Application of memory to data in Python

Python's use of memory
Shallow Copy explain : copy of the reference (copy only the parent object);	Deep copy explanation : A copy of the object resource;

Import module:

>>> Import Copy

>>> a = [1,2,3,[' A ', ' B ', ' d ']]>>> b = a>>> a[1, 2, 3, [' A ', ' B ', ' d ']]>>> b[1, 2, 3, [' A ', ' B ', ' d ']]>>> ID (a) 139712705065616>>> ID (b) 139712705065616# defines a two-tuple list, tag reference, and view memory address consistent, but not as a basis

Call the Copy.copy module to copy a shallow copy

>>> C=copy.copy (a)

Observe the address space of C, which is independent by copy

>>> c[1, 2, 3, [' A ', ' B ', ' d ']]>>> a[1, 2, 3, [' A ', ' B ', ' d ']]>>> ID (c) 139712705068784 #注意 > >> ID (a) 139712705065616 #注意

To add a value to a sequence:

>>> a.append (' d ') >>> a[1, 2, 3, [' A ', ' B ', ' d '], ' d ']>>> b[1, 2, 3, [' A ', ' B ', ' d '], ' d '] #b指向 The same address space >>> c[1, 2, 3, [' A ', ' B ', ' d ']] #c未改变

A shallow copy copies only the parent object:

>>> ID (a[3]) 139712704967456>>> ID (c[3]) 139712704967456>>> ID (a[4]) 139712705357456

#注意上述可变类型的子对象地址空间未改变,

Call the Copy.deepcopy module for copy deep copy

>>> d = copy.deepcopy (a)

View address space

>>> ID (a) 139712705065616>>> ID (d) 139712705065688>>> ID (a[3]) 139712704967456>> > ID (d[3]) 139712705068640 #此处是不一致的

To add a value to a sequence:

>>> a.append (' e ') >>> a[1, 2, 3, [' A ', ' B ', ' d ', ' d '], ' d ', ' E ']>>> d[1, 2, 3, [' A ', ' B ', ' d ', ' d '], ' d ']>>> a[3].append (' x ') >>> a[1, 2, 3, [' A ', ' B ', ' d ', ' d ', ' X '], ' d ', ' E ']>>> d[1, 2, 3, [' A ', ' B ', ' d ', ' d '], ' d ']

Copy of the object resource:

>>> ID (a[3]) 139712704967456>>> ID (d[3]) 139712705068640 #注意上述可变类型的子对象地址空间发生改变

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Application of memory to data in Python