python 变量作用域 v.__sizeof__() python 深复制 一切皆对象 尽量减少内存消耗

时间:2023-03-09 19:31:26
python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

小结:

-1

+=修改旧变量地址的内容;=创建新增内存地址;

1、

id cpy 内存地址

id(object)

2、赋值语句的原理

不复制对象,而是建立目标和对象的绑定。

Assignment statements in Python do not copy objects, they create bindings between a target and an object.

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python 深入理解 赋值、引用、拷贝、作用域 - 江召伟 - 博客园 https://www.cnblogs.com/jiangzhaowei/p/5740913.html

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

a=[1,2,5]
b=a
print(id(a),'--',id(b)) b=[9,8]
print(id(a),'--',id(b)) f=7
g=f
print(id(f),'--',id(g))
g=888
print(id(f),'--',id(g)) class c:
def __init__(self,a):
self.a=a
def f(self):
print(self.a)
c1=c(66)
c2=c('str')
print(id(c1),'--',id(c2)) class cb:
def __init__(self):
self.a=a
def f(self):
print(123)
cb1=cb()
cb2=cb()
print(id(cb1),'--',id(cb2))
import copy gg=9

内存地址   内存标识 内存id

1794696 -- 1794696
1794696 -- 1794760
8791475577680 -- 8791475577680
8791475577680 -- 2024944
31727120 -- 31727176
31727288 -- 31727232

一切皆对象

尽量减少内存消耗

id 内存地址

id(object)

Return the “identity” of an object. This is an integer which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value.

CPython implementation detail: This is the address of the object in memory.

copy — Shallow and deep copy operations — Python 3.8.2rc1 documentation https://docs.python.org/3.8/library/copy.html

Assignment statements in Python do not copy objects, they create bindings between a target and an object.

a = b = c = 1
e, d, f = 1, 1, 1
a = 4
a1 = b1 = c1 = '1'
e1, d1, f1 = '1', '1', '1'
a1 = '2'
import copy x = copy.deepcopy(a)
z = copy.copy(a)
y = a
a = 5
x1 = copy.deepcopy(e1)
z1 = copy.copy(e1)
y1 = e1
e1 = '2'
lc = [1, [2, 3]]
lc1 = copy.copy(lc)
lc2 = copy.deepcopy(lc)
lc = [1, [2, 3, 4]]
dc = {'a':12,12:'a'}
dc1 = copy.copy(dc)
dc2 = copy.deepcopy(dc)
dc = {'a':123,12:'ab'}
dcr = {'a':12,12:'a'}
dcr0=dcr
dcr1 = copy.copy(dcr)
dcr2 = copy.deepcopy(dcr)
dcr = {'a':123,12:{1:1,'a':'a'}}
dcrr = {'a':123,12:{1:1,'a':'a'}}
dcrr0=dcrr
dcrr1 = copy.copy(dcrr)
dcrr2 = copy.deepcopy(dcrr)
dcrr = {'a':123,12:{11:1,'aa':'aa'}}
t = 7

  上述赋值语句 右边值的改变均没有引起左边值的改变。

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

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

  • 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:

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

  • Because deep copy copies everything it may copy too much, such as data which is intended to be shared between copies.

The deepcopy() function avoids these problems by:

  • keeping a memo dictionary of objects already copied during the current copying pass; and

  • letting user-defined classes override the copying operation or the set of components copied.

关于Python中的引用 - 东去春来 - 博客园 https://www.cnblogs.com/yuyan/archive/2012/04/21/2461673.html

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

python  变量作用域  v.__sizeof__()  python  深复制  一切皆对象  尽量减少内存消耗

x,y=1,2
x,y=y,x+y 生成器 - 廖雪峰的官方网站 https://www.liaoxuefeng.com/wiki/1016959663602400/1017318207388128

注意,赋值语句:

a, b = b, a + b

相当于:

t = (b, a + b) # t是一个tuple
a = t[0]
b = t[1]

但不必显式写出临时变量t就可以赋值。