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“Python 官方简明教程”的版本间的差异

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Python 是一个强大易学的程序语言。它拥有高效的数据构造和简洁便利的……
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Python是一个简单易学、功能强大的编程语言。它拥有高效的数据构造和简洁便利的面向对象的程序设计。Python的优美语法和动态输入与解释器自然地融合在一起，使之成为了一个能在大多数平台和众多领域中编写脚本和快速应用程序开发的理想语言。
  
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Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.
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在Python的官方网站 http://www.python.org/ 里，为所有主要的平台提供Pythn的解释器和丰富的标准库，而且都开放免费的源代码或者二进制代码，可以自由分发。这个网站也涵括发布许多第三方Python模块、程序和工具、额外的文档等。
  
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The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python Web site, http://www.python.org/, and may be freely distributed. The same site also contains distributions of and pointers to many free third party Python modules, programs and tools, and additional documentation.
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Python的解释器很易于在C或C++（或其他从C语言调用）扩展新功能和数据类型。Python也很适合于在定制应用中作为一个可扩展的编程语言。
  
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The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). Python is also suitable as an extension language for customizable applications.
 
  
 
This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well.
 
This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well.

2011年5月15日 (日) 15:23的版本

Python是一个简单易学、功能强大的编程语言。它拥有高效的数据构造和简洁便利的面向对象的程序设计。Python的优美语法和动态输入与解释器自然地融合在一起，使之成为了一个能在大多数平台和众多领域中编写脚本和快速应用程序开发的理想语言。

在Python的官方网站 http://www.python.org/ 里，为所有主要的平台提供Pythn的解释器和丰富的标准库，而且都开放免费的源代码或者二进制代码，可以自由分发。这个网站也涵括发布许多第三方Python模块、程序和工具、额外的文档等。

Python的解释器很易于在C或C++（或其他从C语言调用）扩展新功能和数据类型。Python也很适合于在定制应用中作为一个可扩展的编程语言。


This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. It helps to have a Python interpreter handy for hands-on experience, but all examples are self-contained, so the tutorial can be read off-line as well.

For a description of standard objects and modules, see The Python Standard Library. The Python Language Reference gives a more formal definition of the language. To write extensions in C or C++, read Extending and Embedding the Python Interpreter and Python/C API Reference Manual. There are also several books covering Python in depth.

This tutorial does not attempt to be comprehensive and cover every single feature, or even every commonly used feature. Instead, it introduces many of Python’s most noteworthy features, and will give you a good idea of the language’s flavor and style. After reading it, you will be able to read and write Python modules and programs, and you will be ready to learn more about the various Python library modules described in The Python Standard Library.

The Glossary is also worth going through.

  • 1. Whetting Your Appetite
  • 2. Using the Python Interpreter
    • 2.1. Invoking the Interpreter
      • 2.1.1. Argument Passing
      • 2.1.2. Interactive Mode
    • 2.2. The Interpreter and Its Environment
      • 2.2.1. Error Handling
      • 2.2.2. Executable Python Scripts
      • 2.2.3. Source Code Encoding
      • 2.2.4. The Interactive Startup File
  • 3. An Informal Introduction to Python
    • 3.1. Using Python as a Calculator
      • 3.1.1. Numbers
      • 3.1.2. Strings
      • 3.1.3. About Unicode
      • 3.1.4. Lists
    • 3.2. First Steps Towards Programming
  • 4. More Control Flow Tools
    • 4.1. if Statements
    • 4.2. for Statements
    • 4.3. The range() Function
    • 4.4. break and continue Statements, and else Clauses on Loops
    • 4.5. pass Statements
    • 4.6. Defining Functions
    • 4.7. More on Defining Functions
      • 4.7.1. Default Argument Values
      • 4.7.2. Keyword Arguments
      • 4.7.3. Arbitrary Argument Lists
      • 4.7.4. Unpacking Argument Lists
      • 4.7.5. Lambda Forms
      • 4.7.6. Documentation Strings
    • 4.8. Intermezzo: Coding Style
  • 5. Data Structures
    • 5.1. More on Lists
      • 5.1.1. Using Lists as Stacks
      • 5.1.2. Using Lists as Queues
      • 5.1.3. List Comprehensions
      • 5.1.4. Nested List Comprehensions
    • 5.2. The del statement
    • 5.3. Tuples and Sequences
    • 5.4. Sets
    • 5.5. Dictionaries
    • 5.6. Looping Techniques
    • 5.7. More on Conditions
    • 5.8. Comparing Sequences and Other Types
  • 6. Modules
    • 6.1. More on Modules
      • 6.1.1. Executing modules as scripts
      • 6.1.2. The Module Search Path
      • 6.1.3. “Compiled” Python files
    • 6.2. Standard Modules
    • 6.3. The dir() Function
    • 6.4. Packages
      • 6.4.1. Importing * From a Package
      • 6.4.2. Intra-package References
      • 6.4.3. Packages in Multiple Directories
  • 7. Input and Output
    • 7.1. Fancier Output Formatting
      • 7.1.1. Old string formatting
    • 7.2. Reading and Writing Files
      • 7.2.1. Methods of File Objects
      • 7.2.2. The pickle Module
  • 8. Errors and Exceptions
    • 8.1. Syntax Errors
    • 8.2. Exceptions
    • 8.3. Handling Exceptions
    • 8.4. Raising Exceptions
    • 8.5. User-defined Exceptions
    • 8.6. Defining Clean-up Actions
    • 8.7. Predefined Clean-up Actions
  • 9. Classes
    • 9.1. A Word About Names and Objects
    • 9.2. Python Scopes and Namespaces
      • 9.2.1. Scopes and Namespaces Example
    • 9.3. A First Look at Classes
      • 9.3.1. Class Definition Syntax
      • 9.3.2. Class Objects
      • 9.3.3. Instance Objects
      • 9.3.4. Method Objects
    • 9.4. Random Remarks
    • 9.5. Inheritance
      • 9.5.1. Multiple Inheritance
    • 9.6. Private Variables
    • 9.7. Odds and Ends
    • 9.8. Exceptions Are Classes Too
    • 9.9. Iterators
    • 9.10. Generators
    • 9.11. Generator Expressions
  • 10. Brief Tour of the Standard Library
    • 10.1. Operating System Interface
    • 10.2. File Wildcards
    • 10.3. Command Line Arguments
    • 10.4. Error Output Redirection and Program Termination
    • 10.5. String Pattern Matching
    • 10.6. Mathematics
    • 10.7. Internet Access
    • 10.8. Dates and Times
    • 10.9. Data Compression
    • 10.10. Performance Measurement
    • 10.11. Quality Control
    • 10.12. Batteries Included
  • 11. Brief Tour of the Standard Library – Part II
    • 11.1. Output Formatting
    • 11.2. Templating
    • 11.3. Working with Binary Data Record Layouts
    • 11.4. Multi-threading
    • 11.5. Logging
    • 11.6. Weak References
    • 11.7. Tools for Working with Lists
    • 11.8. Decimal Floating Point Arithmetic
  • 12. What Now?
  • 13. Interactive Input Editing and History Substitution
    • 13.1. Line Editing
    • 13.2. History Substitution
    • 13.3. Key Bindings
    • 13.4. Alternatives to the Interactive Interpreter
  • 14. Floating Point Arithmetic: Issues and Limitations
    • 14.1. Representation Error
—————　返回《 Python 手册 》总目录　—————
取自“https://wiki.ubuntu.org.cn/index.php?title=Python_官方简明教程&oldid=143777”