Python 官方简明教程:修订间差异

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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。
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。


本教程向读者非正式地介绍Python语言和系统的基本概念和特征。本教程将帮助您灵巧地掌握Python解释器以及获得实践经验,但所有的例子都是独立的,所以本教程可以离线阅读。


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.
关于标准对像和模块的说明,请参考《Python标准库》。《Python语言参考》对编程语言给出了更正式的定义。需要编写C或C++扩展的朋友请参考《扩展和嵌入式Python解释器和Python/C API接口参考手册》。这些都是有一定深度的Python参考书籍。
 
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.
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.

2011年5月15日 (日) 15:41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。

本教程向读者非正式地介绍Python语言和系统的基本概念和特征。本教程将帮助您灵巧地掌握Python解释器以及获得实践经验,但所有的例子都是独立的,所以本教程可以离线阅读。

关于标准对像和模块的说明,请参考《Python标准库》。《Python语言参考》对编程语言给出了更正式的定义。需要编写C或C++扩展的朋友请参考《扩展和嵌入式Python解释器和Python/C API接口参考手册》。这些都是有一定深度的Python参考书籍。

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 —————