Practice Using Built-in Tools And Third-party Libraries (6) - Chapter 9: Memory Management and Performance Optimization in Python

Practice: Using Built-in Tools and Third-party Libraries

Lesson 6Memory Management and Performance Optimization in Python

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10 questions

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

Question 1.
What is the main advantage of using NumPy over a standard Python list?
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Think about efficiency in calculations.
Question 2.
What does the @profile decorator do?
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Remember, it's related to memory diagnostics.
3Question 3.
What library is preferred for numerical operations due to its speed?
- NumPy
- Pandas
- Matplotlib
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Recall which library specializes in numerical calculations.
4Question 4.
Can Cython be used for debugging?
- True
- False
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Focus on the purpose of Cython.
Question 5.
Create a NumPy solution to generate an array of 10 million random integers and compute the sum of all elements. Show how it compares to using a standard Python list.
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Use numpy for speed vs. the loop.
Question 6.
Write a Cython function to calculate the factorial of a number and compare its performance with a standard Python function.
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Focus on the factorial logic and ensure correct Cython syntax.

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