Generator delegation

Simplify creating generators that forward an existing iterable.

Data processing: need a generator that yields items from another iterable; Async utilities: building lazy pipelines that forward data; Library wrappers: adapting existing sequences to a generator interface

Python codebases, especially in data processing, async utilities, or library wrappers.

def function_name(): yield from iterable

def ...(): yield from ...

function_name: identifier, iterable: expression returning an iterable

• for loops consuming the generator
• list()
• next()
• itertools.chain

• Using a manual for loop with yield
• or using itertools.chain.from_iterable

Forgetting that yield from delegates to sub-iterators and does not yield the iterable itself; using yield from on a non-iterable; missing parentheses.

Simple generator with yield (e.g., def gen(): for i in range(5): yield i) – more verbose; itertools.chain – functional alternative.

Coming from languages with explicit iterators (Java, C#): may expect to need to manually call next() on iterator → yield from hides that detail.

• generator function
• yield expression
• iterator protocol
• itertools.chain

yield from propagates exceptions from the sub-iterator and returns its final value if used in an expression (Python 3.3+). Not suitable if you need to perform extra actions before or after each item.

Reduces boilerplate, makes delegation explicit, preserves lazy evaluation.

Think 'yield from' as a 'pass‑through' generator.

Requires Python 3.3+; yield from delegates to sub-iterator and returns its final value when used in an expression.

Consider using itertools.chain.from_iterable for combining multiple iterables without defining a generator.