File: __init__.py

package info (click to toggle)
sqlalchemy 0.6.3-3%2Bsqueeze1
  • links: PTS, VCS
  • area: main
  • in suites: squeeze
  • size: 10,744 kB
  • ctags: 15,132
  • sloc: python: 93,431; ansic: 787; makefile: 137; xml: 17
file content (27 lines) | stat: -rw-r--r-- 1,032 bytes parent folder | download
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
"""
Illustrates "vertical table" mappings.

A "vertical table" refers to a technique where individual attributes of an object are stored as distinct rows in a table.   
The "vertical table" technique is used to persist objects which can have a varied set of attributes, at the expense of simple query control and brevity.   It is commonly found in content/document management systems in order to represent user-created structures flexibly.

Two variants on the approach are given.  In the second, each row references a "datatype" which contains information about the type of information stored in the attribute, such as integer, string, or date.


Example::

    shrew = Animal(u'shrew')
    shrew[u'cuteness'] = 5
    shrew[u'weasel-like'] = False
    shrew[u'poisonous'] = True

    session.add(shrew)
    session.flush()

    q = (session.query(Animal).
         filter(Animal.facts.any(
           and_(AnimalFact.key == u'weasel-like',
                AnimalFact.value == True))))
    print 'weasel-like animals', q.all()


"""