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In this video, I dive deep into the **Lazy Loading pattern,** one of the simplest and most effective ways to make Python applications feel instantly responsive. I start with a painfully slow CSV-loading example and progressively improve it using **lazy evaluation**, **generators**, **caching**, **time-limited caching**, and even **background preloading**. Along the way, you’ll learn when (and when not) to use lazy loading, how it’s used in real-world libraries, and how to apply it cleanly in your own projects. By the end, you’ll understand how to avoid unnecessary work, reduce memory usage, and make your Python code dramatically faster without overcomplicating your design.

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🔥 GitHub Repository: https://git.arjan.codes/2025/lazy.

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🔖 Chapters:
0:00 Intro
0:48 A Bit of History (and Where You Already See It)
1:53 The Naive (Eager) Approach
2:29 Lazy Loading
3:38 Simple Caching with functools.cache
5:15 Adding a Remote Operation
9:24 Now With Custom Caching
11:13 Lazy Streaming with Generators
15:20 Smarter Preloading
17:21 When (and When Not) to Use Lazy Loading
18:08 Common Mistakes with Lazy Loading
18:52 Final Thoughts

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The Lazy Loading Pattern: How to Make Python Programs Feel Instant