Why Numpy treats a+=b and a=a+b differently

Question

Is the following numpy behavior intentional or is it a bug?

from numpy import *

a = arange(5)
a = a+2.3
print \'a = \', a
# Output: a = 2.3, 3.3, 4.3, 5.3,         


        

Answer 1

@aix is completely right. I just wanted to point out this is not unique to numpy. For example:

>>> a = []
>>> b = a
>>> a += [1]
>>> print a
[1]
>>> print b
[1]
>>> a = a + [2]
>>> print a
[1, 2]
>>> print b
[1]

As you can see += modifies the list and + creates a new list. This hold for numpy as well. + creates a new array so it can be any data type. += modifies the array inplace and it's not practical, and imo desirable, for numpy to change the data type of an array when array content is modified.