How does yield from delegation work? | Interview Question

Q: How does yield from delegation work?

**Target Audience:** Python developers who know what a generator is and want to understand delegation properly; interview candidates who will be asked "isn't it just a loop?". **Difficulty:** Medium **Python version:** All behaviour checked on CPython 3.11.17 and in the page runner (Pyodide 0.25.1, CPython 3.11.3); the bytecode comparison was also run on CPython 3.12.3. > **How to read this doc:** Each idea is explained in plain words first, then tagged with `📌 Interview term:` — that is the exact vocabulary an interviewer expects to hear. Every output shown was printed by a real run; the **Verified** section quotes it word for word. ## 1. Why This Even Matters — A Story First Picture a receptionist at a front desk. A visitor asks a question, and the receptionist says "one moment" and puts the visitor through to a specialist on the phone. From then on the visitor talks *directly* to the specialist: questions go to the specialist, answers come back from the specialist, and if the vi

The problem

Question presented to candidate: "Python has yield from. Isn't that just a shorter way of writing for x in sub: yield x? Explain what it really does, and when the difference matters."

What a strong answer should cover:

yield from <iterable> makes the current generator a pass-through for a sub-iterator: every value the sub-iterator produces goes straight to the outer caller, and the outer generator stays paused at that line until the sub-iterator is exhausted.
It is more than the for loop: send() values, throw() exceptions and close() are forwarded to the subgenerator, which the loop version cannot do (the loop only ever calls next()).
The value of the yield from expression is the subgenerator's return value, carried by StopIteration.value — so result = yield from sub() lets helper generators return results.
Typical uses: flattening recursive structures, splitting a large generator into smaller helper generators, and (historically) the generator-based coroutines that came before async/await. It was added by PEP 380 in Python 3.3.
CPython details: GET_YIELD_FROM_ITER + a SEND loop in the bytecode, and gi_yieldfrom pointing at the current delegate; yield from is a SyntaxError inside async def.

Code / implementation expected: Optional — a small delegating generator that captures a subgenerator's return value, or a recursive flatten.

generators
yield-from

Try it yourself

Sketch your approach before you read the solution. That is what the interview tests.

Stuck? Get a hint.

A short nudge toward the approach. It will not give the answer away.

Solution

Target Audience: Python developers who know what a generator is and want to understand delegation properly; interview candidates who will be asked "isn't it just a loop?". Difficulty: Medium Python version: All behaviour checked on CPython 3.11.17 and in the page runner (Pyodide 0.25.1, CPython 3.11.3); the bytecode comparison was also run on CPython 3.12.3.

How to read this doc: Each idea is explained in plain words first, then tagged with 📌 Interview term: — that is the exact vocabulary an interviewer expects to hear. Every output shown was printed by a real run; the Verified section quotes it word for word.

1. Why This Even Matters — A Story First

Picture a receptionist at a front desk. A visitor asks a question, and the receptionist says "one moment" and puts the visitor through to a specialist on the phone. From then on the visitor talks directly to