This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept. This book is aimed at programmers who have already learned the basics of object-oriented Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer science background, with experience of common Python design patterns.

Embark on a Profound Journey to "Mastering Object-Oriented Programming" In a dynamic world of software development, mastering the art of object-oriented programming (OOP) is pivotal for creating robust, scalable, and maintainable code that powers modern applications. "Mastering Object-Oriented Programming" is your comprehensive guide to navigating the intricate world of OOP principles, design patterns, and best practices. Whether you're a seasoned developer or an aspiring programmer, this book equips you with the knowledge and skills needed to excel in crafting efficient and elegant software solutions. About the Book: "Mastering Object-Oriented Programming" takes you on a transformative journey through the intricacies of OOP, from foundational concepts to advanced techniques. From classes and inheritance to polymorphism and design patterns, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of OOP principles and practical applications in real-world scenarios. Key Features: · Foundational Understanding: Build a solid foundation by comprehending the core principles of object-oriented programming, including classes, objects, and encapsulation. · Inheritance and Polymorphism: Explore the power of inheritance and polymorphism, understanding how to create hierarchical class structures and achieve code reuse. · Abstraction and Encapsulation: Master the art of abstraction, encapsulation, and information hiding for designing clean and maintainable code. · Design Patterns: Dive into essential design patterns, such as Singleton, Factory, Observer, and more, understanding how to apply them to solve common programming challenges. · Object-Oriented Analysis and Design: Learn techniques for analyzing and designing software systems using UML diagrams, use cases, and design principles. · SOLID Principles: Gain insights into the SOLID principles of OOP—Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion—and how they contribute to modular and extensible code. · Testing and Debugging: Explore strategies for unit testing, debugging, and code optimization in the context of object-oriented programming. · Challenges and Trends: Discover challenges in software development, from code maintainability to architectural considerations, and explore emerging trends shaping the future of OOP. Who This Book Is For: "Mastering Object-Oriented Programming" is designed for developers, programmers, software engineers, students, and anyone passionate about writing efficient and maintainable code. Whether you're aiming to enhance your skills or embark on a journey toward becoming an OOP expert, this book provides the insights and tools to navigate the complexities of object-oriented programming. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.

A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Real-life case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.

This book is for Python programmers with an intermediate background and an interest in design patterns implemented in idiomatic Python. Programmers of other languages who are interested in Python can also benefit from this book, but it would be better if they first read some introductory materials that explain how things are done in Python.

This book is intended for Python developers who want to use the principles of test-driven development (TDD) to create efficient and robust applications. In order to get the best out of this book, you should have development experience with Python.

Power up your Python with object-oriented programming and learn how to write powerful, efficient, and re-usable code. Object-Oriented Python is an intuitive and thorough guide to mastering object-oriented programming from the ground up. You’ll cover the basics of building classes and creating objects, and put theory into practice using the pygame package with clear examples that help visualize the object-oriented style. You’ll explore the key concepts of object-oriented programming — encapsulation, polymorphism, and inheritance — and learn not just how to code with objects, but the absolute best practices for doing so. Finally, you’ll bring it all together by building a complex video game, complete with full animations and sounds. The book covers two fully functional Python code packages that will speed up development of graphical user interface (GUI) programs in Python.

A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques Key Features Build an intuitive understanding of object-oriented design, from introductory to mature programs Learn the ins and outs of Python syntax, libraries, and best practices Examine a machine-learning case study at the end of each chapter Book Description Object-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 learn Implement objects in Python by creating classes and defining methods Extend class functionality using inheritance Use exceptions to handle unusual situations cleanly Understand when to use object-oriented features, and more importantly, when not to use them Discover several widely used design patterns and how they are implemented in Python Uncover the simplicity of unit and integration testing and understand why they are so important Learn to statically type check your dynamic code Understand concurrency with asyncio and how it speeds up programs Who this book is for If 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.

This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

Network programming has always been a demanding task. With full-featured and well documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be. Starting with a walkthrough of today's major networking protocols, with this book you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the Web. You'll utilize Python for e-mailing using different protocols and you'll interact with remote systems and IP and DNS networking. As the book progresses, socket programming will be covered, followed by how to design servers and the pros and cons of multithreaded and event-driven architectures. You'll develop practical client-side applications, including web API clients, e-mail clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks.