Generators and Iterators

A generator is a function that produces values one at a time instead of building an entire list in memory. It uses yield instead of return. This is how Python handles large datasets without running out of memory.

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This concept is covered in two parts:

1. Part 1: Iterators — The iterator protocol, memory efficiency, file reading, and itertools basics
2. Part 2: Generators — yield, generator expressions, pipelines, yield from, and send()/throw()

Practice

• Level 2 / 07 Config File Merger
• Module 05 Async Python — generators are the foundation of async
• Module 07 Data Analysis — processing large datasets
• Elite Track / 01 Algorithms Complexity Lab

Quick check: Take the quiz (coming soon)

Review: Flashcard decks Practice reps: Coding challenges

Further Reading

• Generator expressions (Python docs)
• itertools — Functions creating iterators
• PEP 255 — Simple Generators
• PEP 380 — Syntax for Delegating to a Subgenerator (yield from)

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