Hi, I'm new to pytables so I hope this isn't too obvious...
I have some existing h5 files that I read in with: > >> import tables > >> h5slow = tables.openFile(data.h5, 'r') The data is then directly in the root directory, for example: > >> h5slow.root.tag /tag (Array(393816, 2)) '' atom := Int32Atom(shape=(), dflt=0) maindim := 0 flavor := 'numpy' byteorder := 'big' chunkshape := None The problem is when I do a query on this it is very slow. For example, I know that the last entry in my data has a value of 7848107, so searching for this is my cheap test for speed. In Ipython: %timeit result = [x for x in h5slow.root.tag if x[1]==7848107] 1 loops, best of 3: 5.66 s per loop using the read() method gives a slight speed up: %timeit result = [x for x in h5slow.root.tag.read() if x[1]==7848107] 1 loops, best of 3: 2.21 s per loop However when I wrote a little script to convert my data and save it in a new h5 file this is all MUCH faster (100x): %timeit result = [x for x in h5fast.root.detector.readout if x[1]==7848107] 10 loops, best of 3: 53.8 ms per loop In the faster case I created a new h5 file using the data from my original h5 file 'Getting started' instructions in the user manual. The faster case is also a table.Table object and the slow case a array.Array object. > >>h5fast.root.detector.readout /detector/readout (Table(393816,)) 'Readout example' description := { "cpu": Int8Col(shape=(), dflt=0, pos=0), "pnum": Int32Col(shape=(), dflt=0, pos=1)} byteorder := 'little' chunkshape := (1638,) Question: Why is openFile reading the original data file as an array.Array object if querying tables is so much faster? Thanks in advance for any help! Raphael ------------------------------------------------------------------------------ Special Offer-- Download ArcSight Logger for FREE (a $49 USD value)! Finally, a world-class log management solution at an even better price-free! Download using promo code Free_Logger_4_Dev2Dev. Offer expires February 28th, so secure your free ArcSight Logger TODAY! http://p.sf.net/sfu/arcsight-sfd2d _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users