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Learning Python (Powerful Object-Oriented Programming) - 9781098171308

List Price: $79.99
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9781098171308
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  • Product Details

    Author:
    Mark Lutz
    Format:
    Paperback
    Pages:
    1169
    Publisher:
    O'Reilly Media (April 1, 2025)
    Language:
    English
    ISBN-13:
    9781098171308
    ISBN-10:
    1098171306
    Dimensions:
    7" x 9.19"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20260707163249-20260707.xml
    Folder:
    TWO RIVERS
    List Price:
    $79.99
    Country of Origin:
    United States
    Pub Discount:
    60
    Case Pack:
    3
    As low as:
    $68.79
    Publisher Identifier:
    P-PER
    Discount Code:
    C
    Imprint:
    O'Reilly Media
    Weight:
    64.32oz
  • Overview

    Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz's popular training course, this updated sixth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages.

    Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow self-paced tutorial gets you started with Python 3.12 and all other releases in use today. With a pragmatic focus on what you need to know, it also introduces some advanced language features that have become increasingly common in Python code.

    This book helps you:

    • Explore Python's built-in object types such as strings, lists, dictionaries, and files
    • Create and process objects with Python statements, and learn Python's syntax model
    • Use functions and functional programming to avoid redundancy and maximize reuse
    • Organize code into larger components with modules and packages
    • Code robust programs with Python's exception handling and development tools
    • Apply object-oriented programming and classes to make code customizable
    • Survey advanced Python tools including decorators, descriptors, and metaclasses
    • Write idiomatic Python code that runs portably across a wide variety of platforms