一文带你深入了解Python中的深拷贝与浅拷贝数据

a = [1, 2, 3]
b = a  # 这并不是创建副本，而是创建新引用

b[0] = 99
print(a)  # 输出: [99, 2, 3]

import copy

original = [1, [2, 3], 4]
shallow_copy = copy.copy(original)

# 修改顶层元素
shallow_copy[0] = 100
print(original)    # [1, [2, 3], 4] - 不受影响

# 修改嵌套列表
shallow_copy[1][0] = 200
print(original)    # [1, [200, 3], 4] - 受影响！

original_dict = {'a': [1, 2], 'b': 3}
shallow_dict = original_dict.copy()  # 或 copy.copy(original_dict)

shallow_dict['a'][0] = 99
print(original_dict)  # {'a': [99, 2], 'b': 3} - 嵌套列表被修改

import copy

original = [1, [2, 3], 4]
deep_copy = copy.deepcopy(original)

deep_copy[1][0] = 200
print(original)    # [1, [2, 3], 4] - 完全不受影响

import copy

t1 = (1, [2, 3])  # 注意：元组包含可变对象时行为特殊
t2 = copy.copy(t1)
t3 = copy.deepcopy(t1)

t2[1][0] = 99  # 仍然可以修改嵌套列表
print(t1)      # (1, [99, 3]) - 原元组受影响！

class MyClass:
    def __init__(self, value):
        self.value = value
        self.nested = [1, 2, 3]
    
    def __copy__(self):
        print("执行浅拷贝")
        new_obj = MyClass(self.value)
        new_obj.nested = self.nested.copy()  # 手动浅拷贝嵌套列表
        return new_obj
    
    def __deepcopy__(self, memo):
        print("执行深拷贝")
        new_obj = MyClass(self.value)
        new_obj.nested = copy.deepcopy(self.nested, memo)  # 递归深拷贝
        return new_obj

obj = MyClass(10)
shallow = copy.copy(obj)
deep = copy.deepcopy(obj)

a = [1, 2]
b = [a, 3]
a.append(b)  # 循环引用: a -> b -> a

c = copy.deepcopy(a)
print(c[0] is c[1][0])  # True - 保持引用关系
print(c is a)           # False - 新对象

original = [1, [2, 3], 4]
partial_copy = [x if not isinstance(x, list) else x.copy() for x in original]

import json
original = {'a': [1, 2], 'b': 3}
deep_copy = json.loads(json.dumps(original))

import copy
import time

def create_nested_list(depth, size):
    if depth == 0:
        return 0
    return [create_nested_list(depth-1, size) for _ in range(size)]

big_list = create_nested_list(2, 1000)

# 测试浅拷贝
start = time.time()
for _ in range(100):
    shallow = copy.copy(big_list)
print(f"浅拷贝耗时: {(time.time()-start)*1000:.2f}ms")

# 测试深拷贝
start = time.time()
for _ in range(100):
    deep = copy.deepcopy(big_list)
print(f"深拷贝耗时: {(time.time()-start)*1000:.2f}ms")

a = [1, [2, 3]]
b = a.copy()
print(a[1] is b[1])  # True - 共享嵌套列表