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Signed-off-by: Niels Horn <niels.horn@slackbuilds.org> |
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pytables.info | ||
pytables.SlackBuild | ||
README | ||
slack-desc |
PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data. It optimizes memory and disk resources so that data takes much less space than other solutions such as relational or object oriented databases. PyTables has been designed to fulfill the next requirements: 1. Allow to structure your data in a hierarchical way. 2. Easy to use. It implements the NaturalNaming scheme for allowing convenient access to the data. 3. All the cells in datasets can be multidimensional entities. 4. Most of the I/O operations speed should be only limited by the underlying I/O subsystem. 5. Enable the end user to save large datasets in a efficient way, i.e. each single byte of data on disk has to be represented by one byte plus a small fraction when loaded in memory. This requires numpy, numexpr, hdf5 and Cython.