Python High Performance Programming -- Table of Contents -- Python High Performance Programming -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Benchmarking and Profiling -- Designing your application -- Writing tests and benchmarks -- Timing your benchmark -- Finding bottlenecks with cProfile -- Profile line by line with line_profiler -- Optimizing our code -- The dis module -- Profiling memory usage with memory_profiler -- Performance tuning tips for pure Python code -- Summary -- 2. Fast Array Operations with NumPy -- Getting started with NumPy -- Creating arrays -- Accessing arrays -- Broadcasting -- Mathematical operations -- Calculating the Norm -- Rewriting the particle simulator in NumPy -- Reaching optimal performance with numexpr -- Summary -- 3. C Performance with Cython -- Compiling Cython extensions -- Adding static types -- Variables -- Functions -- Classes -- Sharing declarations -- Working with arrays -- C arrays and pointers -- NumPy arrays -- Typed memoryviews -- Particle simulator in Cython -- Profiling Cython -- Summary -- 4. Parallel Processing -- Introduction to parallel programming -- The multiprocessing module -- The Process and Pool classes -- Monte Carlo approximation of pi -- Synchronization and locks -- IPython parallel -- Direct interface -- Task-based interface -- Parallel Cython with OpenMP -- Summary -- Index.