{python}
>>> from sqlalchemy.sql import func
- >>> stmt = session.query(Address.user_id, func.count('*').label('address_count')).group_by(Address.user_id).statement.alias()
+ >>> stmt = session.query(Address.user_id, func.count('*').label('address_count')).group_by(Address.user_id).subquery()
-The `func` keyword generates SQL functions, and the `alias()` method on `Select` (the return value of `query.statement`) creates a SQL alias, in this case an anonymous one which will have a generated name.
+The `func` keyword generates SQL functions, and the `subquery()` method on `Query` produces a SQL expression construct representing a SELECT statement embedded within an alias (it's actually shorthand for `query.statement.alias()`).
-Once we have our statement, it behaves like a `Table` construct, which we created for `users` at the top of this tutorial. The columns on the statement are accessible through an attribute called `c`:
+Once we have our statement, it behaves like a `Table` construct, such as the one we created for `users` at the start of this tutorial. The columns on the statement are accessible through an attribute called `c`:
{python}
{sql}>>> for u, count in session.query(User, stmt.c.address_count).outerjoin((stmt, User.id==stmt.c.user_id)): # doctest: +NORMALIZE_WHITESPACE
return self._compile_context(labels=self._with_labels).statement
statement = property(statement)
+ def subquery(self):
+ """return the full SELECT statement represented by this Query, embedded within an Alias."""
+
+ return self.statement.alias()
+
def with_labels(self):
"""Apply column labels to the return value of Query.statement.