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Make your good Python code even better by following proven and effective pythonic programming tips. Avoid logical errors that usually go undetected by Python linters and code formatters, such as frequent data look-ups in long lists, improper use of local and global variables, and mishandled user input. Discover rare language features, like rational numbers, set comprehensions, counters, and pickling, that may boost your productivity. Discover how to apply general programming patterns, including caching, in your Python code. Become a better-than-average Python programmer, and develop self-documented, maintainable, easy-to-understand programs that are fast to run and hard to break. Python is one of the most popular and rapidly growing modern programming languages. With more than 200 standard libraries and even more third-party libraries, it reaches into the software development areas as diverse as artificial intelligence, bioinformatics, natural language processing, and computer vision. Find out how to improve your understanding of the spirit of the language by using one hundred pythonic tips to make your code safer, faster, and better documented. This programming style manual is a quick reference of helpful hints and a random source of inspiration. Choose the suitable data structures for searching and sorting jobs and become aware of how a wrong choice may cause your application to be completely ineffective. Understand global and local variables, class and instance attributes, and information-hiding techniques. Create functions with flexible interfaces. Manage intermediate computation results by caching them in files and memory to improve performance and reliability. Polish your documentation skills to make your code easy for other programmers to understand. As a bonus, discover Easter eggs cleverly planted in the standard library by its developers. Polish, secure, and speed-up your Python applications, and make them easier to maintain by following pythonic programming tips. What You Need: You will need a Python interpreter (ideally, version 3.4 or above) and the standard Python library that usually comes with the interpreter.
The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.
Getting the most out of Python to improve your codebase Key Features Save maintenance costs by learning to fix your legacy codebase Learn the principles and techniques of refactoring Apply microservices to your legacy systems by implementing practical techniques Book Description Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code. What you will learn Set up tools to effectively work in a development environment Explore how the magic methods of Python can help us write better code Examine the traits of Python to create advanced object-oriented design Understand removal of duplicated code using decorators and descriptors Effectively refactor code with the help of unit tests Learn to implement the SOLID principles in Python Who this book is for This book will appeal to team leads, software architects and senior software engineers who would like to work on their legacy systems to save cost and improve efficiency. A strong understanding of Programming is assumed.
Once you've mastered the basics of Python, how do you skill up to the top 1%? How do you focus your learning time on topics that yield the most benefit for production engineering and data teams—without getting distracted by info of little real-world use? This book answers these questions and more. Based on author Aaron Maxwell's software engineering career in Silicon Valley, this unique book focuses on the Python first principles that act to accelerate everything else: the 5% of programming knowledge that makes the remaining 95% fall like dominos. It's also this knowledge that helps you become an exceptional Python programmer, fast. Learn how to think like a Pythonista: explore advanced Pythonic thinking Create lists, dicts, and other data structures using a high-level, readable, and maintainable syntax Explore higher-order function abstractions that form the basis of Python libraries Examine Python's metaprogramming tool for priceless patterns of code reuse Master Python's error model and learn how to leverage it in your own code Learn the more potent and advanced tools of Python's object system Take a deep dive into Python's automated testing and TDD Learn how Python logging helps you troubleshoot and debug more quickly
Learn to build and manage better software with clean, intuitive, scalable, maintainable, and high-performance Python code. KEY FEATURES ● Comparative analysis of regular and Pythonic coding constructs. ● Illustrates application design paradigms for Python projects. ● Detailed pointers on optimal data processing and application design. ● Highlights accepted conventions for testing and managing production code. DESCRIPTION ‘The Pythonic Way' acquaints you with Python's capabilities beyond basic syntax. This book will help you understand widely accepted Pythonic constructs and procedures, thus enabling you to write reliable, optimized, and modular applications. You'll learn about Pythonic data structures, class and object creation, and more. The book then delves into some of Python's lesser-known but incredibly powerful functionalities such as meta-programming, decorators, context managers, generators, and iterators. Additionally, you'll learn how to accelerate computations by using Pandas Series and Dataframes. You will be introduced to various design patterns that work well with Python applications. Finally, we'll discuss testing frameworks and best practices for testing, packaging, launching, and publishing applications in production environments. This book will empower you as you transition from beginner or competitive Python coding to industry-standard Python software development. Intermediate Python developers will gain a deeper understanding of the language's nuances, enabling them to create better software. WHAT YOU WILL LEARN ● Understand common practices for writing scalable and legible Python code. ● Create robust and maintainable production codebases for time and space performant applications. ● Master effective data processing practices and features like generators and decorators to improve complex computations on large datasets. ● Get familiar with Pythonic design patterns for secure, large-scale applications. ● Learn to organize your project’s code into modules. ● Familiarize yourself with different testing tools and frameworks. WHO THIS BOOK IS FOR This book is a valuable reference manual for novice and intermediate programmers and data scientists to learn about Pythonic standards and conventions. For beginners, this book will get you started with Pythonic thinking. This book will serve as a guide to fine-tune your skills beyond syntax and help build robust Python applications for intermediate Python coders. TABLE OF CONTENTS 1. Introduction to Pythonic Code 2. Pythonic Data Structures 3. Classes and OOP Conventions 4. Python Modules and Metaprogramming 5. Pythonic Décorators and Context Managers 6. Data Processing Done Right 7. Iterators, Generators, and Coroutines 8. Python Descriptors 9. Pythonic Application Design and Architecture 10. Effective Testing for Python Code 11. Production Code Management
Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers: Python data model: understand how special methods are the key to the consistent behavior of objects Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work
This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.
* Covers low-level networking in Python —essential for writing a new networked application protocol. * Many working examples demonstrate concepts in action -- and can be used as starting points for new projects. * Networked application security is demystified. * Exhibits and explains multitasking network servers using several models, including forking, threading, and non-blocking sockets. * Features extensive coverage of Web and E-mail. Describes Python's database APIs.
Get up and running with Python 3.9 through concise tutorials and practical projects in this fully updated third edition. Purchase of the print or Kindle book includes a free eBook in PDF format. Key FeaturesExtensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python codeDiscover how to think like a Python programmerLearn the fundamentals of Python through real-world projects in API development, GUI programming, and data scienceBook Description Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter. The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book. Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned. What you will learnGet Python up and running on Windows, Mac, and LinuxWrite elegant, reusable, and efficient code in any situationAvoid common pitfalls like duplication, complicated design, and over-engineeringUnderstand when to use the functional or object-oriented approach to programmingBuild a simple API with FastAPI and program GUI applications with TkinterGet an initial overview of more complex topics such as data persistence and cryptographyFetch, clean, and manipulate data, making efficient use of Python's built-in data structuresWho this book is for This book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it's not a prerequisite.
Move Beyond Python Code That "Mostly Works" to Code That Is Expressive, Robust, and Efficient Python is arguably the most-used programming language in the world, with applications from primary school education to workaday web development, to the most advanced scientific research institutes. While there are many ways to perform a task in Python, some are wrong, inelegant, or inefficient. Better Python Code is a guide to "Pythonic" programming, a collection of best practices, ways of working, and nuances that are easy to miss, especially when ingrained habits are borrowed from other programming languages. Author David Mertz presents concrete and concise examples of various misunderstandings, pitfalls, and bad habits in action. He explains why some practices are better than others, based on his 25+ years of experience as an acclaimed contributor to the Python community. Each chapter thoroughly covers related clusters of concepts, with chapters sequenced in ascending order of sophistication. Whether you are starting out with Python or are an experienced developer pushing through the limitations of your Python code, this book is for all who aspire to be more Pythonic when writing better Python code. Use the right kind of loops in Python Learn the ins and outs of mutable and immutable objects Get expert advice to avoid Python "gotchas" Examine advanced Python topics Navigate the "attractive nuisances" that exist in Python Learn the most useful data structures in Python and how to avoid misusing them Avoid security mistakes Understand the basics of numeric computation, including floating point numbers and numeric datatypes "My high expectations for this engaging Python book have been exceeded: it offers a great deal of insight for intermediate or advanced programmers to improve their Python skills, includes copious sharing of precious experience practicing and teaching the language, yet remains concise, easy to read, and conversational." --From the Foreword by Alex Martelli Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.