Stabilize iterator batching utility noisy edge lab
Medium Python arena: iterators, generators, laziness, and memory-safe batching
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Missing prerequisites: python-easy-iterator-batches-edge-lab
The initial iterator batching utility solution worked on clean data, but production-like noise now exposes weak assumptions. You are working inside a Python service repository, and the arena only clears when the result is safe, deterministic, and explainable.
Learn to apply iterators, generators, laziness, and memory-safe batching in a Python service repository while explaining the invariant, safety constraints, and hidden edge cases.
- Demonstrates iterators, generators, laziness, and memory-safe batching
- Handles the visible sample and hidden edge cases
- Keeps output deterministic and explainable
- Avoids unsafe dynamic execution
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