 4.
Using multiprocessing allows us to bypass which limitation of Python?
- True
- False
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Consider what limits execution in Python.
Question 5.
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?
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Look for evidence of waiting for data rather than processing.
Question 6.
You are designing a program that performs large scale matrix multiplications. What concurrency model would be appropriate, and how would you implement it?
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Assess the load on the CPU during heavy computations.

5 more questions in this section. Enroll free to practise them all.