引用和值装模作样：python何时做第一个，何时做第二个

我想了解python何时通过值影响变量，何时通过引用影响变量

dataToTreat=[]
for i in (np.arange(5)):
    dataToTreat.append(i)

dataToTreatBis=dataToTreat

print(dataToTreat)
dataToTreatBis=[10,11,12,13,14]
print(dataToTreat) # dataToTreat hasn't changed because of dataToTreatBis

print(" ")
dataToTreat=[]
#data[NdemodB + NdemodA:NdemodB + NdemodA+NtraceA+NtraceB]
for i in range(5):
    dataToTreat.append([0, 1, 2])

dataToTreatBis=dataToTreat

print(dataToTreat[0])
dataToTreatBis[0]=[10,11,12,13,14]
print(dataToTreat[0]) # dataToTreat has changed here !

以下面的例子为例。在这段代码中，我首先创建一个列表“dataToTreat”，然后说“dataToTreatBis=dataToTreat”。但当我将dataToTreatBis更改为dataToTreat时，dataToTreat不受影响

但是在代码的第二部分，我做了同样的事情，但是我更改了数组dataToTreatBis的一个元素：dataToTreatBis[0]。然后dataToTreat也会发生变化

我怎么能猜到呢？在这两种情况下，我都使用列表，当我更改列表的一个元素时，事情是通过引用而不是通过新的值做作来工作的

我只是想了解发生了什么：为什么在第一种情况下我确实复制了变量，但在第二种情况下我只是更改了引用

dataToTreat=[]
for i in (np.arange(5)):
    dataToTreat.append(i)

dataToTreatBis=dataToTreat

print(dataToTreat)
dataToTreatBis=[10,11,12,13,14]
print(dataToTreat) # dataToTreat hasn't changed because of dataToTreatBis

print(" ")
dataToTreat=[]
#data[NdemodB + NdemodA:NdemodB + NdemodA+NtraceA+NtraceB]
for i in range(5):
    dataToTreat.append([0, 1, 2])

dataToTreatBis=dataToTreat

print(dataToTreat[0])
dataToTreatBis[0]=[10,11,12,13,14]
print(dataToTreat[0]) # dataToTreat has changed here !

---

这两次，dataToTreatBis都是对dataToTreat的引用。然而，在第一个实例中，您正在对reatbis执行另一个赋值（完全重写）数据，这会中断链接。在第二个例子中，您只是修改一个元素中的值，因此并没有破坏链接。希望这是清楚的

所有python变量都绑定到内存中的某些对象

第一部分：

import numpy as np

dataToTreat=[]
for i in (np.arange(5)):
    dataToTreat.append(i)

dataToTreatBis=dataToTreat

print(dataToTreat)
dataToTreatBis=[10,11,12,13,14]
print 'dataToTreatBis_id: ', id(dataToTreatBis)
print(dataToTreat) # dataToTreat hasn't changed because of dataToTreatBis
print 'dataToTreat_id: ', id(dataToTreat)

输出：

dataToTreatBis_id:85586968

dataToTreat_id:85586648

第二部分： 由于您定义了一个新的赋值运算符（即

dataToTreat=[]

），因此实际上创建了一个具有新id的新对象

dataToTreat=[]
#data[NdemodB + NdemodA:NdemodB + NdemodA+NtraceA+NtraceB]
for i in (np.arange(5)):
    dataToTreat.append([0, 1, 2])

dataToTreatBis=dataToTreat


print(dataToTreat[0])
dataToTreatBis[0]=[10,11,12,13,14]
print(dataToTreat[0]) # dataToTreat has changed here !
print id(dataToTreatBis)
print id(dataToTreat)
print 'dataToTreatBis_id: ', id(dataToTreatBis)
print 'dataToTreat_id: ', id(dataToTreat)

输出：

dataToTreatBis_id:85586888

dataToTreat_id:85586888

---

如您所见，您正在内存中的同一位置写入，这就是为什么dataToTreat正在更改

您误解了Python变量是什么。理解可变对象也很重要<代码>=可以做两件事-更改名称引用的对象，以及更改可变对象的内容。