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Author: Jason Brownlee
Publisher: SuperFastPython.com
ISBN:
Category : Computers
Languages : en
Pages : 422
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Book Description
File I/O can be faster in Python when using concurrency. * Discover how to write files 3x faster with processes * Discover how to read files 3x faster with processes and threads * Discover how to unzip files 4x faster with processes and threads File I/O stands for File Input/Output, referring to the process of reading data from and writing data to files on a storage device like a hard drive. Studying how to bring concurrency to file I/O is critical for Python developers. Adding concurrency into your file I/O tasks, you can unlock the full potential of modern computer hardware, making your applications more efficient and capable of handling large workloads. The problem is, there is no silver bullet. Each program and each task is different and unique. We cannot know which approach to Python concurrency will give good or even the best performance. Therefore in addition to learning how to perform file I/O operations concurrently, Python developers must learn how to benchmark a suite of different approaches to implementing file I/O operations concurrently. Introducing: "Concurrent File I/O in Python". A new book designed to teach you how to bring concurrency to your file I/O tasks in Python, super fast! You will get rapid-paced tutorials showing you how to bring concurrency to the most common file I/O tasks. Including: * How to perform file I/O operation in the background. * How to concurrently read files from disk and write files to disk. * How to concurrently delete files from disk. * How to concurrently copy, move, and rename files on disk. * How to efficiently append files on disk. * How to concurrently zip files and unzip files on disk. Don't worry if you are new to file I/O or concurrency, you will also get primers on the background required to get the most out of this book, including: * The importance of concurrency for high-performance file I/O. * How to perform common file I/O operations in Python. * How to use Python concurrency APIs including threading, multiprocessing, and asyncio. * How to perform file I/O with coroutines in asyncio using the aiofiles library. * How to use programming patterns for concurrent file I/O. Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to file I/O tasks. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.
Author: Jason Brownlee
Publisher: SuperFastPython.com
ISBN:
Category : Computers
Languages : en
Pages : 422
Get Book Here
Book Description
File I/O can be faster in Python when using concurrency. * Discover how to write files 3x faster with processes * Discover how to read files 3x faster with processes and threads * Discover how to unzip files 4x faster with processes and threads File I/O stands for File Input/Output, referring to the process of reading data from and writing data to files on a storage device like a hard drive. Studying how to bring concurrency to file I/O is critical for Python developers. Adding concurrency into your file I/O tasks, you can unlock the full potential of modern computer hardware, making your applications more efficient and capable of handling large workloads. The problem is, there is no silver bullet. Each program and each task is different and unique. We cannot know which approach to Python concurrency will give good or even the best performance. Therefore in addition to learning how to perform file I/O operations concurrently, Python developers must learn how to benchmark a suite of different approaches to implementing file I/O operations concurrently. Introducing: "Concurrent File I/O in Python". A new book designed to teach you how to bring concurrency to your file I/O tasks in Python, super fast! You will get rapid-paced tutorials showing you how to bring concurrency to the most common file I/O tasks. Including: * How to perform file I/O operation in the background. * How to concurrently read files from disk and write files to disk. * How to concurrently delete files from disk. * How to concurrently copy, move, and rename files on disk. * How to efficiently append files on disk. * How to concurrently zip files and unzip files on disk. Don't worry if you are new to file I/O or concurrency, you will also get primers on the background required to get the most out of this book, including: * The importance of concurrency for high-performance file I/O. * How to perform common file I/O operations in Python. * How to use Python concurrency APIs including threading, multiprocessing, and asyncio. * How to perform file I/O with coroutines in asyncio using the aiofiles library. * How to use programming patterns for concurrent file I/O. Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to file I/O tasks. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.
Author: Tim Peierls
Publisher: Pearson Education
ISBN: 0132702258
Category : Computers
Languages : en
Pages : 428
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Book Description
Threads are a fundamental part of the Java platform. As multicore processors become the norm, using concurrency effectively becomes essential for building high-performance applications. Java SE 5 and 6 are a huge step forward for the development of concurrent applications, with improvements to the Java Virtual Machine to support high-performance, highly scalable concurrent classes and a rich set of new concurrency building blocks. In Java Concurrency in Practice, the creators of these new facilities explain not only how they work and how to use them, but also the motivation and design patterns behind them. However, developing, testing, and debugging multithreaded programs can still be very difficult; it is all too easy to create concurrent programs that appear to work, but fail when it matters most: in production, under heavy load. Java Concurrency in Practice arms readers with both the theoretical underpinnings and concrete techniques for building reliable, scalable, maintainable concurrent applications. Rather than simply offering an inventory of concurrency APIs and mechanisms, it provides design rules, patterns, and mental models that make it easier to build concurrent programs that are both correct and performant. This book covers: Basic concepts of concurrency and thread safety Techniques for building and composing thread-safe classes Using the concurrency building blocks in java.util.concurrent Performance optimization dos and don'ts Testing concurrent programs Advanced topics such as atomic variables, nonblocking algorithms, and the Java Memory Model
Author: Aquiles Carattino
Publisher:
ISBN: 9781716517686
Category :
Languages : en
Pages : 190
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Book Description
Python for the Lab is the first book covering how to develop instrumentation software. It is ideal for researchers willing to automatize their setups and bring their experiments to the next level. The book is the product of countless workshops at different universities, and a carefully design pedagogical strategy. With an easy to follow and task-oriented design, the book uncovers all the best practices in the field. It also shows how to design code for long-term maintainability, opening the doors of fruitful collaboration among researchers from different labs.
Author: Jason Brownlee
Publisher: SuperFastPython.com
ISBN:
Category : Computers
Languages : en
Pages : 104
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Book Description
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.
Author: Mark Summerfield
Publisher: Addison-Wesley
ISBN: 0133373231
Category : Computers
Languages : en
Pages : 326
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Book Description
Winner of the 2014 Jolt Award for "Best Book" “Whether you are an experienced programmer or are starting your career, Python in Practice is full of valuable advice and example to help you improve your craft by thinking about problems from different perspectives, introducing tools, and detailing techniques to create more effective solutions.” —Doug Hellmann, Senior Developer, DreamHost If you’re an experienced Python programmer, Python in Practice will help you improve the quality, reliability, speed, maintainability, and usability of all your Python programs. Mark Summerfield focuses on four key themes: design patterns for coding elegance, faster processing through concurrency and compiled Python (Cython), high-level networking, and graphics. He identifies well-proven design patterns that are useful in Python, illuminates them with expert-quality code, and explains why some object-oriented design patterns are irrelevant to Python. He also explodes several counterproductive myths about Python programming—showing, for example, how Python can take full advantage of multicore hardware. All examples, including three complete case studies, have been tested with Python 3.3 (and, where possible, Python 3.2 and 3.1) and crafted to maintain compatibility with future Python 3.x versions. All code has been tested on Linux, and most code has also been tested on OS X and Windows. All code may be downloaded at www.qtrac.eu/pipbook.html. Coverage includes Leveraging Python’s most effective creational, structural, and behavioral design patterns Supporting concurrency with Python’s multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today’s powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL
Author: Fred B. Schneider
Publisher: Springer Science & Business Media
ISBN: 1461218306
Category : Computers
Languages : en
Pages : 482
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Book Description
Here, one of the leading figures in the field provides a comprehensive survey of the subject, beginning with prepositional logic and concluding with concurrent programming. It is based on graduate courses taught at Cornell University and is designed for use as a graduate text. Professor Schneier emphasises the use of formal methods and assertional reasoning using notation and paradigms drawn from programming to drive the exposition, while exercises at the end of each chapter extend and illustrate the main themes covered. As a result, all those interested in studying concurrent computing will find this an invaluable approach to the subject.
Author: Simon Marlow
Publisher: "O'Reilly Media, Inc."
ISBN: 1449335926
Category : Computers
Languages : en
Pages : 322
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Book Description
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language’s many APIs and frameworks for writing both parallel and concurrent programs. You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions. Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented: Express parallelism in Haskell with the Eval monad and Evaluation Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network
Author: Dr.M Sirish Kumar
Publisher: RAJA SURESH
ISBN: 8196176937
Category : Antiques & Collectibles
Languages : en
Pages : 192
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Book Description
This book aims to provide a broad PYTHON PROGRAMMING for the importance of PYTHON PROGRAMMING is well known in various engineering fields. The book uses to explain the fundamentals of this subject. It provides a logical method of explaining various complicated concepts and stepwise methods to explain important topics. Each chapter is well supported with necessary illustrations. All the chapters in the book are arranged in a proper sequence that permits each topic to build upon earlier studies. PYTHON PROGRAMMING an important research area. The techniques developed in this area so far require to be summarized appropriately. In this book, the fundamental theories of these techniques are introduced. Particularly, the functions required in image processing techniques are introduced.
Author: Jason Brownlee
Publisher: SuperFastPython.com
ISBN:
Category : Computers
Languages : en
Pages : 460
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Book Description
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.
Author:
Publisher: K.S.Sampathkumar
ISBN:
Category :
Languages : en
Pages : 308
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Book Description
