对象定制
高级对象定制技术
Python 中的对象定制使开发者能够创建灵活、强大且智能的对象，以适应各种编程场景。
描述符协议
描述符提供了一种定制属性访问的方式：
class ValidatedAttribute:
def __init__(self, min_value=None, max_value=None):
self.min_value = min_value
self.max_value = max_value
def __set_name__(self, owner, name):
self.name = name
def __get__(self, instance, owner):
return instance.__dict__.get(self.name)
def __set__(self, instance, value):
if self.min_value is not None and value < self.min_value:
raise ValueError(f"Value must be at least {self.min_value}")
if self.max_value is not None and value > self.max_value:
raise ValueError(f"Value must be at most {self.max_value}")
instance.__dict__[self.name] = value
class Person:
age = ValidatedAttribute(0, 120)
def __init__(self, name, age):
self.name = name
self.age = age
元类
元类允许对类的创建进行深度定制：
class SingletonMeta(type):
_instances = {}
def __call__(cls, *args, **kwargs):
if cls not in cls._instances:
cls._instances[cls] = super().__call__(*args, **kwargs)
return cls._instances[cls]
class DatabaseConnection(metaclass=SingletonMeta):
def __init__(self, connection_string):
self.connection_string = connection_string
定制技术比较
| 技术 |
用例 |
复杂度 |
灵活性 |
| 魔法方法 |
基本行为修改 |
低 |
中等 |
| 描述符 |
属性访问控制 |
中等 |
高 |
| 元类 |
类创建定制 |
高 |
非常高 |
代理对象
class LazyProperty:
def __init__(self, function):
self.function = function
self._value = None
def __get__(self, instance, owner):
if self._value is None:
self._value = self.function(instance)
return self._value
class ExpensiveResource:
@LazyProperty
def complex_calculation(self):
## 模拟耗时计算
import time
time.sleep(2)
return sum(range(1000000))
依赖注入模式
class ServiceContainer:
def __init__(self):
self._services = {}
def register(self, service_type, service_implementation):
self._services[service_type] = service_implementation
def resolve(self, service_type):
return self._services.get(service_type)
## 依赖注入可视化
```mermaid
graph TD
A[Service Container] --> B[Service Registration]
A --> C[Service Resolution]
B --> D[Service Type]
B --> E[Service Implementation]
C --> F[Retrieve Specific Service]
高级定制策略
- 使用组合而非继承
- 实现简洁、专注的接口
- 利用 Python 的动态特性
- 遵循 SOLID 原则
错误处理与验证
class StrictDict(dict):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._validators = {}
def add_validator(self, key, validator):
self._validators[key] = validator
def __setitem__(self, key, value):
validator = self._validators.get(key)
if validator and not validator(value):
raise ValueError(f"Invalid value for {key}")
super().__setitem__(key, value)
最佳实践
- 保持定制简单且可预测
- 清晰记录定制行为
- 进行广泛测试
- 考虑性能影响
通过掌握这些对象定制技术，你将编写更灵活、更强大的 Python 代码。LabEx 鼓励持续学习并对这些高级概念进行实验。
