Overview

Unlock the full power of high-performance Python with Python Code Optimization Mastery: 80 PyPy and Numba Projects for JIT Acceleration, Type Hints, and Performance Benchmarking-your complete guide to writing faster, smarter, and more efficient code. Designed for beginners, intermediate developers, data scientists, and performance-driven engineers, this hands-on book breaks down the art of optimization through 80 real-world mini-projects that deliver immediate speedups. From JIT compilation with PyPy and Numba to profiling, caching, vectorization, and type-driven refactoring, you'll master techniques that cut execution time by 10×-100×. Explore core optimization concepts in a clear, practical way-no unnecessary theory, just actionable steps. Learn how to use tools like cProfile, timeit, line_profiler, and Memory Profiler to pinpoint bottlenecks, then apply targeted improvements using type hints, efficient data structures, algorithm redesign, concurrency, and parallelization. Inside, you'll discover: 80 hands-on projects that reinforce concepts through real performance boosts How PyPy's JIT engine speeds up loops, recursion, and heavy functions How Numba optimizes numerical code, simulations, and array operations Type hinting strategies that improve readability and static analysis Benchmarking workflows for reliable before-and-after comparisons Optimization patterns for APIs, scripts, data pipelines, and ML workflows Memory-safe techniques to reduce leaks, fragmentation, and overhead Best practices for writing production-ready, scalable, maintainable code Whether you're building faster APIs, optimizing data-heavy applications, improving simulation workflows, or preparing for high-performance computing roles, this book gives you the skills to compete at a pro level. If you want to master Python optimization with modern tools and real projects-not theory-this is the upgrade your coding career has been waiting for.

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