Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Birmingham, [United Kingdom]
Packt Publishing
2022
|
| Edition: | Second edition. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9781801814010/?ar |
| Summary: | Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge libraries Key Features 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 Book 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 Who this book is for This book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects. |
| Physical Description: | 1 Online-Ressource (606 pages) illustrations |
| ISBN: | 9781801817776 1801817774 9781801814010 |
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| spelling | Nguyen, Quan VerfasserIn aut Advanced Python programming Quan Nguyen Second edition. Birmingham, [United Kingdom] Packt Publishing 2022 1 Online-Ressource (606 pages) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge libraries Key Features 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 Book 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 Who this book is for This book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects. Python (Computer program language) Application software Development Python (Langage de programmation) Logiciels d'application ; Développement Application software ; Development |
| spellingShingle | Nguyen, Quan Advanced Python programming Python (Computer program language) Application software Development Python (Langage de programmation) Logiciels d'application ; Développement Application software ; Development |
| title | Advanced Python programming |
| title_auth | Advanced Python programming |
| title_exact_search | Advanced Python programming |
| title_full | Advanced Python programming Quan Nguyen |
| title_fullStr | Advanced Python programming Quan Nguyen |
| title_full_unstemmed | Advanced Python programming Quan Nguyen |
| title_short | Advanced Python programming |
| title_sort | advanced python programming |
| topic | Python (Computer program language) Application software Development Python (Langage de programmation) Logiciels d'application ; Développement Application software ; Development |
| topic_facet | Python (Computer program language) Application software Development Python (Langage de programmation) Logiciels d'application ; Développement Application software ; Development |
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