Relational Databases: Object Relational Mappers - SQLObject

1. Relational Databases: Object Relational Mappers - SQLObject BCHB524Lecture 22 BCHB524 - Edwards

2. Outline • Object relational mappers • Tables as classes, rows as instances • Advantages & disadvantages • Minimal SQLObject example • Legacy databases • Exercises BCHB524 - Edwards

3. Relational Databases • Store information in a table • Rows represent items • Columns represent items' properties or attributes BCHB524 - Edwards

4. Objects have data members or attributes. Store objects in a list oriterable. Abstract awaydetails of underlyingRDBMS ... as Objects c1 = Country()c1.name = 'Brazil'c1.continent = 'South America'c1.region = 'South America'c1.surfaceArea = 8547403c1.population = 170115000c1.gnp = 776739# initialize c2, ..., c6countryTable = [ c1, c2, c3, c4, c5, c6 ]for cnty in countryTable:if cnty.population > 100000000:print cnty.name, cnty.population BCHB524 - Edwards

5. Pros: Learn one language Ease of development Simplified joins One set of data-types Easy storage of higher-level objects Can apply the power of python as necessary Abstract away RDBMS Distribute CPU load Cons: Execution speed Sometimes forced into poor strategies Optimal SQL construct may be impossible Tend not to take advantage of RDBMS quirks. Can be difficult to apply to legacy databases Pros and Cons BCHB524 - Edwards

6. SQLObject • Just one of many object-relational mappers • Each tool makes different tradeoffs in • Table/row/attribute abstraction • How much SQL you need to know • Overhead • Ease of adapting to legacy databases • SQLObject is almost completely devoid of SQL and is almost entirely "objecty". • See http://sqlobject.org. BCHB524 - Edwards

7. Minimal SQLObject Example:Define the database model (model.py) from sqlobject import *import os.pathdbfile = 'myworld.db3'# Magic formatting for database URIconn_str = os.path.abspath(dbfile)conn_str = 'sqlite:'+ conn_strsqlhub.processConnection = connectionForURI(conn_str)classCountry(SQLObject):    name = StringCol()    continent = StringCol()    region = StringCol()    surfaceArea = FloatCol()    population = IntCol()    gnp = FloatCol() BCHB524 - Edwards

8. Minimal SQLObject Example: Populate the database from model import Country# Initialize the tableCountry.createTable()# Add some rowsc = Country(name="Brazil", continent="South America",            region="South America", surfaceArea=8547403,            population=170115000, gnp=776739)c = Country(name="China", continent="Asia",            region="Eastern Asia", surfaceArea=9572900,            population=1277558000, gnp=982268)# ... c = Country(name="United States", continent="North America",            region="North America", surfaceArea=9363520,            population=278357000, gnp=8510700)# Retrieve and print all countriesfor c in Country.select():print c.id, c.name, c.continent, c.gnp BCHB524 - Edwards

9. Minimal SQLObject Example: Access/Change the database from model import Country# Change country #6c = Country.get(6)c.name = 'United States of America'# Retrieve and print all countriesfor c in Country.select():print c.id, c.name, c.continent, c.gnp BCHB524 - Edwards

10. Minimal SQLObject Example:Access the rows as objects from model import Country# Select countries with more than 500,000,000 in populationfor c in Country.select(Country.q.population >= 500000000):print"A:", c.id, c.name, c.population# Select countries that start with 'U'for c in Country.select(Country.q.name.startswith("U")):print"B:", c.id, c.name, c.population# Lookup by id, exactly 1 country with each idc = Country.get(5)print"C:", c.id, c.name, c.population# Get exception for bad id# c = Country.get(100)# Shortcut for select, countries with continent == 'Asia'for c in Country.selectBy(continent = 'Asia'):print"D:", c.id, c.name, c.population BCHB524 - Edwards

11. Legacy databases • If the legacy database is well-structured, SQLObject can figure out (most of) the definitions • If there is no id column... • Need to tell SQLObject what to use for the ID. • May need to specify the id at instantiation time. • Have to fill in MultipleJoins and ForeignKeys yourself • Need to declare which columns in two different tables should correspond. • Enables SQLObject to make relationships explicit • Enables SQLObject to turn joins into lists BCHB524 - Edwards

12. Legacy databases from sqlobject import *import os.pathdbfile = 'taxa.db3'conn_str = os.path.abspath(dbfile)conn_str = 'sqlite:'+ conn_strsqlhub.processConnection = connectionForURI(conn_str)classTaxonomy(SQLObject):classsqlmeta:        idName = "tax_id"        fromDatabase = True    names = MultipleJoin('Name', joinColumn="tax_id")className(SQLObject):classsqlmeta:        fromDatabase = True    taxa = ForeignKey('Taxonomy', dbName="tax_id") BCHB524 - Edwards

13. Legacy databases # Set up data-modelfrom model import *# get homo sapienshs1 = Taxonomy.get(9606)# select the Taxonomy object# with scientific name Homo sapienshs2 = Taxonomy.selectBy(scientificName='Homo sapiens')[0]# get the name humantry:    hsname = Name.selectBy(name='human')[0]exceptIndexError:print"Can't find name 'human'"    sys.exit(1)# get the Taxonomy object from the Name object# Uses the magic Foreign Key attributehs3 = hsname.taxa# hs1, hs2, hs3 the same!print hs1print hs2print hs3 BCHB524 - Edwards

14. Legacy databases # Set up data-modelfrom model import *# get homo sapienshs = Taxonomy.get(9606)# find rows in the Name table with taxa the same as hs# Use ForeignKey to create condition, equality test# between objectscondition = (Name.q.taxa == hs)for n in Name.select(condition):print n# find rows in the Name table corresonding to hs# Easy shortcut, using MultipleJoin iterablefor n in hs.names:print n.name, "|", n.nameClass# More general conditionscondition = Name.q.name.startswith('Da')for n in Name.select(condition):print n.name, "|", n.nameClass BCHB524 - Edwards

15. Exercises • Read through the SQLObject documentation • Write a python program using SQLObject to lookup the scientific name for a user-supplied organism name. BCHB524 - Edwards