There are currently two ways to construct SQL expressions with
SQLAlchemy without any knowledge of a database connection or
implementation.
One is to use the ProxyEngine, which receives a connect() call when
you are ready to connect it to something, which occurs only within
the scope of the current thread:
e = ProxyEngine()
s = Table('mytable', e, Column()...).select()
e.connect('someengine://')
s.execute()
e.connect('someotherengine://')
s.execute()
This is the way everyone who needs their app to run before a database
is defined has been doing it.
Also, if you create a Table without an explicit engine, it uses a
"default" ProxyEngine that you can later connect to databases via the
"global_connect()" function, so you can also build up your tables
without knowing anything about engines at all.
The other way, which is a little more "underground" and is currently
used just in some of the unit tests, is to construct using
TableClause and ColumnClause objects, which are the "lexical"
component to Table and Column objects:
t = table('mytable', column('col1'), column('col2'))
s = t.select()
print s # will print the select query with a default compiler
# compile 's' against a SQLite engine
e = create_engine('sqlite://')
c = s.compile(e)
# or compile 's' against SQLite's compiler
c = sqlalchemy.databases.sqlite.SQLiteCompiler(s)
# execute
c.execute()
# compile 's' against postgres:
e = create_engine('postgres://')
c = s.compile(e)
# execute
c.execute()
This was a refactoring I came up with after reading the blog post on
SQL-API, to cleanly separate the concepts of "lexical" and "schema"
constructs. TableClause and ColumnClause, since they arent related
to any kind of "schema", dont have any "unique-per-tablename" type
behavior, and also dont have the benefit of column types or foreign
keys (this might change at some point). I have yet to work out a
full set of patterns which can "upgrade" these lexical objects to
"schema-aware" objects in a straightforward way.
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