Hello Fransesc!
>
> No. That's different. It is probably PyTables fault because it should
> check that other third-party library has already closed the file (i.e.
> PyTables should not be the only one accessing the file).
>
> However, I must warn you that opening the same file with two different
> libraries is a sure receipt for failure, mainly because PyTables's
> internal caches for some HDF5 hierarchical aspect of the file.
>
Yes, I fully agree with you. However, the behavior I report occurs without
the user explicitly accessing a single with different bindings. I
discovered it when, in my application which uses PyTables, I tried to use a
module which did its own internal bookkeeping with h5py. My code never asks
the two modules to operate on the same files, but somehow h5py's exitfunc
does something that operates on files opened by pytables. I am not familiar
with the underlying hdf5 library, but it looks like there is some provision
in the hdf5 library for iterating over all open file handles, and h5py is
using this to close them. The relevant code for h5py's exit handler is this:
# === Library init
============================================================def
_exithack(): """ Internal function; do not call unless you want to
lose all your data. """ # If any identifiers have reference
counts > 1 when the library closes, # it freaks out and dumps a
message to stderr. So we have Python dec_ref # everything when the
interpreter's about to exit. cdef int count cdef int i cdef
hid_t *objs count = H5Fget_obj_count(H5F_OBJ_ALL, H5F_OBJ_ALL)
if count > 0: objs = <hid_t*>malloc(sizeof(hid_t)*count)
try: H5Fget_obj_ids(H5F_OBJ_ALL, H5F_OBJ_ALL, count, objs)
for i from 0<=i<count: while
H5Iget_type(objs[i]) != H5I_BADID and H5Iget_ref(objs[i]) > 0:
H5Idec_ref(objs[i]) finally: free(objs)
_conv.unregister_converters()
Source: http://code.google.com/p/h5py/source/browse/trunk/h5py/h5.pyx
line 332 onwards.
I suspect that the actual fault here is of h5py, since they end up
closing files they do not open. However, this bad behavior ends up
biting unsuspecting PyTables users such as myself! Perhaps as you say
it may be possible to check for this condition, and issue the user a
warning about it?
I have reported the issue to h5py as well now:
http://code.google.com/p/h5py/issues/detail?id=136
Hope this helps.
Cheers,
Marco
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