nach der Bestellung gedruckt Neuware - Printed after ordering - Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey Features:Benchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook 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 XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho 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.

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Detalles bibliogr�ficos

T�tulo

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

Editor

Packt Publishing

Fecha de publicaci�n

2022

Idioma

Ingl�s

ISBN 10

1801814015

ISBN 13

9781801814010

Encuadernaci�n

Taschenbuch

Edici�n

2� Edici�n

Estado

Neu

Cat�logos de vendedores

Acerca de

Sinopsis

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.

Acerca del autor

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.

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