RAMArray is compatible to ZBigArray in API and semantic, but stores its
data in RAM only. It is useful in situations where ZBigArray compatible
data type is needed, but the amount of data is small and the data itself
is needed only temporarily - e.g. in a simulation.

Implementation is based on mmapping temporary files from /dev/shm/... and
passing them as file handles, similarly to how ZBigArray works, to BigArray.
We don't use just numpy.ndarray because of append - for ZBigArray append
works in O(1), but more importantly it does not copy data. This way
mmapings previously created for ZBigArray views, continue to correctly
alias array data. If we would be using ndarray directly, since
ndarray.resize copies data, that property would not be preserved.

Original patch by Klaus Wölfel <klaus@nexedi.com>
(!8)