python中的shallow copy 与 deep copy

list = [0, 1, 2, 3, 4, 5]


def function1(list):
    del list[1]
    print(list)


def function2(list):
    print(list)


function1(list)
function2(list)

newList = list.copy()
function2(newList)

"""Generic (shallow and deep) copying operations.

Interface summary:

        import copy

        x = copy.copy(y)        # make a shallow copy of y
        x = copy.deepcopy(y)    # make a deep copy of y

For module specific errors, copy.Error is raised.

The difference between shallow and deep copying is only relevant for
compound objects (objects that contain other objects, like lists or
class instances).

- A shallow copy constructs a new compound object and then (to the
  extent possible) inserts *the same objects* into it that the
  original contains.

- A deep copy constructs a new compound object and then, recursively,
  inserts *copies* into it of the objects found in the original.

Two problems often exist with deep copy operations that don't exist
with shallow copy operations:

 a) recursive objects (compound objects that, directly or indirectly,
    contain a reference to themselves) may cause a recursive loop

 b) because deep copy copies *everything* it may copy too much, e.g.
    administrative data structures that should be shared even between
    copies

Python's deep copy operation avoids these problems by:

 a) keeping a table of objects already copied during the current
    copying pass

 b) letting user-defined classes override the copying operation or the
    set of components copied

This version does not copy types like module, class, function, method,
nor stack trace, stack frame, nor file, socket, window, nor array, nor
any similar types.

Classes can use the same interfaces to control copying that they use
to control pickling: they can define methods called __getinitargs__(),
__getstate__() and __setstate__().  See the documentation for module
"pickle" for information on these methods.
"""

>>> import copy
>>> origin = 1
>>> cop1 = copy.copy(origin) 
#cop1 是 origin 的shallow copy
>>> cop2 = copy.deepcopy(origin) 
#cop2 是 origin 的 deep copy
>>> origin = 2
>>> origin
2
>>> cop1
1
>>> cop2
1
#cop1 和 cop2 都不会随着 origin 改变自己的值
>>> cop1 == cop2
True
>>> cop1 is cop2
True

>>> import copy
>>> origin = [1, 2, [3, 4]]
#origin 里边有三个元素：1， 2，[3, 4]
>>> cop1 = copy.copy(origin)
>>> cop2 = copy.deepcopy(origin)
>>> cop1 == cop2
True
>>> cop1 is cop2
False 
#cop1 和 cop2 看上去相同，但已不再是同一个object
>>> origin[2][0] = "hey!" 
>>> origin
[1, 2, ['hey!', 4]]
>>> cop1
[1, 2, ['hey!', 4]]
>>> cop2
[1, 2, [3, 4]]
#把origin内的子list [3, 4] 改掉了一个元素，观察 cop1 和 cop2

>>> a = [1, 2, 3]
>>> b = a
>>> a = [4, 5, 6] //赋新的值给 a
>>> a
[4, 5, 6]
>>> b
[1, 2, 3]
# a 的值改变后，b 并没有随着 a 变

>>> a = [1, 2, 3]
>>> b = a
>>> a[0], a[1], a[2] = 4, 5, 6 //改变原来 list 中的元素
>>> a
[4, 5, 6]
>>> b
[4, 5, 6]
# a 的值改变后，b 随着 a 变了

>>> import copy
>>> origin = [1, 2, [3, 4]]
#origin 里边有三个元素：1， 2，[3, 4]
>>> cop1 = copy.copy(origin)
>>> cop2 = copy.deepcopy(origin)
>>> cop1 == cop2
True
>>> cop1 is cop2
False 
#cop1 和 cop2 看上去相同，但已不再是同一个object
>>> origin[2][0] = "hey!" 
>>> origin
[1, 2, ['hey!', 4]]
>>> cop1
[1, 2, ['hey!', 4]]
>>> cop2
[1, 2, [3, 4]]
#把origin内的子list [3, 4] 改掉了一个元素，观察 cop1 和 cop2

The difference between shallow and deep copying is only relevant for compound objects (objects that contain other objects, like lists or class instances):

A shallow copy constructs a new compound object and then (to the extent possible) inserts references into it to the objects found in the original.

A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.

两种 copy 只在面对复杂对象时有区别，所谓复杂对象，是指对象中含其他对象（如复杂的 list 和 class）。

由 shallow copy 建立的新复杂对象中，每个子对象，都只是指向自己在原来本体中对应的子对象。而 deep copy 建立的复杂对象中，存储的则是本体中子对象的 copy，并且会层层如此 copy 到底。