物品 #:
147979377
Robust Python: Write Clean and Maintainable Code
88% of respondents would recommend this to a friend
物品 #:
147979377
HKD 567
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現在訂購，約可在下列時間收貨： 星期三, 十月 21
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With these tips and techniques, you'll write clearer and more maintainable code.
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What Stands Out
Code Quality
Focuses on writing clean, maintainable Python code, empowering developers to enhance their coding standards. It addresses common pitfalls that lead to technical debt, making it ideal for both beginners and seasoned programmers.
Practical Guidance
Offers actionable insights and best practices, ensuring readers can implement lessons immediately. The hands-on approach helps build confidence and competence in managing larger codebases effectively.
Comprehensive Coverage
Covers a wide range of topics, from basic syntax to advanced design patterns, appealing to a broad audience. This extensive coverage caters to various skill levels, making it a valuable resource for continuous learning.
產品詳情
- 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 ecosystems Understand how type choices such as classes, dictionaries, and enums reflect specific intents Make Python extensible for the future without adding bloat Use popular Python tools to increase the safety and robustness of your codebase Evaluate current code to detect common maintainability gotchas Build a safety net around your codebase with linters and tests
| Publisher | O'Reilly Media |
| Publication date | 3 Aug. 2021 |
| Language | English |
| Print length | 378 pages |
| ISBN-10 | 1098100662 |
| ISBN-13 | 978-1098100667 |
| Dimensions | 17.78 x 2.54 x 22.86 cm |
Who Should Buy?
-
Beginner Programmers
Ideal for those new to Python seeking to write clean and maintainable code through effective practices.
-
Experienced Developers
Great for seasoned programmers who want to refine their coding style and enhance code quality in projects.
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Students Learning Python
Perfect for students wanting to understand best practices, making their code easier to read and maintain.
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Advanced Coders
May not provide advanced insights for highly experienced programmers who already practice clean coding principles.
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English edition Patrick Viafore Format: Paperback Editorial Review
Robust Python Write Clean And Maintainable Code is a comprehensive guide published by O'Reilly Media on August 3, 2021. This book, written in English, spans 378 pages and is designed to help programmers of all levels write code that is both clean and maintainable. With its practical tips and strategies, readers can better understand Python programming and boost their coding efficiency. The dimensions of the book make it easy to handle, making it a great addition to any developer's library.
Customer Reviews & Ratings
107 客戶評分
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5 星
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4 星
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3 星
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2 星
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優點
- Clear and concise explanations of programming concepts
- Practical tips for writing maintainable code
- Ideal for programmers of all skill levels
- Well-structured and easily navigable content
- Valuable resource for enhancing Python knowledge
缺點
- Some may find the content a bit advanced initially
Product Price History
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HKD 567
現在訂購，約可在下列時間收貨： 星期三, 十月 21
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特色和優勢
- Learn why types are essential in modern development ecosystems
- Understand how type choices such as classes, dictionaries, and enums reflect specific intents
- Make Python extensible for the future without adding bloat
- Use popular Python tools to increase the safety and robustness of your codebase
- Evaluate current code to detect common maintainability gotchas
- Build a safety net around your codebase with linters and tests
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