What Most Python Developers Miss About Generators
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Most Python developers think generators are just about saving memory. That’s only a small part of the story.
In this video, I show how generators give you control over when work happens, and how you can use them to build powerful data pipelines, handle backpressure, enable two-way communication, and even work with async streams.
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🔖 Chapters:
0:00 Intro
0:44 What are Generators?
1:44 Step 1: From Strings to Structured Data
6:36 Sponsored Section (recall.it)
9:08 Step 2: Pipelines with Function Composition
13:15 Step 3: Backpressure — Why This Scales
15:08 Step 4: Two-Way Communication with send()
17:52 Bonus: Generators Can Return a Value
19:08 Step 5: Async Generators
22:58 Final Thoughts
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