Efficient filtering of SQL tables with generator expressions.
Project description
This module allows you to access a (DB API 2) SQL table using nothing but Python to build the query:
>>> from pysqlite2 import dbapi2 as sqlite >>> conn = sqlite.connect("coastline.db") >>> from simpleql.table import Table >>> table = Table(conn, "coastline", verbose=True) >>> print table {'longitude': <simpleql.table.Col object at 0x547070>, 'latitude': <simpleql.table.Col object at 0x547050>} >>> for row in (r for r in table if r.latitude > 83 and (r.longitude < 300 or r.longitude > 320)): ... print row SELECT longitude, latitude FROM coastline WHERE (latitude>83) AND ((longitude<300) OR (longitude>320)); {'longitude': 292.53553099999999, 'latitude': 83.016946000000004} {'longitude': 292.188199, 'latitude': 83.019293000000005} {'longitude': 290.23328500000002, 'latitude': 83.019293000000005} {'longitude': 289.97044, 'latitude': 83.031026999999995} {'longitude': 289.65127000000001, 'latitude': 83.014599000000004} <snip>
As you can see, the query string is built from a generator expression. You can also use list comprehensions. Regular expressions are supported by the use of the re.search method:
>>> table = Table(conn, "table") >>> filtered = (r for r in table if re.search("string", r['column'])) >>> for row in filtered: ... print row SELECT column FROM table WHERE column LIKE "%string%"; <snip>
The advantage of this approach over the similar recipe is that if the (efficient) query builder fails when it encounters a complex filter the data will still be filtered (unefficiently) by the generator expression.
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