使用@property裝飾器可創(chuàng)建受控屬性，1. 用@property定義只讀屬性，訪問時調(diào)用getter方法；2. 用@屬性名.setter添加賦值時的驗證邏輯；3. 用@屬性名.deleter定義刪除屬性時的行為；4. 可創(chuàng)建動態(tài)計算的屬性如面積、直徑等；5. 優(yōu)勢包括封裝性、數(shù)據(jù)驗證、接口兼容性和簡潔語法，最終實現(xiàn)屬性的智能管理而不暴露內(nèi)部數(shù)據(jù)。

Using property decorators in Python allows you to create managed attributes — class attributes that behave like regular attributes but have controlled access through getter, setter, and deleter methods. This is useful for validating data, computing values on demand, or maintaining encapsulation without sacrificing a clean API.

Here's how to use the @property decorator effectively:

1. Basic Usage: Creating a Read-Only Property

You can use @property to turn a method into a "getter" for an attribute.

 class Circle:
    def __init__(self, radius):
        self._radius = radius

    @property
    def radius(self):
        return self._radius

# Usage
c = Circle(5)
print(c.radius) # 5
# c.radius = 10 # AttributeError: can't set attribute (by default)

Here, radius is a managed attribute. Accessing c.radius calls the method, but you can't set it unless you define a setter.

2. Adding a Setter: Allow Controlled Assignment

Use @<property>.setter to define what happens when the attribute is assigned.

 class Circle:
    def __init__(self, radius):
        self._radius = radius

    @property
    def radius(self):
        return self._radius

    @radius.setter
    def radius(self, value):
        if value < 0:
            raise ValueError("Radius cannot be negative")
        self._radius = value

# Usage
c = Circle(5)
c.radius = 10 # Works
# c.radius = -3 # Raises ValueError

Now you can assign to radius , but invalid values are caught.

3. Adding a Deleter: Define Behavior on del

Use @<property>.deleter to specify what happens when del obj.attr is used.

 @radius.deleter
    def radius(self):
        print("Deleting radius...")
        del self._radius

# Usage
del c.radius # Prints message and removes _radius

This is less commonly used but helpful for cleanup.

4. Computed Properties (Lazy or Derived Attributes)

You can use properties to compute values dynamically.

 import math

class Circle:
    def __init__(self, radius):
        self._radius = radius

    @property
    def radius(self):
        return self._radius

    @radius.setter
    def radius(self, value):
        if value < 0:
            raise ValueError("Radius cannot be negative")
        self._radius = value

    @property
    def area(self):
        return math.pi * self._radius ** 2

    @property
    def diameter(self):
        return 2 * self._radius

# Usage
c = Circle(3)
print(c.area) # 28.274...
print(c.diameter) # 6

The area and diameter are not stored — they're computed when accessed, but feel like normal attributes.

5. Why Use Properties? Key Benefits

• Encapsulation : Hide internal representation (eg, _radius )
• Validation : Enforce rules in setters
• Backward Compatibility : Add logic later without changing the interface
• Clean Syntax : Users access via obj.attr , not obj.get_attr()

Summary: Full Example

 class Temperature:
    def __init__(self, celsius=0):
        self._celsius = celsius

    @property
    def celsius(self):
        return self._celsius

    @celsius.setter
    def celsius(self, value):
        if value < -273.15:
            raise ValueError("Temperature below absolute zero is not possible")
        self._celsius = value

    @property
    def fahrenheit(self):
        return self._celsius * 9/5 32

    @fahrenheit.setter
    def fahrenheit(self, value):
        self.celsius = (value - 32) * 5/9 # Reuse celsius validation

# Usage
t = Temperature(25)
print(t.fahrenheit) # 77.0
t.fahrenheit = 86
print(t.celsius) # 30.0

This shows how properties make attributes smart while keeping usage simple.

Basically, just remember:

• Use @property for the getter
• Use @property_name.setter for assignment
• Use @property_name.deleter if needed
• Always validate or compute inside these methods

It's a clean way to manage attribute access without exposing raw data.

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