On 2011-01-21, Damon Lynch <[email protected]> wrote: > On Fri, Jan 21, 2011 at 3:35 AM, Olivier Tilloy <[email protected] > <mailto:[email protected]>> wrote: > > > Out of curiosity, what’s your use case for pickling image metadata? > Ultimately, pickling is no more than serializing data (on disk or in > memory), and this data is already in the image itself and can be > "reconstructed" from just the file name. Wouldn’t that work for you? > > > For instance, the problem of copying photos from memory cards onto the > hard drive and renaming them. For each memory card, a process copies the > photos and reads the metadata. So if you have two memory cards, that's > two processes running in parallel. Both processes then send a message to > a daemon renaming process, whose only task is to rename photos using the > exif information, sequence numbers, and whatever else is needed. The > daemon process itself could load the metadata but it's a relatively slow > operation, and thus better to do in parallel.
I suppose that the daemon in charge of renaming photos only needs a rather small subset of the EXIF/IPTC/XMP metadata in order to proceed to renaming a photo. How about pickling and passing only this subset, e.g. as a dictionary (should be easy since tags can be pickled)? You’ll potentially save a lot of bandwidth in your inter-process communication. > My preliminary testing using multiprocessing, queues and pipes indicates > that in the case of copying and renaming photos in parallel, the > scanning phase (determining what photos are at a location and loading > them into a TreeView to show the user) takes only 6% of the time it > takes to do the same thing with threads and locks. Clearly the > performance gains can be enormous. Impressive gain indeed, way to go! _______________________________________________ Mailing list: https://launchpad.net/~pyexiv2-developers Post to : [email protected] Unsubscribe : https://launchpad.net/~pyexiv2-developers More help : https://help.launchpad.net/ListHelp
