RecSQL's basic idea is to treat numpy record arrays like SQL tables. What it does, in fact, is to represent the arrays as real SQL tables (using SQLite) and provide convenience functions to return recarrays on demand.
This works ok for small tables but less so if you want to access gigabytes of data as recarrays. It's a hack.
Documentation can be found at http://recsql.readthedocs.org/
Source code is available from https://github.com/orbeckst/RecSQL under
the GNU General Public License, version 3 (see also the file
LICENSE in the distribution).
>>> from recsql import SQLarray >>> import numpy >>> a = numpy.rec.fromrecords(numpy.arange(100).reshape(25,4), names='a,b,c,d') >>> Q = SQLarray('my_name', a) >>> print repr(Q.recarray) rec.array([(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (12, 13, 14, 15), (16, 17, 18, 19), (20, 21, 22, 23), (24, 25, 26, 27), (28, 29, 30, 31), (32, 33, 34, 35), (36, 37, 38, 39), (40, 41, 42, 43), (44, 45, 46, 47), (48, 49, 50, 51), (52, 53, 54, 55), (56, 57, 58, 59), (60, 61, 62, 63), (64, 65, 66, 67), (68, 69, 70, 71), (72, 73, 74, 75), (76, 77, 78, 79), (80, 81, 82, 83), (84, 85, 86, 87), (88, 89, 90, 91), (92, 93, 94, 95), (96, 97, 98, 99)], dtype=[('a', '<i4'), ('b', '<i4'), ('c', '<i4'), ('d', '<i4')]) >>> Q.SELECT('*', 'WHERE a < 10 AND b > 5') rec.array([(8, 9, 10, 11)], dtype=[('a', '<i4'), ('b', '<i4'), ('c', '<i4'), ('d', '<i4')]) # creating new SQLarrays: >>> R = Q.selection('a < 20 AND b > 5') >>> print R <recsql.sqlarray.SQLarray object at 0x...>
The latest version of the package is available on GitHub https://github.com/orbeckst/RecSQL
RecSQL is also listed on PyPi http://pypi.python.org/pypi/RecSQL and can thus be installed with
pip install RecSQL
See :doc:`INSTALL` for further installation instructions.
A git repository of the package is hosted at http://github.com/orbeckst/RecSQL .
Please submit problems, questions and questions through the issue tracker. Pull requests are also very welcome.