Python中浅拷贝的四种实现方法小结
更新时间:2021年11月04日 17:14:20 作者:qdPython
本文主要介绍了Python中浅拷贝的四种实现方法小结,文中通过示例代码介绍的非常详细,具有一定的参考价值,感兴趣的小伙伴们可以参考一下
方式一:使用切片 [:]
列表
# 浅拷贝 [:] old_list = [1, 2, [3, 4]] new_list = old_list[:] old_list.append(5) old_list[2][0] += 97 print("Old list:", old_list, "old list id:", id(old_list), " old list[0] id:", id(old_list[2])) print("new list:", new_list, "new list id:", id(new_list), " new list[0] id:", id(new_list[2])) # 输出结果 Old list: [1, 2, [100, 4], 5] old list id: 4537660608 old list[0] id: 4537659840 new list: [1, 2, [100, 4]] new list id: 4537711424 new list[0] id: 4537659840
方式二:使用工厂函数
工厂函数简介
- 工厂函数看上去像函数,但实际是一个类
- 调用时,生成该数据类型类型的一个实例
可变对象的工厂函数
- list()
- set()
- dict()
列表
old_list = [1, 2, [3, 4]] new_list = list(old_list) old_list.append(5) old_list[2][0] += 97 print("Old list:", old_list, "old list id:", id(old_list), " old list[0] id:", id(old_list[2])) print("new list:", new_list, "new list id:", id(new_list), " new list[0] id:", id(new_list[2]))
集合
old_set = {1, 2, 3} new_set = set(old_set) old_set.add(4) print("Old set:", old_set, "old set id:", id(old_set)) print("new set:", new_set, "new set id:", id(new_set)) # 输出结果 Old set: {1, 2, 3, 4} old set id: 4484723648 new set: {1, 2, 3} new set id: 4484723872
字典
old_dict = {"name": "小明"} new_dict = dict(old_dict) old_dict["second"] = "Python" print("Old dict:", old_dict, "old dict id:", id(old_dict)) print("new dict:", new_dict, "new dict id:", id(new_dict)) # 输出结果 Old dict: {'name': '小明', 'second': 'Python'} old dict id: 4514161536 new dict: {'name': '小明'} new dict id: 4515690304
方式三:使用数据类型自带的 copy 方法
列表
old_list = [1, 2, [3, 4]] new_list = old_list.copy() old_list.append(5) old_list[2][0] += 97 print("Old list:", old_list, "old list id:", id(old_list), " old list[0] id:", id(old_list[2])) print("new list:", new_list, "new list id:", id(new_list), " new list[0] id:", id(new_list[2])) # 输出结果 Old list: [1, 2, [100, 4], 5] old list id: 4309832000 old list[0] id: 4310372992 new list: [1, 2, [100, 4]] new list id: 4309735296 new list[0] id: 4310372992
集合
old_set = {1, 2, 3} new_set = old_set.copy() old_set.add(4) print("Old set:", old_set, "old set id:", id(old_set)) print("new set:", new_set, "new set id:", id(new_set)) # 输出结果 Old set: {1, 2, 3, 4} old set id: 4309931392 new set: {1, 2, 3} new set id: 4309930944
字典
old_dict = {"name": "小明"} new_dict = old_dict.copy() old_dict["second"] = "Python" print("Old dict:", old_dict, "old dict id:", id(old_dict)) print("new dict:", new_dict, "new dict id:", id(new_dict)) # 输出结果 Old dict: {'name': '小明', 'second': 'Python'} old dict id: 4308452288 new dict: {'name': '小明'} new dict id: 4308452224
源码
def copy(self, *args, **kwargs): # real signature unknown """ Return a shallow copy of the list. """ pass
已经写的很清楚,这是浅拷贝
方式四:使用 copy 模块的 copy 方法
列表
from copy import copy old_list = [1, 2, [3, 4]] new_list = copy(old_list) old_list.append(5) old_list[2][0] += 97 print("Old list:", old_list, "old list id:", id(old_list), " old list[0] id:", id(old_list[2])) print("new list:", new_list, "new list id:", id(new_list), " new list[0] id:", id(new_list[2])) # 输出结果 Old list: [1, 2, [100, 4], 5] old list id: 4381013184 old list[0] id: 4381159936 new list: [1, 2, [100, 4]] new list id: 4381012800 new list[0] id: 4381159936
集合
from copy import copy old_set = {1, 2, 3} new_set = copy(old_set) old_set.add(4) print("Old set:", old_set, "old set id:", id(old_set)) print("new set:", new_set, "new set id:", id(new_set)) # 输出结果 Old set: {1, 2, 3, 4} old set id: 4381115552 new set: {1, 2, 3} new set id: 4381115776
字典
from copy import copy old_dict = {"name": "小明"} new_dict = copy(old_dict) old_dict["second"] = "Python" print("Old dict:", old_dict, "old dict id:", id(old_dict)) print("new dict:", new_dict, "new dict id:", id(new_dict)) # 输出结果 Old dict: {'name': '小明', 'second': 'Python'} old dict id: 4381159680 new dict: {'name': '小明'} new dict id: 4379632576
到此这篇关于Python中浅拷贝的四种实现方法小结的文章就介绍到这了,更多相关Python 浅拷贝内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!
相关文章
Python图像锐化与边缘检测之Scharr,Canny,LOG算子详解
图像锐化和边缘检测主要包括一阶微分锐化和二阶微分锐化,本文主要讲解常见的图像锐化和边缘检测方法,即Scharr算子、Canny算子和LOG算子,需要的可以参考一下2022-12-12一文详解如何从根本上优雅地解决VSCode中的Python模块导入问题
有时你可能会遇到这种问题,明明用pip安装好了一个python模块,但在VScode中总是显示错误,这篇文章主要给大家介绍了关于如何从根本上优雅地解决VSCode中的Python模块导入问题的相关资料,需要的朋友可以参考下2024-07-07
最新评论