Python内置函数之tuple()与type()的实用指南

# 从列表创建元组
list_data = [1, 2, 3, 4, 5]
tuple_from_list = tuple(list_data)
print(f"列表转元组: {tuple_from_list}")  # 输出: (1, 2, 3, 4, 5)

# 从字符串创建（字符元组）
string_data = "hello"
tuple_from_string = tuple(string_data)
print(f"字符串转元组: {tuple_from_string}")  # 输出: ('h', 'e', 'l', 'l', 'o')

# 从范围对象创建
range_data = range(5)
tuple_from_range = tuple(range_data)
print(f"范围转元组: {tuple_from_range}")  # 输出: (0, 1, 2, 3, 4)

# 空元组
empty_tuple = tuple()
print(f"空元组: {empty_tuple}")  # 输出: ()

# 从字典创建（只获取键）
dict_data = {'a': 1, 'b': 2, 'c': 3}
tuple_from_dict = tuple(dict_data)
print(f"字典键元组: {tuple_from_dict}")  # 输出: ('a', 'b', 'c')

class DataProcessor:
    @staticmethod
    def get_coordinates():
        """返回坐标（使用元组保护数据）"""
        return (10.5, 20.3)  # 不可修改的坐标
    
    @staticmethod
    def get_student_info():
        """返回学生信息（多返回值）"""
        name = "张三"
        age = 20
        grade = 90.5
        return (name, age, grade)  # 打包返回
    
    @staticmethod
    def process_data(*args):
        """处理可变数量参数"""
        return tuple(args)  # 转换为元组
    
    @staticmethod
    def create_immutable_config(config_dict):
        """创建不可变配置"""
        return tuple(config_dict.items())

# 使用示例
processor = DataProcessor()

# 获取坐标（不可修改）
coords = processor.get_coordinates()
print(f"坐标: {coords}")
print(f"X坐标: {coords[0]}")
print(f"Y坐标: {coords[1]}")

# 多返回值解包
name, age, grade = processor.get_student_info()
print(f"学生: {name}, 年龄: {age}, 成绩: {grade}")

# 处理可变参数
data_tuple = processor.process_data(1, 2, 3, 4, 5)
print(f"处理结果: {data_tuple}")

# 不可变配置
config = {"host": "localhost", "port": 8080, "debug": True}
immutable_config = processor.create_immutable_config(config)
print(f"配置元组: {immutable_config}")

# 基本类型检测
print(f"整数的类型: {type(42)}")          # 输出: <class 'int'>
print(f"字符串的类型: {type('hello')}")    # 输出: <class 'str'>
print(f"列表的类型: {type([1, 2, 3])}")    # 输出: <class 'list'>
print(f"元组的类型: {type((1, 2, 3))}")   # 输出: <class 'tuple'>

# 自定义类的类型
class Person:
    pass

person = Person()
print(f"自定义类的类型: {type(person)}")  # 输出: <class '__main__.Person'>

# 与__class__比较
print(f"type与__class__相同: {type(person) == person.__class__}")  # 输出: True

# 类型比较
num = 100
print(f"num是整数: {type(num) == int}")      # 输出: True
print(f"num是字符串: {type(num) == str}")    # 输出: False

class TypeChecker:
    @staticmethod
    def safe_operation(value, operation):
        """安全的类型化操作"""
        value_type = type(value)
        
        if value_type in (int, float):
            return operation(value)
        else:
            return f"不支持的类型: {value_type}"
    
    @staticmethod
    def filter_by_type(data, target_type):
        """按类型过滤数据"""
        return [item for item in data if type(item) == target_type]
    
    @staticmethod
    def validate_input(value, expected_type, default=None):
        """验证输入类型"""
        if type(value) == expected_type:
            return value
        elif default is not None:
            return default
        else:
            raise TypeError(f"期望类型: {expected_type}, 实际类型: {type(value)}")

# 使用示例
checker = TypeChecker()

# 安全操作
print(f"安全计算: {checker.safe_operation(10, lambda x: x * 2)}")
print(f"安全计算: {checker.safe_operation('text', lambda x: x * 2)}")

# 类型过滤
mixed_data = [1, "hello", 3.14, "world", 5, 6.28]
numbers_only = checker.filter_by_type(mixed_data, int)
floats_only = checker.filter_by_type(mixed_data, float)
print(f"整数: {numbers_only}")
print(f"浮点数: {floats_only}")

# 输入验证
try:
    valid = checker.validate_input(100, int, 0)
    print(f"验证通过: {valid}")
    
    invalid = checker.validate_input("100", int, 0)
    print(f"验证结果: {invalid}")
except TypeError as e:
    print(f"验证失败: {e}")

# 动态创建简单类
# 等效于: class Person: pass
Person = type('Person', (), {})
person1 = Person()
print(f"动态创建的类: {Person}")
print(f"类名: {Person.__name__}")
print(f"实例: {person1}")

# 带属性的类
Student = type('Student', (), {
    'name': '张三',
    'age': 20,
    'greet': lambda self: f"你好，我是{self.name}"
})
student1 = Student()
print(f"学生姓名: {student1.name}")
print(f"问候: {student1.greet()}")

# 带继承的类
class Animal:
    def speak(self):
        return "动物叫声"

# 动态创建继承类
Dog = type('Dog', (Animal,), {
    'breed': '金毛',
    'bark': lambda self: f"{self.breed}在汪汪叫"
})
dog1 = Dog()
print(f"狗的品种: {dog1.breed}")
print(f"狗叫: {dog1.bark()}")
print(f"动物方法: {dog1.speak()}")

class DynamicClassFactory:
    @staticmethod
    def create_class(class_name, base_classes=(), attributes=None, methods=None):
        """动态创建类"""
        class_dict = {}
        
        # 添加属性
        if attributes:
            class_dict.update(attributes)
        
        # 添加方法
        if methods:
            for method_name, method_func in methods.items():
                class_dict[method_name] = method_func
        
        # 创建类
        new_class = type(class_name, base_classes, class_dict)
        return new_class
    
    @staticmethod
    def create_data_class(class_name, field_names):
        """创建类似数据类的简单类"""
        class_dict = {'__slots__': field_names}
        
        # 添加初始化方法
        def init_method(self, *args):
            for field, value in zip(field_names, args):
                setattr(self, field, value)
        
        class_dict['__init__'] = init_method
        
        # 添加字符串表示
        def repr_method(self):
            fields = ', '.join(f'{field}={getattr(self, field)}' 
                              for field in field_names)
            return f'{class_name}({fields})'
        
        class_dict['__repr__'] = repr_method
        
        return type(class_name, (), class_dict)
    
    @staticmethod
    def add_method_to_class(cls, method_name, method_func):
        """向现有类添加方法"""
        setattr(cls, method_name, method_func)
        return cls

# 使用示例
factory = DynamicClassFactory()

# 创建数据类
Point = factory.create_data_class('Point', ['x', 'y', 'z'])
point = Point(1, 2, 3)
print(f"点对象: {point}")
print(f"点坐标: ({point.x}, {point.y}, {point.z})")

# 创建复杂类
Calculator = factory.create_class(
    'Calculator',
    (),
    {
        'version': '1.0',
        'description': '简单的计算器类'
    },
    {
        'add': lambda self, a, b: a + b,
        'multiply': lambda self, a, b: a * b
    }
)

calc = Calculator()
print(f"计算器版本: {calc.version}")
print(f"加法: {calc.add(5, 3)}")
print(f"乘法: {calc.multiply(5, 3)}")

# 动态添加方法
def power_method(self, base, exp):
    return base ** exp

Calculator = factory.add_method_to_class(Calculator, 'power', power_method)
print(f"幂运算: {calc.power(2, 3)}")

class TypeSafeConfig:
    def __init__(self):
        self._config = {}
        self._types = {}
    
    def set_config(self, key, value, value_type=None):
        """设置类型安全的配置"""
        if value_type is None:
            value_type = type(value)
        
        # 验证类型
        if not isinstance(value, value_type):
            raise TypeError(f"值类型不匹配: 期望{value_type}, 实际{type(value)}")
        
        self._config[key] = value
        self._types[key] = value_type
        
        # 创建属性
        setattr(self, key, value)
    
    def get_config_as_tuple(self, *keys):
        """获取配置为元组"""
        if not keys:
            return tuple(self._config.items())
        return tuple((key, self._config[key]) for key in keys)
    
    def validate_all(self):
        """验证所有配置类型"""
        for key, expected_type in self._types.items():
            actual_value = self._config[key]
            if not isinstance(actual_value, expected_type):
                return False, f"{key}类型错误"
        return True, "所有配置类型正确"
    
    def __repr__(self):
        """配置表示"""
        items = [f"{k}={v}({self._types[k].__name__})" 
                for k, v in self._config.items()]
        return f"TypeSafeConfig({', '.join(items)})"

# 使用示例
config = TypeSafeConfig()

# 设置配置
config.set_config('app_name', 'MyApp', str)
config.set_config('port', 8080, int)
config.set_config('debug', True, bool)
config.set_config('timeout', 30.5, float)

print(f"配置信息: {config}")
print(f"配置元组: {config.get_config_as_tuple('app_name', 'port')}")

# 类型验证
is_valid, message = config.validate_all()
print(f"类型验证: {message}")

# 类型错误示例
try:
    config.set_config('error', 'not_a_number', int)
except TypeError as e:
    print(f"类型错误: {e}")

class APIBuilder:
    def __init__(self, base_name="DynamicAPI"):
        self.base_name = base_name
        self.endpoints = []
    
    def add_endpoint(self, endpoint_name, method_func, method_type='GET'):
        """添加API端点"""
        self.endpoints.append({
            'name': endpoint_name,
            'func': method_func,
            'type': method_type
        })
        return self
    
    def build(self, class_name=None):
        """构建API类"""
        if class_name is None:
            class_name = self.base_name
        
        # 创建类字典
        class_dict = {
            '__doc__': f'动态生成的API类: {class_name}',
            'endpoints': self.endpoints.copy()
        }
        
        # 为每个端点添加方法
        for endpoint in self.endpoints:
            method_name = f"{endpoint['type'].lower()}_{endpoint['name']}"
            
            def create_handler(func):
                def handler(self, *args, **kwargs):
                    return func(*args, **kwargs)
                handler.__name__ = method_name
                handler.__doc__ = f"{endpoint['type']} {endpoint['name']} endpoint"
                return handler
            
            class_dict[method_name] = create_handler(endpoint['func'])
        
        # 创建类
        api_class = type(class_name, (), class_dict)
        return api_class

# 使用示例
builder = APIBuilder()

# 定义处理函数
def get_users():
    return ["user1", "user2", "user3"]

def create_user(name, age):
    return {"id": 1, "name": name, "age": age}

def delete_user(user_id):
    return {"status": "deleted", "user_id": user_id}

# 添加端点
builder.add_endpoint('users', get_users, 'GET')
builder.add_endpoint('users', create_user, 'POST')
builder.add_endpoint('user', delete_user, 'DELETE')

# 构建API类
UserAPI = builder.build('UserAPI')
api = UserAPI()

# 使用API
print(f"获取用户: {api.get_users()}")
print(f"创建用户: {api.post_users('张三', 25)}")
print(f"删除用户: {api.delete_user(1)}")

# 检查类信息
print(f"类名: {UserAPI.__name__}")
print(f"文档: {UserAPI.__doc__}")
print(f"端点列表: {UserAPI.endpoints}")

class TupleAdvanced:
    @staticmethod
    def named_tuple_factory(field_names):
        """创建类似命名元组的结构"""
        def create_named_tuple(*values):
            if len(values) != len(field_names):
                raise ValueError(f"需要{len(field_names)}个值，得到{len(values)}个")
            
            # 返回字典而不是元组，但可以通过字段名访问
            class NamedTuple:
                def __init__(self, values):
                    for name, value in zip(field_names, values):
                        setattr(self, name, value)
                
                def __iter__(self):
                    return iter(getattr(self, name) for name in field_names)
                
                def __repr__(self):
                    fields = ', '.join(f'{name}={getattr(self, name)}' 
                                      for name in field_names)
                    return f'NamedTuple({fields})'
            
            return NamedTuple(values)
        
        return create_named_tuple
    
    @staticmethod
    def tuple_swap(a, b):
        """使用元组交换变量"""
        return (b, a)
    
    @staticmethod
    def unpack_nested(tuple_data):
        """解包嵌套元组"""
        result = []
        for item in tuple_data:
            if isinstance(item, tuple):
                result.extend(item)
            else:
                result.append(item)
        return tuple(result)

# 使用示例
advanced = TupleAdvanced()

# 类似命名元组
Point = advanced.named_tuple_factory(['x', 'y', 'z'])
point = Point(1, 2, 3)
print(f"点对象: {point}")
print(f"x坐标: {point.x}")
print(f"遍历坐标: {[coord for coord in point]}")

# 变量交换
x, y = 10, 20
print(f"交换前: x={x}, y={y}")
x, y = advanced.tuple_swap(x, y)
print(f"交换后: x={x}, y={y}")

# 嵌套解包
nested = ((1, 2), 3, (4, 5, 6))
flattened = advanced.unpack_nested(nested)
print(f"嵌套元组: {nested}")
print(f"展开后: {flattened}")

class TypeSystem:
    @staticmethod
    def is_same_type(obj1, obj2):
        """检查两个对象是否为相同类型"""
        return type(obj1) is type(obj2)
    
    @staticmethod
    def get_type_hierarchy(cls):
        """获取类的继承层次"""
        hierarchy = []
        current = cls
        while current is not object:
            hierarchy.append(current.__name__)
            current = current.__base__
        hierarchy.append('object')
        return ' -> '.join(reversed(hierarchy))
    
    @staticmethod
    def create_type_checker(*allowed_types):
        """创建类型检查器"""
        def type_checker(value):
            if not any(isinstance(value, t) for t in allowed_types):
                allowed_names = [t.__name__ for t in allowed_types]
                raise TypeError(f"只允许类型: {allowed_names}")
            return value
        return type_checker

# 使用示例
type_system = TypeSystem()

# 类型比较
print(f"相同类型检查: {type_system.is_same_type(10, 20)}")
print(f"不同类型检查: {type_system.is_same_type(10, '20')}")

# 继承层次
class Animal: pass
class Mammal(Animal): pass
class Dog(Mammal): pass

hierarchy = type_system.get_type_hierarchy(Dog)
print(f"Dog的继承层次: {hierarchy}")

# 类型检查器
number_checker = type_system.create_type_checker(int, float)
try:
    result = number_checker(10)
    print(f"数字检查通过: {result}")
    
    result = number_checker("text")
    print(f"检查结果: {result}")
except TypeError as e:
    print(f"类型检查失败: {e}")