Get an A grade in C As with any major language, mastery of C can take you to some very interesting new places. Almost 50 years after it first appeared, it's still the world's most popular programming language and is used as the basis of global industry's core systems, including operating systems, high-performance graphics applications, and microcontrollers. This means that fluent C users are in big demand at the sharp end in cutting-edge industries--such as gaming, app development, telecommunications, engineering, and even animation--to translate innovative ideas into a smoothly functioning reality. To help you get to where you want to go with C, this 2nd edition of C Programming For Dummies covers everything you need to begin writing programs, guiding you logically through the development cycle: from initial design and testing to deployment and live iteration. By the end you'll be au fait with the do's and don'ts of good clean writing and easily able to produce the basic--and not-so-basic--building blocks of an elegant and efficient source code. Write and compile source code Link code to create the executable program Debug and optimize your code Avoid common mistakes Whatever your destination: tech industry, start-up, or just developing for pleasure at home, this easy-to-follow, informative, and entertaining guide to the C programming language is the fastest and friendliest way to get there!

Learn the essentials of working with Flutter and Dart to build full stack applications that meet the needs of a cloud-driven world. Together, the Flutter open source UI software development kit and the Dart programming language for client development provide a unified solution to building applications capable of targeting multiple platforms. Recipes in this cookbook show you how this potent combination provides an efficient approach to application development. Typically used in frontend development, Flutter helps you develop cross-platform applications for Android, iOS, Linux, Mac, Windows, and the Google Fuchsia operating system. The Dart SDK provides native access to third-party solutions, including APIs, databases, and authentication. When used in concert with Flutter, Dart allows you to compile source code ahead of time to native code. This cookbook shows you how to: Write effective Dart code by using variables and data structures Build applications with Flutter by exploring widgets and data handling Understand cloud provider solutions and learn how to integrate them with Flutter Manage data through APIs using Google Cloud Serverless Work with Firebase solutions such as Authentication and the Cloud Firestore database Build web applications that also work with mobile and desktop platforms

Learning to program isn't just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.

This book brings together a number of researchers and developers from industry and academia who report on their work. It is of interest to language designers and the creators of toolkits, UIMSs, and other user interface tools.

Systems programming provides the foundation for the world's computation. Writing performance-sensitive code requires a programming language that puts programmers in control of how memory, processor time, and other system resources are used. The Rust systems programming language combines that control with a modern type system that catches broad classes of common mistakes, from memory management errors to data races between threads. With this practical guide, experienced systems programmers will learn how to successfully bridge the gap between performance and safety using Rust. Jim Blandy, Jason Orendorff, and Leonora Tindall demonstrate how Rust's features put programmers in control over memory consumption and processor use by combining predictable performance with memory safety and trustworthy concurrency. You'll learn: Rust's fundamental data types and the core concepts of ownership and borrowing How to write flexible, efficient code with traits and generics How to write fast, multithreaded code without data races Rust's key power tools: closures, iterators, and asynchronous programming Collections, strings and text, input and output, macros, unsafe code, and foreign function interfaces This revised, updated edition covers the Rust 2021 Edition.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.

Formal Languages and Computation: Models and Their Applications gives a clear, comprehensive introduction to formal language theory and its applications in computer science. It covers all rudimental topics concerning formal languages and their models, especially grammars and automata, and sketches the basic ideas underlying the theory of computation, including computability, decidability, and computational complexity. Emphasizing the relationship between theory and application, the book describes many real-world applications, including computer science engineering techniques for language processing and their implementation. Covers the theory of formal languages and their models, including all essential concepts and properties Explains how language models underlie language processors Pays a special attention to programming language analyzers, such as scanners and parsers, based on four language models-regular expressions, finite automata, context-free grammars, and pushdown automata Discusses the mathematical notion of a Turing machine as a universally accepted formalization of the intuitive notion of a procedure Reviews the general theory of computation, particularly computability and decidability Considers problem-deciding algorithms in terms of their computational complexity measured according to time and space requirements Points out that some problems are decidable in principle, but they are, in fact, intractable problems for absurdly high computational requirements of the algorithms that decide them In short, this book represents a theoretically oriented treatment of formal languages and their models with a focus on their applications. It introduces all formalisms concerning them with enough rigors to make all results quite clear and valid. Every complicated mathematic

Because of its portability and platform-independence, Java is the ideal computer programming language to use when working on graph algorithms and other mathematical programming problems. Collecting some of the most popular graph algorithms and optimization procedures, A Java Library of Graph Algorithms and Optimization provides the source code for a library of Java programs that can be used to solve problems in graph theory and combinatorial optimization. Self-contained and largely independent, each topic starts with a problem description and an outline of the solution procedure, followed by its parameter list specification, source code, and a test example that illustrates the usage of the code. The book begins with a chapter on random graph generation that examines bipartite, regular, connected, Hamilton, and isomorphic graphs as well as spanning, labeled, and unlabeled rooted trees. It then discusses connectivity procedures, followed by a paths and cycles chapter that contains the Chinese postman and traveling salesman problems, Euler and Hamilton cycles, and shortest paths. The author proceeds to describe two test procedures involving planarity and graph isomorphism. Subsequent chapters deal with graph coloring, graph matching, network flow, and packing and covering, including the assignment, bottleneck assignment, quadratic assignment, multiple knapsack, set covering, and set partitioning problems. The final chapters explore linear, integer, and quadratic programming. The appendices provide references that offer further details of the algorithms and include the definitions of many graph theory terms used in the book.

Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever. Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzecri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields. This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.

Python Workout presents 50 exercises designed to deepen the reader's skill with Python. Readers will not only tackle exercises using built-in data structures, but also more advanced techniques, such as functional programming, object-oriented programming, iterators, and generators. With each engaging challenge, readers will practice a new skill and learn how to apply it to everyday coding tasks. Key Features 50 hands-on exercises and solutions Basic Python sequence types Python dictionaries and sets Functional programming in Python Creating your own classes Working with Python objects Generator functions Intended for readers with basic Python skills. About the technology Python is a versatile, elegant, general purpose programming language. Essential for data analysis, web development, artificial intelligence, games, desktop apps, and more, Python skills are a hot commodity. Reuven M. Lerner, an independent consultant for more than two decades, teaches Python, data science, and Git to companies around the world. His Better developers newsletter and blog are read by thousands of Python developers each week. Reuven has written a monthly column, "At the Forge," for Linux Journal since 1996 and is a panellist on the weekly Freelancers Show podcast. Reuven lives with his wife and three children in Modi'in, Israel, and can be reached at https://lerner.co.il/ or on Twitter at @reuvenmlerner.

The inside guide to the next generation of data storage technology VMware Software-Defined Storage, A Guide to the Policy Driven, Software-Defined Storage Era presents the most in-depth look at VMware's next-generation storage technology to help solutions architects and operational teams maximize quality storage design. Written by a double VMware Certified Design Expert, this book delves into the design factors and capabilities of Virtual SAN and Virtual Volumes to provide a uniquely detailed examination of the software-defined storage model. Storage-as-a-Service (STaaS) is discussed in terms of deployment through VMware technology, with insight into the provisioning of storage resources and operational management, while legacy storage and storage protocol concepts provide context and demonstrate how Virtual SAN and Virtual Volumes are meeting traditional challenges. The discussion on architecture emphasizes the economies of storage alongside specific design factors for next-generation VMware based storage solutions, and is followed by an example in which a solution is created based on the preferred option identified from a selection of cross-site design options. Storage hardware lifecycle management is an ongoing challenge for IT organizations and service providers. VMware is addressing these challenges through the software-defined storage model and Virtual SAN and Virtual Volumes technologies; this book provides unprecedented detail and expert guidance on the future of storage. * Understand the architectural design factors of VMware-based storage * Learn best practices for Virtual SAN stretched architecture implementation * Deploy STaaS through vRealize Automation and vRealize Orchestrator * Meet traditional storage challenges with next-generation storage technology Virtual SAN and Virtual Volumes are leading the way in efficiency, automation, and simplification, while maintaining enterprise-class features and performance. As organizations around the world are looking to cut costs without sacrificing performance, availability, or scalability, VMware-based next-generation storage solutions are the ideal platform for tomorrow's virtual infrastructure. VMware Software-Defined Storage provides detailed, practical guidance on the model that is set to transform all aspects of vSphere data center storage.

Are you a programmer who wants to get started quickly in a new language? This book is for you. Are you a novice who wants to learn to program? This book is not for you. Are you a Python programmer who needs encyclopaedic information? This book is not for you. Like any mainstream language, Python has loops, if statements, assignment statements, functions, etc. I'll show you what these look like in Python. I won't waste your time telling you what they're good for. Python has features you may not be familiar with--iterators, list comprehensions, maybe even dictionaries. I'll spend more time on these. I'll cover some of the library functions I found most immediately useful, and tell you where to find more. In short, this book will help you hit the ground running. Next week, you'll be ready to buy that Python encyclopaedia.

Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you'll get a chance to revisit the concepts you've covered so far. What You Will Learn Use Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

Series in Computational Physics Steven A. Gottlieb and Rubin H. Landau, Series Editors Introduction to Python for Science and Engineering This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips. Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader. David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He is an elected fellow of the American Physical Society and American Association for the Advancement of Science (AAAS), and is a Guggenheim Fellow.

Develop and use bots in video gaming to automate game processes and see possible ways to avoid this kind of automation. This book explains how bots can be very helpful in games such as multiplayer online games, both for training your character and for automating repetitious game processes in order to start a competition with human opponents much faster. Some players might use bots for cheating or avoiding game rules to gain an advantage over opponents - a sophisticated form of hacking that includes some elements of artificial intelligence (AI). However, while Practical Video Game Bots considers these topics, it is not a cheater's guide. Rather, this book is an attempt to overcome the information vacuum regarding bot development in video game applications. Through the use of three case study game examples, it covers most methods and technologies that are used by bot developers, and the details of anti-cheating systems. This book provides answers and useful advice for topics such as process automation, reverse engineering, and network applications. Modern bot applications use technologies from all these domains. You will also consider the work mechanisms of different kinds of bots and will write simple prototypes. What You Will Learn Discover bots and apply them to game applications Use clicker bots with OS-level embedding data, output-device capture, and more Develop in-game bots, with process memory analysis and access Work with out-game bots, with network interception and embedding data Deal with input device emulation and OS-level interception data Who This Book Is For Those with some prior experience in game development and coding experience in Python, C++, and Windows APIs.

PhoneGap is a standards-based, open-source development framework that can be deployed to any mobile device without losing the features of the native app-allowing for access to device contacts, the local file system, camera, and media on multiple platforms without requiring users to write a single line of code. Ideal for intermediate to advanced users, PhoneGap Build: Developing Cross Platform Mobile Applications in the Cloud offers the comprehensive coverage you need to harness the power of this dynamic tool. It provides complete coverage of the cloud computing platform and the theories behind cloud computing, using a series of engaging examples. The book explains the differences between existing mobile platforms, the different types of browsers they support, and the programming languages and integrated development environment required to develop apps for each of them. It then describes how PhoneGap makes the task of developing cross-platform mobile apps easier. This book will teach you how to use: HTML5, CSS3, and JavaScript to develop apps for devices across various mobile operating systems PhoneGap Build to develop mobile apps in the cloud PhoneGap with Sencha Touch and jQuery Mobile Back end databases to store and retrieve information The text starts with simpler applications and gradually moves toward describing advanced concepts and how to exploit different application programming interfaces and methods. By the time you finish the book, you will learn how to develop feature-rich mobile applications that can run on the cloud to support different platforms. Supplying authoritative guidance and proven best practices for designing cloud-based applications, the book is an ideal reference for cloud system developers, architects, and IT professionals. It is also suitable for use in instructional settings.

You won't get far as a Visual Basic developer unless you know how to write database applications. That's where this book comes in. It shows you how to use Visual Studio 2008 and ADO.NET 3.5 to develop database applications the way the best professionals do. That includes the full gamut of skills you need, from using prototyping features that generate ADO.NET code...to writing your own ADO.NET code from scratch so you can closely control how the database processing works...to using .NET 3.5 features like LINQ and the ADO.NET Entity Framework that actually change the way you think about handling data. What's more, this book takes you from beginner to database professional in a logical progression that makes each step easier to master: In section 1, you will get a basic introduction to databases, SQL, and ADO.NET. If you already have ADO.NET experience, you can skip ahead. In section 2, you will quickly be prototyping database applications using Rapid Application Development (RAD) tools like data sources. In section 3, you will learn how to build 3-layer applications the ways the pros do, with presentation, business, and database classes. This is where you'll get into ADO.N ET coding to create your own database classes. Section 4 covers LINQ (Language-Integrated Query), a .NET 3.5 feature that lets you handle all types of data using a query language that's integrated into Visual Basic and that saves you a lot of ADO.NET coding. That means you'll learn how to: Use LINQ to DataSet to query the data in typed or untyped datasets; Use LINQ to SQL, which allows you to generate an object model from the objects in a SQL Server database that can then be used to access and update the database data...a feature that offers you some of the same benefits as the Entity Framework; Use LINQ to XML to manipulate XML data much more easily than you can using the Document Object Model; Use LINQ data source controls with web applications. In section 5, you will learn to work with the ADO.NET Entity Framework...another way to let .NET generate the code you need and do more of the work for you. Using this feature, you create an Entity Data Model that defines a conceptual model for the business objects used by an application, a storage model for the objects in a database, and mappings that relate the two. Then: You can use LINQ or a special form of SQL to retrieve data into the business objects; You can work with the business objects and save changes to the database using generated code; You can use Entity data source controls with web applications.

Finite Element Computations in Mechanics with R: A Problem-Centred Programming Approach provides introductory coverage of the finite element method (FEM) with the R programming language, emphasizing links between theory and implementation of FEM for problems in engineering mechanics. Useful for students, practicing engineers, and researchers, the text presents the R programming as a convenient easy-to-learn tool for analyzing models of mechanical systems, with finite element routines for structural, thermal, and dynamic analyses of mechanical systems, and also visualization of the results. Full-color graphics are used throughout the text.

A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required. The Second Edition was thoroughly reorganized and rewritten based on classroom experience to incorporate: A spiral approach, starting with turtle graphics, and then revisiting concepts in greater depth using numeric, textual, and image data Clear, concise explanations written for beginning students, emphasizing core principles A variety of accessible examples, focusing on key concepts Diagrams to help visualize new concepts New sections on recursion and exception handling, as well as an earlier introduction of lists, based on instructor feedback The text offers sections designed for approximately one class period each, and proceeds gradually from procedural to object-oriented design. Examples, exercises, and projects are included from diverse application domains, including finance, biology, image processing, and textual analysis. It also includes a brief "How-To" sections that introduce optional topics students may be interested in exploring. The text is written to be read, making it a good fit in flipped classrooms. Designed for either classroom use or self-study, all example programs and solutions to odd-numbered exercises (except for projects) are available at: http://www.central.edu/go/conciseintro/.

It's axiomatic to state that people fear what they do not understand, and this is especially true when it comes to technology. However, despite their prevalence, computers remain shrouded in mystery, and many users feel apprehensive when interacting with them. Smartphones have only exacerbated the issue. Indeed, most users of these devices leverage only a small fraction of the power they hold in their hands. How Things Work: The Computer Science Edition is a roadmap for readers who want to overcome their technophobia and harness the full power of everyday technology. Beginning with the basics, the book demystifies the mysterious world of computer science, explains its fundamental concepts in simple terms, and answers the questions many users feel too intimidated to ask. By the end of the book, readers will understand how computers and smart devices function and, more important, how they can make these devices work for them. To complete the picture, the book also introduces readers to the darker side of modern technology: security and privacy concerns, identity theft, and threats from the Dark Web.

Behavioural type systems in programming languages support the specification and verification of properties of programs beyond the traditional use of type systems to describe data processing. A major example of such a property is correctness of communication in concurrent and distributed systems, motivated by the importance of structured communication in modern software. Behavioural Types: from Theory to Tools presents programming languages and software tools produced by members of COST Action IC1201: Behavioural Types for Reliable Large-Scale Software Systems, a European research network that was funded from October 2012 to October 2016. As a survey of the most recent developments in the application of behavioural type systems, it is a valuable reference for researchers in the field, as well as an introduction to the area for graduate students and software developers.