IndiaBIX

Python Programming - Generators

Exercise : Generators - General Questions
  • Generators - General Questions
6.
What is the purpose of the next() function when working with generators?
It generates the next random number
It retrieves the next element from the generator
It initializes the generator function
It terminates the generator
Answer: Option
Explanation:
The next() function is used to retrieve the next element produced by a generator. It advances the generator's state and returns the value generated by the yield statement.
7.
How does a generator handle large datasets compared to a list?
Generators are slower than lists for large datasets
Generators consume more memory than lists
Generators are not suitable for large datasets
Generators are more memory-efficient than lists
Answer: Option
Explanation:
Generators produce values on-the-fly, allowing them to handle large datasets efficiently by not storing the entire sequence in memory. This makes generators more memory-efficient than lists.
8.
What will happen if a generator function reaches the end of its execution?
It raises a StopIteration exception
It automatically restarts from the beginning
It continues to the next iteration
It raises a GeneratorExit exception
Answer: Option
Explanation:
When a generator function completes its execution or reaches a return statement, it raises a StopIteration exception to indicate the end of the iteration.
9.
What is the advantage of using the yield from statement in a generator function?
It replaces the yield keyword
It simplifies the generator function syntax
It allows delegation to another generator
It is used for generator initialization
Answer: Option
Explanation:
The yield from statement in a generator function allows delegation to another generator, simplifying the syntax and enabling one generator to yield values from another.
10.
What is the main difference between a generator and a list comprehension?
Generators are used for creating lists, while list comprehensions produce iterators
List comprehensions create lists in memory, while generators produce values on-the-fly
List comprehensions can only be used with numerical data, while generators work with any data type
Generators use the list() constructor, while list comprehensions use generator()
Answer: Option
Explanation:
List comprehensions create lists in memory, whereas generators produce values on-the-fly and do not store the entire sequence in memory. Generators are more memory-efficient.
Quick links
Quantitative Aptitude
Verbal (English)
Reasoning
Programming
Interview
Placement Papers