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Dancing with Python
Develop skills in Python and Quantum Computing by implementing exciting algorithms, mathematical functions, classical searching, data analysis, plotting data, machine learning techniques, and quantum circuits.Key FeaturesCreate quantum circuits and algorithms using Qiskit and run them on quantum computing hardware and simulatorsLearn the Pythonic way to write elegant and efficient codeDelve into Python's advanced features, including machine learning, analyzing data, and searchingBook DescriptionDancing with Python helps you learn Python and quantum computing in a practical way. It will help you explore how to work with numbers, strings, collections, iterators, and files.The book goes beyond functions and classes and teaches you to use Python and Qiskit to create gates and circuits for classical and quantum computing. Learn how quantum extends traditional techniques using the Grover Search Algorithm and the code that implements it. Dive into some advanced and widely used applications of Python and revisit strings with more sophisticated tools, such as regular expressions and basic natural language processing (NLP). The final chapters introduce you to data analysis, visualizations, and supervised and unsupervised machine learning.By the end of the book, you will be proficient in programming the latest and most powerful quantum computers, the Pythonic way.What you will learnExplore different quantum gates and build quantum circuits with Qiskit and PythonWrite succinct code the Pythonic way using magic methods, iterators, and generatorsAnalyze data, build basic machine learning models, and plot the resultsSearch for information using the quantum Grover Search AlgorithmOptimize and test your code to run efficientlyWho this book is forThe book will help you get started with coding for Python and Quantum Computing. Basic familiarity with algebra, geometry, trigonometry, and logarithms is required as the book does not cover the detailed mathematics and theory of quantum computing. You can check out the author’s Dancing with Qubits book, also published by Packt, for an approachable and comprehensive introduction to quantum computing.
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Numbers And Functions: Theory, Formulation And Python Codes
This unique volume covers two fundamental elements of computational methods — numbers and functions. It provides an in-depth discussion of the behaviors of numbers, including both real and complex numbers. The discussion leads to the important closure properties of numbers, ensuring solution consistence and existence, and also possible failure in numerical computations in science and engineering.This text then introduces types of functions that take numbers as independent variables and produce a single number. Approaches for constructing inverse functions are also provided. Frequently used basis functions are introduced, with detailed studies on their properties and behaviors. Techniques are presented for constructing basis functions and their use in function approximation in computational methods.
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Learn coding with Python and JavaScript
Whether on the computer, tablet, mobile phone, in the car or in the coffee machine - computer programs determine our everyday life. Software is becoming increasingly important, hardly anything works without the mysterious power of algorithms. But how do programs work? And how do you develop them? This book teaches you the basics of programming. Using everyday examples, you will first learn the basic concepts of programming, which are similar in all programming languages. Based on these basic ideas, you will then learn two popular and very useful programming languages, Python and JavaScript, in a systematic way and with many practical exercises, which you can use for a wide range of different tasks. The book is aimed at novice programmers of all ages (from students to professionals) who have no previous programming experience.
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Hands-On Blockchain for Python Developers
Write popular DeFi and NFT smart contracts with Vyper, a Pythonic programming language, and integrate blockchain with real-world applications using Python Key FeaturesUse the world's easiest programming language to build web3 applicationsWrite common smart contracts like decentralized exchanges, NFT marketplaces, and lending applicationsUnlock deeper levels of insights with technologies relating to blockchain, such as IPFS and Layer 2Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionWe are living in the age of decentralized fi nance and NFTs. People swap tokens on Uniswap, borrow assets from Aave, send payments with stablecoins, trade art NFTs on OpenSea, and more. To build applications of this kind, you need to know how to write smart contracts.This comprehensive guide will help you explore all the features of Vyper, a programming language designed to write smart contracts. You’ll also explore the web3.py library. As you progress, you’ll learn how to connect to smart contracts, read values, and create transactions. To make sure your foundational knowledge is strong enough, the book guides you through Ape Framework, which can help you create decentralized exchanges, NFT marketplaces, voting applications, and more. Each project provides invaluable insights and hands-on experience, equipping you with the skills you need to build real-world blockchain solutions.By the end of this book, you’ll be well versed with writing common Web3 applications such as a decentralized exchange, an NFT marketplace, a voting application, and more.What you will learnUnderstand blockchain and smart contractsLearn how to write smart contracts with VyperExplore how to use the web3.py library and Ape FrameworkDiscover related technologies such as Layer 2 and IPFSGain a step-by-step guide to writing an automated market maker (AMM) decentralized exchange (DEX) smart contractBuild innovative, interactive, and token-gated Web3 NFT applicationsWho this book is forThis blockchain book is for developers interested in understanding blockchain and smart contracts. It is suitable for both technology enthusiasts looking to explore blockchain technology and programmers who aspire to become smart contract engineers. Basic knowledge of GNU/Linux and Python programming is mandatory to get started with this book.
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Machine Learning and Python for Human Behavior, Emotion, and Health Status Analysis
This book is a practical guide for individuals interested in exploring and implementing smart home applications using Python. Comprising six chapters enriched with hands-on codes, it seamlessly navigates from foundational concepts to cutting-edge technologies, balancing theoretical insights and practical coding experiences. In short, it is a gateway to the dynamic intersection of Python programming, smart home technology, and advanced machine learning applications, making it an invaluable resource for those eager to explore this rapidly growing field.Key Features:• Throughout the book, practicality takes precedence, with hands-on coding examples accompanying each concept to facilitate an interactive learning journey.• Striking a harmonious balance between theoretical foundations and practical coding, the book caters to a diverse audience, including smart home enthusiasts and researchers.• The content prioritizes real-world applications, ensuring readers can immediately apply the knowledge gained to enhance smart home functionalities.• Covering Python basics, feature extraction, deep learning, and XAI, the book provides a comprehensive guide, offering an overall understanding of smart home applications.
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Programming with Python
Based on the latest version of the language, this book offers a self-contained, concise and coherent introduction to programming with Python. The book’s primary focus is on realistic case study applications of Python. Each practical example is accompanied by a brief explanation of the problem-terminology and concepts, followed by necessary program development in Python using its constructs, and simulated testing. Given the open and participatory nature of development, Python has a variety of incorporated data structures, which has made it difficult to present it in a coherent manner. Further, some advanced concepts (super, yield, generator, decorator, etc.) are not easy to explain. The book specially addresses these challenges; starting with a minimal subset of the core, it offers users a step-by-step guide to achieving proficiency.
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Parametric and Generative Design with Rhino Python and Grasshopper
Learn how to create simple to complex parametric models with Rhino Python and Grasshopper (GH) in your form finding and design exploration. Tap into the generative power of Rhino via Grasshopper’s intuitive drag-n-drop visual scripting interface and combine GH nodes with Python to generate virtually any geometry.You’ll start by working through a series of bite-sized exercises to get up-to-speed with basics like creating curves and surfaces, utilizing input widgets, working with lists and data trees, and editing geometry with operations like loft, pipe, and extrude. Then you’ll elevate your skills by learning how to generate popular effects like attractors, tessellations, spirals andloops, stacking and voxelizing, cracks and wireframes, plus their variations. After getting comfortable with GH essentials, in the second half of the book you’ll work through five complex application workshops—(1) Generating basket and textile weaved versions of a 3D model; (2) Creating sliceforms from meshes by cutting interlocking cross sections at various angles and intervals; (3) Making tiles, lithophanes, and molds by generating Breps from images, and projecting them onto other objects as decorative elements; (4) Generating fractals and tree-like canopies from L-systems, and (5) Creating city skyline models from building footprints (GIS data). With five applications under your belt, you’ll wrap up the book by learning how to package Rhino Python and Grasshopper scripts into plugins suitable for online publication.Whether you are interested in architecture, landscape, industrial, product, jewelry, fashion, or naval design, Parametric & Generative Design with Rhino Python and Grasshopper will add many tools to your generative repertoire.You Will Learn to· Generate a wide range of parametric models using Grasshopper and Python scripting· Produce models from images and project them onto other objects as decorative elements· Source building footprints (GIS) data and generate city skyline models from themWho Is This Book ForThis book is for Rhino users who want to learn Grasshopper and Python for parametric design and form finding; some basic knowledge of Python is helpful but not required
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Introduction to GIS Programming and Fundamentals with Python and ArcGIS®
Combining GIS concepts and fundamental spatial thinking methodology with real programming examples, this book introduces popular Python-based tools and their application to solving real-world problems. It elucidates the programming constructs of Python with its high-level toolkits and demonstrates its integration with ArcGIS Theory. Filled with hands-on computer exercises in a logical learning workflow this book promotes increased interactivity between instructors and students while also benefiting professionals in the field with vital knowledge to sharpen their programming skills. Readers receive expert guidance on modules, package management, and handling shapefile formats needed to build their own mini-GIS. Comprehensive and engaging commentary, robust contents, accompanying datasets, and classroom-tested exercises are all housed here to permit users to become competitive in the GIS/IT job market and industry.
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Ethics, Machine Learning, and Python in Geospatial Analysis
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques. Scholars and practitioners can now enhance their analytical capabilities and unlock deeper insights from geospatial data with the guidance of this pivotal book. From manipulating data structures to employing machine learning algorithms, it equips readers with the tools and knowledge to tackle complex geospatial problems confidently and precisely. With Ethics, Machine Learning, and Python in Geospatial Analysis , the era of cumbersome manual processes gives way to a new frontier of efficient, data-driven analysis, empowering scholars to make meaningful contributions to geospatial science.
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Python for Bioinformatics
In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language.This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.
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Robust Python
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes.In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code.Learn why types are essential in modern development ecosystemsUnderstand how type choices such as classes, dictionaries, and enums reflect specific intentsMake Python extensible for the future without adding bloatUse popular Python tools to increase the safety and robustness of your codebaseEvaluate current code to detect common maintainability gotchasBuild a safety net around your codebase with linters and tests
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André Antoine
André Antoine, founder of the Théâtre Libre in 1887, was one of the initiators of the modern theatre. This full-length study of Antoine's work in English for more than sixty years is notable for its attention to the variousness of Antoine's remarkable career. It explores the power and some of the inherent contradictions of Antoine's stage realism, his creation of a repertory theatre noted for its ensemble playing, and his innovatory work in directing Shakespeare and the French classics. In the final section, Antoine's encounters, c.1918, with the new medium of film are discussed. The book will be of interest to students and teachers of drama, theatre history, film studies and literature, and to the general reader. It includes a chronology of Antoine's productions and theatre career and is generously illustrated with drawings and photographs.
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Programming Python
Once you've come to grips with the core Python language, learning how to build Python applications presents a far more interesting challenge. Tap this book's wealth of practical advice, snippets of code, and patterns of program design to take your Python skills to the next level. You'll start with in-depth discussions of core concepts and then progress toward complete programs in different application domains, including: * GUI programming * Internet scripting * Parallel processing * Database management * Networked applications * System administration * Text processing Most programming experts consider this classic book, now updated for Python 3.x, to be the industry standard for learning Python application programming. With clear and concise explanations of Python syntax and programming techniques, and numerous examples that illustrate both correct usage and common idioms, Programming Python shows you the right way to code with Python.
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Practical Computer Architecture with Python and ARM
Learn computer architecture with Python and ARM, simulating assembly program execution and designing a computer simulatorPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesBuild a computer simulator with Python: Learn computer architecture by designing and constructing a simulatorPython for architecture: Use Python to simulate and execute assembly language instructionsARM programming on Raspberry Pi: Explore ARM assembly language and run programs on Raspberry PiBook DescriptionThis comprehensive guide offers a unique and immersive learning experience by combining Python programming with ARM architecture.Starting with an introduction to computer architecture and the flow of data within a computer system, you’ll progress to building your own interpreter using Python. You’ll see how this foundation enables the simulation of computer operations and learn ways to enhance a simulator by adding new instructions and displaying improved results.As you advance, you’ll explore the TC1 Assembler and Simulator Program to gain insights into instruction analysis and explore practical examples of simulators. This will help you build essential skills in understanding complex computer instructions, strengthening your grasp of computer architecture. Moreover, you’ll be introduced to the Raspberry Pi operating system, preparing you to delve into the detailed language of the ARM computer. This includes exploring the ARM instruction set architecture, data-processing instructions, subroutines, and the stack.With clear explanations, practical examples, and coding exercises, this resource will enable you to design and construct your own computer simulator, simulate assembly language programs, and leverage the Raspberry Pi for ARM programming.What you will learnMaster the core principles of computer architectureUnderstand the role of registers, memory, and data flow in computersDiscover how to design and implement a computer simulator using PythonSimulate and execute assembly language programs on the simulatorEnhance the simulator using new instructions for improved outputAnalyze complex computer instructions for deeper architectural understandingExplore the ARM instruction set and data processing on the Raspberry PiDevelop proficiency in writing, assembling, and running ARM code on the Raspberry PiWho this book is forThis book is for university students studying computer science, particularly those enrolled in a computer architecture module. With its practical approach and succinct explanations, it is also suitable for hobbyists, enthusiasts, and self-learners seeking a deeper understanding of computer systems. The book assumes foundational knowledge of number bases, binary arithmetic, and Boolean logic concepts. While it primarily caters to the computer science field, this book is less geared toward electrical or electronics engineering.
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Extracting Intelligence from RSS News Feeds Using Python and AI
In a world flooded with digital information, the ability to automatically extract meaningful and actionable insights from global news feeds is a critical skill. Extracting Actionable Information from RSS Feeds Using Python and AI offers a hands-on guide for leveraging Python and OpenAI to transform raw RSS content—both in English and non-English languages—into structured, insightful data.This book walks readers through building intelligent pipelines that go beyond simple feed parsing. Using advanced natural language processing and AI techniques, readers will learn how to extract vital elements from each news article, including:Author identificationDetailed, AI-generated summariesAssessment of global, political, and social relevanceDetection of potential threats or risksNamed entity recognition (people, places, organizations)Whether you're building real-time threat intelligence systems, media monitoring dashboards, or conducting geopolitical analysis, this book equips you with the tools and source code to accelerate your development. Each chapter includes fully functional Python scripts that can be immediately applied or extended to meet specific needs.Designed for developers, analysts, and technologists, this practical and forward-looking book bridges the gap between unstructured content and actionable intelligence—at the speed of the global news cycle.What You’ll Learn:Understand how to collect and process RSS feed data from both English and non-English sources using Python.Apply OpenAI-powered natural language processing to extract key elements such as author, summary, relevance, and threat indicators from news articles.Perform named entity recognition (NER) to identify and extract people, places, and organizations mentioned in each article.Evaluate the geopolitical, social, and political relevance of news stories using AI-driven content analysis techniques.Utilize and customize the provided Python source code to build or enhance real-time content extraction and analysis tools.Who This Book Is for:Primary Target Readers include:Data Analysts and Intelligence Professionals: Professionals in government, cybersecurity, media monitoring, or corporate intelligence who need to extract and act on relevant news information in real time.Python Developers and AI Enthusiasts: Intermediate to advanced Python programmers looking to integrate AI for real-world content analysis, especially those interested in OpenAI and natural language processing.Journalists and Media Researchers: Those seeking to automate content curation, perform author attribution, or assess bias and relevance across diverse news sources globally.Academics and Students in Data Science, AI, or Digital Humanities: Educators and learners looking for applied projects in NLP, multilingual processing, and AI-driven analysis.Tech-Savvy Policy Makers and Think Tank Researchers: Readers who monitor emerging global narratives and want automated tools to help assess political, social, and security i
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