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Expert Python Programming -
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book• Based on the latest stable version of Python (version 3.5)• Creating well manageable code that will run in various environments with different sets of dependencies• Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn• Conventions and best practices that are widely adopted in the python community• Package python code effectively for community and production use• Easy and lightweight ways to automate code deployment on remote systems• Improve your code's quality, reliability, and performance• Write concurrent code in python• Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming
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Mastering Python Design Patterns
Exploit various design patterns to master the art of solving problems using PythonKey FeaturesMaster the application design using the core design patterns and latest features of Python 3.7Learn tricks to solve common design and architectural challengesChoose the right plan to improve your programs and increase their productivityBook DescriptionPython is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.What you will learnExplore Factory Method and Abstract Factory for object creationClone objects using the Prototype patternMake incompatible interfaces compatible using the Adapter patternSecure an interface using the Proxy patternChoose an algorithm dynamically using the Strategy patternKeep the logic decoupled from the UI using the MVC patternLeverage the Observer pattern to understand reactive programmingExplore patterns for cloud-native, microservices, and serverless architecturesWho this book is forThis book is for intermediate Python developers. Prior knowledge of design patterns is not required to enjoy this book.
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Python Programming
Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader.Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming.This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool.Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers’ skills and understanding.Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.
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Python Object-Oriented Programming
A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniquesKey FeaturesBuild an intuitive understanding of object-oriented design, from introductory to mature programsLearn the ins and outs of Python syntax, libraries, and best practicesExamine a machine-learning case study at the end of each chapterBook DescriptionObject-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python’s classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python’s exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs.What you will learnImplement objects in Python by creating classes and defining methodsExtend class functionality using inheritanceUse exceptions to handle unusual situations cleanlyUnderstand when to use object-oriented features, and more importantly, when not to use themDiscover several widely used design patterns and how they are implemented in PythonUncover the simplicity of unit and integration testing and understand why they are so importantLearn to statically type check your dynamic codeUnderstand concurrency with asyncio and how it speeds up programsWho this book is forIf you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.
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Python 3 Using DeepSeek
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
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Mastering Algorithms with Python
Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides. Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference. Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence. What You Will Learn - - - - Who This Book Is For Software developers, data scientists, machine learning professionals and any curious learners about computer algorithms.
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Object-Oriented Approach to Problem Solving and Machine Learning with Python
This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.
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Python Programming
This book explores Python's rich history, dynamic features, and its wide-ranging applications in web development, data science, and machine learning. From its installation process to interactive help, readers embark on a journey through Python's unique characteristics and its distinctions from other programming languages. It lays a solid foundation for beginners and seasoned programmers alike.Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan)
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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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Python Object-Oriented Programming
This hands-on guide empowers Python developers to write clean, production-ready code using real-world OOP, design patterns, and concurrency tools. Fully updated for Python 3.13 with new type hinting and modern software engineering practices.Key FeaturesMaster OOP fundamentals with hands-on examples and expert insightsLearn design patterns and type hinting with real-world Python 3.13 codeDevelop scalable programs using testing and concurrency best practicesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionLearn to write effective, maintainable, and scalable Python applications by mastering object-oriented programming with this updated fifth edition. Whether you’re transitioning from scripting to structured development or refining your OOP skills, this book offers a clear, practical path forward.You’ll explore Python’s approach to OOP, from class creation and inheritance to polymorphism and abstraction, while discovering how to make smarter decisions about when and how to use these tools. You’ll apply what you learn through hands-on examples and exercises.Updated for Python 3.13, this edition simplifies complex topics such as abstract base classes, testing with unittest and pytest, and async programming with asyncio. It introduces a new chapter on Python’s type hinting ecosystem—crucial for modern Python development.Written by long-time Python experts Steven Lott and Dusty Phillips, this edition emphasizes clarity, testability, and professional software engineering practices. It helps you move beyond scripting to building well-structured, production-ready Python systems.By the end of this book, you’ll be confident in applying OOP principles, design patterns, type hints, and concurrency tools to create robust and maintainable Python applications.What you will learnWrite Python classes and implement object behaviorsApply inheritance, polymorphism, and compositionUnderstand when to use OOP—and when not toUse type hints and perform static and runtime checksExplore common and advanced design patterns in PythonWrite unit and integration tests with unittest and pytestImplement concurrency with asyncio, futures, and threadsRefactor procedural code into well-designed OOP structuresWho this book is forPython developers who want to deepen their understanding of object-oriented programming to write maintainable, scalable, and professional-grade code. Ideal for developers transitioning from scripting to software engineering or those coming from other OOP languages looking to master Python’s idiomatic approach. Basic Python knowledge is required.
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