Computer & Internet

Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, and caches.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective.

Using the simple, robust, Python-based Django framework, you can build powerful Web solutions with remarkably few lines of code. In Python Web Development with Django®, three experienced Django and Python developers cover all the techniques, tools, and concepts you need to make the most of Django 1.0, including all the major features of the new release.

Quickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest.

Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.

Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages.

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.

Use Python's built-in features to create innovative graphics for data visualization and technical illustrations. This book goes beyond simple commands and libraries to explain how to not only display but also rotate, shade, and edit graphics for any purpose.

Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to others.

​Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Create descriptors and see ideas and examples of how to use descriptors effectively. In this short book, you’ll explore descriptors in general, with a deep explanation of what descriptors are, how they work, and how they're used. Once you understand the simplicity of the descriptor protocol, the author delves into using and creating descriptors in practice, with plenty of tips, patterns, and real-world guidance. Because descriptors are inherently flexible, you’ll work with multiple examples illustrating how to best take advantage of them.

Key Features Use powerful tools such as doctest and unittest to make testing convenient Apply automation testing to an existing legacy system that isn't test oriented A practical guide to ease testing in Python using real-world examples

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.

Gain the techniques and tools that enable a smooth and efficient software development process in this quick and practical guide on Python continuous integration (CI) and continuous delivery (CD). Based on example applications, this book introduces various kinds of testing and shows you how to set up automated systems that run these tests, and install applications in different environments in controlled ways. Python Continuous Integration and Delivery tackles the technical problems related to software development that are typically glossed over in pure programming texts.

Master Spring basics and core topics, and share the authors’ insights and real–world experiences with remoting, Hibernate, and EJB. Beyond the basics, you'll learn how to leverage the Spring Framework to build the various tiers and parts of an enterprise Java application: transactions, web and presentation tiers, deployment, and much more. A full sample application allows you to apply many of the technologies and techniques covered in Pro Spring 5 and see how they work together.

The Python ecosystem is vast and far-reaching in both scope and depth. Starting out in this crazy, open-source forest is daunting, and even with years of experience, it still requires continual effort to keep up-to-date with the best libraries and techniques. This report helps you explore some of the lesser known Python libraries and tools, including third-party modules and several extremely useful tools in the standard library that deserve more attention.

Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing.

Learn software engineering and coding best practices to write Python code right and error free. In this book you’ll see how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding.

Learn the key differences between containers and virtual machines. Adopting a project based approach, this book introduces you to a simple Python application to be developed and containerized with Docker.

Master the Java EE 8 and JSF (JavaServer Faces) APIs and web framework with this practical, projects-driven guide to web development. This book combines theoretical background with a practical approach by building four real-world applications. By developing these JSF web applications, you'll take a tour through the other Java EE technologies such as JPA, CDI, Security, WebSockets, and more.

Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models, and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations.