Python Parallel Programming Cookbook下载

AI100_小助手 2018-08-24 12:11:13

Introduction 2
The parallel computing memory architecture 3
Memory organization 6
Parallel programming models 14
How to design a parallel program 16
How to evaluate the performance of a parallel program 19
Introducing Python 21
Python in a parallel world 26
Introducing processes and threads 26
Start working with processes in Python 27
Start working with threads in Python 29
Chapter 2: Thread-based Parallelism 33
Introduction 34
Using the Python threading module 35
How to define a thread 35
How to determine the current thread 37
How to use a thread in a subclass 39
Thread synchronization with Lock and RLock
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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. Table of Contents Chapter 1: Getting Started with Parallel Computing and Python Chapter 2: Thread-based Parallelism Chapter 3: Process-based Parallelism Chapter 4: Asynchronous Programming Chapter 5: Distributed Python Chapter 6: GPU Programming with Python

《Python Parallel Programming Cookbook》中文版

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Chapter 1, Sockets, IPv4, and Simple Client/Server Programming, introduces you to Python's core networking library with various small tasks and enables you to create your first clientserver application. Chapter 2, Multiplexing Socket I/O for Better Performance, discusses various useful techniques for scaling your client/server applications with default and third-party libraries. OneKing.Soul Preface [ 2 ] Chapter 3, IPv6, Unix Domain Sockets, and Network Interfaces, focuses more on administering your local machine and looking after your local area network. Chapter 4, Programming with HTTP for the Internet, enables you to create a mini commandline browser with various features such as submitting web forms, handling cookies, managing partial downloads, compressing data, and serving secure content over HTTPS. Chapter 5, Email Protocols, FTP, and CGI Programming, brings you the joy of automating your FTP and e-mail tasks such as manipulating your Gmail account, and reading or sending emails from a script or creating a guest book for your web application. We learn to write email clients with SMTP and POP3. Chapter 6, Programming Across Machine Boundaries, gives you a taste of automating your system administration and deployment tasks over SSH. You can run commands, install packages, or set up new websites remotely from your laptop. Chapter 7, Working with Web Services – XML-RPC, SOAP, and REST, introduces you to various API protocols such as XML-RPC, SOAP, and REST. You can programmatically ask any website or web service for information and interact with them. For example, you can search for products on Amazon or Google. Chapter 8, Network Monitoring and Security, introduces you to various techniques for capturing, storing, analyzing, and manipulating network packets. This encourages you to go further to investigate your network security issues using concise Python scripts. Chapter 9, Network Modeling, introduces you to the world of network simulations and emulations. You learn to simulate networks with NS-3, and emulate networking systems with Mininet and its extensions. Chapter 10, Getting Started with SDN, discusses the enterprise SDN controllers, configuring them to use in Software-Defined Networks. We learn to develop SDN visually with MiniEdit, and configure the networks with OpenDaylight, ONOS, Floodlight, Ryu, and POX controllers. Chapter 11, Authentication, Authorization, and Accounting (AAA), introduces how the networks are secured, and discusses configuring LDAP clients with Python, accounting aspects of the network, and authentication and access of network services. Chapter 12, Open and Proprietary Networking Solutions, discusses in detail, configuring largescale enterprise networking projects, including a few projects from Cisco, Juniper, VMware, and the Linux Foundation.

《Python Parallel Programming Cookbook》翻译计划在线阅读： Read the doc编译状态: CircleCI状态: 本书结合Python讨论了线程、进程和异步编程三种模型，是Python并行编程不错的参考书籍。译者平时主要写 Python，职业是 SRE(Devops)。大学期间给 CSDN 兼职翻译了很多文章（有稿费），给 Importnew 和伯乐在线也翻译了很多文章（没有稿费）。这本书是业余时间翻译的，所以没办法保证完成时间，但是感觉圣诞节之前差不多能完成。由于时间仓促、经常加班、心情不好、个人专业深度有限，所以文中出现错误在所难免。鼓励读者自己尝试运行书中的代码，如果发现错误、错别字等欢迎提交 PR，Issue 也行。本书绝大部分尊重原著，译者忍不住会在书中卖弄自己的小聪明宣扬自己的人生观，这些一般都会加特殊的标注。如何参与翻

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