=========
 README
=========

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/


Example
-------

  >>> 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...>



Availability
------------

The latest version of the package is being made available via the
internet at 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 .


Getting Involved
----------------

Please submit problems, questions and questions through the issue
tracker https://github.com/orbeckst/RecSQL/issues . Pull requests are
also very welcome.