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Introduction to Generators: Yielding Values for Efficient Iteration

Generators simplify lazy evaluation by providing a concise and readable way to create iterators. While an iterator is implemented as a class with the __iter__() and __next__() methods, a generator is implemented as a function that uses the yield keyword to produce values one at a time. Generators maintain their state automatically between calls, making them more intuitive and efficient for many use cases.

A generator is a special type of function that:

Uses the yield keyword instead of return;
Pauses execution and retains its state when yield is called;
Resumes execution from where it left off when the generator is called again.


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def example_generator():
    yield "First value"
    yield "Second value"
    yield "Third value"

gen = example_generator()
print(next(gen))  # Output: First value
print(next(gen))  # Output: Second value
print(next(gen))  # Output: Third value


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import random

def limited_dice_roller(num_rolls):
    for _ in range(num_rolls):
        yield random.randint(1, 6)

# Using the limited dice roller
print("Rolling the dice:")
for roll in limited_dice_roller(5):
    print(f"Rolled: {roll}")

Differences Between Iterator and Generator

Tehtävä

Swipe to start coding

In the previous task, you implemented an infinite dice roller using a custom iterator class. Now, you will simplify the same functionality by using a generator function. Generators provide a concise and readable way to produce values lazily using the yield keyword.

Define the generator function. Use the yield keyword inside the dice_roller function to produce random dice rolls between 1 and 6. Use the random.randint() function to simulate each roll.
Call the dice_roller() function to create a generator object and assign it to the variable dice_generator.
Use a for loop with enumerate() to iterate over the generator. Stop the iteration after 10 rolls using an if condition and the break statement.

Ratkaisu

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Osio 6. Luku 4

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Introduction to Generators: Yielding Values for Efficient Iteration

A generator is a special type of function that:

Uses the yield keyword instead of return;
Pauses execution and retains its state when yield is called;
Resumes execution from where it left off when the generator is called again.


              123456789
            
def example_generator():
    yield "First value"
    yield "Second value"
    yield "Third value"

gen = example_generator()
print(next(gen))  # Output: First value
print(next(gen))  # Output: Second value
print(next(gen))  # Output: Third value


              12345678910
            
import random

def limited_dice_roller(num_rolls):
    for _ in range(num_rolls):
        yield random.randint(1, 6)

# Using the limited dice roller
print("Rolling the dice:")
for roll in limited_dice_roller(5):
    print(f"Rolled: {roll}")

Differences Between Iterator and Generator

Tehtävä

Swipe to start coding

Define the generator function. Use the yield keyword inside the dice_roller function to produce random dice rolls between 1 and 6. Use the random.randint() function to simulate each roll.
Call the dice_roller() function to create a generator object and assign it to the variable dice_generator.
Use a for loop with enumerate() to iterate over the generator. Stop the iteration after 10 rolls using an if condition and the break statement.

Ratkaisu

Vaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista

Oliko kaikki selvää?

Kiitos palautteestasi!

Osio 6. Luku 4

Vaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista