Search results for "Data Structures using C"
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Concepts in Programming Languages
For undergraduate and beginning graduate students, this textbook explains and examines the central concepts used in modern programming languages, such as functions, types, memory management, and control. The book is unique in its comprehensive presentation and comparison of major object-oriented programming languages. Separate chapters examine the history of objects, Simula and Smalltalk, and the prominent languages C++ and Java. The author presents foundational topics, such as lambda calculus and denotational semantics, in an easy-to-read, informal style, focusing on the main insights provided by these theories. Advanced topics include concurrency, concurrent object-oriented programming, program components, and inter-language interoperability. A chapter on logic programming illustrates the importance of specialized programming methods for certain kinds of problems. This book will give the reader a better understanding of the issues and tradeoffs that arise in programming language design, and a better appreciation of the advantages and pitfalls of the programming languages they use.
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Beginning C# 7 Hands-On – Advanced Language Features
An advanced C# beginners guide to some of the tougher parts of the C# language!About This Book• Learn C#, Visual Studio, and object-oriented programming• Get practical examples of advanced C# language features so that you can easily master them yourself• Use the C# programming language to work generics and lambda expressions• Program C# and SQL Server 2017• Get ready for your first MVC applicationsWho This Book Is ForThis book is for anyone who is interested in learning how to program the more advanced aspects of the C# language. Previous programming knowledge of C# is required, at least to the level of basic object-oriented programming. Readers can benefit from first reading Tom Owsiak's companion book, Beginning C# 7 Hands-On – The Core Language, as a preparation for the more advanced elements and techniques presented in this book.What You Will Learn• Learn C# advanced language elements and techniques• Discover advanced C# techniques with hands-on working examples• Build on your knowledge of OOP by using C# generics and lambda expressions• Work with C# and LINQ custom data types• Program C# and SQL Server 2017 to manage and query data• Create your first full MVC applicationIn DetailBeginning C# 7 Hands-On – Advanced Language Features assumes that you've mastered the basic elements of the C# language and that you're now ready to learn the more advanced C# language and syntax, line by line, in a working Visual Studio environment. You'll learn how to code advanced C# language topics including generics, lambda expressions, and anonymous methods.You'll learn to use query syntax to construct queries and deploy queries that perform aggregation functions. Work with C# and SQL Server 2017 to perform complex joins and stored procedures. Explore advanced file access methods, and see how to serialize and deserialize objects – all by writing working lines of code that you can run within Visual Studio.This book is designed for beginner C# developers who have mastered the basics now, and anyone who needs a fast reference to using advanced C# language features in practical coding examples. You'll also take a look at C# through web programming with web forms.By the time you've finished this book, you'll know all the critical advanced elements of the C# language and how to program everything from C# generics to XML, LINQ, and your first full MVC web applications. These are the advanced building blocks that you can then combine to exploit the full power of the C# programming language, line by line.Style and approachA comprehensive book that blends theory with just the right amount of practical code implementations, to help you get up and running with the C# programming language and its advanced features. You'll also get to work with other tools and technologies that complement C# programming. Each core part of the C# language is coded as you learn, and code output is tested every time to verify the syntax is working as expected, so it's easy for you to learn dire
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R 1,963.69
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Programming Rust
Rust combines low-level control with memory safety, making it an ideal choice for systems programming. This practical guide is for experienced programmers looking to write fast, reliable code while avoiding common pitfalls like data races and buffer overflows. Authors Jim Blandy, Jason Orendorff, and Leonora Tindall explain Rust's unique approach to ownership, borrowing, and concurrency, helping you build safe, high-performance applications.Fully updated for Rust's 2024 edition, this book introduces the latest language advancements while covering essential topics like generics, async programming, and C interoperability. Whether you're working on low-latency systems, embedded software, or multithreaded applications, this edition equips you with the knowledge to write efficient, production-ready Rust code.Learn Rust's core principles, including ownership, borrowing, and lifetimesWrite safe, efficient concurrent code without data racesUse powerful features like macros, closures, and async programmingIntegrate Rust with C and C++ through FFI and unsafe codeApply best practices to write performance-critical, memory-safe applications
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PL / I Structured Programming
A complete course in the PL/I programming language, presented in a simple and logical manner with many features to help the reader grasp the material quickly: checkpoint questions interspersed throughout each chapter; a detailed index to help locate references to technical points and answers to questions; a glossary of terms, and more. Also includes a section on debugging techniques to aid in coding and testing programs, and a case study in each chapter.
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Data Wrangling Workshop
A beginner's guide to simplifying Extract, Transform, Load (ETL) processes with the help of hands-on tips, tricks, and best practices, in a fun and interactive wayKey FeaturesExplore data wrangling with the help of real-world examples and business use casesStudy various ways to extract the most value from your data in minimal timeBoost your knowledge with bonus topics, such as random data generation and data integrity checksBook DescriptionWhile a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.What you will learnGet to grips with the fundamentals of data wranglingUnderstand how to model data with random data generation and data integrity checksDiscover how to examine data with descriptive statistics and plotting techniquesExplore how to search and retrieve information with regular expressionsDelve into commonly-used Python data science librariesBecome well-versed with how to handle and compensate for missing dataWho this book is forThe Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
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Python for Engineers and Scientists
This book equips technical professionals with a complete, structured path to mastering Python for real-world engineering and scientific applications. As Python becomes central to research labs, automation, simulation, and data-driven engineering, the learning curve remains steep. This book bridges that gap with a practical roadmap from fundamentals to professional-grade scientific computing.The book begins by building a strong programming foundation—covering Python’s architecture, essential syntax, data structures, modules, functions, control flow, and object-oriented design. Readers learn not only how to write Python, but why the language behaves the way it does, ensuring deep understanding and strong problem-solving skills. From there, the focus shifts to practical engineering tools. Dedicated chapters train readers in file handling, math modules, and key scientific libraries including NumPy, SciPy, Pandas, and Matplotlib, enabling efficient computation, signal processing, data analysis, and high-quality visualization. Advanced chapters then showcase Python’s versatility through GUI development with Kivy, database work with SQLAlchemy, and hands-on control system modeling and analysis. Each topic is rooted in industry and academic scenarios, making the content directly applicable to automation, simulation, data workflows, and engineering computation.Whether you're a student building foundational skills or a professional modernizing engineering workflows, this guide provides the programming depth, scientific tools, and applied knowledge needed to use Python confidently for prototyping, simulation, analysis, and automation. It is the one-stop resource for mastering Python in technical disciplines.What you will learn:Learn core Python programming concepts, including variables, loops, functions, and object-oriented principles in a scientific and engineering context.Build strong skills in key scientific Python libraries such as NumPy, Pandas, Matplotlib, and SciPy for computation, analysis, and visualization.Apply Python to real-world engineering scenarios, including dynamic control systems and automation workflows.Develop interactive engineering applications by creating graphical user interfaces (GUIs) with Kivy. Who this book is for:This book is intended for practicing engineers and scientists across various disciplines of engineering who need to use Python for complex problem-solving, simulation, and data analysis in their work.
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Graphical Programming Using LabVIEW™
In this book, the authors focus on efficient ways to program instrumentation and automation systems using LabVIEW™, a system design platform and development environment commonly used for data acquisition, instrument control, and industrial automation on a variety of operating systems. Starting with the concepts of data flow and concurrent programming, the authors go on to address the development of state machines, event programming and consumer producer systems. Chapters cover the following topics: Introduction to LabVIEW™, debugging tools, structures, SubVIs, structures - LabVIEW™ features, organizing front panel and block diagram, using software resources, using hardware resources, implementing test machines with a basic architecture, controlling the user interface, error handling, responding to the user interactions, the ATM review project, communication between loops at different rates, preventing race conditions, advanced use of software resources, and real-time programming. This book helps undergraduate and graduate students learn how to identify the most suitable design patterns depending on the application, and how to implement them in conjunction with data acquisition and instrumentation control systems. It is also a helpful resource for engineers and scientists who want to implement binary files to record data, control the user interface and implement efficient ways of programming.
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Process Algebra: Equational Theories of Communicating Processes
Process algebra is a widely accepted and much used technique in the specification and verification of parallel and distributed software systems. This book sets the standard for the field. It assembles the relevant results of most process algebras currently in use, and presents them in a unified framework and notation. The authors describe the theory underlying the development, realization and maintenance of software that occurs in parallel or distributed systems. A system can be specified in the syntax provided, and the axioms can be used to verify that a composed system has the required external behaviour. As examples, two protocols are completely specified and verified in the text: the Alternating-Bit Protocol for Data Communication, and Fischer's Protocol of Mutual Exclusion. The book serves as a reference text for researchers and graduate students in computer science, offering a complete overview of the field and referring to further literature where appropriate.
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Getting Started with Python Data Analysis
Learn to use powerful Python libraries for effective data processing and analysisAbout This Book• Learn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and Matplotlib• Create, manipulate, and analyze your data to extract useful information to optimize your system• A hands-on guide to help you learn data analysis using PythonWho This Book Is ForIf you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.What You Will Learn• Understand the importance of data analysis and get familiar with its processing steps• Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis• Create effective visualizations to present your data using Matplotlib• Process and analyze data using the time series capabilities of Pandas• Interact with different kind of database systems, such as file, disk format, Mongo, and Redis• Apply the supported Python package to data analysis applications through examples• Explore predictive analytics and machine learning algorithms using Scikit-learn, a Python libraryIn DetailData analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It's often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis.With this book, we will get you started with Python data analysis and show you what its advantages are.The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems.Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples.Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn. Style and approachThis is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required.
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Hands-On RESTful Python Web Services
Explore the best tools and techniques to create lightweight, maintainable, and scalable Python web servicesKey FeaturesCombine Python with different data sources to build complex RESTful APIs from scratchConfigure and fine-tune your APIs using the best tools and techniques availableUse command-line and GUI tools to test CRUD operations performed by RESTful Web Services or APIsBook DescriptionPython is the language of choice for millions of developers worldwide that builds great web services in RESTful architecture. This second edition of Hands-On RESTful Python Web Services will cover the best tools you can use to build engaging web services.This book shows you how to develop RESTful APIs using the most popular Python frameworks and all the necessary stacks with Python, combined with related libraries and tools. You’ll learn to incorporate all new features of Python 3.7, Flask 1.0.2, Django 2.1, Tornado 5.1, and also a new framework, Pyramid. As you advance through the chapters, you will get to grips with each of these frameworks to build various web services, and be shown use cases and best practices covering when to use a particular framework.You’ll then successfully develop RESTful APIs with all frameworks and understand how each framework processes HTTP requests and routes URLs. You’ll also discover best practices for validation, serialization, and deserialization. In the concluding chapters, you will take advantage of specific features available in certain frameworks such as integrated ORMs, built-in authorization and authentication, and work with asynchronous code. At the end of each framework, you will write tests for RESTful APIs and improve code coverage.By the end of the book, you will have gained a deep understanding of the stacks needed to build RESTful web services.What you will learnSelect the most appropriate framework based on requirementsDevelop complex RESTful APIs from scratch using PythonUse requests handlers, URL patterns, serialization, and validationsAdd authentication, authorization, and interaction with ORMs and databasesDebug, test, and improve RESTful APIs with four frameworksDesign RESTful APIs with frameworks and create automated testsWho this book is forThis book is for web developers who have a working knowledge of Python and would like to build amazing web services by taking advantage of the various frameworks of Python. You should have some knowledge of RESTful APIs.
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Software Architecture with C# 10 and .NET 6
Design scalable and high-performance enterprise applications using the latest features of C# 10 and .NET 6Key FeaturesGain comprehensive software architecture knowledge and the skillset to create fully modular appsSolve scalability problems in web apps using enterprise architecture patternsMaster new developments in front-end architecture and the application of AI for software architectsBook DescriptionSoftware architecture is the practice of implementing structures and systems that streamline the software development process and improve the quality of an app. This fully revised and expanded third edition, featuring the latest features of .NET 6 and C# 10, enables you to acquire the key skills, knowledge, and best practices required to become an effective software architect. Software Architecture with C# 10 and .NET 6, Third Edition features new chapters that describe the importance of the software architect, microservices with ASP.NET Core, and analyzing the architectural aspects of the front-end in the applications, including the new approach of .NET MAUI. It also includes a new chapter focused on providing a short introduction to artificial intelligence and machine learning using ML.NET, and updated chapters on Azure Kubernetes Service, EF Core, and Blazor. You will begin by understanding how to transform user requirements into architectural needs and exploring the differences between functional and non-functional requirements. Next, you will explore how to choose a cloud solution for your infrastructure, taking into account the factors that will help you manage a cloud-based app successfully. Finally, you will analyze and implement software design patterns that will allow you to solve common development problems. By the end of this book, you will be able to build and deliver highly scalable enterprise-ready apps that meet your business requirements.What you will learnUse proven techniques to overcome real-world architectural challengesApply architectural approaches such as layered architectureLeverage tools such as containers to manage microservices effectivelyGet up to speed with Azure features for delivering global solutionsProgram and maintain Azure Functions using C# 10Understand when it is best to use test-driven development (TDD)Implement microservices with ASP.NET Core in modern architecturesEnrich your application with Artificial IntelligenceGet the best of DevOps principles to enable CI/CD environmentsWho this book is forThis book is for engineers and senior software developers aspiring to become architects or looking to build enterprise applications with the .NET Stack. Basic familiarity with C# and .NET is required to get the most out of this book.
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Joe Celko's Data, Measurements and Standards in SQL
Joe Celko has looked deep into the code of SQL programmers and found a consistent and troubling pattern - a frightening lack of consistency between their individual encoding schemes and those of the industries in which they operate. This translates into a series of incompatible databases, each one an island unto itself that is unable to share information with others in an age of internationalization and business interdependence. Such incompatibility severely hinders information flow and the quality of company data.Data, Measurements and Standards in SQL reveals the shift these programmers need to make to overcome this deadlock. By collecting and detailing the diverse standards of myriad industries, and then giving a declaration for the units that can be used in an SQL schema, Celko enables readers to write and implement portable data that can interface to any number of external application systems! This book doesn't limit itself to one subject, but serves as a detailed synopsis of measurement scales and data standards for all industries, thereby giving RDBMS programmers and designers the knowledge and know-how they need to communicate effectively across business boundaries.
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