High Performance Python - Info and Reading Options

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Intro -- Copyright -- Table of Contents -- Foreword -- Preface -- Who This Book Is For -- Who This Book Is Not For -- What You'll Learn -- Python 3 -- Changes from Python 2.7 -- License -- How to Make an Attribution -- Errata and Feedback -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Understanding Performant Python -- The Fundamental Computer System -- Computing Units -- Memory Units -- Communications Layers -- Putting the Fundamental Elements Together -- Idealized Computing Versus the Python Virtual Machine -- So Why Use Python? -- How to Be a Highly Performant Programmer -- Good Working Practices -- Some Thoughts on Good Notebook Practice -- Getting the Joy Back into Your Work -- Chapter 2. Profiling to Find Bottlenecks -- Profiling Efficiently -- Introducing the Julia Set -- Calculating the Full Julia Set -- Simple Approaches to Timing-print and a Decorator -- Simple Timing Using the Unix time Command -- Using the cProfile Module -- Visualizing cProfile Output with SnakeViz -- Using line_profiler for Line-by-Line Measurements -- Using memory_profiler to Diagnose Memory Usage -- Introspecting an Existing Process with PySpy -- Bytecode: Under the Hood -- Using the dis Module to Examine CPython Bytecode -- Different Approaches, Different Complexity -- Unit Testing During Optimization to Maintain Correctness -- No-op profile Decorator -- Strategies to Profile Your Code Successfully -- Wrap-Up -- Chapter 3. Lists and Tuples -- A More Efficient Search -- Lists Versus Tuples -- Lists as Dynamic Arrays -- Tuples as Static Arrays -- Wrap-Up -- Chapter 4. Dictionaries and Sets -- How Do Dictionaries and Sets Work? -- Inserting and Retrieving -- Deletion -- Resizing -- Hash Functions and Entropy -- Dictionaries and Namespaces -- Wrap-Up

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