今天来给大家讲一下深浅拷贝，深浅拷贝需要用到copy模块，这里需要导入copy模块
import copy
今天的博客结构是这样的，先对字符串和数字这两种类分别使用赋值、浅拷贝、深拷贝
1、首先来看下赋值的方法
a1 = "abc" a2 = "123" b1 = a1 b2 = a2 print(id(a1),id(b1),sep="/",end="\n") # 27299360/27299360 print(id(a2),id(b2),sep="/",end="\n") # 30486656/30486656 b1 = "add" b2 = "789" print(b1,a1) # add abc print(b2,a2) # 789 123
2、在来看下浅拷贝的方法
a3 = copy.copy(a1) a4 = copy.copy(a2) print(id(a3),id(a1),sep="/",end="\n") # 7179808/7179808 print(id(a4),id(a2),sep="/",end="\n") # 7876736/7876736 a3 = "had" a4 = "678" print(a3,a1) # had abc print(a4,a2) # 678 123
3、最后在看下深拷贝的方法
a5 = copy.deepcopy(a1) a6 = copy.deepcopy(a2) print(id(a5),id(a1),sep="/",end="\n") # 26840608/26840608 print(id(a6),id(a2),sep="/",end="\n") # 27537536/27537536 a5 = "def" a6 = "456" print(a5,a1) # def abc print(a6,a2) # 456 123
结论：对于字符串和数字无论是赋值，浅拷贝，深拷贝，均对原来的变量没有影响
在来看下赋值，浅拷贝，深拷贝对列表和字典的影响，其实上述对list和dict的影响是一样的
首先我们用list来举例，先说下一个没有嵌套的list
1、先说下赋值
l1 = ["a","b","c"]
l2 = l1
print(id(l1),id(l2),sep="/",end="\n")
# 30744488/30744488
l2.append("d")
print(l2,l1,sep="/",end="\n")
# [‘a‘, ‘b‘, ‘c‘, ‘d‘]/[‘a‘, ‘b‘, ‘c‘, ‘d‘]
print(id(l1),id(l2),sep="/",end="\n")
# 28516264/28516264
2、在来看下浅拷贝
l1 = ["a","b","c"]
l2 = copy.copy(l1)
print(id(l1),id(l2),sep="/",end="\n")
# 30892240/30893000
l2.append("d")
print(l1,l2)
# [‘a‘, ‘b‘, ‘c‘] [‘a‘, ‘b‘, ‘c‘, ‘d‘]
print(id(l1),id(l2),sep="/",end="\n")
# 31088848/31089608
3、最后在来看下深拷贝
l1 = ["a","b","c"]
l2 = copy.deepcopy(l1)
print(l1,l2)
# [‘a‘, ‘b‘, ‘c‘] [‘a‘, ‘b‘, ‘c‘]
print(id(l1),id(l2),sep="/",end="\n")
# 28450728/28467408
l2.append("d")
print(l1,l2)
# [‘a‘, ‘b‘, ‘c‘] [‘a‘, ‘b‘, ‘c‘, ‘d‘]
print(id(l1),id(l2),sep="/",end="\n")
# 28712872/28729552
结论：对于没有嵌套的list或者字典，如果使用赋值的方法，修改一个变量会对另外一个变量有影响，对于深拷贝和浅拷贝，修改一个变量，对另外一个变量是没有影响
然后我们在用有嵌套的字典来看下
1、
d1 = {"k1":"v1","k2":"v2","k3":["a","b","c"]}
d2 = d1
print(id(d1),id(d2))
# 27455632 27455632
d2["k1"] = "V1"
print(d2,d1)
# {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]}print(id(d1),id(d2))
# 27127952 27127952
d2["k3"][0] = "A"
print(d1,d2)
# {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘A‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘A‘, ‘b‘, ‘c‘]}
print(id(d1),id(d2))
# 26931344 26931344
2、在来看下浅拷贝
d1 = {"k1":"v1","k2":"v2","k3":["a","b","c"]}
d2 = copy.copy(d1)
print(id(d1),id(d2))
# 27455680 27831392
d2["k1"] = "V1"
print(d1,d2)
# {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]}
print(id(d1),id(d2))
# 7205056 7253088
d2["k3"][0] = "A"
print(d1,d2)
# {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘A‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘A‘, ‘b‘, ‘c‘]}
print(id(d1),id(d2))
# 26931392 29797472
3、最后在看下深拷贝
d1 = {"k1":"v1","k2":"v2","k3":["a","b","c"]}
d2 = copy.deepcopy(d1)
print(id(d1),id(d2))
# 27586704 30576880
print(d1,d2)
# {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]} {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]}
d2["k1"] = "V1"
print(d1,d2)
# {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]}
print(id(d1),id(d2))
# 27062416 28348656
d2["k3"][0] = "A"
print(id(d1),id(d2))
# 27193488 28152048
print(d1,d2)
# {‘k1‘: ‘v1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘a‘, ‘b‘, ‘c‘]} {‘k1‘: ‘V1‘, ‘k2‘: ‘v2‘, ‘k3‘: [‘A‘, ‘b‘, ‘c‘]}
结论：对于赋值的方法，无论是修改第一层的值，还是第二层的值，均会对另外一个变量有影响；对于浅拷贝，修改第一层的值对另外一个变量没有影响，但是修改第二层的值，则会同步修改原来的变量；对于深拷贝，无论是修改第一层还是第二层甚至是更多层，都对原来的变量没有任何影响
时间： 2025-01-01 20:56:00