# Extending and Embedding the Python Interpreter

This document describes how to write modules in C or C++ to extend the Python interpreter with new modules. Those modules can not only define new functions but also new object types and their methods. The document also describes how to embed the Python interpreter in another application, for use as an extension language. Finally, it shows how to compile and link extension modules so that they can be loaded dynamically (at run time) into the interpreter, if the underlying operating system supports this feature.

This document assumes basic knowledge about Python. For an informal introduction to the language, see Python Tutorial. Dokumentacja języka Python gives a more formal definition of the language. Biblioteka standardowa Pythona 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 Reference Manual.

## 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.

Zobacz także

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. Rozszerzanie Pythona za pomocą C lub C++
  - 1.1. Prosty przykład
  - 1.2. Intermezzo: Błędy i Wyjątki
  - 1.3. Z powrotem do Przykładu
  - 1.4. Zadanie zainicjowania i tabela sposobów postępowania modułu.
  - 1.5. Kompilacja i łączenie
  - 1.6. Wywoływanie zadań języka pytonowskiego z C
  - 1.7. Wydobywanie parametrów w zadaniach rozszerzających
  - 1.8. Parametry kluczowe dla zadań rozszerzających
  - 1.9. Budowanie dowolnych wartości
  - 1.10. Liczby odniesień
  - 1.11. Pisanie rozszerzeń w C++
  - 1.12. Dostarczanie sprzęgu programowania aplikacji (API) języka C dla modułu rozszerzającego
- 2. Defining Extension Types: Tutorial
  - 2.1. The Basics
  - 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. Defining Extension Types: Assorted Topics
  - 3.1. Finalizowanie i de-alokacja
  - 3.2. Prezentacja Przedmiotów
  - 3.3. Zarządzanie własnościami
  - 3.4. Porównywanie przedmiotów
  - 3.5. Wsparcie protokołu abstrakcyjnego
  - 3.6. Wsparcie dla słabych odniesień
  - 3.7. Więcej sugestii
- 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