Python Caching with `functools.cache` and `lru_cache`
Learn how to speed up Python functions with functools.cache and lru_cache, when caching helps, and how to control cache size and eviction.
Learn Python programming from scratch
Learn how to speed up Python functions with functools.cache and lru_cache, when caching helps, and how to control cache size and eviction.
Learn to speed up file I/O and data processing in Python with buffering, binary modes, streaming, and memory-mapped files.
Learn which Python collection is fastest for your use case: list vs set vs dict vs deque, plus performance tips for sorting, filtering, and membership testing.
Learn to recognize and fix the most common Python anti-patterns that make code harder to read, test, and maintain.
Learn how to design Python modules that are easy to import, understand, and reuse across projects without causing unexpected side effects.
Learn how to use the strategy pattern in Python to make algorithms swappable at runtime, with practical examples using both classes and functions.
Learn how to refactor Python code safely using tests, small changes, and proven techniques that prevent introducing bugs during restructuring.
Apply safe refactoring techniques to a complete Python project, transforming messy code into clean, maintainable modules step by step.