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Efficient Data Handling in Python

bookIntroduction to Generator Functions

Generator functions are a special type of function in Python that allow you to produce a sequence of values over time, instead of computing them all at once and returning them in a list. You define a generator function just like a normal function, but instead of using the return statement to send a value back, you use the yield keyword. When Python encounters yield, it pauses the function, saves its state, and sends the yielded value to the caller. The next time you ask for a value, the function resumes right where it left off. This technique is called lazy evaluation, because values are produced only when you need them, not in advance. This makes generator functions very memory efficient, especially when working with large or infinite sequences.


              
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def square_numbers(n):
    for i in range(1, n + 1):
        yield i * i

# Using the generator function
for square in square_numbers(5):
    print(square)
copy

1. Which of the following best describes the role of the yield keyword in a generator function?

2. Which statements are true about the differences between return and yield in Python functions?

question mark

Which of the following best describes the role of the yield keyword in a generator function?

Select the correct answer

question mark

Which statements are true about the differences between return and yield in Python functions?

Select the correct answer

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 1

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Suggested prompts:

Can you explain how the `yield` keyword works in more detail?

What are some practical use cases for generator functions?

How do generator functions differ from regular functions that return lists?

bookIntroduction to Generator Functions

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Generator functions are a special type of function in Python that allow you to produce a sequence of values over time, instead of computing them all at once and returning them in a list. You define a generator function just like a normal function, but instead of using the return statement to send a value back, you use the yield keyword. When Python encounters yield, it pauses the function, saves its state, and sends the yielded value to the caller. The next time you ask for a value, the function resumes right where it left off. This technique is called lazy evaluation, because values are produced only when you need them, not in advance. This makes generator functions very memory efficient, especially when working with large or infinite sequences.


              
1234567

            
def square_numbers(n):
    for i in range(1, n + 1):
        yield i * i

# Using the generator function
for square in square_numbers(5):
    print(square)
copy

1. Which of the following best describes the role of the yield keyword in a generator function?

2. Which statements are true about the differences between return and yield in Python functions?

question mark

Which of the following best describes the role of the yield keyword in a generator function?

Select the correct answer

question mark

Which statements are true about the differences between return and yield in Python functions?

Select the correct answer

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 1
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