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 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 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 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.

Python isn't all about object-oriented programming. Discover a valuable way of thinking about code design through a function-first approach - and learn when you need to use it. Now with detailed exercises at the end of every chapter! Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn how, when, and why to adopt functional elements in your projects Explore the Python modules essential to functional programming, like itertools and functools Revised to cover new features of Python 3.10, exercises at the end of every chapter, and more Book DescriptionNot enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with examples centered around data cleaning and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though - you'll also see how Python's native object-orientation is used in conjunction with functional programming techniques. By the end of this book, you'll be well versed in the essential functional programming features of Python, and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language. What you will learn Use Python's libraries to avoid the complexities of state-changing classes Leverage built-in higher-order functions to avoid rewriting common algorithms Write generator functions to create lazy processing Design and implement decorators for functional composition Make use of Python type annotations to describe parameters and results of functions Apply functional programming to concurrency and web services Explore the PyMonad library for stateful simulations Who this book is forThe functional paradigm is very useful for programmers working in data science, but any Python developer who wants to create more reliable, succinct, and expressive code will have much to learn from this book. No prior knowledge of functional programming is required to get started, though Python programming knowledge is assumed. A running Python environment is essential.

Complete recipes spread across 15 chapters to help you overcome commonly faced issues by Python for everybody across the globe. Each recipe takes a problem-solution approach to resolve for effective Python. Key Features Develop expressive and effective Python programs Best practices and common idioms through carefully explained recipes Discover new ways to apply Python for data-focused development Make use of Python's optional type annotations Book DescriptionPython is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation. What you will learn See the intricate details of the Python syntax and how to use it to your advantage Improve your coding with Python readability through functions Manipulate data effectively using built-in data structures Get acquainted with advanced programming techniques in Python Equip yourself with functional and statistical programming features Write proper tests to be sure a program works as advertised Integrate application software using Python Who this book is forThe Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help.

Gain comprehensive insights into programming practices, and code portability and reuse to build flexible and maintainable apps using object-oriented principles Key Features Extend core OOP techniques to increase integration of classes created with Python Explore various Python libraries for handling persistence and object serialization Learn alternative approaches for solving programming problems, with different attributes to address your problem domain Book DescriptionObject-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs. By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python. What you will learn Explore a variety of different design patterns for the __init__() method Learn to use Flask to build a RESTful web service Discover SOLID design patterns and principles Use the features of Python 3's abstract base Create classes for your own applications Design testable code using pytest and fixtures Understand how to design context managers that leverage the 'with' statement Create a new type of collection using standard library and design techniques Develop new number types above and beyond the built-in classes of numbers Who this book is forThis book is for developers who want to use Python to create efficient programs. A good understanding of Python programming is required to make the most out of this book. Knowledge of concepts related to object-oriented design patterns will also be useful.

Test your Python programming skills by solving real-world problems Key Features Access built-in documentation tools and improve your code. Discover how to make the best use of decorator and generator functions Enhance speed and improve concurrency by conjuring tricks from the PyPy project Book DescriptionThis book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You'll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You'll understand the implementation of collections, decimals, and fraction modules. If you haven't used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you'll learn what you've been missing out on. We'll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you'll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We'll take you through the depths of the PyPy project, where you'll come across several exciting ways that you can improve speed and concurrency. Finally, we'll take time to explore the PEPs of the latest versions to discover some interesting hacks. What you will learn Know the differences between .py and .pyc files Explore the different ways to install and upgrade Python packages Understand the working of the PyPI module that enhances built-in decorators See how coroutines are different from generators and how they can simulate multithreading Grasp how the decimal module improves floating point numbers and their operations Standardize sub interpreters to improve concurrency Discover Python's built-in docstring analyzer Who this book is forWhether you've been working with Python for a few years or you're a seasoned programmer, you'll have a lot of new tricks to walk away with.

Create succinct and expressive implementations with functional programming in Python Key Features Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance Get familiar with complex concepts such as monads, concurrency, and immutability Apply functional Python to common Exploratory Data Analysis (EDA) programming problems Book DescriptionIf you're a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you'll explore common functional features such as first-class and higher-order functions, pure functions, and more. You'll see how these are accomplished in Python 3.6 to give you the core foundations you'll build upon. After that, you'll discover common functional optimizations for Python to help your apps reach even higher speeds. You'll learn FP concepts such as lazy evaluation using Python's generator functions and expressions. Moving forward, you'll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you'll at look at the PyMonad project and some larger examples to put everything into perspective. What you will learn Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs Use Python strings with object-oriented suffix notation and prefix notation Avoid stateful classes with families of tuples Design and implement decorators to create composite functions Use functions such as max(), min(), map(), filter(), and sorted() Write higher-order functions Who this book is forThis book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed.

The latest in modern Python recipes for the busy modern programmer About This Book * Develop succinct, expressive programs in Python * Learn the best practices and common idioms through carefully explained and structured recipes * Discover new ways to apply Python for the new age of development Who This Book Is For The book is for web developers, programmers, enterprise programmers, engineers, big data scientist, and so on. If you are a beginner, Python Cookbook will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help. What You Will Learn * See the intricate details of the Python syntax and how to use it to your advantage * Improve your code readability through functions in Python * Manipulate data effectively using built-in data structures * Get acquainted with advanced programming techniques in Python * Equip yourself with functional and statistical programming features * Write proper tests to be sure a program works as advertised * Integrate application software using Python In Detail Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation. Style and approach This book takes a recipe-based approach, where each recipe addresses specific problems and issues. The recipes provide discussions and insights and an explanation of the problems.

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If you are a Python beginner who is looking to learn the language through interesting projects, this book is for you. A basic knowledge of programming and statistics is beneficial to get the most out of the book.

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 objectoriented 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.