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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 and hdf5, both of which are available from
SlackBuilds.org.
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