Concurrent And Parallel Programming In Python
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Parallel And High Performance Programming With Python
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Author : Fabio Nelli
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2023-04-13
Parallel And High Performance Programming With Python written by Fabio Nelli and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-13 with Computers categories.
Unleash the capabilities of Python and its libraries for solving high performance computational problems. KEY FEATURES ● Explores parallel programming concepts and techniques for high-performance computing. ● Covers parallel algorithms, multiprocessing, distributed computing, and GPU programming. ● Provides practical use of popular Python libraries/tools like NumPy, Pandas, Dask, and TensorFlow. DESCRIPTION This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing. The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing. The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them. By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead. WHAT WILL YOU LEARN ● Build faster, smarter, and more efficient applications for data analysis, machine learning, and scientific computing ● Implement parallel algorithms in Python ● Best practices for designing, implementing, and scaling parallel programs in Python WHO IS THIS BOOK FOR? This book is aimed at software developers who wish to take their careers to the next level by improving their skills and learning about concurrent and parallel programming. It is also intended for Python developers who aspire to write fast and efficient programs, and for students who wish to learn the fundamentals of parallel computing and its practical uses. TABLE OF CONTENTS 1. Introduction to Parallel Programming 2. Building Multithreaded Programs 3. Working with Multiprocessing and mpi4py Library 4. Asynchronous Programming with AsyncIO 5. Realizing Parallelism with Distributed Systems 6. Maximizing Performance with GPU Programming using CUDA 7. Embracing the Parallel Computing Revolution 8. Scaling Your Data Science Applications with Dask 9. Exploring the Potential of AI with Parallel Computing 10. Hands-on Applications of Parallel Computing
Concurrent And Parallel Programming In Python
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Author : Parker Dean
language : en
Publisher:
Release Date : 2025-10-09
Concurrent And Parallel Programming In Python written by Parker Dean and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-09 with Computers categories.
Elevate your Python skills with this hands-on guide to concurrent and parallel programming, empowering beginners to advanced developers to optimize code for speed and efficiency. Master multithreading for IO-bound tasks, asyncio for scalable asynchronous operations, and multiprocessing to bypass the GIL for CPU-intensive workloads. Through practical examples, real-world projects like web scrapers, data pipelines, and servers, and best practices for error handling, profiling, and scaling, build high-performance applications for web development, data processing, automation, and more.
Mastering Concurrency In Python
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Author : Quan Nguyen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-27
Mastering Concurrency In Python written by Quan Nguyen and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-27 with Computers categories.
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems Key FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book Description Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming. Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples. By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language What you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is for This book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
Mastering Concurrency And Parallel Programming Unlock The Secrets Of Expert Level Skills Pdf
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Author : Larry Jones
language : en
Publisher: Walzone Press
Release Date : 2025-03-18
Mastering Concurrency And Parallel Programming Unlock The Secrets Of Expert Level Skills Pdf written by Larry Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-18 with Computers categories.
Unlock the full potential of modern computing with "Mastering Concurrency and Parallel Programming: Unlock the Secrets of Expert-Level Skills." Designed for experienced programmers eager to enhance their expertise, this comprehensive guide delves into the intricate world of concurrency and parallelism. As computing power becomes more sophisticated, understanding and applying these concepts are crucial for crafting efficient and scalable software solutions. This book stands as an essential resource, offering in-depth coverage of foundational principles and advanced techniques to navigate the complexities of multi-core processors and distributed systems. Within its pages, readers will explore the core strategies that underpin effective thread management, synchronization, and task parallelism, gaining insights into both lock-based and lock-free algorithms. Practical case studies, enriched with real-world examples, provide a clear pathway to mastering intricate concurrency patterns, memory models, and the debugging tools essential for robust concurrent application development. The inclusion of advanced topics like transactional memory and speculative execution keeps readers at the forefront of technological innovation, equipping them to tackle cutting-edge challenges with confidence and precision. Whether you're optimizing for performance or ensuring software reliability, "Mastering Concurrency and Parallel Programming" is a must-read that empowers you to transcend traditional programming boundaries. With its elegant prose and structured approach, this book transforms complex subjects into accessible, actionable knowledge, making it an indispensable companion for any programmer ready to elevate their craft and stay ahead in the rapidly evolving world of concurrent computing.
Parallel And Concurrent Programming With Python 1
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Author :
language : en
Publisher:
Release Date : 2019
Parallel And Concurrent Programming With Python 1 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Parallel programming unlocks a program's ability to execute multiple instructions simultaneously, increases the overall processing throughput, and is key to writing faster and more efficient applications. Curious about how parallel programming works in the real world? In this course, join instructors Barron and Olivia Stone as they introduce the basics of parallel programming in Python, providing the foundational knowledge you need to write more efficient, performant code. Barron and Olivia explain concepts like threading and mutual exclusion in a fun and informative way, relating them to everyday activities you perform in the kitchen. To cement the ideas, they demo them in action using Python. Each lesson is short and practical, driving home the theory with hands-on techniques.
Efficient And Parallel Python Programming
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Author : Matthew D Passmore
language : en
Publisher: Independently Published
Release Date : 2024-05-28
Efficient And Parallel Python Programming written by Matthew D Passmore and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-28 with Computers categories.
Unlock the full potential of Python with this comprehensive guide to efficient and parallel programming. In today's fast-paced world, building scalable, responsive, and high-performance applications is essential. This practical handbook provides the tools and techniques you need to master concurrent development and take your Python skills to the next level. Inside, you'll discover: Foundations of Concurrency and Parallelism: Understand the core concepts and differences between concurrent and parallel programming. Learn how to choose the right approach for your specific needs. Advanced Python Techniques: Dive into Python's threading, multiprocessing, and asynchronous programming features. Master the use of libraries such as concurrent.futures, asyncio, and more. Real-World Applications: Explore detailed examples and case studies demonstrating how to apply these techniques in real-world scenarios, from web development to data processing. Performance Optimization: Learn how to profile and optimize your code for maximum efficiency. Discover best practices for avoiding common pitfalls and bottlenecks. Hands-On Projects: Put theory into practice with hands-on projects designed to reinforce your learning and build your confidence in applying concurrent and parallel programming techniques. . Whether you're a seasoned developer looking to refine your skills or a newcomer eager to learn about concurrent development, "Efficient and Parallel Python Programming" offers a clear, practical roadmap for building fast, scalable, and robust applications. Embrace the future of Python programming and transform your development workflow with this essential handbook.
Advanced Python Programming
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Author : Dr. Gabriele Lanaro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-02-28
Advanced Python Programming written by Dr. Gabriele Lanaro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Computers categories.
Create distributed applications with clever design patterns to solve complex problems Key FeaturesSet up and run distributed algorithms on a cluster using Dask and PySparkMaster skills to accurately implement concurrency in your codeGain practical experience of Python design patterns with real-world examplesBook Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: Python High Performance - Second Edition by Gabriele LanaroMastering Concurrency in Python by Quan NguyenMastering Python Design Patterns by Sakis KasampalisWhat you will learnUse NumPy and pandas to import and manipulate datasetsAchieve native performance with Cython and NumbaWrite asynchronous code using asyncio and RxPyDesign highly scalable programs with application scaffoldingExplore abstract methods to maintain data consistencyClone objects using the prototype patternUse the adapter pattern to make incompatible interfaces compatibleEmploy the strategy pattern to dynamically choose an algorithmWho this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
Concurrent Programming In Python
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Author : Mithun Lakshmanswamy
language : en
Publisher:
Release Date : 2018
Concurrent Programming In Python written by Mithun Lakshmanswamy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"In this course, you will skill-up with techniques related to various aspects of concurrent programming in Python, including common thread programming techniques and approaches to parallel processing. Filled with examples, this course will show you all you need to know to start using concurrency in Python. You will learn about the principal approaches to concurrency that Python has to offer, including libraries and tools needed to exploit the performance of your processor. Learn the basic theory and history of parallelism and choose the best approach when it comes to parallel processing. After taking this course you will have gained an in-depth knowledge of using threads and processes with the help of real-world examples."--Resource description page.
Mastering Python Concurrency And Parallelism Unlock The Secrets Of Expert Level Skills
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Author : Larry Jones
language : en
Publisher: Walzone Press
Release Date : 2025-03-05
Mastering Python Concurrency And Parallelism Unlock The Secrets Of Expert Level Skills written by Larry Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-05 with Computers categories.
Unlock the full potential of your Python programming with "Mastering Python Concurrency and Parallelism: Unlock the Secrets of Expert-Level Skills." This comprehensive guide is crafted for experienced developers ready to elevate their expertise in concurrent and parallel computing. Through detailed exploration of threading, asyncio, and multiprocessing, you'll gain the insights needed to optimize your software for today's multi-core processors, ensuring peak performance and efficiency in your applications. Navigate through the nuanced world of Python concurrency with expertly organized chapters covering essential concepts, real-world applications, and advanced techniques. From demystifying the Global Interpreter Lock (GIL) to designing sophisticated concurrent data structures, this book offers unparalleled clarity and practical knowledge. Each chapter builds on the previous one, providing a seamless learning curve that empowers you to master the intricacies of writing robust, scalable concurrent code. Whether you're developing high-demand web servers, crafting precise financial models, or engineering responsive IoT systems, this book equips you with the tools to succeed. Real-world case studies and best practices accentuate the theoretical, allowing you to apply concepts to your unique challenges. Redefine your development capabilities and achieve new heights in software performance with this essential resource for mastering concurrency in Python.
Fast Python
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Author : Tiago Antao
language : en
Publisher: Simon and Schuster
Release Date : 2023-07-04
Fast Python written by Tiago Antao and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.
Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you’ll see how to optimize the whole system, from code to architecture. What’s Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antão is one of the co-authors of Biopython, a major bioinformatics package written in Python. Table of Contents: PART 1 - FOUNDATIONAL APPROACHES 1 An urgent need for efficiency in data processing 2 Extracting maximum performance from built-in features 3 Concurrency, parallelism, and asynchronous processing 4 High-performance NumPy PART 2 - HARDWARE 5 Re-implementing critical code with Cython 6 Memory hierarchy, storage, and networking PART 3 - APPLICATIONS AND LIBRARIES FOR MODERN DATA PROCESSING 7 High-performance pandas and Apache Arrow 8 Storing big data PART 4 - ADVANCED TOPICS 9 Data analysis using GPU computing 10 Analyzing big data with Dask