Concurrent Numpy In Python
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Concurrent Numpy In Python
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Author : Jason Brownlee
language : en
Publisher: SuperFastPython.com
Release Date :
Concurrent Numpy In Python written by Jason Brownlee and has been published by SuperFastPython.com this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Concurrency in NumPy is not an afterthought * Discover matrix multiplication that is 2.7x faster. * Discover array initialization that is up to 3.2x faster. * Discover sharing copied arrays that is up to 516.91x faster. NumPy is how we represent arrays of numbers in Python. An entire ecosystem of third-party libraries has been developed around NumPy arrays, from machine learning and deep learning to image and computer vision and more. Given the wide use of NumPy, it is essential we know how to get the most out of our system when using it. We cannot afford to have CPU cores sit idle when performing mathematical operations on arrays. Therefore we must know how to correctly harness concurrency in NumPy, such as: * NumPy has multithreaded algorithms and functions built-in (using BLAS). * NumPy will release the infamous GIL so Python threads can run in parallel. * NumPy arrays can be shared efficiently between Python processes using shared memory. The problem is, no one is talking about how. Introducing: "Concurrent NumPy in Python". A new book designed to teach you how to bring concurrency to your NumPy programs in Python, super fast! You will get fast-paced tutorials showing you how to bring concurrency to the most common NumPy tasks. Including: * Parallel array multiplication, common math functions, matrix solvers, and decompositions. * Parallel array filling and parallel creation of arrays of random numbers. * Parallel element-wise array arithmetic and common array math functions * Parallel programs for working with many NumPy arrays with thread and process pools. * Efficiently share arrays directly, and copies of arrays between Python processes. Don't worry if you are new to NumPy programming or concurrency, you will also get primers on the background required to get the most out of this book, including: * The importance of concurrency when using NumPy and the cost of approaching it naively. * How to perform common NumPy operations and math functions. * How to install, query, and configure BLAS libraries for built-in multithreaded NumPy functions. * How to use Python concurrency APIs including threading, multiprocessing, and pools of workers. Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to your NumPy projects. Learn Python concurrency correctly, step-by-step.
Python Concurrency With Asyncio
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Author : Matthew Fowler
language : en
Publisher: Simon and Schuster
Release Date : 2022-03
Python Concurrency With Asyncio written by Matthew Fowler 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 2022-03 with Computers categories.
Learn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library. Use coroutines and tasks alongside async/await syntax to run code concurrently Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology It’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable. About the book Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance. What's inside Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code About the reader For intermediate Python programmers. No previous experience of concurrency required. About the author Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. Table of Contents 1 Getting to know asyncio 2 asyncio basics 3 A first asyncio application 4 Concurrent web requests 5 Non-blocking database drivers 6 Handling CPU-bound work 7 Handling blocking work with threads 8 Streams 9 Web applications 10 Microservices 11 Synchronization 12 Asynchronous queues 13 Managing subprocesses 14 Advanced asyncio
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 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.
Python Concurrent Futures Interview Questions
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Author : Jason Brownlee
language : en
Publisher: SuperFastPython.com
Release Date :
Python Concurrent Futures Interview Questions written by Jason Brownlee and has been published by SuperFastPython.com this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
How well do you know the ThreadPoolExecutor and ProcessPoolExecutor in Python? The concurrent.futures module provides the ability to launch parallel and concurrent tasks in Python using thread and process-based concurrency. Importantly, the ThreadPoolExecutor and ProcessPoolExecutor offer the same modern interface with asynchronous tasks, Future objects, and the ability to wait on groups of tasks. The concurrent.futures module with the ThreadPoolExecutor and ProcessPoolExecutor classes offers the best way to execute ad hoc tasks concurrently in Python, and few developers know about it, let alone how to use it well. * Do you know how to handle task results in the order tasks finish? * Do you know how to wait for the first task to fail? * Do you know how many workers are created by default? Discover 130+ interview questions and their answers on the concurrent.futures module. * Study the questions and answers and improve your skill. * Test yourself to see what you really know, and what you don't. * Select questions to interview developers on a new role. Prepare for an interview or test your ThreadPoolExecutor and ProcessPoolExecutor skills in Python today.
Advanced Python Automation
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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2024-10-26
Advanced Python Automation written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Computers categories.
"Advanced Python Automation: Build Robust and Scalable Scripts" is a comprehensive guide crafted to elevate your automation skills using Python, one of the most versatile programming languages available today. This book delves into the essential techniques and tools required to create sophisticated and efficient scripts, suitable for both beginners and experienced programmers. With its emphasis on practicality, the book methodically covers topics ranging from setting up a development environment to mastering error handling and debugging, ensuring you develop a strong foundation in Python automation. Throughout the chapters, readers will explore advanced techniques such as task scheduling, data collection, and interacting with APIs and web services. The book extends further into cutting-edge methods, including cloud resource management, machine learning integration, and serverless computing, enhancing your capability to build scalable and robust automation systems. By embracing both foundational and advanced concepts, this book equips you with the skills necessary to automate a wide range of tasks, improve productivity, and harness the full potential of Python in your automation projects.
Python End To End Data Analysis
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Author : Phuong Vothihong
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-05-31
Python End To End Data Analysis written by Phuong Vothihong 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 2017-05-31 with Computers categories.
Leverage the power of Python to clean, scrape, analyze, and visualize your data About This Book Clean, format, and explore your data using the popular Python libraries and get valuable insights from it Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. What You Will Learn Understand the importance of data analysis and master its processing steps Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy Clean and transform your data and apply advanced statistical analysis to create attractive visualizations Analyze images and time series data Mine text and analyze social networks Perform web scraping and work with different databases, Hadoop, and Spark Use statistical models to discover patterns in data Detect similarities and differences in data with clustering Work with Jupyter Notebook to produce publication-ready figures to be included in reports In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need! In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You'll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You'll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python's tools for supervised machine learning. The course provides you with highly practical content explaining data analysis with Python, from the following Packt books: Getting Started with Python Data Analysis. Python Data Analysis Cookbook. Mastering Python Data Analysis. By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights. Style and approach Learn Python data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. It offers you a useful way of analyzing the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of data analysis.
High Performance Python
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Author : Micha Gorelick
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-04-30
High Performance Python written by Micha Gorelick and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-30 with Computers categories.
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker
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.
Advanced Python Programming
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Author : Quan Nguyen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-25
Advanced Python Programming 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 2022-03-25 with Computers categories.
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge libraries Key FeaturesBenchmark, 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 learnWrite 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.