Python中这两个数组声明之间有什么区别？

Question

What is the difference between these two array declarations in Python?

table = [[0]*100]*100
table = numpy.zeros([100,100], int)

Answer 1

They have nothing in common in fact. The second is a numpy 2D array. The first is not anything useful - it's an array of 100 items, each one of which is a reference to a SINGLE array of 100 zeroes:

table = [[0]*100]*100
table[1][0]=222
print table[0][0]

This prints '222'!

table = numpy.zeros([100,100], int)
table[1][0]=222
print table[0][0]

This prints '0'!

Answer 2

Well, for once, the first one is dangerously wrong. See this:

In [8]: table = [[0]*2]*10

In [9]: table
Out[9]: 
[[0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0],
 [0, 0]]

In [10]: table[0][1] = 5

In [11]: table
Out[11]: 
[[0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5],
 [0, 5]]

It happens because the way you declared table , the sub-list is duplicated all over again. See this FAQ for info on doing this correctly.