本文目录导读：
我来详细讲解Python案例封装复用的多种方法和最佳实践。
函数封装（基础复用）
# 原始案例：计算圆形面积
def calculate_circle_area(radius):
"""计算圆形面积"""
import math
return math.pi * radius ** 2
# 封装复用
def calculate_area(shape, *args):
"""
通用面积计算函数
:param shape: 形状类型 circle/rectangle/triangle
:param args: 对应参数
"""
import math
if shape == 'circle':
radius = args[0]
return math.pi * radius ** 2
elif shape == 'rectangle':
length, width = args
return length * width
elif shape == 'triangle':
base, height = args
return 0.5 * base * height
else:
raise ValueError(f"不支持的形状: {shape}")
# 使用示例
print(calculate_area('circle', 5)) # 圆形
print(calculate_area('rectangle', 4, 6)) # 矩形
类封装（面向对象复用）
class DataProcessor:
"""数据处理类封装"""
def __init__(self, data):
self.data = data
self.processed_data = None
def clean_data(self):
"""数据清洗"""
self.processed_data = [
item.strip() for item in self.data
if item and not item.isspace()
]
return self
def transform_data(self, func):
"""数据转换"""
if self.processed_data is None:
self.clean_data()
self.processed_data = [func(item) for item in self.processed_data]
return self
def filter_data(self, condition):
"""数据过滤"""
if self.processed_data is None:
self.clean_data()
self.processed_data = [
item for item in self.processed_data
if condition(item)
]
return self
def get_result(self):
"""获取结果"""
return self.processed_data
# 使用示例
processor = DataProcessor([" apple ", "banana", "", " cherry "])
result = (processor
.clean_data()
.transform_data(str.upper)
.filter_data(lambda x: len(x) > 5)
.get_result())
print(result) # ['BANANA', 'CHERRY']
装饰器封装（功能增强复用）
import time
from functools import wraps
def timer_decorator(func):
"""计时装饰器"""
@wraps(func)
def wrapper(*args, **kwargs):
start = time.time()
result = func(*args, **kwargs)
end = time.time()
print(f"{func.__name__} 执行时间: {end - start:.4f}秒")
return result
return wrapper
def cache_decorator(func):
"""缓存装饰器"""
cache = {}
@wraps(func)
def wrapper(*args, **kwargs):
# 创建缓存键
key = str(args) + str(sorted(kwargs.items()))
if key not in cache:
cache[key] = func(*args, **kwargs)
return cache[key]
return wrapper
# 使用示例
@timer_decorator
@cache_decorator
def fibonacci(n):
"""斐波那契数列"""
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
print(fibonacci(30)) # 第一次计算并缓存
print(fibonacci(30)) # 从缓存读取
模块封装（项目级复用）
文件结构
project/
├── utils/
│ ├── __init__.py
│ ├── data_handler.py
│ └── validators.py
├── core/
│ ├── __init__.py
│ └── calculator.py
└── main.pyutils/validators.py
def validate_email(email):
"""验证邮箱格式"""
import re
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
return bool(re.match(pattern, email))
def validate_phone(phone):
"""验证手机号"""
import re
pattern = r'^1[3-9]\d{9}$'
return bool(re.match(pattern, phone))
core/calculator.py
class StatisticsCalculator:
"""统计计算器"""
@staticmethod
def mean(data):
"""计算平均值"""
return sum(data) / len(data) if data else 0
@staticmethod
def median(data):
"""计算中位数"""
sorted_data = sorted(data)
n = len(sorted_data)
if n % 2 == 0:
return (sorted_data[n//2 - 1] + sorted_data[n//2]) / 2
return sorted_data[n//2]
@staticmethod
def standard_deviation(data):
"""计算标准差"""
import math
mean = StatisticsCalculator.mean(data)
variance = sum((x - mean) ** 2 for x in data) / len(data)
return math.sqrt(variance)
main.py
from utils.validators import validate_email, validate_phone
from core.calculator import StatisticsCalculator
# 使用工具函数
emails = ["test@example.com", "invalid-email"]
valid_emails = [email for email in emails if validate_email(email)]
print(f"有效邮箱: {valid_emails}")
# 使用统计计算器
data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
calc = StatisticsCalculator()
print(f"平均值: {calc.mean(data)}")
print(f"中位数: {calc.median(data)}")
print(f"标准差: {calc.standard_deviation(data):.2f}")
配置文件封装（参数复用）
config/settings.py
import json
import os
from typing import Any, Dict
class Config:
"""配置管理类"""
_instance = None
def __new__(cls):
if cls._instance is None:
cls._instance = super().__new__(cls)
cls._instance._config = {}
return cls._instance
def load_from_file(self, filepath: str):
"""从文件加载配置"""
if not os.path.exists(filepath):
raise FileNotFoundError(f"配置文件不存在: {filepath}")
with open(filepath, 'r', encoding='utf-8') as f:
if filepath.endswith('.json'):
self._config = json.load(f)
elif filepath.endswith('.toml'):
import tomli
self._config = tomli.load(f)
return self
def get(self, key: str, default: Any = None) -> Any:
"""获取配置值"""
keys = key.split('.')
value = self._config
for k in keys:
if isinstance(value, dict):
value = value.get(k, default)
else:
return default
return value
def set(self, key: str, value: Any):
"""设置配置值"""
keys = key.split('.')
config = self._config
for k in keys[:-1]:
if k not in config:
config[k] = {}
config = config[k]
config[keys[-1]] = value
# 使用示例
config = Config()
config.load_from_file('config/app.json')
db_host = config.get('database.host', 'localhost')
db_port = config.get('database.port', 5432)
最佳实践建议
封装原则
# 1. 单一职责原则
class UserManager:
"""用户管理类 - 只负责用户相关操作"""
def create_user(self, username, email):
pass
def delete_user(self, user_id):
pass
def update_user(self, user_id, data):
pass
# 2. 接口简单易用
class EmailSender:
"""邮件发送器 - 简单接口"""
def send(self, to, subject, body):
"""简化的发送方法"""
return self._send_email(to, subject, body)
def _send_email(self, to, subject, body):
"""实际发送逻辑"""
# 实现细节
pass
# 3. 提供默认参数
def process_data(data, format='json', encoding='utf-8'):
"""数据处理函数，提供默认参数"""
if format == 'json':
import json
return json.dumps(data, ensure_ascii=False)
elif format == 'csv':
import csv
# 处理逻辑
pass
文档和测试
def calculate_discount(price: float, discount: float = 0.1) -> float:
"""
计算折扣价格
Args:
price: 原价
discount: 折扣率，默认0.1（10%）
Returns:
折扣后的价格
Raises:
ValueError: 当折扣率不在0-1之间时
"""
if not 0 <= discount <= 1:
raise ValueError(f"折扣率必须在0-1之间，当前为{discount}")
return price * (1 - discount)
# 测试用例
def test_calculate_discount():
assert calculate_discount(100) == 90
assert calculate_discount(100, 0.2) == 80
assert calculate_discount(0) == 0
import pytest
with pytest.raises(ValueError):
calculate_discount(100, 1.5)
这些封装方法可以让你在项目中高效复用代码，减少重复工作，提高开发效率,选择合适的封装方式取决于具体需求和场景。
