Learning Embedded Android N Programming. Click here to enter text

Stefano Viola, Ivan Morgillo

Take a deep dive into the Android build system and its customization with Learning Embedded Android Programming, written to help you master the steep learning curve of working with embedded Android. Start by exploring the basics of Android OS, discover Google’s “repo” system, and discover how to retrieve AOSP source code. You'll then find out to set up the build environment and the first AOSP system. Next, learn how to customize the boot sequence with a new animation, and use an Android “kitchen” to “cook” your custom ROM. By the end of the book, you'll be able to build customized Android open source projects by developing your own set of features.

Learning Embedded Linux Using the Yocto Project. Develop powerful embedded Linux systems with the Yocto Project components

Alexandru Vaduva, Vaduva Jan Alexandru

Learning Ext JS. Create powerful web applications with the new and improved Ext JS 5 library

Carlos A Mendez Segura, Crysfel Villa, Armando Gonzalez, CARLOS ALBERTO MÉNDEZ SEGURA

Learning F# Functional Data Structures and Algorithms. Get started with F# and explore functional programming paradigm with data structures and algorithms

Adnan Masood

Learning Firefox OS Application Development. Learn to design, build, and deploy your Firefox OS applications, built with web technologies, to the Firefox Marketplace

Tanay Pant

With broad compatibility, the latest in web technologies, and powerful development tools, Firefox is a great choice for both web developers and end users. Firefox OS’s promotion of HTML5 as a first class citizen opens up the walled gardens of mobile application development for web developers. It is because of this initiative that no special SDKs are required to develop for Firefox OS. This book will help you excel in the art of developing applications for Firefox OS. It sequentially covers knowledge building, skills acquisition, and practical applications. Starting with an introduction to Firefox OS, usage of WebIDE, and then the application structure, this book introduces applications of increasing complexity with each chapter. An application that measures your tapping speed, a geolocation tagging application, and a photo editing and sharing application are the three applications that will be built from scratch. You will learn about topics such as the difference between various types of Firefox OS applications, application manifest files, offline apps, and designing principles for applications. You will also learn to test and submit the applications to the marketplace and finally maintain the repository of the Firefox OS application. By the end, you will be able to develop beautifully designed, fully-fledged, and rigorously tested Firefox OS applications and also share them at the Firefox OS Marketplace.

Learning Flask Framework. Build dynamic, data-driven websites and modern web applications with Flask

Charles Leifer, Matthew Copperwaite

Learning Force.com Application Development. Use the Force.com platform to design and develop real-world, cutting-edge cloud applications

Chamil Madusanka

Learning Functional Data Structures and Algorithms. Click here to enter text

Atul S. Khot, Raju Kumar Mishra

Functional data structures have the power to improve the codebase of an application and improve efficiency. With the advent of functional programming and with powerful functional languages such as Scala, Clojure and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread safe by definition and hence very appealing for writing robust concurrent programs. How do we express traditional algorithms in functional setting? Won’t we end up copying too much? Do we trade performance for versioned data structures? This book attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidation of what functional programming is all about. Next, you’ll get to know about Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make immutable data structures efficient and practical. Scala is the primary implementation languages for most of the examples. At times, we also present Clojure snippets to illustrate the underlying fundamental theme. While writing code, we use ADTs (abstract data types). Stacks, Queues, Trees and Graphs are all familiar ADTs. You will see how these ADTs are implemented in a functional setting. We look at implementation techniques like amortization and lazy evaluation to ensure efficiency.By the end of the book, you will be able to write efficient functional data structures and algorithms for your applications.

Learning Functional Programming in Go. Change the way you approach your applications using functional programming in Go

Lex Sheehan

Lex Sheehan begins slowly, using easy-to-understand illustrations and working Go code to teach core functional programming (FP) principles such as referential transparency, laziness, recursion, currying, and chaining continuations.This book is a tutorial for programmers looking to learn FP and apply it to write better code. Lex guides readers from basic techniques to advanced topics in a logical, concise, and clear progression.The book is divided into four modules. The first module explains the functional style of programming: pure functional programming, manipulating collections, and using higher-order functions. In the second module, you will learn design patterns that you can use to build FP-style applications. In the next module, you will learn FP techniques that you can use to improve your API signatures, increase performance, and build better cloud-native applications. The last module covers Category Theory, Functors, Monoids, Monads, Type classes and Generics.By the end of the book, you will be adept at building applications the FP way.

Learning Game AI Programming with Lua. Leverage the power of Lua programming to create game AI that focuses on motion, animation, and tactics

David Young

Learning GDScript by Developing a Game with Godot 4. A fun introduction to programming in GDScript 2.0 and game development using the Godot Engine

Sander Vanhove

In the digital landscape driven by interactive experiences, the demand for creative individuals with the skills to create captivating games has never been higher. Written by Sander Vanhove, a seasoned game developer with over 20 games to his credit, this book will serve as your entry point into game development, showing you how to leverage the powerful features of the open-source, versatile GDScript 2.0 to develop your ideas, from simple platformers to complex RPGs.Whether you're an aspiring game developer, a hobbyist seeking a creative outlet, or simply someone intrigued by the world of game programming, this book will guide you through the intricacies of the Godot 4 game engine. Starting with a primer on the fundamentals of programming, you’ll cover everything from data to logic, while familiarizing yourself with Godot’s built-in tools such as the physics engine, navigation, and cameras. As you progress, you’ll unlock deeper insights into more advanced tools that will take your programming to the next level. Aided by easy-to-follow step-by-step tutorials, examples, exercises, and experiments, you’ll seamlessly integrate this newfound knowledge to create a Vampire Survivor-like game from scratch.By the end of this book, you’ll have become proficient in leveraging the Godot 4 game engine to bring your gaming visions to life.

Learning Geospatial Analysis with Python. An effective guide to geographic information systems and remote sensing analysis using Python 3

Joel Lawhead

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data.This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.

Learning Geospatial Analysis with Python. If you know Python and would like to use it for Geospatial Analysis this book is exactly what you've been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how

Joel Lawhead

Geospatial analysis is used in almost every field you can think of from medicine, to defense, to farming. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data.Learning Geospatial Analysis with Python uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms.Learning Geospatial Analysis with Python starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data.This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don't become bogged down in just getting ready to do analysis.Learning Geospatial Analysis with Python will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.

Learning Geospatial Analysis with Python. Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7 - Third Edition

Joel Lawhead

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python.This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data.By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.

Learning Geospatial Analysis with Python. Unleash the power of Python 3 with practical techniques for learning GIS and remote sensing - Fourth Edition

Joel Lawhead

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python.This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products.By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.

Learning Go Programming. Click here to enter text

Vladimir Vivien, Parth Desai

The Go programming language has firmly established itself as a favorite for building complex and scalable system applications. Go offers a direct and practical approach to programming that let programmers write correct and predictable code using concurrency idioms and a full-featured standard library.This is a step-by-step, practical guide full of real world examples to help you get started with Go in no time at all. We start off by understanding the fundamentals of Go, followed by a detailed description of the Go data types, program structures and Maps. After this, you learn how to use Go concurrency idioms to avoid pitfalls and create programs that are exact in expected behavior. Next, you will be familiarized with the tools and libraries that are available in Go for writing and exercising tests, benchmarking, and code coverage. Finally, you will be able to utilize some of the most important features of GO such as, Network Programming and OS integration to build efficient applications. All the concepts are explained in a crisp and concise manner and by the end of this book; you would be able to create highly efficient programs that you can deploy over cloud.