Cool idea, but why not just have a log file on the side that the decorator
writes to? HDF5 only allocates a certain amount of space for attributes /
attribute names. (You can check the spec but I think it is something like
64 k.) So if you are writing an excessive number of attributes you may run
into problems. If it is really important that this log goes into the HDF5
file itself, I would consider looking at the variable length string atom
for VLArrays:
http://pytables.github.com/usersguide/libref.html?highlight=vlstring#vlstringatom
On Thu, Mar 15, 2012 at 8:03 AM, Alvaro Tejero Cantero <alv...@minin.es>wrote:
> Hi,
>
> Here's my last question for today (I sent them separately because they
> are quite unrelated).
>
> I am thinking of writing a python decorator that for any processing
> function (e.g. band-pass filter of median of data[0:3,:]) logs to the
> attributes of the target HDF5 column
>
> * the name of the function,
> * the location of the repository where it lives and a string
> identifying the commit,
> * the arguments that were passed to it (or at least the parameters
> that tune the function; see below)
>
> The goal is to keep my data processing functions generic, yet be able
> (for scientific traceability) to track how a particular result was
> generated. I am still thinking how to report arguments that are long
> arrays without making all of the functions accept as an argument a
> HDF5 tree location string.
>
> Any thoughts / prior art?
>
> regards,
>
> Álvaro.
>
>
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