Python 简明教程

Python - Object Internals

internals of Python objects 更深入地说明了 Python 如何管理和处理数据。这些知识对于编写高效、经过优化的代码以及进行高效调试至关重要。

The internals of Python objects provides deeper insights into how Python manages and manipulates data. This knowledge is essential for writing efficient, optimized code and for effective debugging.

无论我们是通过引用计数和垃圾回收管理内存来处理不可变对象还是可变对象，还是利用特殊方法和插槽，掌握这些概念对于精通 Python 编程至关重要。

Whether we’re handling immutable or mutable objects by managing memory with reference counting and garbage collection or leveraging special methods and slots, grasping these concepts is fundamental to mastering Python programming.

了解 Python’s object internals 对于优化代码和调试至关重要。以下是 Python 对象内部结构主要方面的概述 −

Understanding Python’s object internals is crucial for optimizing code and debugging. Following is an overview of the key aspects of Python object internals −

Object Structure

在 Python 中，每个对象都是一个复杂的数据结构，其封装了各种信息。了解对象结构有助于开发人员掌握 Python 如何管理内存和处理数据。

In Python every object is a complex data structure that encapsulates various pieces of information. Understanding the object structure helps developers to grasp how Python manages memory and handles data.

每个 python 对象主要包括以下两个部分 −

Each python object mainly consists of two parts as mentioned below −

Object Header: This is a crucial part of every Python object that contains essential information for the Python interpreter to manage the object effectively. It typically consists of two main components namely Reference count and Type Pointer.
Object Data: This data is the actual data contained within the object which can differ based on the object’s type. For example an integer contains its numeric value while a list contains references to its elements.

Object Identity

Object Identity 是对象的标识，是一个表示其内存地址的唯一整数。在对象的整个生命周期内它保持不变。 Python 中的每个对象都具有一个唯一标识符，可以通过 id() function 获得。

Object Identity is the identity of an object which is an unique integer that represents its memory address. It remains constant during the object’s lifetime. Every object in Python has a unique identifier obtained using the id() function.

Example

以下是获取对象标识的示例代码 −

Following is the example code of getting the Object Identity −

a = "Tutorialspoint"
print(id(a))  # Example of getting the id of an string object

执行上述代码，我们将得到以下输出 −

On executing the above code we will get the following output −

2366993878000

Note: 内存地址在每次执行代码时都会更改。

Note: The memory address will change on every execution of the code.

Object Type

Object Type 是对象的类型，它定义了可以在其上执行的操作。例如，整数、字符串和列表有不同的类型。它由其类定义，可以使用 type() function 访问。

Object Type is the type of an object defines the operations that can be performed on it. For example integers, strings and lists have distinct types. It is defined by its class and can be accessed using the type() function.

Example

以下是示例 −

Here is the example of it −

a = "Tutorialspoint"
print(type(a))

执行以上代码，我们将获得以下 output -

On executing the above code we will get the following output −

<class 'str'>

Object Value

Object Value 的对象是它所保存的实际数据。这可以是原语值（例如整数或字符串），或可以是更复杂的数据结构，比如 lists 或 dictionaries 。

Object Value of an object is the actual data it holds. This can be a primitive value like an integer or string, or it can be more complex data structures like lists or dictionaries.

Example

以下是对象值示例 −

Following is the example of the object value −

b = "Welcome to Tutorialspoint"
print(b)

执行以上代码，我们将获得以下 output -

On executing the above code we will get the following output −

Welcome to Tutorialspoint

Memory Management

Memory management in Python 是语言设计中至关重要的一方面，因为它可以确保在处理对象生命周期和垃圾回收时高效利用资源。以下是 Python 中内存管理的主要组成部分：−

Memory management in Python is a critical aspect of the language’s design by ensuring efficient use of resources while handling object lifetimes and garbage collection. Here are the key components of memory management in Python −

Reference Counting: Python uses reference counting to manage memory. Each object keeps track of how many references point to it. When this count drops to zero then the memory can be freed.
Garbage Collection: In addition to reference counting the Python employs a garbage collector to identify and clean up reference cycles.

Example

以下是内存管理中获取引用计数的示例 −

Following is the example of the getting the reference counting in memory management −

import sys
c = [1, 2, 3]
print(sys.getrefcount(c))  # Shows the reference count

执行以上代码，我们将获得以下 output -

On executing the above code we will get the following output −

Attributes and Methods

Python 对象可以有 attributes 和 methods ，它们使用点符号访问。其中属性存储数据，而方法定义行为。

Python objects can have attributes and methods which are accessed using dot notation. In which Attributes store data while methods define the behavior.

Example

class MyClass:
   def __init__(self, value):
      self.value = value

   def display(self):
      print(self.value)

obj = MyClass(10)
obj.display()

执行以上代码，我们将获得以下 output -

On executing the above code we will get the following output −

最后，了解 Python 的对象内部结构有助于优化性能并有效调试。通过掌握对象在内存中的结构和管理方式，开发人员可以在编写 Python 代码时做出明智的决策。

Finally, understanding Python’s object internals helps optimize performance and debug effectively. By grasping how objects are structured and managed in memory where developers can make informed decisions when writing Python code.