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Hand-written tutorials, ordered as a recommended learning path.

1. 61 Advanced Dataclasses Go beyond basic dataclass usage with post-init processing, field factories, inheritance, frozen instances, and custom serialization. 6 min read →
2. 62 Descriptors & Properties Understand Python's descriptor protocol, how properties work internally, and how to build reusable validation descriptors. 6 min read →
3. 63 itertools Recipes Master Python's itertools module with practical recipes for grouping, windowing, chaining, and processing iterables efficiently. 7 min read →
4. 64 Memory & GC Explore how CPython manages memory with reference counting, generational garbage collection, and practical tips to avoid memory leaks. 6 min read →
5. 65 Metaclasses Demystify Python metaclasses with practical examples. Learn how classes are created, when to use metaclasses, and real-world patterns. 5 min read →
6. 66 pathlib Guide Replace os.path with pathlib for cleaner, more readable file path handling in Python. Covers all essential operations with examples. 5 min read →
7. 67 __slots__ Optimization Learn how __slots__ reduces memory usage in Python classes, when to use it, and the trade-offs involved. 6 min read →
8. 68 asyncio Learn Python's asyncio — coroutines, tasks, event loops, async generators, and building concurrent I/O-bound applications. 3 min read →
9. 69 Dataclasses Master Python dataclasses — automatic __init__, __repr__, ordering, immutability, default factories, and post-init processing. 3 min read →
10. 70 Advanced Decorators Go beyond basic decorators: decorator factories, class decorators, functools.wraps, stacking behavior, and real-world patterns used in production Python code. 7 min read →
11. 71 Generators Deep Dive A thorough exploration of Python generators: yield mechanics, send and throw, generator pipelines, memory efficiency, coroutine basics, and practical patterns. 8 min read →
12. 72 Django ORM How Django QuerySets lazily build SQL, how to avoid N+1 queries with select_related and prefetch_related, and patterns to keep the ORM fast under real load. 4 min read →
13. 73 FastAPI DI How FastAPI's Depends system actually works, the lifecycle of dependencies, scoping with yield, and patterns for testable, layered FastAPI apps. 5 min read →
14. 74 asyncio Loop Understand how Python's asyncio event loop schedules coroutines, what await actually does, and how to avoid the classic mistakes that turn async code into a tangle of bugs. 5 min read →
15. 75 Decorators A practical tour of Python decorators: how they work under the hood, when to use them, and how to write decorators that preserve metadata, accept arguments, and stack cleanly. 5 min read →
16. 76 Logging How to set up Python logging properly: loggers vs handlers, structured logs, contextual fields, log levels that scale, and how to avoid the classic print-debug trap. 4 min read →
17. 77 MP vs Threads When to use threads, when to use processes, and why the GIL shapes both choices. A practical comparison with code, benchmarks, and patterns for real workloads. 5 min read →
18. 78 Async & Await A gentle introduction to Python's async and await — coroutines, the event loop, awaiting tasks, asyncio.gather for concurrency, and when async actually helps. 5 min read →
19. 79 Error Handling A practical guide to error handling in Python — catching specific exceptions, the else and finally clauses, raising and re-raising, custom exception types, and habits that lead to robust code. 5 min read →
20. 80 f-Strings A complete guide to Python f-strings — basic interpolation, format specifiers for numbers and dates, alignment and padding, debug syntax, and when to choose other formatting methods. 5 min read →