图解python中赋值、浅拷贝、深拷贝的区别

1, 赋值

Python中，对象的赋值都是进行对象引用（内存地址）传递, 赋值（=），就是创建了对象的一个新的引用，修改其中任意一个变量都会影响到另一个

will = ["Will", 28, ["Python", "C#", "JavaScript"]]
wilber = will
print('will>>', will, id(will))
print('wilber>>', wilber, id(wilber))
print('will的各个元素id>>', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])
print('---'*30)
will[0] = "Wilber"
will[2].append("CSS")
print('will>>', will, id(will))
print('wilber>>', wilber, id(wilber))
print('will的各个元素id>>', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])
#输出为
will>> ['Will', 28, ['Python', 'C#', 'JavaScript']] 43988040
wilber>> ['Will', 28, ['Python', 'C#', 'JavaScript']] 43988040
will的各个元素id>> [31326928, 493056320, 43988808]
wilber的各个元素id>> [31326928, 493056320, 43988808]
------------------------------------------------------------------------------------------
will>> ['Wilber', 28, ['Python', 'C#', 'JavaScript', 'CSS']] 43988040
wilber>> ['Wilber', 28, ['Python', 'C#', 'JavaScript', 'CSS']] 43988040
will的各个元素id>> [44016672, 493056320, 43988808]
wilber的各个元素id>> [44016672, 493056320, 43988808]

2, 浅拷贝

浅拷贝会创建一个新的对象，这个例子中”wilber is not will”但是，对于对象中的元素，浅拷贝就只会使用原始元素的引用（内存地址），也就是说”wilber[i] is will[i]”
当对will进行修改的时候: 由于list的第一个元素是不可变类型，所以will对应的list的第一个元素会使用一个新的对象39758496;
但是list的第三个元素是一个可变类型，修改操作不会产生新的对象，所以will的修改结果会相应的反应到wilber上
浅拷贝：创建一个新的对象，但它包含的是对原始对象中包含项的引用（如果用引用的方式修改其中一个对象，另外一个也会修改改变）{1,完全切片方法；2，工厂函数，如list()；3，copy模块的copy()函数}
切片也是浅拷贝

import copy
will = ["Will", 28, ["Python", "C#", "JavaScript"]]
wilber = copy.copy(will)
print('will>>   ', will, id(will))
print('wilber>> ', wilber, id(wilber))
print('will的各个元素id>>  ', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])
print('---'*30)
will[0] = "Wilber"
will[2].append("CSS")
print('will>>   ', will, id(will))
print('wilber>> ', wilber, id(wilber))
print('will的各个元素id>>  ', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])

#输出为
will>>    ['Will', 28, ['Python', 'C#', 'JavaScript']] 43862024
wilber>>  ['Will', 28, ['Python', 'C#', 'JavaScript']] 43861896
will的各个元素id>>   [31261392, 493056320, 43862088]
wilber的各个元素id>> [31261392, 493056320, 43862088]
------------------------------------------------------------------------------------------
will>>    ['Wilber', 28, ['Python', 'C#', 'JavaScript', 'CSS']] 43862024
wilber>>  ['Will', 28, ['Python', 'C#', 'JavaScript', 'CSS']] 43861896
will的各个元素id>>   [43886384, 493056320, 43862088]
wilber的各个元素id>> [31261392, 493056320, 43862088]

3,深拷贝

跟浅拷贝类似，深拷贝也会创建一个新的对象，这个例子中”wilber is not will” 但是，对于对象中的元素，深拷贝都会重新生成一份（有特殊情况，下面会说明），而不是简单的使用原始元素的引用（内存地址）
深拷贝：创建一个新的对象，并且递归的复制它所包含的对象（修改其中一个，另外一个不会改变）{copy模块的deep.deepcopy()函数}

import copy
will = ["Will", 28, ["Python", "C#", "JavaScript"]]
wilber = copy.deepcopy(will)
print('will>>   ', will, id(will))
print('wilber>> ', wilber, id(wilber))
print('will的各个元素id>>  ', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])
print('---'*30)
will[0] = "Wilber"
will[2].append("CSS")
print('will>>   ', will, id(will))
print('wilber>> ', wilber, id(wilber))
print('will的各个元素id>>  ', [id(ele) for ele in will])
print('wilber的各个元素id>>',[id(ele) for ele in wilber])
# 输出为
will>>    ['Will', 28, ['Python', 'C#', 'JavaScript']] 37373960
wilber>>  ['Will', 28, ['Python', 'C#', 'JavaScript']] 37373832
will的各个元素id>>   [31195856, 493056320, 37374024]
wilber的各个元素id>> [31195856, 493056320, 37373768]
------------------------------------------------------------------------------------------
will>>    ['Wilber', 28, ['Python', 'C#', 'JavaScript', 'CSS']] 37373960
wilber>>  ['Will', 28, ['Python', 'C#', 'JavaScript']] 37373832
will的各个元素id>>   [37398264, 493056320, 37374024]
wilber的各个元素id>> [31195856, 493056320, 37373768]

4,特殊情况

对于非容器类型（如数字、字符串、和其他’原子’类型的对象）没有拷贝这一说
也就是说，对于这些类型，”obj is copy.copy(obj)” 、”obj is copy.deepcopy(obj)”
如果元祖变量只包含原子类型对象，则不能深拷贝，看下面的例子

import copy
books=('a','b','c')
books1,books2 =  copy.copy(books),copy.deepcopy(a)
>>books is books1 is books2
# true

a = 'python'
b,c = copy.copy(a),copy.deepcopy(a)
In [19]: a is b is c
Out[19]: True
In [20]: id(a),id(b),id(c)
Out[20]: (55466056, 55466056, 55466056)


In [30]: t1=('a','b','c',['d'])

In [31]: t2,t3 =  copy.copy(t1),copy.deepcopy(t1)

In [32]: t1 is t2 is t3
Out[32]: False

In [33]: id(t1), id(t2), id(t3)
Out[33]: (89247560, 89247560, 88537672)

• Python中对象的赋值都是进行对象引用（内存地址）传递
• 使用copy.copy()，可以进行对象的浅拷贝，它复制了对象，但对于对象中的元素，依然使用原始的引用.
• 如果需要复制一个容器对象，以及它里面的所有元素（包含元素的子元素），可以使用copy.deepcopy()进行深拷贝
• 对于非容器类型（如数字、字符串、和其他’原子’类型的对象）没有被拷贝一说
• 如果元祖变量只包含原子类型对象，则不能深拷贝

列表的浅拷贝示例

import copy
a = [1,2,3,4,['a','b']] #定义一个列表a
b = a #赋值
c = copy.copy(a) #浅拷贝
d = copy.deepcopy(a) #深拷贝
a.append(5)
a[0] = '10'
print('A0',a,id(a))

# [1, 2, 3, 4, ['a', 'b'], 5] #a添加一个元素5
print('B0',b,id(b))
# [1, 2, 3, 4, ['a', 'b'], 5] #b跟着添加一个元素5
print('C0',c,id(c))
# [1, 2, 3, 4, ['a', 'b']] #c保持不变
print('D0',d,id(d))
# [1, 2, 3, 4, ['a', 'b']] #d保持不变
a[4].append('c')
a[4][1]='ASDF'
print('A1',a,id(a))
# [1, 2, 3, 4, ['a', 'b', 'c'], 5] #a中的list(即a[4])添加一个元素c
print('B1',b,id(a))
# [1, 2, 3, 4, ['a', 'b', 'c'], 5] #b跟着添加一个元素c
print('C1',c,id(c))
# [1, 2, 3, 4, ['a', 'b', 'c']] #c跟着添加一个元素c
print('D1',d,id(d))
[1, 2, 3, 4, ['a', 'b']] #d保持不变

2. 单个列表的copy

names = ['alex','jack','1','mack','racheal','shanshan']
n2 = names
n3 = names.copy()
n4 = names[:]

print('第一轮','names',names,id(names))
print('第一轮','n2',n2,id(n2))
print('第一轮','n3',n3,id(n3))
print('第一轮','n4',n4,id(n4))

names.append('hery')
names[0]="Alex"
print('第二轮','names',names,id(names))
print('第二轮','n2',n2,id(n2))
print('第二轮','n3',n3,id(n3))
print('第二轮','n4',n4,id(n4))
输出:
第一轮 names ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167690376
第一轮 n2 ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167690376
第一轮 n3 ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167692616
第一轮 n4 ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167713928
第二轮 names ['Alex', 'jack', '1', 'mack', 'racheal', 'shanshan', 'hery'] 167690376
第二轮 n2 ['Alex', 'jack', '1', 'mack', 'racheal', 'shanshan', 'hery'] 167690376
第二轮 n3 ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167692616
第二轮 n4 ['alex', 'jack', '1', 'mack', 'racheal', 'shanshan'] 167713928

3, 字符串的copy

import copy
name="hahah"   #字符串
name1=copy.copy(name)
name2=copy.deepcopy(name)
print('第一次',id(name),id(name1),id(name2))

sum=111   #数字
sum1=copy.copy(sum)
sum2=copy.deepcopy(sum)
print('第二次',id(sum),id(sum1),id(sum2))
输出:
第一次 31179752 31179752 31179752
第二次 1702001568 1702001568 1702001568

4, 字典的copy

import copy
call = {
    'cpu':[80,25],
    'mem':[80,],
    'disk':[80,]
}
new_call_1 = copy.copy(call)
new_call_2 = copy.deepcopy(call)
print('修改前call1为：%s' %(call),id(call))
# #修改新模版
call['disk'] = 66
call['disk_2'] = 67
call['cpu'].append(20)
call['cpu'][1]=11
new_call_1['cpu'].append(33)
new_call_1['disk'][0] = 77
new_call_1['mem'] = 75
new_call_2['disk'][0] = 79
# #查看新旧模版的值
print('call1为：%s' %(call),id(call))
print('new_call_1为：%s' %(new_call_1),id(new_call_1))
print('new_call_2为：%s' %(new_call_2),id(new_call_2))
输出:
修改前call1为：{'cpu': [80, 25], 'mem': [80], 'disk': [80]} 4411328
call1为：{'cpu': [80, 11, 20, 33], 'mem': [80], 'disk': 66, 'disk_2': 67} 4411328
new_call_1为：{'cpu': [80, 11, 20, 33], 'mem': 75, 'disk': [77]} 4452424
new_call_2为：{'cpu': [80, 25], 'mem': [80], 'disk': [79]} 31977616

Python 打印进度条

import time
for i in range(0,101,2):
     time.sleep(0.1)
     char_num = i//2      #打印多少个'*'
     per_str = '\r%s%% : %s\n' % (i, '>>>' * char_num) if i == 100 else '\r%s%% : %s'%(i,'*'*char_num)
     print(per_str,end='', flush=True)