Kivy Interactive Applications And Games In Python Second Edition
Kivy Interactive Applications And Games In Python Second Edition Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Kivy Interactive Applications And Games In Python Second Edition book. This book definitely worth reading, it is an incredibly well-written.
Kivy - Interactive Applications and Games in Python Second Edition by Roberto Ulloa Pdf
If you are a Python developer who wants to create exciting and dynamic UI/UX applications that are compatible with multiple platforms, then this is the book for you. No prior experience with Kivy is required, although you should be familiar with Python and have a fair understanding of software engineering concepts such as inheritance, classes, and instances.
Kivy – Interactive Applications and Games in Python by Roberto Ulloa Pdf
Kivy – Interactive Applications and Games in Python Second Edition, will equip you with all the necessary knowledge to create interactive, responsive, and cross-platform applications and games. This book introduces the Kivy language and the necessary components so you can implement a graphical user interface (GUI) and learn techniques to handle events, detect gestures, and control multi-touch actions. You will learn strategies to animate your applications, and obtain interactive, professional-looking, and responsive results. You will be applying this knowledge throughout the book by developing three applications and tackling their diverse programming challenges.
For Python developers this is the clearest guide to the interactive world of Kivi, ideal for meeting modern expectations of tablets and smartphones. From building a UI to controlling complex multi-touch events, it's all here. Overview Use Kivy to implement apps and games in Python that run on multiple platforms Discover how to build a User Interface (UI) through the Kivy Language Glue the UI components with the logic of the applications through events and the powerful Kivy properties Detect gestures, create animations, and schedule tasks Control multi-touch events in order to improve the User Experience (UX) In Detail Mobiles and tablets have brought with them a dramatic change in the utility of applications. Compatibility has become essential, and this has increased the kind of interaction that users expect: gestures, multi-touches, animations, and magic pens. Kivy is an open source Python solution that covers these market needs with an easy-to-learn and rapid development approach. Kivy is growing fast and gaining attention as an alternative to the established developing platforms. Kivy: Interactive Applications in Python quickly introduces you to the Kivy development methodology. You will learn some examples of how to use many of the Kivy components, as well as understand how to integrate and combine them into big projects. This book serves as a reference guide and is organized in such a way that once finished, you will have already completed your first project. You will start by learning the Kivy Language for building User Interfaces (UI) and vector figures. We then proceed to the uses of Kivy events and properties to glue the UI with the application logic. You then go on to build an entire User Interface (UI) starting from a hand-made sketch. Furthermore, you will go on to understand how to use the canvas and drawing instructions to create different types of geometrical figures. Finally, you will be introduced to a big set of interactive and smooth features: transformations (scale, rotate, and translate), gestures, animations, scheduling tasks, and multi-touch elements. Kivy: Interactive Applications in Python expands your knowledge by introducing various components that improve the User Experience (UX). Towards the end of the book, you will be confident to utilize Kivy components and strategies to start any application or game you have in mind. What you will learn from this book Build a User Interface (UI) using the Kivy Language Understand and alter the order of execution of the drawing instructions Use the powerful Kivy properties to keep the UI always updated with the last user interactions Bind and unbind Kivy events to control widgets (UI components), touches, the mouse and keyboard, animations, and clock Scale, rotate, and translate widgets Control and switch between different screens Develop and use your own single gestures Create animations and combine them to bring widgets to life Add different types of translations to the animations Comprehend the main strategies to control the multi-touch events Schedule single or repetitive tasks such as animations Approach Kivy: Interactive Applications in Python is an easy-to-follow book that will guide you into the world of Kivy. Who this book is written for This book is aimed at Python developers who are familiar with Python and have a good understanding of concepts like inheritance, classes, and instances. No previous experience of Kivy is required, though some knowledge of event handling, scheduling, and user interfaces, in general, would boost your learning.
This book is intended for programmers who are comfortable with the Python language and who want to build desktop and mobile applications with rich GUI in Python with minimal hassle. Knowledge of Kivy is not strictly required—every aspect of the framework is described when it's first used.
Building Android Apps in Python Using Kivy with Android Studio by Ahmed Fawzy Mohamed Gad Pdf
Start building Python-based Android applications using Kivy with Android Studio. Through in-depth examples, this book teaches you everything you need to create your first Android application in Python and publish on Google Play. Building Android Apps in Python Using Kivy with Android Studio takes you through the basics of Kivy by discussing its application structure, widgets, and event handling. The KV language is then introduced for separating the logic and GUI by adding widgets within a KV file. You will then learn how to utilize Android camera using Kivy, build the HTTP server using Flask, and create and manage multiple screens to help you design your own applications. Through detailed step-by-step instructions, you will create your first multi-level cross-platform game that includes animation and sound effects. Following this, the process of converting the Kivy application into an Android application using Buildozer and Python-4-Android is covered in detail. You will then learn how to edit the generated Android Studio project into Android Studio by adding extensions to the original application. The widgets added in Kivy could be handled within Android Studio. Moreover, Android views could be added to enrich the Kivy application. The resulting Android application created with Kivy can be hosted on Google Play to download and install as a regular Android application. At the end, this book will give you the basic knowledge of Kivy needed to build cross-platform Android applications, produce an Android Studio project, and understand how it all works in detail. What You Will Learn Build cross-platform applications from scratch using Kivy in detailCreate a cross-platform interactive multi-level game from the ground upExamine the pipeline of building an Android app from the Python Kivy appUnderstand the structure of the Android Studio project produced by KivyRecognize how to extend the application within Android Studio by adding more Android views to the application main activity. Who This Book Is For Python developers with no previous experience in Kivy who are looking to create their first Android application completely in Python.
Introduction to Computation and Programming Using Python, second edition by John V. Guttag Pdf
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Build mobile apps efficiently with Kivy, the Python-powered graphical toolkit for creating natural user interfaces with elegant multitouch support. With this hands-on guide, you’ll learn step-by-step how to build and deploy a complete Kivy app for iOS and Android devices. If you’re just beginning to work with Python, but are reasonably familiar with its syntax, you’re ready to go. Each chapter includes exercises, using examples that run on Python 3 and Python 2.7. Learn how Kivy simplifies mobile development with its cross-platform API and domain-specific Kv language, and why this free and open source toolkit is ideal for commercial products. Design custom widgets with the Kv language Delve into Kivy events, event handlers, and properties Dynamically change which Kivy widgets are displayed Understand and apply iterative development principles Create basic animations, using Canvas and graphics primitives Store local data with Kivy’s powerful key value store Add basic gestures to switch between app views Improve your app’s usability with Kivy’s built-in widgets Deploy the app to your Android or iOS device, using Buildozer
Kivy: Interactive Applications in Python by Roberto Ulloa Pdf
This book is aimed at Python developers who are familiar with Python and have a good understanding of concepts like inheritance, classes, and instances. No previous experience of Kivy is required, though some knowledge of event handling, scheduling, and user interfaces, in general, would boost your learning.
You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work with files Looping and logic Data structures using lists and dictionaries Program design Object-oriented programming Inheritance and composition Modules, classes, and objects Python packaging Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3
Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.
Enhance your skills in developing multi-touch applications with Kivy About This Book Create most diverse apps and learn how to distribute them with the help of the Kivy framework Explore Kivy API to develop user interfaces and control multi-touch events Step-by-step recipes that provide deeper understanding of the Kivy 1.9.0 framework Build and use your own events, widgets and gestures using features and tools in Kivy Who This Book Is For This book is intended for developers who want to use features of the Kivy framework and develop multi-touch applications. Prior experience with Kivy is not required, although familiarity with Python is expected. What You Will Learn Access widgets defined inside Kv language in your Python code Handle Kivy events to control widgets, touches, the mouse, the keyboard, and animations Recognize touch shapes and detecting multi-tapping Create custom events and declare properties Organizing your layouts while working with the ActionBar Store and retrieve the coordinate space context Create your own shader and render in a framebuffer Leverage Factory objects, multi-touch in iOS and multi-touch in Android In Detail Kivy is an open-source Python library for rapid development of applications that make use of innovative user interfaces, such as multi-touch apps. It is a promising Python framework to develop UI and UX apps in a cross-platform environment, under the Python philosophy. Kivy Cookbook is a practical book that will guide you through the Kivy framework to develop apps and get your apps ready for distribution in App Store and Android devices. You will start off with installing Kivy and building your interfaces. You will learn how to work the accelerometer and create custom events. Then, you will understand how to use the basics, buttons, labels and text inputs and manipulate the widget tree. Next, you will be able to work with manipulating instructions, create an atlas and layouts. Moving on, you will learn packing for Windows and packing for iOS, and use TestDrive. By the end of the book, you will have learnt in detail the relevant features and tools in Kivy and how to create portable packages to distribute your apps in the most used platforms. Style and approach This is an easy-to-follow practical guide packed with graspable recipes that cover important tasks to be performed while developing multi-touch applications with Kivy. All the code used in each recipe is explained in detail.
Julia 1.0 Programming Complete Reference Guide by Ivo Balbaert,Adrian Salceanu Pdf
Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key FeaturesLeverage Julia's high speed and efficiency to build fast, efficient applicationsPerform supervised and unsupervised machine learning and time series analysisTackle problems concurrently and in a distributed environmentBook Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo BalbaertJulia Programming Projects by Adrian SalceanuWhat you will learnCreate your own types to extend the built-in type systemVisualize your data in Julia with plotting packagesExplore the use of built-in macros for testing and debuggingIntegrate Julia with other languages such as C, Python, and MATLABAnalyze and manipulate datasets using Julia and DataFramesDevelop and run a web app using Julia and the HTTP packageBuild a recommendation system using supervised machine learningWho this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.
Learning Data Mining with Python by Robert Layton Pdf
The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK. Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.
This is a great book for Python Beginner and Advanced Learner which covers Basics to Advanced Python Programming where each topic is explained with the help of Illustrations and Examples. More than 450 solved programs of this book are tested in Python 3.4.3 for windows. The range of Python Topics covered makes this book unique which can be used as a self study material or for instructor assisted teaching. This books covers Python Syllabus of all major national and international universities. Also it includes frequently asked questions for interviews and examination which are provided at the end of each chapter.
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data
