Python Processpoolexecutor Jump Start

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Python ProcessPoolExecutor Jump-Start

Author : Jason Brownlee
Publisher : SuperFastPython.com
ISBN 13 :
Total Pages : 129 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python ProcessPoolExecutor Jump-Start by : Jason Brownlee

Download or read book Python ProcessPoolExecutor Jump-Start written by Jason Brownlee and published by SuperFastPython.com. This book was released on with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: How much faster could your python code run ( if it used all CPU cores)? The ProcessPoolExecutor class provides modern process pools for CPU-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 ProcessPoolExecutor Jump-Start". A new book designed to teach you modern process 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 ProcessPoolExecutor. Including: * How to create process pools and when to use them. * How to configure process pools including the number of workers. * How to execute tasks with worker processes and handle results. * How to execute tasks in the process 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 parallel Fibonacci calculator 4x faster than the sequential version. Each of the 7 lessons was carefully designed to teach one critical aspect of the ProcessPoolExecutor, 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
ISBN 13 :
Total Pages : 98 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python ThreadPool Jump-Start by : Jason Brownlee

Download or read book Python ThreadPool Jump-Start written by Jason Brownlee and published by SuperFastPython.com. This book was released on 2022-08-09 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Multiprocessing Jump-Start

Author : Jason Brownlee
Publisher : SuperFastPython
ISBN 13 :
Total Pages : 139 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python Multiprocessing Jump-Start by : Jason Brownlee

Download or read book Python Multiprocessing Jump-Start written by Jason Brownlee and published by SuperFastPython. This book was released on 2022-07-28 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Threading Jump-Start

Author : Jason Brownlee
Publisher : SuperFastPython
ISBN 13 :
Total Pages : 140 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python Threading Jump-Start by : Jason Brownlee

Download or read book Python Threading Jump-Start written by Jason Brownlee and published by SuperFastPython. This book was released on 2022-08-04 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
ISBN 13 :
Total Pages : 179 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python Asyncio Jump-Start by : Jason Brownlee

Download or read book Python Asyncio Jump-Start written by Jason Brownlee and published by SuperFastPython.com. This book was released on with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Python Multiprocessing Pool Jump-Start

Author : Jason Brownlee
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (414 download)

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Book Synopsis Python Multiprocessing Pool Jump-Start by : Jason Brownlee

Download or read book Python Multiprocessing Pool Jump-Start written by Jason Brownlee and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Python Multiprocessing Jump-Start

Author : Jason Brownlee
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (429 download)

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Book Synopsis Python Multiprocessing Jump-Start by : Jason Brownlee

Download or read book Python Multiprocessing Jump-Start written by Jason Brownlee and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Python Concurrent Futures Interview Questions

Author : Jason Brownlee
Publisher : SuperFastPython.com
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4./5 ( download)

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Book Synopsis Python Concurrent Futures Interview Questions by : Jason Brownlee

Download or read book Python Concurrent Futures Interview Questions written by Jason Brownlee and published by SuperFastPython.com. This book was released on with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Learning Concurrency in Python

Author : Elliot Forbes
Publisher : Packt Publishing Ltd
ISBN 13 : 178728316X
Total Pages : 352 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Learning Concurrency in Python by : Elliot Forbes

Download or read book Learning Concurrency in Python written by Elliot Forbes and published by Packt Publishing Ltd. This book was released on 2017-08-16 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Using Asyncio in Python

Author : Caleb Hattingh
Publisher : O'Reilly Media
ISBN 13 : 1492075302
Total Pages : 166 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Using Asyncio in Python by : Caleb Hattingh

Download or read book Using Asyncio in Python written by Caleb Hattingh and published by O'Reilly Media. This book was released on 2020-01-30 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re among the Python developers put off by asyncio’s complexity, it’s time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework and end-user developers. The features you need to consider are a small subset of the whole asyncio API, but picking out the right features is the tricky part. That’s where this practical book comes in. Veteran Python developer Caleb Hattingh helps you gain a basic understanding of asyncio’s building blocks—enough to get started writing simple event-based programs. You’ll learn why asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simpleway to support thousands of simultaneous socket connections. Get a critical comparison of asyncio and threading for concurrent network programming Take an asyncio walk-through, including a quickstart guidefor hitting the ground looping with event-based programming Learn the difference between asyncio features for end-user developers and those for framework developers Understand asyncio’s new async/await language syntax, including coroutines and task and future APIs Get detailed case studies (with code) of some popular asyncio-compatible third-party libraries

Machine Learning Mastery With Python

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 177 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning Mastery With Python by : Jason Brownlee

Download or read book Machine Learning Mastery With Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2016-04-08 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advanced Guide to Python 3 Programming

Author : John Hunt
Publisher : Springer Nature
ISBN 13 : 3031403363
Total Pages : 638 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Advanced Guide to Python 3 Programming by : John Hunt

Download or read book Advanced Guide to Python 3 Programming written by John Hunt and published by Springer Nature. This book was released on 2023-11-02 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Guide to Python 3 Programming 2nd Edition delves deeply into a host of subjects that you need to understand if you are to develop sophisticated real-world programs. Each topic is preceded by an introduction followed by more advanced topics, along with numerous examples, that take you to an advanced level. This second edition has been significantly updated with two new sections on advanced Python language concepts and data analytics and machine learning. The GUI chapters have been rewritten to use the Tkinter UI library and a chapter on performance monitoring and profiling has been added. In total there are 18 new chapters, and all remaining chapters have been updated for the latest version of Python as well as for any of the libraries they use. There are eleven sections within the book covering Python Language Concepts, Computer Graphics (including GUIs), Games, Testing, File Input and Output, Databases Access, Logging, Concurrency and Parallelism, Reactive Programming, Networking and Data Analytics. Each section is self-contained and can either be read on its own or as part of the book as a whole. It is aimed at those who have learnt the basics of the Python 3 language but wish to delve deeper into Python’s eco system of additional libraries and modules.

Effective Python

Author : Brett Slatkin
Publisher : Pearson Education
ISBN 13 : 0134034287
Total Pages : 251 pages
Book Rating : 4.1/5 (34 download)

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Book Synopsis Effective Python by : Brett Slatkin

Download or read book Effective Python written by Brett Slatkin and published by Pearson Education. This book was released on 2015 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effective Python will help students harness the full power of Python to write exceptionally robust, efficient, maintainable, and well-performing code. Utilizing the concise, scenario-driven style pioneered in Scott Meyers's best-selling Effective C++, Brett Slatkin brings together 53 Python best practices, tips, shortcuts, and realistic code examples from expert programmers. Each section contains specific, actionable guidelines organized into items, each with carefully worded advice supported by detailed technical arguments and illuminating examples.

Python for Probability, Statistics, and Machine Learning

Author : José Unpingco
Publisher : Springer
ISBN 13 : 3030185451
Total Pages : 384 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Python for Probability, Statistics, and Machine Learning by : José Unpingco

Download or read book Python for Probability, Statistics, and Machine Learning written by José Unpingco and published by Springer. This book was released on 2019-06-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated *Programming Tips* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.

Parallel Programming with Python

Author : Jan Palach
Publisher : Packt Publishing Ltd
ISBN 13 : 178328840X
Total Pages : 173 pages
Book Rating : 4.7/5 (832 download)

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Book Synopsis Parallel Programming with Python by : Jan Palach

Download or read book Parallel Programming with Python written by Jan Palach and published by Packt Publishing Ltd. This book was released on 2014-06-25 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

Imbalanced Classification with Python

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 463 pages
Book Rating : 4./5 ( download)

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Book Synopsis Imbalanced Classification with Python by : Jason Brownlee

Download or read book Imbalanced Classification with Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2020-01-14 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imbalanced classification are those classification tasks where the distribution of examples across the classes is not equal. Cut through the equations, Greek letters, and confusion, and discover the specialized techniques data preparation techniques, learning algorithms, and performance metrics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently develop robust models for your own imbalanced classification projects.

The Hitchhiker's Guide to Python

Author : Kenneth Reitz
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491933224
Total Pages : 338 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis The Hitchhiker's Guide to Python by : Kenneth Reitz

Download or read book The Hitchhiker's Guide to Python written by Kenneth Reitz and published by "O'Reilly Media, Inc.". This book was released on 2016-08-30 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversity—and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.