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Python Multiprocessing Pool Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython

Page : 75 pages

File Size : 50,60 MB

Release : 2022-07-19

Category : Computers

ISBN :

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Book Description

How much faster could your python code run (if it used all CPU cores)? The multiprocessing.Pool class provides easy-to-use process-based concurrency. This is not some random third-party library, this is a class provided in the Python standard library (already installed on your system). This is the class you need to use to make your code run faster. There's just one problem. No one knows about it (or how to use it well). Introducing: "Python Multiprocessing Pool Jump-Start". A new book designed to teach you multiprocessing pools in Python, super fast! You will get a fast-paced, 7-part course to get you started and make you awesome at using the multiprocessing pool. Each of the 7 lessons was carefully designed to teach one critical aspect of the multiprocessing pool, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understood the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from outdated StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Python Multiprocessing Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython

Page : 139 pages

File Size : 25,31 MB

Release : 2022-07-28

Category : Computers

ISBN :

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Book Description

Unlock parallel programming in Python (and run your code on all CPUs). The multiprocessing module provides easy-to-use process-based concurrency in Python. Unlike Python threading, multiprocessing side-steps the infamous Global Interpreter Lock (GIL), allowing full parallelism in Python. This is not some random third-party library, this is an API provided in the Python standard library (already installed on your system). This is the API you need to use to make your code run faster. There's just one problem. Few developers know about it (or how to use it well). Introducing: "Python Multiprocessing Jump-Start". A new book designed to teach you the multiprocessing module in Python, super fast! You will get a fast-paced, 7-part course to get you started and make you awesome at using the multiprocessing API. Each of the 7 lessons was carefully designed to teach one critical aspect of the multiprocessing module, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understand the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Python ThreadPoolExecutor Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython

Page : 130 pages

File Size : 30,51 MB

Release :

Category : Computers

ISBN :

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Book Description

How much faster could your Python code run (if you used 100s of thread workers)? The ThreadPoolExecutor class provides modern thread pools for IO-bound tasks. This is not some random third-party library, this is a class provided in the Python standard library (already installed on your system). This is the class you need to make your code run faster. There's just one problem. No one knows about it (or how to use it well). Introducing: "Python ThreadPoolExecutor Jump-Start". A new book designed to teach you thread pools in Python, super fast! You will get a rapid-paced, 7-part course to get you started and make you awesome at using the ThreadPoolExecutor. Including: * How to create thread pools and when to use them. * How to configure thread pools including the number of threads. * How to execute tasks with worker threads and handle for results. * How to execute tasks in the thread pool asynchronously. * How to query and get results from handles on asynchronous tasks called futures. * How to wait on and manage diverse collections of asynchronous tasks. * How to develop a concurrent website status checker that is 5x faster than the sequential version. Each of the 7 lessons was carefully designed to teach one critical aspect of the ThreadPoolExecutor, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understood the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Python ThreadPool Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython.com

Page : 98 pages

File Size : 19,34 MB

Release : 2022-08-09

Category : Computers

ISBN :

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Book Description

How much faster could your Python code run (if you used 100s of threads)? The ThreadPool class provides easy-to-use thread-based concurrency for IO-bound tasks. This is not some random third-party library, this is a class provided in the Python standard library (already installed on your system). This is the class you need to make your code run faster. There's just one problem. No one knows about it (or how to use it well). Introducing: "Python ThreadPool Jump-Start". A new book designed to teach you thread pools in Python, super fast! You will get a rapid-paced, 7-part course to get you started and make you awesome at using the ThreadPool. Including: * How to create thread pools and when to use them. * How to configure thread pools including the number of threads. * How to execute tasks with worker threads and wait for results. * How to execute tasks in the thread pool asynchronously. * How to execute tasks lazily and respond to results as tasks complete. * How to handle results with callbacks and check the status of tasks. * How to develop a port scanner that is 70x faster than the sequential version. Each of the 7 lessons was carefully designed to teach one critical aspect of the ThreadPool, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understood the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Python Threading Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython

Page : 140 pages

File Size : 19,78 MB

Release : 2022-08-04

Category : Computers

ISBN :

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Book Description

Unlock concurrency with Python threads (and run 100s or 1,000s of tasks simultaneously) The threading module provides easy-to-use thread-based concurrency in Python. Unlike Python multiprocessing, the threading module is limited by the infamous Global Interpreter Lock (GIL). Critically, the GIL is released when performing blocking I/O. Additionally, threads can share memory making them perfectly suited to I/O-bound tasks such as reading and writing from files and socket connections. This is the API you need to use to make your code run faster. Introducing: "Python Threading Jump-Start". A new book designed to teach you the threading module in Python, super fast! You will get a rapid-paced, 7-part course to get you started and make you awesome at using the threading API. Each of the 7 lessons was carefully designed to teach one critical aspect of the threading module, with explanations, code snippets and worked examples. You will discover: * How to choose tasks that are well suited to threads. * How to create and run new threads. * How to locate and query running threads. * How to use locks, semaphores, barriers and more. * How to share data between threads using queues. * How to execute ad hoc tasks with reusable worker threads. * How to gracefully stop and forcefully kill threads. Each lesson ends with an exercise for you to complete to confirm you understand the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Python Asyncio Jump-Start

Author : Jason Brownlee

Publisher : SuperFastPython.com

Page : 179 pages

File Size : 23,34 MB

Release :

Category : Computers

ISBN :

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Book Description

Asyncio is an exciting new addition to Python. It allows regular Python programs to be developed using the asynchronous programming paradigm. It includes changes to the language to support coroutines as first-class objects, such as the async def and await expressions, and the lesser discussed async for and async with expressions for asynchronous iterators and context managers respectively. Asyncio is the way to rapidly develop scalable Python programs capable of tens or hundreds of thousands of concurrent tasks. Developing concurrent programs using coroutines and the asyncio module API can be very challenging for beginners, especially those new to asynchronous programming. Introducing: "Python Asyncio Jump-Start". A new book designed to teach you asyncio in Python, super fast! You will get a rapid-paced, 7-part course focused on getting you started and make you awesome at using asyncio. Including: * How to define, schedule, and execute asynchronous tasks as coroutines. * How to manage groups of asynchronous tasks, including waiting for all tasks, the first that, or the first task to fail. * How to define, create, and use asynchronous iterators, generators, and context manages * How to share data between coroutines with queues and how to synchronize coroutines to make code coroutine-safe. * How to run commands as subprocesses and how to implement asynchronous socket programming with streams. * How to develop a port scanner that is nearly 1,000 times faster than the sequential version. Each of the 7 lessons was carefully designed to teach one critical aspect of asyncio, with explanations, code snippets, and complete examples. Each lesson ends with an exercise for you to complete to confirm you understood the topic, a summary of what was learned, and links for further reading if you want to go deeper. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.



Machine Learning Mastery With Python

Author : Jason Brownlee

Publisher : Machine Learning Mastery

Page : 177 pages

File Size : 12,69 MB

Release : 2016-04-08

Category : Computers

ISBN :

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Book Description

The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this Ebook, learn exactly how to get started and apply machine learning using the Python ecosystem.



Topics in Parallel and Distributed Computing

Author : Sushil K Prasad

Publisher : Morgan Kaufmann

Page : 359 pages

File Size : 17,89 MB

Release : 2015-09-16

Category : Computers

ISBN : 0128039388

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Book Description

Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline. The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology. However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists. This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula. - Contributed and developed by the leading minds in parallel computing research and instruction - Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline - Succinctly addresses a range of parallel and distributed computing topics - Pedagogically designed to ensure understanding by experienced engineers and newcomers - Developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts



Python Concurrency with Asyncio

Author : Matthew Fowler

Publisher : Simon and Schuster

Page : 374 pages

File Size : 25,31 MB

Release : 2022-03

Category : Computers

ISBN : 1617298662

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Book Description

It's easy to overload standard Python and watch your programs slow to a crawl. The 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. "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.



Learning Concurrency in Python

Author : Elliot Forbes

Publisher : Packt Publishing Ltd

Page : 352 pages

File Size : 42,53 MB

Release : 2017-08-16

Category : Computers

ISBN : 178728316X

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Book Description

Practically and deeply understand concurrency in Python to write efficient programs About This Book Build highly efficient, robust, and concurrent applications Work through practical examples that will help you address the challenges of writing concurrent code Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available Who This Book Is For This book is for Python developers who would like to get started with concurrent programming. Readers are expected to have a working knowledge of the Python language, as this book will build on these fundamentals concepts. What You Will Learn Explore the concept of threading and multiprocessing in Python Understand concurrency with threads Manage exceptions in child threads Handle the hardest part in a concurrent system — shared resources Build concurrent systems with Communicating Sequential Processes (CSP) Maintain all concurrent systems and master them Apply reactive programming to build concurrent systems Use GPU to solve specific problems In Detail Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices. Style and approach This easy-to-follow guide teaches you new practices and techniques to optimize your code, and then moves toward more advanced ways to effectively write efficient Python code. Small and simple practical examples will help you test the concepts yourself, and you will be able to easily adapt them for any application.