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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
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.
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.
By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence. Dive into the TDD workflow, including the unit test/code cycle and refactoring Use unit tests for classes and functions, and functional tests for user interactions within the browser Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests Test and automate your deployments with a staging server Apply tests to the third-party plugins you integrate into your site Run tests automatically by using a Continuous Integration environment Use TDD to build a REST API with a front-end Ajax interface
Explore Twisted, the Python-based event-driven networking engine, and review several of its most popular application projects. It is written by community leaders who have contributed to many of the projects covered, and share their hard-won insights and experience. Expert Twisted starts with an introduction to event-driven programming, explaining it in the context of what makes Twisted unique. It shows how Twisted's design emphasizes testability as a solution to common challenges of reliability, debugging, and start-to-finish causality that are inherent in event-driven programming. It also explains asynchronous programming, and the importance of functions, deferreds, and coroutines. It then uses two popular applications, treq and klein, to demonstrate calling and writing Web APIs with Twisted. The second part of the book dives into Twisted projects, in each case explaining how the project fits into the Twisted ecosystem and what it does, and offers several examples to bring readers up to speed, with pointers to additional resources for more depth. Examples include using Twisted with Docker, as a WSGI container, for file sharing, and more. What You'll LearnIntegrate Twisted and asyncio using adapters Automate software build, test, and release processes with Buildbot Create clients and servers with Autobahn Transfer files with Magic Wormhole Distribute cloud-based file storage with Tahoe LAFSUnderstand HTTP/2 with Python and Twisted Support for asynchronous tasks using Django Channels Who This Book Is For Readers should have some Python experience and understand the essentials of containers and protocols, but need not be familiar with Twisted or the associated projects covered in the book.
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.
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems Key FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book Description Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming. Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples. By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language What you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is for This book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
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.
Python's built-in unittest module is showing it's age; hard to extend, debug and track what's going on. The pytest framework overcomes these problems and simplifies testing your Python software. Many users love to use pytest and the improvement in their testing shows! This book is the ideal introduction to pytest, teaching you how to write ...
Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers: Python data model: understand how special methods are the key to the consistent behavior of objects Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work