99. Generators with yield from

Here are 10 Python code snippets demonstrating the use of yield from for delegating part of a generator’s iteration to another generator:

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1. Simple Delegation

def generator1():
    yield from [1, 2, 3]

def generator2():
    yield from generator1()
    yield 4

for value in generator2():
    print(value)  # Output: 1, 2, 3, 4

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2. Delegating Multiple Iterables

def generator():
    yield from range(3)
    yield from "abc"

for value in generator():
    print(value)  # Output: 0, 1, 2, a, b, c

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3. Delegating to Another Generator Function

def sub_generator():
    for i in range(5):
        yield i

def main_generator():
    yield "Start"
    yield from sub_generator()
    yield "End"

for value in main_generator():
    print(value)  # Output: Start, 0, 1, 2, 3, 4, End

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4. Flattening Nested Lists

def flatten(nested):
    for item in nested:
        if isinstance(item, list):
            yield from flatten(item)
        else:
            yield item

nested_list = [1, [2, [3, 4]], 5]
for value in flatten(nested_list):
    print(value)  # Output: 1, 2, 3, 4, 5

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5. Combining Results from Multiple Generators

def letters():
    yield from "abc"

def numbers():
    yield from range(1, 4)

def combined():
    yield from letters()
    yield from numbers()

for value in combined():
    print(value)  # Output: a, b, c, 1, 2, 3

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6. Delegating to Built-in Generators

def generate_squares(n):
    yield from (x ** 2 for x in range(n))

for square in generate_squares(4):
    print(square)  # Output: 0, 1, 4, 9

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7. Bidirectional Communication

def subgen():
    while True:
        value = (yield)
        print(f"Received: {value}")

def delegator():
    yield from subgen()

gen = delegator()
next(gen)  # Initialize the generator
gen.send("Hello")  # Output: Received: Hello
gen.send("World")  # Output: Received: World

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8. Handling Return Values

def subgen():
    yield 1
    yield 2
    return "Done"

def delegator():
    result = yield from subgen()
    print(f"Subgen returned: {result}")

for value in delegator():
    print(value)
# Output:
# 1
# 2
# Subgen returned: Done

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9. Processing Nested Iterables

def process_nested(iterables):
    for iterable in iterables:
        yield from iterable

nested = [[1, 2], (3, 4), {5, 6}]
for value in process_nested(nested):
    print(value)  # Output: 1, 2, 3, 4, 5, 6

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10. Generator Pipelines

def read_lines(lines):
    yield from lines

def filter_lines(lines, keyword):
    for line in lines:
        if keyword in line:
            yield line

lines = ["apple pie", "banana bread", "apple crumble"]
filtered = filter_lines(read_lines(lines), "apple")

for line in filtered:
    print(line)
# Output:
# apple pie
# apple crumble

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These examples illustrate how yield from simplifies delegation between generators, making it easier to compose and manage generator logic while maintaining readability.