Foundations of Python Network Programming, Third Edition, covers all of the classic topics found in the second edition of this book, including network protocols, network data and errors, email, server architecture, and HTTP and web applications, plus updates for Python 3. Some of the new topics in this edition include: • Extensive coverage of the updated SSL support in Python 3 • How to write your own asynchronous I/O loop. • An overview of the "asyncio" framework that comes with Python 3.4. • How the Flask web framework connects URLs to your Python code. • How cross-site scripting and cross-site request forgery can be used to attack your web site, and how to protect against them. • How a full-stack web framework like Django can automate the round trip from your database to the screen and back. If you're a Python programmer who needs a deep understanding of how to use Python for network-related tasks and applications, this is the book for you. From web application developers, to systems integrators, to system administrators—this book has everything that you need to know.
The comprehensive guide to building network applications with Python
Author: John Goerzen
This second edition of Foundations of Python Network Programming targets Python 2.5 through Python 2.7, the most popular production versions of the language. Python has made great strides since Apress released the first edition of this book back in the days of Python 2.3. The advances required new chapters to be written from the ground up, and others to be extensively revised. You will learn fundamentals like IP, TCP, DNS and SSL by using working Python programs; you will also be able to familiarize yourself with infrastructure components like memcached and message queues. You can also delve into network server designs, and compare threaded approaches with asynchronous event-based solutions. But the biggest change is this edition's expanded treatment of the web. The HTTP protocol is covered in extensive detail, with each feature accompanied by sample Python code. You can use your HTTP protocol expertise by studying an entire chapter on screen scraping and you can then test lxml and BeautifulSoup against a real-world web site. The chapter on web application programming now covers both the WSGI standard for component interoperability, as well as modern web frameworks like Django. Finally, all of the old favorites from the first edition are back: E-mail protocols like SMTP, POP, and IMAP get full treatment, as does XML-RPC. You can still learn how to code Python network programs using the Telnet and FTP protocols, but you are likely to appreciate the power of more modern alternatives like the paramiko SSH2 library. If you are a Python programmer who needs to learn the network, this is the book that you want by your side.
* Totaling 900 pages and covering all of the topics important to new and intermediate users, Beginning Python is intended to be the most comprehensive book on the Python ever written. * The 15 sample projects in Beginning Python are attractive to novice programmers interested in learning by creating applications of timely interest, such as a P2P file-sharing application, Web-based bulletin-board, and an arcade game similar to the classic Space Invaders. * The author Magnus Lie Hetland, PhD, is author of Apress’ well-received 2002 title, Practical Python, ISBN: 1-59059-006-6. He’s also author of the popular online guide, Instant Python Hacking (http://www.hetland.org), from which both Practical Python and Beginning Python are based.
Practical Maya Programming with Python is a practical tutorial packed with plenty of examples and sample projects which guides you through building reusable, independent modules and handling unexpected errors. If you are a developer looking to build a powerful system using Python and Maya's capabilities, then this book is for you. Practical Maya Programming with Python is perfect for intermediate users with basic experience in Python and Maya who want to better their knowledge and skills.
Build smarter programs with the power of neural networks and the simplicity of PythonAbout This Book* Make your roots stronger in neural networks by this concept-rich yet highly practical guide; from single layer to multiple layers with the help of Python* Through this book, you will develop a strong background in neural networks, regardless of your level of previous knowledge in this subject* You will be able to implement solutions from scratch, so the whole process on foundations of neural network solution design will be paced by youWho This Book Is ForThis book is designed for novices as well as intermediate Python developers who have a statistical background and want to work with neural networks to get better results from complex data. It also contains enough food for thought for those who want to improve their skills in machine learning and deep learning.What You Will Learn* See the latest innovations in the field* Become fluent in Python to develop neural networks solutions capable of solving complex and interesting tasks* Implement neural networks step-by-step* Solve your complex computational problems with the aid of neural networks and Python* The reader will be able to set up his/her neural network with ease, according to the objective he/she wants to apply.* The reader will be able to design time series based models using RNNs in Python.* Will be able to design high level solutions with CNNs in PythonIn DetailIf you wish to solve your complex computational problem efficiently, neural networks come to the rescue. This book will teach you how to ace neural networks and solve your computational problems with Python-right from predicting to self-learning models-with ease. We start off with neural network design, then you'll build a solid foundational knowledge of how a neural network learns from data, and the principles behind it.This book cover various types of neural networks including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but also see a generalization of these networks. With the help of practical examples and real-world use cases, you will learn to implement these neural networks in your applications.
Advances in Computational Science: Lectures Presented at the International Conference on Computational Methods in Sciences and Engineering 2008
Author: George Maroulis
Publisher: American Inst. of Physics
The aim of ICCMSE 2008 is to bring together computational scientists and engineers from several disciplines in order to share methods, methodologies and ideas. The potential readers are all the scientists with interest in: Computational Mathematics, Theoretical Physics, Computational Physics, Theoretical Chemistry, Computational Chemistry, Mathematical Chemistry, Computational Engineering, Computational Mechanics, Computational Biology and Medicine, Scientific Computation, High Performance Computing, Parallel and Distributed Computing, Visualization, Problem Solving Environments, Software Tools, Advanced Numerical Algorithms, Modelling and Simulation of Complex Systems, Web-based Simulation and Computing, Grid-based Simulation and Computing, Computational Grids, and Computer Science.
Aimed toward the working programmer, this guide provides readers with everything they need to know to become experts at using the Hypertext Markup Language (HTML) to post on the Web. Liberally illustrated and detailed examples provide complete background and hands-on information to let programmers of any level design, install, and operate customized Web-specific CGI programs. CD contains ready-to-run programs and code fragments.
How to Set Up and Maintain a Virtual Machine Environment with Python
Author: W. David Ashley
Discover the essential concepts of libvirt development and see how to interface to Linux virtualization environments, such as QEMU/KVM, XEN, Virtuozzo, VMWare ESX, LXC, Bhyve, and more. This book will prepare you to set up and maintain a virtual machine environment. You'll start by reviewing virtualization in general and then move on to libvirt-specific concepts using Python, including virtualized operating systems and networks, connections, storage pools, and event and error handling. This work concludes with a comprehensive look at the XML schema definitions for domains, networks, devices, network filtering, storage, node devices, and more. The libvirt API covers the entire life cycle of virtual objects, from creation to destruction. It contains everything needed for the management of a virtual object during that life cycle. While libvirt has APIs that support many languages, Foundations of Libvirt Development concentrates on Python exclusively, and how to use the APIs to control virtual machines under the QEMU/KVM system. and more. What You'll Learn Interface Python to the libvirt library. Review the class layout and methods of the libvirt library. Install and manipulate virtual machines via Python/libvirt. Create XML to manipulate domains, networks, and devices. Write Python programs to perform libvirt functions without human intervention. Who This Book Is ForMaintainers of virtual machines in a UNIX/Linux environment ranging from managing code on a single virtual machine through an entire installation of virtual machines.