Python augmented assignment issue

Question

i ran into something interesting about the python augmented assignment +=

it seems to be automatic data type conversion is not always done for a +

Answer 1

If array is numpy.array (you don't actually specify), then the issue that's happening is because these arrays cannot change their type. When you create the array without a type specifier, it guesses a type. If you then attempt to do an operation that type doesn't support (like adding it to a type with a larger domain, like complex), numpy knows perform the calculation, but it also knows that the result can only be stored in the type with the larger domain. It complains (on my machine, anyway, the first time I do such an assignment) that the result doesn't fit. When you do a regular addition, a new array has to be made in any case, and numpy gives it the correct type.

>>> a=numpy.array([1])
>>> a.dtype
dtype('int32')
>>> b=numpy.array([1+1j])
>>> b.dtype
dtype('complex128')
>>> a+b
array([ 2.+1.j])
>>> (a+b).dtype
dtype('complex128')
>>> a+=b
>>> a
array([2])
>>> a.dtype
dtype('int32')
>>>