SQLAlchemy 1.1 Documentation
SQLAlchemy ORM
- Object Relational Tutorial
- Mapper Configuration
- Relationship Configuration
- Loading Objects
- Using the Session
- Events and Internals
- ORM Extensions
- ORM Examples
Project Versions
SQL Expressions as Mapped Attributes¶
Attributes on a mapped class can be linked to SQL expressions, which can be used in queries.
Using a Hybrid¶
The easiest and most flexible way to link relatively simple SQL expressions to a class is to use a so-called
“hybrid attribute”,
described in the section Hybrid Attributes. The hybrid provides
for an expression that works at both the Python level as well as at the
SQL expression level. For example, below we map a class User
,
containing attributes firstname
and lastname
, and include a hybrid that
will provide for us the fullname
, which is the string concatenation of the two:
from sqlalchemy.ext.hybrid import hybrid_property
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
firstname = Column(String(50))
lastname = Column(String(50))
@hybrid_property
def fullname(self):
return self.firstname + " " + self.lastname
Above, the fullname
attribute is interpreted at both the instance and
class level, so that it is available from an instance:
some_user = session.query(User).first()
print some_user.fullname
as well as usable within queries:
some_user = session.query(User).filter(User.fullname == "John Smith").first()
The string concatenation example is a simple one, where the Python expression
can be dual purposed at the instance and class level. Often, the SQL expression
must be distinguished from the Python expression, which can be achieved using
hybrid_property.expression()
. Below we illustrate the case where a conditional
needs to be present inside the hybrid, using the if
statement in Python and the
sql.expression.case()
construct for SQL expressions:
from sqlalchemy.ext.hybrid import hybrid_property
from sqlalchemy.sql import case
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
firstname = Column(String(50))
lastname = Column(String(50))
@hybrid_property
def fullname(self):
if self.firstname is not None:
return self.firstname + " " + self.lastname
else:
return self.lastname
@fullname.expression
def fullname(cls):
return case([
(cls.firstname != None, cls.firstname + " " + cls.lastname),
], else_ = cls.lastname)
Using column_property¶
The orm.column_property()
function can be used to map a SQL
expression in a manner similar to a regularly mapped Column
.
With this technique, the attribute is loaded
along with all other column-mapped attributes at load time. This is in some
cases an advantage over the usage of hybrids, as the value can be loaded
up front at the same time as the parent row of the object, particularly if
the expression is one which links to other tables (typically as a correlated
subquery) to access data that wouldn’t normally be
available on an already loaded object.
Disadvantages to using orm.column_property()
for SQL expressions include that
the expression must be compatible with the SELECT statement emitted for the class
as a whole, and there are also some configurational quirks which can occur
when using orm.column_property()
from declarative mixins.
Our “fullname” example can be expressed using orm.column_property()
as
follows:
from sqlalchemy.orm import column_property
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
firstname = Column(String(50))
lastname = Column(String(50))
fullname = column_property(firstname + " " + lastname)
Correlated subqueries may be used as well. Below we use the select()
construct to create a SELECT that links together the count of Address
objects available for a particular User
:
from sqlalchemy.orm import column_property
from sqlalchemy import select, func
from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Address(Base):
__tablename__ = 'address'
id = Column(Integer, primary_key=True)
user_id = Column(Integer, ForeignKey('user.id'))
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
address_count = column_property(
select([func.count(Address.id)]).\
where(Address.user_id==id).\
correlate_except(Address)
)
In the above example, we define a select()
construct like the following:
select([func.count(Address.id)]).\
where(Address.user_id==id).\
correlate_except(Address)
The meaning of the above statement is, select the count of Address.id
rows
where the Address.user_id
column is equated to id
, which in the context
of the User
class is the Column
named id
(note that id
is
also the name of a Python built in function, which is not what we want to use
here - if we were outside of the User
class definition, we’d use User.id
).
The select.correlate_except()
directive indicates that each element in the
FROM clause of this select()
may be omitted from the FROM list (that is, correlated
to the enclosing SELECT statement against User
) except for the one corresponding
to Address
. This isn’t strictly necessary, but prevents Address
from
being inadvertently omitted from the FROM list in the case of a long string
of joins between User
and Address
tables where SELECT statements against
Address
are nested.
If import issues prevent the column_property()
from being defined
inline with the class, it can be assigned to the class after both
are configured. In Declarative this has the effect of calling Mapper.add_property()
to add an additional property after the fact:
User.address_count = column_property(
select([func.count(Address.id)]).\
where(Address.user_id==User.id)
)
For many-to-many relationships, use and_()
to join the fields of the
association table to both tables in a relation, illustrated
here with a classical mapping:
from sqlalchemy import and_
mapper(Author, authors, properties={
'book_count': column_property(
select([func.count(books.c.id)],
and_(
book_authors.c.author_id==authors.c.id,
book_authors.c.book_id==books.c.id
)))
})
Using a plain descriptor¶
In cases where a SQL query more elaborate than what orm.column_property()
or hybrid_property
can provide must be emitted, a regular Python
function accessed as an attribute can be used, assuming the expression
only needs to be available on an already-loaded instance. The function
is decorated with Python’s own @property
decorator to mark it as a read-only
attribute. Within the function, object_session()
is used to locate the Session
corresponding to the current object,
which is then used to emit a query:
from sqlalchemy.orm import object_session
from sqlalchemy import select, func
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
firstname = Column(String(50))
lastname = Column(String(50))
@property
def address_count(self):
return object_session(self).\
scalar(
select([func.count(Address.id)]).\
where(Address.user_id==self.id)
)
The plain descriptor approach is useful as a last resort, but is less performant in the usual case than both the hybrid and column property approaches, in that it needs to emit a SQL query upon each access.