High Performance Python (2025 Edition) – Practical Performant Programming for Humans

 

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⚡ High Performance Python (2025 Edition) – Practical Performant Programming for Humans

📘 Title: High Performance Python: Practical Performant Programming for Humans
👨‍💻 Authors: Micha Gorelick & Ian Ozsvald
🏢 Publisher: O’Reilly Media
📅 Year: 2025
📥 👉 DOWNLOAD Free PDF NOW

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🚀 Master the Art of Writing Fast and Efficient Python Code

Your Python code might run correctly — but does it run fast enough?

In the latest 2025 edition of “High Performance Python: Practical Performant Programming for Humans”, experts Micha Gorelick and Ian Ozsvald show how to make your Python applications leaner, faster, and more scalable — without sacrificing readability or developer happiness.

This edition has been fully updated for Python 3.12+, introducing new optimization tools, concurrency models, and memory profiling techniques that match today’s data-intensive workloads.

If you work with big data, numerical computing, or ML pipelines, this is the definitive guide to Python performance optimization.

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📚 What You’ll Learn Inside

🧩 1. Profiling and Measuring Performance

• Learn how to profile CPU and memory usage effectively
• Identify slow code paths using cProfile, line_profiler, and memory_profiler
• Visualize bottlenecks with flame graphs and performance dashboards

⚙️ 2. Writing Faster Python

• Choose the right data structures for speed and efficiency
• Optimize loops, comprehensions, and generators
• Understand Python’s internals (bytecode, GIL, memory model)
• Refactor Python code for minimal overhead

🧠 3. Parallelism and Concurrency

• Harness true parallelism with multiprocessing, asyncio, and threading
• Learn when to use concurrent.futures vs. async I/O
• Build scalable systems using Ray and Dask for distributed computing

🧮 4. Numerical and Scientific Computing

• Accelerate math-heavy workloads with NumPy, Numba, and Cython
• Optimize vectorized operations and memory layout
• Offload computations to GPU using CuPy and PyTorch
• Integrate with C/C++ extensions for critical speedups

💾 5. Working with Big Data

• Handle large datasets efficiently using Polars and Vaex
• Improve I/O with memory mapping, chunking, and streaming
• Build fast data pipelines with Apache Arrow and Parquet

🧰 6. Real-World Performance Engineering

• Case studies: optimizing data science workflows, AI models, and APIs
• Debugging performance regressions and scaling in production
• Balancing readability, maintainability, and raw speed

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👨‍💻 Who This Book Is For

✅ Data scientists and ML engineers handling large datasets
✅ Backend developers optimizing APIs and real-time services
✅ Quantitative analysts and HPC professionals
✅ Python power users seeking expert-level performance tuning
✅ Researchers building fast numerical or simulation code

💡 No C background needed — this book teaches performance without forcing you to abandon Pythonic style.

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💡 Why This Book Stands Out

• 🧩 Written by two leading Python performance experts
• ⚙️ Combines theory + practical tools used in real-world projects
• 🧠 Updated for Python 3.12, new async features, and high-performance libraries
• 📊 Includes visual profiling and performance testing frameworks
• 🚀 Ideal for developers working with AI, data pipelines, and scientific computing

🎯 Stop guessing why your code is slow — learn to measure, optimize, and scale Python like a professional.

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📌 “Correct code works. High-performance code wins.” — Micha Gorelick & Ian Ozsvald

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