Скачать или смотреть Python Deep Dive For Sleep (Part 3: Generators and Iterators)

Python Iterators & Generators: The Hidden Machinery Behind `for` Loops | Deep Dive

Think you know how `for item in my_list:` works? Think again. Join us for an eye-opening journey into one of Python's most elegant and sophisticated systems—the iteration protocol that powers everything from simple loops to complex asynchronous programming.

🎯 Perfect For:
✅ Python developers who want to understand the "why" behind iteration
✅ Technical interview preparation (iterator questions are everywhere!)
✅ Performance optimization and memory-conscious programming
✅ Anyone building data processing pipelines or async applications
✅ Developers transitioning from other languages who want to "think Pythonically"

💡 Key Insights You'll Gain:
See exactly how `iter()` and `next()` orchestrate every `for` loop
Understand why `LOAD_FAST` makes local variables faster (with proof!)
Learn to build memory-efficient data processing pipelines
Master the patterns that separate junior from senior Python developers
Discover the elegant engineering behind Python's most-used features

🔧 Practical Skills:
Debug iteration issues using the protocol directly
Choose between generators, comprehensions, and iterators confidently
Build custom iterators for complex use cases
Optimize memory usage in data-heavy applications
Avoid the classic pitfalls that cause production bugs

🚀 Advanced Topics Covered:
Generator-based coroutines and the path to `async`/`await`
Lazy evaluation strategies for large datasets
Iterator exhaustion and reusability patterns
The `send()` method and bidirectional generators
Performance profiling of different iteration approaches

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*📚 Essential Resources:*
PEP 234 (Iterators): https://peps.python.org/pep-0234/
PEP 255 (Simple Generators): https://peps.python.org/pep-0255/
PEP 380 (yield from): https://peps.python.org/pep-0380/
Python Data Model: https://docs.python.org/3/reference/d...

*🎬 Related Deep Dives:*
The Python Interpreter (how bytecode powers iteration)
Python Memory Management (why lazy evaluation matters)
Async/Await Deep Dive (the modern evolution of generators)

*⏰ Timestamps:*
0:00 Introduction: Beyond Basic `for` Loops
2:15 Deconstructing the `for` Loop Protocol
6:30 Iterables vs Iterators: The Critical Distinction
10:45 Why Iterators Are Themselves Iterable
13:20 Class-Based Iterators: Maximum Control
17:40 Generator Functions: The Elegant Solution
21:10 `yield` vs `return`: A Tale of Two Keywords
24:30 Memory Efficiency & Lazy Evaluation
27:50 List Comprehensions vs Generator Expressions
30:15 Advanced Techniques: `send()` and `yield from`
32:45 Common Pitfalls & Safe Patterns
34:20 Conclusion

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