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Python Multiprocessing Pool Jump Start
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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 SuperFastPython. This book was released on 2022-07-19 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Stop copy-pasting code from outdated StackOverflow answers.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.
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.
Book Synopsis Python ThreadPoolExecutor Jump-Start by : Jason Brownlee
Download or read book Python ThreadPoolExecutor Jump-Start written by Jason Brownlee and published by SuperFastPython. This book was released on with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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.
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.
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.
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.
Book Synopsis Topics in Parallel and Distributed Computing by : Sushil K Prasad
Download or read book Topics in Parallel and Distributed Computing written by Sushil K Prasad and published by Morgan Kaufmann. This book was released on 2015-09-16 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
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.
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.
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
Book Synopsis Effective Computation in Physics by : Anthony Scopatz
Download or read book Effective Computation in Physics written by Anthony Scopatz and published by "O'Reilly Media, Inc.". This book was released on 2015-06-25 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: More physicists today are taking on the role of software developer as part of their research, but software development isnâ??t always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. Youâ??ll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results. In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures
Book Synopsis Python Parallel Programming Cookbook by : Giancarlo Zaccone
Download or read book Python Parallel Programming Cookbook written by Giancarlo Zaccone and published by Packt Publishing Ltd. This book was released on 2015-08-26 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master efficient parallel programming to build powerful applications using Python About This Book Design and implement efficient parallel software Master new programming techniques to address and solve complex programming problems Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depth Who This Book Is For Python Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing. What You Will Learn Synchronize multiple threads and processes to manage parallel tasks Implement message passing communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational tasks Write efficient programs by adopting the event-driven programming model Explore the cloud technology with DJango and Google App Engine Apply parallel programming techniques that can lead to performance improvements In Detail Parallel programming techniques are required for a developer to get the best use of all the computational resources available today and to build efficient software systems. From multi-core to GPU systems up to the distributed architectures, the high computation of programs throughout requires the use of programming tools and software libraries. Because of this, it is becoming increasingly important to know what the parallel programming techniques are. Python is commonly used as even non-experts can easily deal with its concepts. This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will also understand the StarCluster framework, Pycsp, Scoop, and Disco modules in Python. Further on, you will learn GPU programming with Python using the PyCUDA module along with evaluating performance limitations. Next you will get acquainted with the cloud computing concepts in Python, using Google App Engine (GAE), and building your first application with GAE. Lastly, you will learn about grid computing concepts in Python and using PyGlobus toolkit, GFTP and GASS COPY to transfer files, and service monitoring in PyGlobus. Style and approach A step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts.
Book Synopsis Python for Finance by : Yves J. Hilpisch
Download or read book Python for Finance written by Yves J. Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2018-12-05 with total page 682 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
Book Synopsis Jumpstart Snowflake by : Dmitry Anoshin
Download or read book Jumpstart Snowflake written by Dmitry Anoshin and published by Apress. This book was released on 2019-12-20 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users
Book Synopsis High Performance Python by : Micha Gorelick
Download or read book High Performance Python written by Micha Gorelick and published by O'Reilly Media. This book was released on 2020-04-30 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Python Essential Reference by : David M Beazley
Download or read book Python Essential Reference written by David M Beazley and published by Addison-Wesley Professional. This book was released on 2009-06-29 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library. Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source. Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms. This fourth edition of Python Essential Reference features numerous improvements, additions, and updates: Coverage of new language features, libraries, and modules Practical coverage of Python's more advanced features including generators, coroutines, closures, metaclasses, and decorators Expanded coverage of library modules related to concurrent programming including threads, subprocesses, and the new multiprocessing module Up-to-the-minute coverage of how to use Python 2.6’s forward compatibility mode to evaluate code for Python 3 compatibility Improved organization for even faster answers and better usability Updates to reflect modern Python programming style and idioms Updated and improved example code Deep coverage of low-level system and networking library modules — including options not covered in the standard documentation
