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Key benefits

Benchmark, profile, and accelerate Python programs using optimization tools

Scale applications to multiple processors with concurrent programming

Make applications robust and reusable using effective design patterns

Description

Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level. This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models. The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming. You'll also understand the common problems that cause undesirable behavior in concurrent programs. Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable. By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.

What you will learn

Write efficient numerical code with NumPy, pandas, and Xarray

Use Cython and Numba to achieve native performance

Find bottlenecks in your Python code using profilers

Optimize your machine learning models with JAX

Implement multithreaded, multiprocessing, and asynchronous programs

Solve common problems in concurrent programming, such as deadlocks

Tackle architecture challenges with design patterns

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Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

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Total € 109.97

Krishnan Raghavan May 23, 2022

Python is a programming language that is mostly used for fast prototyping and software development both by beginners for its easy-to-learn syntax as well as by experienced programmers. It's not a language preferred when it comes to scaling or speed. Most programmers prefer other programming languages for this. The author of this book has tried to show that this is not really necessary and even Python has enough tools and support for optimizing and scaling.This book is best utilized by intermediate to expert programmers who are looking to scale up their applications and make them more robust.What I learnt from this book:1. How to identify sections of the code that is slowing down and increasing the execution time and how to optimize and increase the performance of the code using data structures, algorithms and third-party tools efficiently.2. Fast Array Operations with NumPy, Pandas and Xarray to implement fast numerical algorithms.3. Improve performance with Cython and other compilers like Numba Framework that can be used to compile Python code.4. Tools and Libraries that help implement parallelism and concurrency for web requests, Image processing tasks, deadlock, and Race Conditions kinds of situations.5. Factory Design Patterns and benefits of using Factory design patterns instead of direct object instantiation.6. How to implement Concurrency and Parallel Programming on multi-core processors and GPUs. Very useful for data science projects.At the end of each chapter, the author has provided a summary that helps in revising the chapter and questions that will test your knowledge about the chapter. Wherever applicable, additional material for reading is suggested.This book has helped me understand topics of which I was not aware previously. Kudos to Quan Nguyen for the effort in bringing out this excellent book. Thank you very much, Quan Nguyen.

Amazon Verified review

Ryan Zurrin Jun 10, 2022

The media could not be loaded. Advanced Python Programming 2nd edition by Quan Nguyen. Over 500 pages of pythonic knowledge that I consider a must know for anyone using python programming professionally. As a fulltime student working as a researcher, researching Breast Cancer detection using machine learning, I use python daily and this book has been so helpful for me in developing and strengthening areas I was previously lacking.Another one of the things I loved about this book is the example they use throughout the book, a simple particle simulator. If you love physics as I do, you will fall in love with this example, and how it grows throughout the book, getting better and better as we learn how to use more powerful techniques to achieve the best performance from whatever we are building.Advanced Python Programming 2nd Edition also covers topics like Machine Learning, just the basics, but it is a good start. It gets into how to use Concurrency and parallel processing, what the differences are between them, and what some of the common mistakes us beginners usually face when first starting out in these tough areas of python programming. This book is truly a toolbox of techniques for us to use, which can help us to become masters of this unique and diverse programming language.There is a whole section on Design Patterns which was recently so helpful for me in my research. I had to build a singleton class and had no idea what that even was, and I was able to look it up in this book and learn exactly what I needed to do to implement one on my own. Other design patterns covered are things like the Factory Pattern, the Builder Pattern, Creational Patterns – for which the Singleton was a part of, the Adapter Pattern, the Decorator Pattern, Bridge Pattern and more. It really gets into the nitty gritty of how to properly program in python.So, if you are programming in python professionally already or just looking for a book to boost up what you already know this book is for you. It does not get into the basics of python so it starts out assuming you already have that experience so if you never programmed in python before you may want to start someplace else before trying this book, but I think it is a great book for anyone who plans to use python on a regular basis.Packt books has done it again and brought us another great technical book by another great author, Quan Nguyen who does wonders in this book. Advanced Python Programming 2nd edition is an amazing book so I’d say pick it up if you can, it will not disappoint.

Amazon Verified review

Jaime Sierra Silva (Consignment) Nov 24, 2022

Python is a very versatile language, in general, one thing is to learn a language and another thing is to use it in the most optimal way, so that the software that is developed is of a performance for its users and the structure in which it is located.In "Advanced Python Programming", the author delves into techniques and practices to optimize programs written in Python, so that it uses optimally the resources at its disposal and fulfills its objectives in the best way. The book takes us through the different aspects to consider to improve our codes, the only goal is to be a better Python developer.

Amazon Verified review

jml May 13, 2022

Advanced Python Programming, Second Edition offers a variety of in-depth coverage in its roughly 550 pages. The book starts off with optimization techniques, useful to all Python programmers but especially those focusing on mathematical specialties (NumPy, Pandas, and Xarray). There’s also a neat introduction to machine learning, which leads smoothly into a treatment of parallel and threaded processing. Deadlocks, thread starvation, and the global interpreter lock are explained in a context useful to Python professionals. Finally, several in-depth chapters are devoted to the care and feeding of various design patterns and factories. If you're not comfortable with those functions when you start the book, you probably will be once you finish it. The author, Quan Nguyen, has done a solid job of presenting the material without overwhelming the reader, using code examples, projects, and diagrams where appropriate. Chapters are well-paced making for a very readable book. As the title indicates, this is not a beginner’s guide or a Python tutorial, but experienced programmers will definitely pick up some new knowledge from a thorough reading.

Amazon Verified review

Jaelyn Jensen May 20, 2022

First impression was "Even though it's pretty long (~550 pages), this will be an easy read, because I already have substantial experience with Design Patterns in C++."Well, it was a lot more than just a Design Patterns in Python3 book. I wasn't very far into the book when my hubris became embarrassingly obvious. The author didn't even start in on the Design Patterns stuff until nearly 2/3rds of the way through the book. Well, that part was a comparably easy read, partially because using the GoF patterns in Python is a little easier than in C++. Well, mostly, anyway. Python3 makes using most of the GoF patterns pretty straightforward.The first two-thirds of the book were more challenging (and informative) than I expected. The author takes a deep dive into various ways to optimize and improve your code. Of course, he started off with the observation that the choice of algorithm totally dominates that process. But I certainly learned a lot about Python3 (and various library) optimizations.I got introduced to a lot of different things in Python3 that I didn't know existed, and got to review some things I had not encountered in a long time. In a way, learning Python is a lot like learning Java, in the sense that the syntax of the language is pretty easy to understand. The problem is that learning the proper syntax rules puts you at about 5% of the way to being a proficient programmer. Learning the "Pythonic" way of doing stuff (like making appropriate use of things like tuples and dictionaries) gets you to maybe 15%. Learning a huge body of existing libraries gets you to about 80%, after which incremental gains get more challenging.I think that this book can get you to almost 100% (actually, 100% might not really be achievable in any discipline -- or maybe the field just continues to expand) of the way to production programming. Well, this book and a few years of experience. If you already have a bit of Python3 experience, then this book is a great follow-on to get your Python3 chops to the next level.I liked the way the assessment questions were used, and I appreciated the coverage of the assessment answers at the end. The assessments were well-done.I can think of only two things to suggest for improvement. The first would be to make this into 3 books instead of one huge tome. That might have made it somewhat less overwhelming The second would be to provide an overview of how to use the various help facilities in Python. Although by the time you really need this book, you probably already have that 2nd part figured out.This book will be one that I return to often for reference.

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Advanced Python Programming: Accelerate your Python programs using proven techniques and design patterns , Second Edition

What do you get with Print?