> That is of great help! I had tried parsing a dtype in createTable (not > accepted), but I never thought of trying an np-ndarray with that > dtype. If that works, it will solve my problem (will try at work > tomorrow).
OK, I have now tried creating a table using a nump.recarray in the description field, and on close reading of the Library reference sec. 4.2.3 regarding the createTable method I see that this is indeed documented there and so is the pydoc you get when you do, e.g., a h5file.createtable? in an IPython shell. What mislead me, was the Tutorial chapter 3 in the User's Guide, which I followed to get a good understanding. First, in sec. 3.1.5 "Creating a new table" an example is shown where you use an IsDescription instance as the description parameter, and later in the more complicated example on p. 34-35 in sec. 3.4 "Multidimensional table cells and automatic sanity checks", it is also shown that you can use a dictionary with XXXCol() instances as the dictionary values. >From that example I got the impression that if you had a dtype, the path to creating a table of that type would be to first create such a dictionary or a Description instance translating the dtype values, i.e., '<f8' to the XXXCol() instances, e.g., Float32Col(), which is why I started looking for a factory method like Description.from_dtype(). To not lead other numpy users along the same erroneous path (because the Library reference is not the first chaper you start reading from beginning to end), I could suggest to mention the recarray createtable path somewhere in the tutorial section in Sec. 3.1.5 or 3.4, alternatively write a chapter or an appendix specifically targeted at the PyTables/numpy interplay, as it seems like there are many nifty tricks you can use to get your work done very easy and fast if you are working with numpy arrays together with PyTables. Finally, I would also suggest to extend the implementation of createTable such that the description paramer can also accept a np.dtype instance. Personally, I append to a table in chunks of, say 1MB to keep down memory usage (I may have 1GB in a single table), and here I prefer to first define the table, and then append data (seems like the cleanest thing to do), so I therefore first use h5file.createTable(...,description=np.empty(0, dtype=my_dtype), ...) to define the table based on a dtype, which seems kinda awkward as inside this method you are extracting the dtype from array. Having the possibility to do h5file.createTable(...,description=my_dtype, ...) seems more intuitive for me. Finally, this should not be considered as a rant, just some observations from a new user. My general impression is that the "product" is well very polished and stable, the user's guide is well-written and the package is very, very nice (it is an answer to my praisers and the end of a long frustrating search for a package which could need my needs). As mentioned in another post, there is an issue with installing LZO for windows users and other details, but overall very good. I am actually thrilled about PyTables, and I have eagerly demonstrated its capabilities to my co-workers today (first create an HDF5 and then browse and filter it using VITables), and they are impressed as well. I think it is amazing that such a product is available under a free license, and I would like to thank the creators for taking their time to make it. Cheers, Kim ------------------------------------------------------------------------------ Let Crystal Reports handle the reporting - Free Crystal Reports 2008 30-Day trial. Simplify your report design, integration and deployment - and focus on what you do best, core application coding. Discover what's new with Crystal Reports now. http://p.sf.net/sfu/bobj-july _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
