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Coding For Dummies, All New Edition
Your first step toward thinking like a coder Coding For Dummies is one of the most popular get-started guides for new coders. This all- new edition demystifies essential coding concepts before diving into building simple apps in Python and JavaScript. For anyone brand-new to writing code, this book is an ideal first step, because you'll get an overview of how coding works, the essential tools of coding, and how to apply coding in different ways. Plus, you'll get insight into how new tools like AI can quickly boost your coding know-how. Enter the world of code with this easy-to-follow Dummies guide! Learn the basics of coding, including key concepts you'll need in every coding languageGet a rundown of the most popular language, and start coding in JavaScript and PythonFollow step-by-step instructions to build your first appsDiscover how AI can help you become a better, faster coder Looking for a foundation in the basics of coding, plus simple tasks to help you get started? Coding For Dummies is the book for you.
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Solid Mechanics With Python: Non-cartesian Coordinates
This comprehensive volume covers the fundamental principles of solid mechanics, focusing on the mechanical behavior of solids in two and three dimensions under various types of loads. The solids are defined in non-Cartesian coordinate systems, such as polar, cylindrical, and spherical coordinate systems.The methodology and techniques to solve solid mechanics problems are explained in detail, formulated and demonstrated with numerous examples and illustrations. Two major approaches, the stress method and the displacement method, are introduced. Python is used for formulation derivation, solving problems symbolically or numerically, and plotting results graphically.Written in Jupyter notebook format, this useful reference text offers a unified environment for theory description, code execution, and formulation, for easy reading and practicing.
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Raspberry Pi Supercomputing and Scientific Programming
Build an inexpensive cluster of multiple Raspberry Pi computers and install all the required libraries to write parallel and scientific programs in Python 3. This book covers setting up your Raspberry Pis, installing the necessary software, and making a cluster of multiple Pis. Once the cluster is built, its power has to be exploited by means of programs to run on it. So, Raspberry Pi Supercomputing and Scientific Programming teaches you to code the cluster with the MPI4PY library of Python 3. Along the way, you will learn the concepts of the Message Passing Interface (MPI) standards and will explore the fundamentals of parallel programming on your inexpensive cluster. This will make this book a great starting point for supercomputing enthusiasts who want to get started with parallel programming. The book finishes with details of symbolic mathematics and scientific and numerical programming in Python, using SymPi, SciPy, NumPy, and Matplotlib. You’ll see how to process signals and images, carry out calculations using linear algebra, and visualize your results, all using Python code. With the power of a Raspberry Pi supercomputer at your fingertips, data-intensive scientific programming becomes a reality at home.What You Will Learn Discover the essentials of supercomputingBuild a low-cost cluster of Raspberry Pis at homeHarness the power of parallel programming and the Message Passing Interface (MPI)Use your Raspberry Pi for symbolic, numerical, and scientific programmingWho This Book Is ForPython 3 developers who seek the knowledge of parallel programming, Raspberry Pi enthusiasts, researchers, and the scientific Python community.
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MCP Standard
Master the art of building feature-rich Model Context Protocol (MCP) servers in TypeScript, by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor. In the world of AI development mired in a chaotic mess of proprietary, incompatible APIs, the Model Context Protocol is the open standard that will become the universal language for AI tools. This book will be your invaluable companion for understanding this solution. The book takes you on a full, hands-on journey through MCP, looking at it not just as a technical specification but also as a way to help AI-native transformation. It first finds the "why", the tool's issue -- and shows how MCP is the only logical solution. After that, the book goes into deep detail about the protocol's architecture, breaking down the roles of the Host, Client, and Server, and giving you a guide to its main language of Tools, Resources, and Prompts. Using the official TypeScript SDK, you will learn how to build a full-featured MCP server from scratch. You will learn best practices for everything from schema design with Zod to adding advanced features like elicitation and server-side sampling. The book is unique in its holistic approach. It doesn't just tell you how to do something; it also has a whole section on production readiness and security that talks about the MCP security model, threat landscapes, and client-side hardening. This book will give developers, architects, and technical leaders not only the tactical skills they need to succeed in the next wave of software development but also the strategic vision they need to do so. By the end of this book, you will not only have learnt how to use the MCP, but you will have gained a deep understanding of MCP in the context of the larger shift from cloud-native to AI-native. You Will Learn To: Master the art of building feature-rich MCP servers in TypeScript, from basic tools to advanced capabilities like elicitation, resource linking, and server-side sampling.Understand the complete MCP architecture and protocol specification, enabling you to debug complex interactions and build custom clients or servers.Implement a robust, multi-layered security strategy for your MCP deployments, including authentication, authorization, and client-side hardening against common threats.Solve the "M x N" integration problem by designing decoupled, scalable, and future-proof AI systems that are not locked into a single model vendor.Gain a strategic understanding of MCP's role in the broader AI-native transformation, which empowers you to make informed architectural decisions for your organization. This Book is For: Software developers, AI engineers, and solutions architects who are creating apps that interface with large language models should read this book.
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Introduction to Numerical Programming
Makes Numerical Programming More Accessible to a Wider AudienceBearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-HowThe book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionalityContains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problemsAddresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysisThis text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
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Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
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Mathematical Methods using Python
This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy).
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JavaScript : Object-Oriented Programming
Build sophisticated web applications by mastering the art of Object-Oriented JavascriptAbout This Book* Learn popular Object-Oriented programming (OOP) principles and design patterns to build robust apps* Implement Object-Oriented concepts in a wide range of frontend architectures* Capture objects from real-world elements and create object-oriented code that represents them* Learn the latest ES6 features and how to test and debug issues with JavaScript code using various modern mechanismsWho This Book Is ForJavaScript developers looking to enhance their web developments skills by learning object-oriented programming.What You Will Learn* Get acquainted with the basics of JavaScript language constructs along with object-oriented programming and its application.* Learn to build scalable server application in JavaScript using Node.js* Generate instances in three programming languages: Python, JavaScript, and C#* Work with a combination of access modifiers, prefixes, properties, fields, attributes, and local variables to encapsulate and hide data* Master DOM manipulation, cross-browser strategies, and ES6* Identify and apply the most common design patterns such as Singleton, Factory, Observer, Model-View-Controller, and Mediator Patterns* Design applications using a modular architecture based on SOLID principlesIn DetailJavaScript is the behavior, the third pillar in today's paradigm that looks at web pages as something that consists of : content (HTML), presentation (CSS), and behavior (JavaScript). Using JavaScript, you can create interactive web pages along with desktop widgets, browser, and application extensions, and other pieces of software. Object-oriented programming, which is popularly known as OOP, is basically based on the concept of objects rather than actions.The first module will help you master JavaScript and build futuristic web applications. You will start by getting acquainted with the language constructs and how to organize code easily. You develop concrete understanding of variable scoping, loops, and best practices on using types and data structures, as well as the coding style and recommended code organization patterns in JavaScript. The book will also teach you how to use arrays and objects as data structures. By the end of the book, you will understand how reactive JavaScript is going to be the new paradigm.The second module is an easy-to-follow course, which includes hands-on examples of solutions to common problems with object-oriented code. It will help to identify objects from real-life scenarios, to protect and hide data with the data encapsulation features of Python, JavaScript, and C#. You will discover the advantage of duck typing in both Python and JavaScript, while you work with interfaces and generics in C#. With a fair understanding of interfaces, multiple inheritance, and composition, you will move on to refactor existing code and to organize your source for easy maintenance and extension.The third modul
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Learn Robotics Programming
Gain experience of building a next-generation collaboration robotKey FeaturesGet up and running with the fundamentals of robotic programmingProgram a robot using Python and the Raspberry Pi 3Learn to build a smart robot with interactive and AI-enabled behaviorsBook DescriptionWe live in an age where the most difficult human tasks are now automated. Smart and intelligent robots, which will perform different tasks precisely and efficiently, are the requirement of the hour. A combination of Raspberry Pi and Python works perfectly when making these kinds of robots. Learn Robotics Programming starts by introducing you to the basic structure of a robot, along with how to plan, build, and program it. As you make your way through the book, you will gradually progress to adding different outputs and sensors, learning new building skills, and writing code for interesting behaviors with sensors. You'll also be able to update your robot, and set up web, phone, and Wi-Fi connectivity in order to control it. By the end of the book, you will have built a clever robot that can perform basic artificial intelligence (AI) operations.What you will learnConfigure a Raspberry Pi for use in a robotInterface motors and sensors with a Raspberry PiImplement code to make interesting and intelligent robot behaviorsUnderstand the first steps in AI behavior such as speech recognition visual processingControl AI robots using Wi-FiPlan the budget for requirements of robots while choosing partsWho this book is forLearn Robotics Programming is for programmers, developers, and enthusiasts interested in robotics and developing a fully functional robot. No major experience required just some programming knowledge would be sufficient.
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Beyond Vibe Coding
AI is transforming software development, shifting programmers from writing code to collaborating with AI in an intent-driven workflow-this is vibe coding. Vibe Coding: The Future of Programming explores how AI-powered coding assistants like GitHub Copilot and OpenAI Codex are reshaping the way we build software, from automating routine coding tasks to influencing architecture and design decisions.Written by Addy Osmani, this guide provides developers, tech leads, and organizations with practical strategies to integrate AI into their workflows effectively. Learn how to refine AI-generated code, master prompt engineering, and explore advanced techniques like model fine-tuning and multi-agent coding systems. Whether you're adopting AI tools today or preparing for the future of software engineering, this book offers insights and hands-on examples to keep your skills sharp in this evolving landscape.Understand how AI-assisted development is reshaping programmingMaster techniques for refining, validating, and debugging AI-generated codeExplore multi-agent coding systems and AI-driven software workflowsFuture-proof your career by adapting to AI's growing role in development
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Multi-Agent Programming:
Multi-Agent Systems are a promising technology to develop the next generation open distributed complex software systems. The main focus of the research community has been on the development of concepts (concerning both mental and social attitudes), architectures, techniques, and general approaches to the analysis and specification of multi-agent systems. This contribution has been fragmented, without any clear way of “putting it all together”, rendering it inaccessible to students and young researchers, non-experts, and practitioners. Successful multi-agent systems development is guaranteed only if we can bridge the gap from analysis and design to effective implementation.Multi-Agent Programming: Languages, Tools and Applications presents a number of mature and influential multi-agent programming languages, platforms, development tools and methodologies, and realistic applications, summarizing the state of the art in an accessible manner for professionals and computer science students at all levels.
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Beginning Python Games Development, Second Edition
Beginning Python Games Development, Second Edition teaches you how to create compelling games using Python and the PyGame games development library. It will teach you how to create visuals, do event handling, create 3D games, add media elements, and integrate OpenGL into your Python game.In this update to the first ever book to cover the popular open source PyGame games development library, you'll stand to gain valuable technical insights and follow along with the creation of a real-world, freely downloadable video game. Written by industry veterans and Python experts Will McGugan and Harrison Kinsley, this is a comprehensive, practical introduction to games development in Python. You can also capitalize upon numerous tips and tricks the authors have accumulated over their careers creating games for some of the world's largest game developers.
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Practical Programming Model for the Multi-Core Era
The Third International Workshop on OpenMP, IWOMP 2007, was held at Beijing,China.This year’sworkshopcontinuedits traditionofbeingthe premier opportunity to learn more about OpenMP, to obtain practical experience and to interact with OpenMP users and developers. The workshop also served as a forum for presenting insights gained by practical experience, as well as research ideas and results related to OpenMP. A total of 28 submissions were received in response to a call for papers. Each submissionwasevaluatedbythreereviewersandadditionalreviewswerereceived for some papers. Based on the feedback received, 22 papers were accepted for inclusion in the proceedings. Of the 22 papers, 14 were accepted as full papers. We also accepted eight short papers, for each of which there was an opportunity to givea shortpresentationat the workshop,followed byposter demonstrations. Each paper was judged according to its originality, innovation, readability, and relevance to the expected audience. Due to the limited scope and time of the workshop and the high number of submissions received, only 50% of the total submissions were able to be included in the ?nal program. In addition to the contributed papers, the IWOMP 2007 program featured several keynote and banquet speakers: Trevor Mudge, Randy Brown, and Shah, Sanjiv. These speakers were selected due to their signi?cant contributions and reputation in the ?eld. A tutorial session and labs were also associated with IWOMP 2007.
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