Thanks David, I'll look into it now. Regarding the allocation/deallocation times I think that is not an issue for me. The chunks are generated by a fortran routine that takes several minutes to run (I am collecting a few thousand points before saving to disk). They are approximately the same size but not exactly. I want them to be stored for later retrieval and analysis in a convenient way. Thanks, regards ----------------------------------------- You'll probably want the EArray. createEArray() on a new h5file, then append to it. http://www.pytables.org/docs/manual/ch04.html#EArrayMethodsDescr If your chunks are always the same size it might be best to try and do your work in-place and not allocate a new NumPy array each time. In theory 'del' ing the object when you're done with it should work but the garbage collector may not act quickly enough for your liking/the allocation step may start slowing you down. What do I mean? Well, you could clear the array when you're done with it using foo[:] = 0 (or nan, or whatever) and when you're "building it up" use the inplace augmented assignment operators as much as possible (+=, /=, -=, *=, %=, etc.). David