Question

Since when did numpy allow you to define an array of python objects? Objects array with numpy.

Is there any fundamental difference between these arrays and a python list?

What is the difference between these arrays and say, a python tuple?

There are several handy numpy functions I would like to use, i.e. masks and element-wise operations, on an array of python objects and I would like to use them in my analysis, but I’m worried about using a feature I can’t find documentation for anywhere. Is there any documentation for this ‘object’ datatype?

Was this feature was added in preparation for merging numpy into the standard library?

Answer 1

The “fundamental” difference is that a Numpy array is fixed-size, while a Python list is a dynamic array.

>>> class Foo:
...  pass
... 
>>> x = numpy.array([Foo(), Foo()])
>>> x.append(Foo())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'numpy.ndarray' object has no attribute 'append'

(You can get around this with numpy.concatenate, but still Numpy arrays aren’t meant as a drop-in replacement for list.)

Arrays of object are perfectly well documented, but be aware that you’ll have to pass dtype=object sometimes:

>>> numpy.array(['hello', 'world!'])
array(['hello', 'world!'], 
      dtype='|S6')
>>> numpy.array(['hello', 'world!'], dtype=object)
array(['hello', 'world!'], dtype=object)