Build modular React web apps that are scalable, maintainable and powerful using design patterns and insightful practices Key Features * Get familiar with design patterns in React like Render props and Controlled/uncontrolled inputs * Learn about class/ functional, style and high order components with React * Work through examples that can be used to create reusable code and extensible designs Book Description React is an adaptable JavaScript library for building complex UIs from small, detached bits called components. This book is designed to take you through the most valuable design patterns in React, helping you learn how to apply design patterns and best practices in real-life situations. You’ll get started by understanding the internals of React, in addition to covering Babel 7 and Create React App 2.0, which will help you write clean and maintainable code. To build on your skills, you will focus on concepts such as class components, stateless components, and pure components. You'll learn about new React features, such as the context API and React Hooks that will enable you to build components, which will be reusable across your applications. The book will then provide insights into the techniques of styling React components and optimizing them to make applications faster and more responsive. In the concluding chapters, you’ll discover ways to write tests more effectively and learn how to contribute to React and its ecosystem. By the end of this book, you will be equipped with the skills you need to tackle any developmental setbacks when working with React. You’ll be able to make your applications more flexible, efficient, and easy to maintain, thereby giving your workflow a boost when it comes to speed, without reducing quality. What you will learn * Get familiar with the new React features,like context API and React Hooks * Learn the techniques of styling and optimizing React components * Make components communicate with each other by applying consolidate patterns * Use server-side rendering to make applications load faster * Write a comprehensive set of tests to create robust and maintainable code * Build high-performing applications by optimizing components Who this book is for This book is for web developers who want to increase their understanding of React and apply it to real-life application development. Prior experience with React and JavaScript is assumed.

Gain a complete overview of Oracle CX Cloud Suite and its tools for functions ranging from marketing to sales and commerce to service Key Features * Make optimal use of your Oracle CX Cloud Suite to improve business results * Achieve improved customer insights through Oracle CX’s advanced capabilities * Learn how to design a CX solution architecture Book Description Oracle CX Cloud offers features and capabilities that help companies excel at sales, customer management, and much more. This book is a detailed guide to implementing cloud solutions and helping administrators of all levels thoroughly understand the platform. Oracle CX Cloud Suite begins with an introduction to high-level Oracle architecture and examines what CX offers over CRM. You’ll explore the different cloud-based tools for marketing, sales, and customer services, among others. The book then delves into deployment by covering basic settings, setting up users, and provisioning. You’ll see how to integrate the CX suite to work together to interact with the environment and connect with legacy systems, social connectors, and internet services. The book concludes with a use case demonstrating how the entire Oracle CX Suite is set up, and also covers how to leverage Oracle ICS and Oracle CX Cloud for hybrid deployment. By end of the book, you will have learned about the working of the Oracle CX Cloud Suite and how to orchestrate user experience across all products seamlessly. What you will learn * Differentiate between Oracle CRM and CX Cloud suites * Explore a variety of Oracle CX Cloud tools for marketing and sales * Set up users and database connections during deployment * Employ Cloud Suite CX tools to aid in planning and analysis * Implement hybrid Oracle CX solutions and connect with legacy systems * Integrate with social media connectors like Facebook and LinkedIn * Leverage Oracle ICS and Oracle CX Suite to improve business results Who this book is for This book is for administrators who want to develop and strengthen their Oracle CX Cloud Suite skills in the areas of configuration and system management. Whether you are a new administrator or an experienced professional, this book will enhance your understanding of the new Oracle CX features.

Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs Key Features * Work with large amounts of agile data using distributed datasets and in-memory caching * Source data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3 * Employ the easy-to-use PySpark API to deploy big data Analytics for production Book Description Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs. You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark. By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively. What you will learn * Get practical big data experience while working on messy datasets * Analyze patterns with Spark SQL to improve your business intelligence * Use PySpark's interactive shell to speed up development time * Create highly concurrent Spark programs by leveraging immutability * Discover ways to avoid the most expensive operation in the Spark API: the shuffle operation * Re-design your jobs to use reduceByKey instead of groupBy * Create robust processing pipelines by testing Apache Spark jobs Who this book is for This book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to magnify the impact of your business, this book is for you.

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features * Your entry point into the world of artificial intelligence using the power of Python * An example-rich guide to master various RL and DRL algorithms * Explore the power of modern Python libraries to gain confidence in building self-trained applications Book Description Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL. By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems. This Learning Path includes content from the following Packt products: * Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran * Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani What you will learn * Train an agent to walk using OpenAI Gym and TensorFlow * Solve multi-armed-bandit problems using various algorithms * Build intelligent agents using the DRQN algorithm to play the Doom game * Teach your agent to play Connect4 using AlphaGo Zero * Defeat Atari arcade games using the value iteration method * Discover how to deal with discrete and continuous action spaces in various environments Who this book is for If you’re an ML/DL enthusiast interested in AI and want to explore RL and deep RL from scratch, this Learning Path is for you. Prior knowledge of linear algebra is expected.

Explore the different data mining techniques using the libraries and packages offered by Python Key Features * Grasp the basics of data loading, cleaning, analysis, and visualization * Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining * Your one-stop guide to build efficient data mining pipelines without going into too much theory Book Description Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining. This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you will learn * Explore the methods for summarizing datasets and visualizing/plotting data * Collect and format data for analytical work * Assign data points into groups and visualize clustering patterns * Learn how to predict continuous and categorical outputs for data * Clean, filter noise from, and reduce the dimensions of data * Serialize a data processing model using scikit-learn’s pipeline feature * Deploy the data processing model using Python’s pickle module Who this book is for Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

Manipulate and analyze network data with the power of Python and NetworkX Key Features * Understand the terminology and basic concepts of network science * Leverage the power of Python and NetworkX to represent data as a network * Apply common techniques for working with network data of varying sizes Book Description NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. What you will learn * Use Python and NetworkX to analyze the properties of individuals and relationships * Encode data in network nodes and edges using NetworkX * Manipulate, store, and summarize data in network nodes and edges * Visualize a network using circular, directed and shell layouts * Find out how simulating behavior on networks can give insights into real-world problems * Understand the ongoing impact of network science on society, and its ethical considerations Who this book is for If you are a programmer or data scientist who wants to manipulate and analyze network data in Python, this book is perfect for you. Although prior knowledge of network science is not necessary, some Python programming experience will help you understand the concepts covered in the book easily.

Gain hands-on experience with industry-standard data analysis and machine learning tools in Python Key Features * Learn techniques to use data to identify the exact problem to be solved * Visualize data using different graphs * Identify how to select an appropriate algorithm for data extraction Book Description Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data. As you delve into later chapters, you’ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. By the end of this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. What you will learn * Install the required packages to set up a data science coding environment * Load data into a Jupyter Notebook running Python * Use Matplotlib to create data visualizations * Fit a model using scikit-learn * Use lasso and ridge regression to reduce overfitting * Fit and tune a random forest model and compare performance with logistic regression * Create visuals using the output of the Jupyter Notebook Who this book is for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful.

Concepts, tools, and techniques to explore deep learning architectures and methodologies Key Features * Explore advanced deep learning architectures using various datasets and frameworks * Implement deep architectures for neural network models such as CNN, RNN, GAN, and many more * Discover design patterns and different challenges for various deep learning architectures Book Description Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems. Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations. By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world. What you will learn * Implement CNNs, RNNs, and other commonly used architectures with Python * Explore architectures such as VGGNet, AlexNet, and GoogLeNet * Build deep learning architectures for AI applications such as face and image recognition, fraud detection, and many more * Understand the architectures and applications of Boltzmann machines and autoencoders with concrete examples * Master artificial intelligence and neural network concepts and apply them to your architecture * Understand deep learning architectures for mobile and embedded systems Who this book is for If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book

Explore the entire Hyperledger blockchain family, including frameworks such as Fabric, Sawtooth, Indy, Burrow, and Iroha; and tools such as Composer, Explorer, and Caliper. Key Features * Plan, design, and create a full-fledged private decentralized application using Hyperledger services * Master the ins and outs of the Hyperledger network using real-world examples * Packed with problem-solution-based recipes to tackle pain areas in the blockchain development cycle Book Description Hyperledger is an open-source project and creates private blockchain applications for a range of domains. This book will be your desk reference as you explore common and not-so-common challenges faced while building blockchain networks using Hyperledger services. We'll work through all Hyperledger platform modules to understand their services and features and build end-to-end blockchain applications using various frameworks and tools supported by Hyperledger. This book's independent, recipe-based approach (packed with real-world examples) will familiarize you with the blockchain development cycle. From modeling a business network to integrating with various tools, you will cover it all. We'll cover common and not-so-common challenges faced in the blockchain life cycle. Later, we'll delve into how we can interact with the Hyperledger Fabric blockchain, covering all the principles you need to master, such as chaincode, smart contracts, and much more. We'll also address the scalability and security issues currently faced in blockchain development. By the end of this book, you will be able to implement each recipe to plan, design, and create a full-fledged, private, decentralized application to meet organizational needs. What you will learn * Create the most popular permissioned blockchain network with Fabric and Composer * Build permissioned and permission-less blockchains using Sawtooth * Utilize built-in Iroha asset/account management with role-based permissions * Implement and run Ethereum smart contracts with Burrow * Get to grips with security and scalability in Hyperledger * Explore and view blockchain data using Hyperledger Explorer * Produce reports containing performance indicators and benchmarks using Caliper Who this book is for This book is for blockchain developers who want to understand how they can apply Hyperledger services in their day-to-day projects. This book uses a recipe-based approach to help you use Hyperledger to build powerful, decentralized autonomous applications. We assume the reader has a basic knowledge of the Blockchain technology and cryptography concepts

Learn to design and build Virtual Reality experiences, applications, and games in Unreal Engine 4 through a series of practical, hands-on projects that teach you to create controllable avatars, user interfaces, and more. Key Features * Deploy your virtual reality applications on the latest Oculus Go and Samsung Gear * Build real-world applications such as 3D UIs, mini games, and 360° media player applications using Unreal Engine 4 * Master multiplayer networking and build rich multi-user VR experiences Book Description Unreal Engine 4 (UE4) is a powerful tool for developing VR games and applications. With its visual scripting language, Blueprint, and built-in support for all major VR headsets, it's a perfect tool for designers, artists, and engineers to realize their visions in VR. This book will guide you step-by-step through a series of projects that teach essential concepts and techniques for VR development in UE4. You will begin by learning how to think about (and design for) VR and then proceed to set up a development environment. A series of practical projects follows, taking you through essential VR concepts. Through these exercises, you'll learn how to set up UE4 projects that run effectively in VR, how to build player locomotion schemes, and how to use hand controllers to interact with the world. You'll then move on to create user interfaces in 3D space, use the editor's VR mode to build environments directly in VR, and profile/optimize worlds you've built. Finally, you'll explore more advanced topics, such as displaying stereo media in VR, networking in Unreal, and using plugins to extend the engine. Throughout, this book focuses on creating a deeper understanding of why the relevant tools and techniques work as they do, so you can use the techniques and concepts learned here as a springboard for further learning and exploration in VR. What you will learn * Understand design principles and concepts for building VR applications * Set up your development environment with Unreal Blueprints and C++ * Create a player character with several locomotion schemes * Evaluate and solve performance problems in VR to maintain high frame rates * Display mono and stereo videos in VR * Extend Unreal Engine's capabilities using various plugins Who this book is for This book is for anyone interested in learning to develop Virtual Reality games and applications using UE4. Developers new to UE4 will benefit from hands-on projects that guide readers through clearly-explained steps, while both new and experienced developers will learn crucial principles and techniques for VR development in UE4.

Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key Features * Understand effective synchronization strategies for faster processing using GPUs * Write parallel processing scripts with PyCuda and PyOpenCL * Learn to use the CUDA libraries like CuDNN for deep learning on GPUs Book Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learn * Utilize Python libraries and frameworks for GPU acceleration * Set up a GPU-enabled programmable machine learning environment on your system with Anaconda * Deploy your machine learning system on cloud containers with illustrated examples * Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm. * Perform data mining tasks with machine learning models on GPUs * Extend your knowledge of GPU computing in scientific applications Who this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.

Design, deploy, and manage large-scale containers using Kubernetes Key Features * Gain insight into the latest features of Kubernetes, including Prometheus and API aggregation * Discover ways to keep your clusters always available, scalable, and up-to-date * Master the skills of designing and deploying large clusters on various cloud platforms Book Description If you are running a number of containers and want to be able to automate the way they’re managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: * Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White * Mastering Kubernetes - Second Edition by Gigi Sayfan What you will learn * Download, install, and configure the Kubernetes code base * Create and configure custom Kubernetes resources * Use third-party resources in your automation workflows * Deliver applications as standard packages * Set up and access monitoring and logging for Kubernetes clusters * Set up external access to applications running in the cluster * Manage and scale Kubernetes with hosted platforms on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) * Run multiple clusters and manage them from a single control plane Who this book is for If you are a developer or a system administrator with an intermediate understanding of Kubernetes and want to master its advanced features, then this book is for you. Basic knowledge of networking is required to easily understand the concepts explained.

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features * Migrate models trained with other deep learning frameworks on Caffe2 * Integrate Caffe2 with Android or iOS and implement deep learning models for mobile devices * Leverage the distributed capabilities of Caffe2 to build models that scale easily Book Description Caffe2 is a popular deep learning library used for fast and scalable training and inference of deep learning models on various platforms. This book introduces you to the Caffe2 framework and shows how you can leverage its power to build, train, and deploy efficient neural network models at scale. It will cover the topics of installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. It will also show how to import models from Caffe and from other frameworks using the ONNX interchange format. It covers the topic of deep learning accelerators such as CPU and GPU and shows how to deploy Caffe2 models for inference on accelerators using inference engines. Caffe2 is built for deployment to a diverse set of hardware, using containers on the cloud and resource constrained hardware such as Raspberry Pi, which will be demonstrated. By the end of this book, you will be able to not only compose and train popular neural network models with Caffe2, but also be able to deploy them on accelerators, to the cloud and on resource constrained platforms such as mobile and embedded hardware. What you will learn * Build and install Caffe2 * Compose neural networks * Train neural network on CPU or GPU * Import a neural network from Caffe * Import deep learning models from other frameworks * Deploy models on CPU or GPU accelerators using inference engines * Deploy models at the edge and in the cloud Who this book is for Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.

Learn end-to-end automation testing techniques for web and mobile browsers using Selenium WebDriver, AppiumDriver, Java, and TestNG Key Features * Explore the Selenium grid architecture and build your own grid for browser and mobile devices * Use ExtentReports for processing results and SauceLabs for cloud-based test services * Unlock the full potential of Selenium to test your web applications. Book Description Selenium WebDriver 3.x is an open source API for testing both browser and mobile applications. With the help of this book, you can build a solid foundation and can easily perform end-to-end testing on web and mobile browsers.You'll begin by being introduced to the Selenium Page Object Model for software development. You'll architect your own framework with a scalable driver class, Java utility classes, and support for third-party tools and plugins. You'll design and build a Selenium grid from scratch to enable the framework to scale and support different browsers, mobile devices, and platforms.You'll strategize and handle a rich web UI using the advanced WebDriver API and learn techniques to handle real-time challenges in WebDriver. You'll perform different types of testing, such as cross-browser testing, load testing, and mobile testing. Finally, you will also be introduced to data-driven testing, using TestNG to create your own automation framework.By the end of this Learning Path, you'll be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. This Learning Path includes content from the following Packt products: * Selenium WebDriver 3 Practical Guide - Second Edition by Unmesh Gundecha * Selenium Framework Design in Data-Driven Testing by Carl Cocchiaro What you will learn * Use different mobile and desktop browser platforms with Selenium 3 * Use the Actions API for performing various keyboard and mouse actions * Design the Selenium Driver Class for local, remote, and third-party grid support * Build page object classes with the Selenium Page Object Model * Develop data-driven test classes using the TestNG framework * Encapsulate data using the JSON protocol * Build a Selenium Grid for RemoteWebDriver testing * Build and use utility classes in synchronization, file I/O, reporting and test listener classes Who this book is for This Learning Path is ideal for software quality assurance/testing professionals, software project managers, or software developers interested in using Selenium for testing their applications. Professionals responsible for designing and building enterprise-based testing frameworks will also find this Learning Path useful. Prior programming experience in Java are TestNG is necessary.

Enhance your development skills with Java’s state-of-the-art features and projects to make your applications leaner and faster Key Features * Overcome the challenges involved in migrating to new versions of Java * Discover how Oracle has bridged the gap between Java and native code * Make the best use of new Java features and libraries in your applications Book Description With its new six-monthly release cadence, Java is moving forward faster. In addition to planned version releases, a lot of work is currently being undertaken on various Java projects at Oracle. In order to make best use of the new features in their applications and libraries, you must be well-versed with the most recent advancements. Java 11 and 12 – New Features will take you through the latest developments in Java, right from variable type inference and simplified multithreading through to performance improvements, which are covered in depth to help you make your applications more efficient. This book explains the relevance and applicability of Java's new features, and answers your questions on whether to invest in migrating to new Java versions and when to migrate. You'll also get to grips with platform features, such as AppCDS and new garbage collectors, to tune and optimize your application—from reduced launch time and latency to improved performance and throughput. By the end of this book, you will be equipped with a thorough understanding of the new features of Java 11, 12, and Project Amber, and possess the skills to apply them with a view to improving your application's performance. What you will learn * Study type interference and how to work with the var type * Understand Class-Data Sharing, its benefits, and limitations * Discover platform options to reduce your application’s launch time * Improve application performance by switching garbage collectors * Get up to date with the new Java release cadence * Define and assess decision criteria for migrating to a new version of Java Who this book is for If you’re an executive or solutions architect responsible for technology selection or Java migration decisions, this Java book is for you. You’ll also benefit from this book if you’re a computer science enthusiast curious to learn about the latest and upcoming Java features. This book will help you migrate your solutions from Java 8 or older to the latest Java release.

Learn to create and customize impressive Drupal 8 modules to extend your website's functionalities Key Features * Explore a plethora of Drupal 8 APIs and get the best out of them using the power of PHP coding * Learn to implement efficient data management and data security by creating dedicated modules for it. * Stay up to date with the changes introduced in the new Drupal 8 releases Book Description Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7. The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries. You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general. By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you’ll even contribute it back to the Drupal community. What you will learn * Develop Drupal 8 modules that do all the things you want * Master numerous Drupal 8 sub-systems and APIs in the process * Model, store, manipulate and process data to serve your purposes * Display data and content in a clean and secure way using the Drupal 8 theme system * Test your business logic to prevent regressions * Stay ahead of the curve and write code following the current best practices Who this book is for The primary target of this book is Drupal developers who want to learn how to write modules and develop in Drupal 8. It is also intended for Drupal site builders and PHP developers who have basic Object Oriented Programming skills. A little bit of Symfony experience is helpful but not mandatory.

Discover advanced virtualization techniques and strategies to deliver centralized desktop and application services Key Features * Leverage advanced desktop virtualization techniques and strategies to transform your organization * Build better virtualized services for your users with VMware Horizon 7.8 * Develop and deploy end-to-end virtualized solutions Book Description Desktop virtualization can be tough, but VMware Horizon 7.8 changes all that. With a rich and adaptive UX, improved security,and a range of useful features for storage and networking optimization, there's plenty to love. But to properly fall in love with it, you need to know how to use it, and that means venturing deeper into the software and taking advantage of its extensive range of features, many of which are underused and underpromoted. This guide will take you through everything you need to know to not only successfully virtualize your desktop infrastructure, but also to maintain and optimize it to keep all your users happy. We'll show you how to assess and analyze your infrastructure, and how to use that analysis to design a solution that meets your organizational and user needs. Once you've done that, you'll find out how to build your virtualized environment, before deploying your virtualized solution. But more than that,we'll also make sure you know everything you need to know about the full range of features on offer, including the mobile cloud, so that you can use them to take full control of your virtualized infrastructure. What you will learn * Successfully configure Horizon 7.8 for the needs of your users * Deliver virtual desktops, session-based desktops, and hosted applications * Become familiar with how to develop, and deploy, a complete, end-to-end solution * Discover how to optimize desktop OS images for virtual desktops * Build, optimize, and tune desktop operating systems to deliver a superior end user experience * Explore the Horizon 7.8 infrastructure so that you can take full advantage of it Who this book is for This book is ideal for system admins, and solution architects interested in gaining hands-on experience with virtualization. It will take you to an advanced level, but at a pace that ensures you are always solving real-world problems. Some experience in desktop management using Windows and Microsoft Office (and familiarity with Active Directory, SQL, Windows Remote Desktop Session Hosting, and VMware vSphere technology) is necessary.

A comprehensive guide to understanding network architecture, communication protocols, and network analysis to build secure applications compatible with the latest versions of C# 8 and .NET Core 3.0 Key Features * Explore various network architectures that make distributed programming possible * Learn how to make reliable software by writing secure interactions between clients and servers * Use .NET Core for network device automation, DevOps, and software-defined networking Book Description The C# language and the .NET Core application framework provide the tools and patterns required to make the discipline of network programming as intuitive and enjoyable as any other aspect of C# programming. With the help of this book, you will discover how the C# language and the .NET Core framework make this possible. The book begins by introducing the core concepts of network programming, and what distinguishes this field of programming from other disciplines. After this, you will gain insights into concepts such as transport protocols, sockets and ports, and remote data streams, which will provide you with a holistic understanding of how network software fits into larger distributed systems. The book will also explore the intricacies of how network software is implemented in a more explicit context, by covering sockets, connection strategies such as Transmission Control Protocol (TCP) and User Datagram Protocol (UDP), asynchronous processing, and threads. You will then be able to work through code examples for TCP servers, web APIs served over HTTP, and a Secure Shell (SSH) client. By the end of this book, you will have a good understanding of the Open Systems Interconnection (OSI) network stack, the various communication protocols for that stack, and the skills that are essential to implement those protocols using the C# programming language and the .NET Core framework. What you will learn * Understand the breadth of C#'s network programming utility classes * Utilize network-layer architecture and organizational strategies * Implement various communication and transport protocols within C# * Discover hands-on examples of distributed application development * Gain hands-on experience with asynchronous socket programming and streams * Learn how C# and the .NET Core runtime interact with a hosting network * Understand a full suite of network programming tools and features Who this book is for If you're a .NET developer or a system administrator with .NET experience and are looking to get started with network programming, then this book is for you. Basic knowledge of C# and .NET is assumed, in addition to a basic understanding of common web protocols and some high-level distributed system designs.

Start empowering users and protecting corporate data, while managing identities and access with Microsoft Azure in different environments Key Features * Understand how to identify and manage business drivers during transitions * Explore Microsoft Identity and Access Management as a Service (IDaaS) solution * Over 40 playbooks to support your learning process with practical guidelines Book Description Microsoft Azure and its Identity and access management are at the heart of Microsoft's software as service products, including Office 365, Dynamics CRM, and Enterprise Mobility Management. It is crucial to master Microsoft Azure in order to be able to work with the Microsoft Cloud effectively. You’ll begin by identifying the benefits of Microsoft Azure in the field of identity and access management. Working through the functionality of identity and access management as a service, you will get a full overview of the Microsoft strategy. Understanding identity synchronization will help you to provide a well-managed identity. Project scenarios and examples will enable you to understand, troubleshoot, and develop on essential authentication protocols and publishing scenarios. Finally, you will acquire a thorough understanding of Microsoft Information protection technologies. What you will learn * Apply technical descriptions to your business needs and deployments * Manage cloud-only, simple, and complex hybrid environments * Apply correct and efficient monitoring and identity protection strategies * Design and deploy custom Identity and access management solutions * Build a complete identity and access management life cycle * Understand authentication and application publishing mechanisms * Use and understand the most crucial identity synchronization scenarios * Implement a suitable information protection strategy Who this book is for This book is a perfect companion for developers, cyber security specialists, system and security engineers, IT consultants/architects, and system administrators who are looking for perfectly up–to-date hybrid and cloud-only scenarios. You should have some understanding of security solutions, Active Directory, access privileges/rights, and authentication methods. Programming knowledge is not required but can be helpful for using PowerShell or working with APIs to customize your solutions.

Conquer complex and interesting programming challenges by building robust and concurrent applications with caches, cryptography, and parallel programming. Key Features * Understand how to use .NET frameworks like the Task Parallel Library (TPL)and CryptoAPI * Develop a containerized application based on microservices architecture * Gain insights into memory management techniques in .NET Core Book Description This Learning Path shows you how to create high performing applications and solve programming challenges using a wide range of C# features. You’ll begin by learning how to identify the bottlenecks in writing programs, highlight common performance pitfalls, and apply strategies to detect and resolve these issues early. You'll also study the importance of micro-services architecture for building fast applications and implementing resiliency and security in .NET Core. Then, you'll study the importance of defining and testing boundaries, abstracting away third-party code, and working with different types of test double, such as spies, mocks, and fakes. In addition to describing programming trade-offs, this Learning Path will also help you build a useful toolkit of techniques, including value caching, statistical analysis, and geometric algorithms. This Learning Path includes content from the following Packt products: * C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan * Practical Test-Driven Development using C# 7 by John Callaway, Clayton Hunt * The Modern C# Challenge by Rod Stephens What you will learn * Measure application performance using BenchmarkDotNet * Leverage the Task Parallel Library (TPL) and Parallel Language Integrated Query (PLINQ)library to perform asynchronous operations * Modify a legacy application to make it testable * Use LINQ and PLINQ to search directories for files matching patterns * Find areas of polygons using geometric operations * Randomize arrays and lists with extension methods * Use cryptographic techniques to encrypt and decrypt strings and files Who this book is for If you want to improve the speed of your code and optimize the performance of your applications, or are simply looking for a practical resource on test driven development, this is the ideal Learning Path for you. Some familiarity with C# and .NET will be beneficial.

Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features * Turn your designs into working software by learning the Python syntax * Write robust code with a solid understanding of Python data structures * Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: * Learn Python Programming - Second Edition by Fabrizio Romano * Python Data Structures and Algorithms by Benjamin Baka * Python 3 Object-Oriented Programming by Dusty Phillips What you will learn * Use data structures and control flow to write code * Use functions to bundle together a sequence of instructions * Implement objects in Python by creating classes and defining methods * Design public interfaces using abstraction, encapsulation and information hiding * Raise, define, and manipulate exceptions using special error objects * Create bulletproof and reliable software by writing unit tests * Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.