# 扩展和嵌入 Python 解释器

本文档描述了如何使用 C 或 C++ 编写模块以使用新模块来扩展 Python 解释器的功能。 这些模块不仅可以定义新的函数，还可以定义新的对象类型及其方法。 该文档还描述了如何将 Python 解释器嵌入到另一个应用程序中，以用作扩展语言。 最后，它展示了如何编译和链接扩展模块，以便它们可以动态地（在运行时）加载到解释器中，如果底层操作系统支持此特性的话。

This document assumes basic knowledge about Python. For an informal introduction to the language, see Python 教程. Python 语言参考 gives a more formal definition of the language. Python 标准库 documents the existing object types, functions and modules (both built-in and written in Python) that give the language its wide application range.

For a detailed description of the whole Python/C API, see the separate Python/C API 参考手册.

## Recommended third party tools

This guide only covers the basic tools for creating extensions provided as part of this version of CPython. Third party tools like Cython, cffi, SWIG and Numba offer both simpler and more sophisticated approaches to creating C and C++ extensions for Python.

参见

Python Packaging User Guide: Binary Extensions
  The Python Packaging User Guide not only covers several available tools that simplify the creation of binary extensions, but also discusses the various reasons why creating an extension module may be desirable in the first place.

## Creating extensions without third party tools

This section of the guide covers creating C and C++ extensions without assistance from third party tools. It is intended primarily for creators of those tools, rather than being a recommended way to create your own C extensions.

- 1. Extending Python with C or C++
  - 1.1. A Simple Example
  - 1.2. Intermezzo: Errors and Exceptions
  - 1.3. Back to the Example
  - 1.4. The Module's Method Table and Initialization Function
  - 1.5. Compilation and Linkage
  - 1.6. Calling Python Functions from C
  - 1.7. Extracting Parameters in Extension Functions
  - 1.8. Keyword Parameters for Extension Functions
  - 1.9. Building Arbitrary Values
  - 1.10. 引用计数
  - 1.11. Writing Extensions in C++
  - 1.12. Providing a C API for an Extension Module
- 2. 自定义扩展类型：教程
  - 2.1. 基础
  - 2.2. Adding data and methods to the Basic example
  - 2.3. Providing finer control over data attributes
  - 2.4. Supporting cyclic garbage collection
  - 2.5. Subclassing other types
- 3. 定义扩展类型：已分类主题
  - 3.1. 终结和内存释放
  - 3.2. 对象展示
  - 3.3. Attribute Management
  - 3.4. Object Comparison
  - 3.5. Abstract Protocol Support
  - 3.6. Weak Reference Support
  - 3.7. 更多建议
- 4. Building C and C++ Extensions
  - 4.1. Building C and C++ Extensions with distutils
  - 4.2. Distributing your extension modules
- 5. Building C and C++ Extensions on Windows
  - 5.1. A Cookbook Approach
  - 5.2. Differences Between Unix and Windows
  - 5.3. Using DLLs in Practice

## Embedding the CPython runtime in a larger application

Sometimes, rather than creating an extension that runs inside the Python interpreter as the main application, it is desirable to instead embed the CPython runtime inside a larger application. This section covers some of the details involved in doing that successfully.

- 1. Embedding Python in Another Application
  - 1.1. Very High Level Embedding
  - 1.2. Beyond Very High Level Embedding: An overview
  - 1.3. Pure Embedding
  - 1.4. Extending Embedded Python
  - 1.5. Embedding Python in C++
  - 1.6. Compiling and Linking under Unix-like systems