From: Jonathan Ellis Date: Sun, 23 Jul 2006 03:35:03 +0000 (+0000) Subject: de-tabbify X-Git-Tag: rel_0_2_7~57 X-Git-Url: http://git.ipfire.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=423735300cd5557f61386d86cb3ad90bed146b7d;p=thirdparty%2Fsqlalchemy%2Fsqlalchemy.git de-tabbify --- diff --git a/lib/sqlalchemy/ext/sqlsoup.py b/lib/sqlalchemy/ext/sqlsoup.py index 45cff40c74..f8e20a95d3 100644 --- a/lib/sqlalchemy/ext/sqlsoup.py +++ b/lib/sqlalchemy/ext/sqlsoup.py @@ -8,43 +8,43 @@ to declare table or mapper classes ahead of time. Suppose we have a database with users, books, and loans tables (corresponding to the PyWebOff dataset, if you're curious). For testing purposes, we'll create this db as follows: - >>> from sqlalchemy import create_engine - >>> e = create_engine('sqlite:///:memory:') - >>> for sql in _testsql: e.execute(sql) #doctest: +ELLIPSIS - <... + >>> from sqlalchemy import create_engine + >>> e = create_engine('sqlite:///:memory:') + >>> for sql in _testsql: e.execute(sql) #doctest: +ELLIPSIS + <... Creating a SqlSoup gateway is just like creating an SqlAlchemy engine: - >>> from sqlalchemy.ext.sqlsoup import SqlSoup - >>> db = SqlSoup('sqlite:///:memory:') + >>> from sqlalchemy.ext.sqlsoup import SqlSoup + >>> db = SqlSoup('sqlite:///:memory:') or, you can re-use an existing metadata: - >>> db = SqlSoup(BoundMetaData(e)) + >>> db = SqlSoup(BoundMetaData(e)) You can specify a schema within the database for your SqlSoup: - # >>> db.schema = myschemaname + # >>> db.schema = myschemaname Loading objects =============== Loading objects is as easy as this: - >>> users = db.users.select() - >>> users.sort() - >>> users - [MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0), MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1)] + >>> users = db.users.select() + >>> users.sort() + >>> users + [MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0), MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1)] Of course, letting the database do the sort is better (".c" is short for ".columns"): - >>> db.users.select(order_by=[db.users.c.name]) - [MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1), MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0)] + >>> db.users.select(order_by=[db.users.c.name]) + [MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1), MappedUsers(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0)] Field access is intuitive: - >>> users[0].email - u'student@example.edu' + >>> users[0].email + u'student@example.edu' Of course, you don't want to load all users very often. The common case is to select by a key or other field: - >>> db.users.selectone_by(name='Bhargan Basepair') - MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1) + >>> db.users.selectone_by(name='Bhargan Basepair') + MappedUsers(name='Bhargan Basepair',email='basepair@example.edu',password='basepair',classname=None,admin=1) All the SqlAlchemy mapper select variants (select, select_by, selectone, selectone_by, selectfirst, selectfirst_by) are available. See the SqlAlchemy documentation for details: @@ -55,9 +55,9 @@ Modifying objects ================= Modifying objects is intuitive: - >>> user = _ - >>> user.email = 'basepair+nospam@example.edu' - >>> db.flush() + >>> user = _ + >>> user.email = 'basepair+nospam@example.edu' + >>> db.flush() (SqlSoup leverages the sophisticated SqlAlchemy unit-of-work code, so multiple updates to a single object will be turned into a single UPDATE @@ -65,13 +65,13 @@ statement when you flush.) To finish covering the basics, let's insert a new loan, then delete it: - >>> db.loans.insert(book_id=db.books.selectfirst(db.books.c.title=='Regional Variation in Moss').id, user_name=user.name) - MappedLoans(book_id=2,user_name='Bhargan Basepair',loan_date=None) - >>> db.flush() + >>> db.loans.insert(book_id=db.books.selectfirst(db.books.c.title=='Regional Variation in Moss').id, user_name=user.name) + MappedLoans(book_id=2,user_name='Bhargan Basepair',loan_date=None) + >>> db.flush() - >>> loan = db.loans.selectone_by(book_id=2, user_name='Bhargan Basepair') - >>> db.delete(loan) - >>> db.flush() + >>> loan = db.loans.selectone_by(book_id=2, user_name='Bhargan Basepair') + >>> db.delete(loan) + >>> db.flush() Joins @@ -83,15 +83,19 @@ more efficient to have the database perform the necessary join. (Here we do not have "a lot of data," but hopefully the concept is still clear.) SQLAlchemy is smart enough to recognize that loans has a foreign key to users, and uses that as the join condition automatically. - >>> join1 = db.join(db.users, db.loans, isouter=True) - >>> join1.select_by(name='Joe Student') - [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))] + >>> join1 = db.join(db.users, db.loans, isouter=True) + >>> join1.select_by(name='Joe Student') + [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0))] + +If you join tables that have an identical column name, pass use_lables to your +select: + >>> db.with_labels(join1).select() You can compose arbitrarily complex joins by combining Join objects with tables or other joins. - >>> join2 = db.join(join1, db.books) - >>> join2.select() - [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0),id=1,title='Mustards I Have Known',published_year='1989',authors='Jones')] + >>> join2 = db.join(join1, db.books) + >>> join2.select() + [MappedJoin(name='Joe Student',email='student@example.edu',password='student',classname=None,admin=0,book_id=1,user_name='Joe Student',loan_date=datetime.datetime(2006, 7, 12, 0, 0),id=1,title='Mustards I Have Known',published_year='1989',authors='Jones')] """ from sqlalchemy import *