Sorting array using indices results in too many indices for array

In Python 3, dir(np.array(colour_map.keys())) shows that this class not satisfy the array_like requirement which is specified as being necessary in the documentation for numpy.array https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.array.html

The definition of array_like was explored in more detail here numpy: formal definition of "array_like" objects?

It seems that np.array doesn't check whether array_like is satisfied, and will happily construct a Numpy array from an object which does not satisfy it.

Then when you try to index it, the indexing doesn't work.

Here's an example with my_object designed not to be array_like.

class my_object():
    def greet(self):
        print("hi!")

a = my_object()
a.greet()
print(dir(a))  # no __array__ attribute

b = np.array(a)

b[0]

results in

hi!
['__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', 'greet']
Traceback (most recent call last):
  File "C:/path/to/my/script.py", 
line 35, in <module>
    b[0]
IndexError: too many indices for array

Now let's try making it array-like (or at least sufficiently array-like for this to work):

class my_object():
    def greet(self):
        print("hi!")

    def __array__(self):
        return np.array([self])

a = my_object()

b = np.array(a)

b[0].greet()  # Now we can index b successfully

results in:

hi!