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.