Hello,

I encountered an unexpected behavior when using wendelin.bigarray.array_zodb.ZBigArray.

When initializing a ZBigArray by using a list for the shape parameter, the append method will raise an error:

>>> from wendelin.bigarray.array_zodb import ZBigArray
>>> zbig_array = ZBigArray(shape=[1], dtype=float)
>>> zbig_array.append([1])
ValueError: all the input array dimensions except for theconcatenation axis must match exactly

It will raise this error because it will come to [] != () here: zbig_array.shape returns a list, but the shape property of the adhoc created array which is supposed to be appended returns a tuple.

It's fair to say this is actually an users error, because the numpy documentation clearly specifies the shape parameter as a tuple of ints.

Nevertheless recent versions of numpy.ndarray still do accept a list as a valid input of shape:

>>> import numpy
>>> numpy.__version__
1.23.1
>>> numpy.ndarray(shape=[2]).shape
(2,)
>>> numpy.ndarray(shape=[2]).shape == numpy.ndarray(shape=(2,)).shape
True

What is the preferred way how to handle this difference in behavior between numpy.ndarray and wendelin.bigarray.array_zodb.ZBigArray?

I've thought about:

1. Simply wrapping shape into a tuple call here (e.g. self._shape = tuple(shape)).

2. Somehow improve the error message. It's perhaps not a big deal, but it can be confusing and time-consuming when encountering the described append scenario with the bad shape parameter.

Best, Levin

/cc @kirr