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Python Programming - Generators

Exercise : Generators - General Questions
  • Generators - General Questions
36.
How does the generator.throw(StopIteration) method affect a running generator?
It raises a StopIteration exception inside the generator
It forcibly terminates the generator
It has no effect on the running generator
It restarts the generator from the beginning
Answer: Option
Explanation:
generator.throw(StopIteration) forcibly terminates the running generator by raising a StopIteration exception.
37.
How does the itertools.filterfalse() function behave when used with a generator?
It filters elements that evaluate to False in the generator
It filters elements that evaluate to True in the generator
It stops the generator after one iteration
It interleaves values from different generators
Answer: Option
Explanation:
itertools.filterfalse() filters elements in the generator that evaluate to False based on the provided function.
38.
What is the purpose of the itertools.groupby() function when used with generators?
It groups consecutive equal elements from the generator
It interleaves values from different generators
It stops the generator after one iteration
It creates pairs of values from the generators
Answer: Option
Explanation:
itertools.groupby() groups consecutive equal elements from the generator based on a key function. 
import itertools

def my_generator():
    yield 1
    yield 1
    yield 2
    yield 3
    yield 3

grouped_generator = itertools.groupby(my_generator())

for key, group in grouped_generator:
    print(f"Key: {key}, Group: {list(group)}")
39.
How does the generator.__iter__() method differ from the iter() built-in function when applied to a generator?
They are equivalent in functionality
generator.__iter__() is not a valid method for generators
generator.__iter__() returns the generator itself, while iter() returns a new iterator
iter() is used for generators, and generator.__iter__() is used for other iterable objects
Answer: Option
Explanation:
generator.__iter__() returns the generator itself, treating the generator as its own iterator. iter() returns a new iterator object for the generator. 
def my_generator():
    yield 1
    yield 2
    yield 3

# Using generator.__iter__()
gen_iter = my_generator().__iter__()
print(next(gen_iter))  # Output: 1

# Using iter()
iter_obj = iter(my_generator())
print(next(iter_obj))  # Output: 1
40.
What is the purpose of the itertools.islice() function when used with generators?
It slices a generator into specified ranges
It checks if a generator is iterable
It initializes the generator function
It generates an infinite sequence of numbers
Answer: Option
Explanation:
itertools.islice() is used to slice a generator into specified ranges, allowing you to extract a portion of the generator's elements without consuming the entire sequence. 
import itertools

def my_generator():
    for i in range(10):
        yield i

# Using itertools.islice() to slice the generator
sliced_generator = itertools.islice(my_generator(), 2, 7)

for value in sliced_generator:
    print(value)
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