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python类之间的意外继承

attributes inheritance dictionary class python

Shaun Han · 技术社区 · 4 年前

我对列表副本有一些问题:

所以在我得到 E0 从 'get_edge' E0级 'E0_copy = list(E0)' . 我想在这里 E0_copy 是一个深刻的副本 E0级 ,我通过了进入之内 'karger(E)' . 但在主要功能上。
为什么 'print E0[1:10]'

下面是我的代码:

def get_graph():
    f=open('kargerMinCut.txt')
    G={}
    for line in f:
        ints = [int(x) for x in line.split()]
        G[ints[0]]=ints[1:len(ints)]
    return G

def get_edge(G):
    E=[]
    for i in range(1,201):
        for v in G[i]:
            if v>i:
                E.append([i,v])
    print id(E)
    return E

def karger(E):
    import random
    count=200 
    while 1:
        if count == 2:
            break
        edge = random.randint(0,len(E)-1)
        v0=E[edge][0]
        v1=E[edge][1]                   
        E.pop(edge)
        if v0 != v1:
            count -= 1
            i=0
            while 1:
                if i == len(E):
                    break
                if E[i][0] == v1:
                    E[i][0] = v0
                if E[i][1] == v1:
                    E[i][1] = v0
                if E[i][0] == E[i][1]:
                    E.pop(i)
                    i-=1
                i+=1

    mincut=len(E)
    return mincut


if __name__=="__main__":
    import copy
    G = get_graph()
    results=[]
    E0 = get_edge(G)
    print E0[1:10]               ## this result is not equal to print2
    for k in range(1,5):
        E0_copy=list(E0)         ## I guess here E0_coypy is a deep copy of E0
        results.append(karger(E0_copy))
       #print "the result is %d" %min(results)
    print E0[1:10]               ## this is print2

0 回复 | 直到 7 年前

279

Sarthak Ahuja 8 年前

E0_copy 不是深度复制。你不能用 list() (二者) list(...) testList[:] 是浅拷贝)。

copy.deepcopy(...) 用于深度复制列表。

deepcopy(x, memo=None, _nil=[])
    Deep copy operation on arbitrary Python objects.

>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = list(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b   # b changes too -> Not a deepcopy.
[[1, 10, 3], [4, 5, 6]]

现在看看 deepcopy 操作

>>> import copy
>>> b = copy.deepcopy(a)
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 10, 3], [4, 5, 6]]
>>> a[0][1] = 9
>>> a
[[1, 9, 3], [4, 5, 6]]
>>> b    # b doesn't change -> Deep Copy
[[1, 10, 3], [4, 5, 6]]

Tom Wyllie 6 年前

在python中,有一个名为“copy”的模块,其中包含两个有用的函数

import copy
copy.copy()
copy.deepcopy()

copy()是一个浅层复制函数,如果给定的参数是一个复合数据结构,例如 ,则python将创建另一个相同类型的对象(在本例中为 新建列表 )但对于旧列表中的所有内容,只复制了它们的引用

# think of it like
newList = [elem for elem in oldlist]

直观地说,我们可以假设deepcopy()将遵循相同的范例,唯一的区别是对于每个范例 我们将递归地调用deepcopy

但这是错误的!

deepcopy()实际上保留了原始复合数据的图形结构:

a = [1,2]
b = [a,a] # there's only 1 object a
c = deepcopy(b)

# check the result
c[0] is a # return False, a new object a' is created
c[0] is c[1] # return True, c is [a',a'] not [a',a'']

这是一个棘手的部分,在deepcopy()的过程中,一个哈希表(python中的字典)被用来映射:

official doc

aljgom Miles 7 年前

如果列表的内容是基本数据类型,则可以使用

new_list = [i for i in old_list]

您可以将其嵌套为多维列表,如:

new_grid = [[i for i in row] for row in grid]

tailor_raj 12 年前

list elements 是 immutable objects deepcopy 从 copy 模块。

list 这样地。

a = [0,1,2,3,4,5,6,7,8,9,10]
b = a[:] #deep copying the list a and assigning it to b
print id(a)
20983280
print id(b)
12967208

a[2] = 20
print a
[0, 1, 20, 3, 4, 5, 6, 7, 8, 9,10]
print b
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9,10]

Mystic 4 年前

1号: list() [:] , copy.copy() 都是浅薄的复制品。如果一个物体是复合的,它们都不适合。你需要使用 copy.deepcopy()

第二条: b = a a 和 b 一 甚至在改变 .

将a设置为b

如果混蛋 一 到 b 直接, 一 b 共享一个引用。

>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = a
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0] = 1
>>> a
[1, [4, 5, 6]]
>>> b
[1, [4, 5, 6]]


>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = a
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 10, 3], [4, 5, 6]]

卷影副本

`列表()`

列表() 和 [:] 都是一样的。除第一层更改外,所有其他层的更改都将被传输。

>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = list(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0] = 1
>>> a
[1, [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]


>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = list(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 10, 3], [4, 5, 6]]

`[:]`

>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = a[:]
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0] = 1
>>> a
[1, [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]


>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = a[:]
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 10, 3], [4, 5, 6]]

# =========== [:] ===========
>>> a = [[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b = a[:]
>>> a
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> a[0][2] = 4
>>> a
[[1, 2, 4], [4, 5, 6]]
>>> b
[[1, 2, 4], [4, 5, 6]]


>>> a = [[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b = a[:]
>>> a
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> a[0][2][0] = 999
>>> a
[[1, 2, [999, 6]], [4, 5, 6]]
>>> b
[[1, 2, [999, 6]], [4, 5, 6]]



# =========== list() ===========
>>> a = [[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b = list(a)
>>> a
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> a[0][2] = 4
>>> a
[[1, 2, 4], [4, 5, 6]]
>>> b
[[1, 2, 4], [4, 5, 6]]


>>> a = [[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b = list(a)
>>> a
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> b
[[1, 2, [3.5, 6]], [4, 5, 6]]
>>> a[0][2][0] = 999
>>> a
[[1, 2, [999, 6]], [4, 5, 6]]
>>> b
[[1, 2, [999, 6]], [4, 5, 6]]

通过 `copy()`

你会发现的和 [:] . 他们都是 浅拷贝

here .

>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = copy.copy(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 10, 3], [4, 5, 6]]

`deepcopy()`

>>> import copy
>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = copy.deepcopy(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0] = 1
>>> a
[1, [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]


>>> a = [[1, 2, 3], [4, 5, 6]]
>>> b = copy.deepcopy(a)
>>> a
[[1, 2, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]
>>> a[0][1] = 10
>>> a
[[1, 10, 3], [4, 5, 6]]
>>> b
[[1, 2, 3], [4, 5, 6]]

rnbguy 9 年前

只是一个递归的深度复制函数。

def deepcopy(A):
    rt = []
    for elem in A:
        if isinstance(elem,list):
            rt.append(deepcopy(elem))
        else:
            rt.append(elem)
    return rt

copy 模块。

AnupamChugh 5 年前

  b = [x[:] for x in a]

ShellayLee 4 年前

将列表视为一棵树,python中的deep\u副本可以最简洁地写成

def deep_copy(x):
    if not isinstance(x, list):
        return x
    else:
        return [deep_copy(elem) for elem in x]

它基本上是以深度优先的方式递归遍历列表。

-1

Shubham Kumar 4 年前

如果不允许直接导入模块,可以将自己的deepcopy函数定义为-

def copyList(L):
if type(L[0]) != list:
    return [i for i in L]
else:
    return [copyList(L[i]) for i in range(len(L))]

它的工作可以很容易地被视为-

>>> x = [[1,2,3],[3,4]]
>>> z = copyList(x)
>>> x
[[1, 2, 3], [3, 4]]
>>> z
[[1, 2, 3], [3, 4]]
>>> id(x)
2095053718720
>>> id(z)
2095053718528
>>> id(x[0])
2095058990144
>>> id(z[0])
2095058992192
>>>

-2

Kwaw Annor Farshid Ashouri 5 年前

这更像是蟒蛇

my_list = [0, 1, 2, 3, 4, 5]  # some list
my_list_copy = list(my_list)  # my_list_copy and my_list does not share reference now.

注意:这对于引用对象的列表是不安全的