SQLAlchemy 2.0 Documentation
SQLAlchemy ORM
- ORM Quick Start
- ORM Mapped Class Configuration
- Relationship Configuration
- ORM Querying Guide
- Writing SELECT statements for ORM Mapped Classes
- Writing SELECT statements for Inheritance Mappings
- ORM-Enabled INSERT, UPDATE, and DELETE statements
- Column Loading Options¶
- Relationship Loading Techniques
- ORM API Features for Querying
- Legacy Query API
- Using the Session
- Events and Internals
- ORM Extensions
- ORM Examples
Project Versions
Column Loading Options¶
About this Document
This section presents additional options regarding the loading of columns. The mappings used include columns that would store large string values for which we may want to limit when they are loaded.
View the ORM setup for this page. Some
of the examples below will redefine the Book
mapper to modify
some of the column definitions.
Limiting which Columns Load with Column Deferral¶
Column deferral refers to ORM mapped columns that are omitted from a SELECT statement when objects of that type are queried. The general rationale here is performance, in cases where tables have seldom-used columns with potentially large data values, as fully loading these columns on every query may be time and/or memory intensive. SQLAlchemy ORM offers a variety of ways to control the loading of columns when entities are loaded.
Most examples in this section are illustrating ORM loader options. These
are small constructs that are passed to the Select.options()
method
of the Select
object, which are then consumed by the ORM
when the object is compiled into a SQL string.
Using load_only()
to reduce loaded columns¶
The load_only()
loader option is the most expedient option to use
when loading objects where it is known that only a small handful of columns will
be accessed. This option accepts a variable number of class-bound attribute
objects indicating those column-mapped attributes that should be loaded, where
all other column-mapped attributes outside of the primary key will not be part
of the columns fetched . In the example below, the Book
class contains
columns .title
, .summary
and .cover_photo
. Using
load_only()
we can instruct the ORM to only load the
.title
and .summary
columns up front:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import load_only
>>> stmt = select(Book).options(load_only(Book.title, Book.summary))
>>> books = session.scalars(stmt).all()
SELECT book.id, book.title, book.summary
FROM book
[...] ()
>>> for book in books:
... print(f"{book.title} {book.summary}")
100 Years of Krabby Patties some long summary
Sea Catch 22 another long summary
The Sea Grapes of Wrath yet another summary
A Nut Like No Other some long summary
Geodesic Domes: A Retrospective another long summary
Rocketry for Squirrels yet another summary
Above, the SELECT statement has omitted the .cover_photo
column and
included only .title
and .summary
, as well as the primary key column
.id
; the ORM will typically always fetch the primary key columns as these
are required to establish the identity for the row.
Once loaded, the object will normally have lazy loading behavior
applied to the remaining unloaded attributes, meaning that when any are first
accessed, a SQL statement will be emitted within the current transaction in
order to load the value. Below, accessing .cover_photo
emits a SELECT
statement to load its value:
>>> img_data = books[0].cover_photo
SELECT book.cover_photo AS book_cover_photo
FROM book
WHERE book.id = ?
[...] (1,)
Lazy loads are always emitted using the Session
to which the
object is in the persistent state. If the object is detached
from any Session
, the operation fails, raising an exception.
As an alternative to lazy loading on access, deferred columns may also be
configured to raise an informative exception when accessed, regardless of their
attachment state. When using the load_only()
construct, this
may be indicated using the load_only.raiseload
parameter.
See the section Using raiseload to prevent deferred column loads for
background and examples.
Tip
as noted elsewhere, lazy loading is not available when using Asynchronous I/O (asyncio).
Using load_only()
with multiple entities¶
load_only()
limits itself to the single entity that is referred
towards in its list of attributes (passing a list of attributes that span more
than a single entity is currently disallowed). In the example below, the given
load_only()
option applies only to the Book
entity. The User
entity that’s also selected is not affected; within the resulting SELECT
statement, all columns for user_account
are present, whereas only
book.id
and book.title
are present for the book
table:
>>> stmt = select(User, Book).join_from(User, Book).options(load_only(Book.title))
>>> print(stmt)
SELECT user_account.id, user_account.name, user_account.fullname,
book.id AS id_1, book.title
FROM user_account JOIN book ON user_account.id = book.owner_id
If we wanted to apply load_only()
options to both User
and
Book
, we would make use of two separate options:
>>> stmt = (
... select(User, Book)
... .join_from(User, Book)
... .options(load_only(User.name), load_only(Book.title))
... )
>>> print(stmt)
SELECT user_account.id, user_account.name, book.id AS id_1, book.title
FROM user_account JOIN book ON user_account.id = book.owner_id
Using load_only()
on related objects and collections¶
When using relationship loaders to control the
loading of related objects, the
Load.load_only()
method of any relationship loader may be used
to apply load_only()
rules to columns on the sub-entity. In the example below,
selectinload()
is used to load the related books
collection
on each User
object. By applying Load.load_only()
to the resulting
option object, when objects are loaded for the relationship, the
SELECT emitted will only refer to the title
column
in addition to primary key column:
>>> from sqlalchemy.orm import selectinload
>>> stmt = select(User).options(selectinload(User.books).load_only(Book.title))
>>> for user in session.scalars(stmt):
... print(f"{user.fullname} {[b.title for b in user.books]}")
SELECT user_account.id, user_account.name, user_account.fullname
FROM user_account
[...] ()
SELECT book.owner_id AS book_owner_id, book.id AS book_id, book.title AS book_title
FROM book
WHERE book.owner_id IN (?, ?)
[...] (1, 2)
Spongebob Squarepants ['100 Years of Krabby Patties', 'Sea Catch 22', 'The Sea Grapes of Wrath']
Sandy Cheeks ['A Nut Like No Other', 'Geodesic Domes: A Retrospective', 'Rocketry for Squirrels']
load_only()
may also be applied to sub-entities without needing
to state the style of loading to use for the relationship itself. If we didn’t
want to change the default loading style of User.books
but still apply
load only rules to Book
, we would link using the defaultload()
option, which in this case will retain the default relationship loading
style of "lazy"
, and applying our custom load_only()
rule to
the SELECT statement emitted for each User.books
collection:
>>> from sqlalchemy.orm import defaultload
>>> stmt = select(User).options(defaultload(User.books).load_only(Book.title))
>>> for user in session.scalars(stmt):
... print(f"{user.fullname} {[b.title for b in user.books]}")
SELECT user_account.id, user_account.name, user_account.fullname
FROM user_account
[...] ()
SELECT book.id AS book_id, book.title AS book_title
FROM book
WHERE ? = book.owner_id
[...] (1,)
Spongebob Squarepants ['100 Years of Krabby Patties', 'Sea Catch 22', 'The Sea Grapes of Wrath']
SELECT book.id AS book_id, book.title AS book_title
FROM book
WHERE ? = book.owner_id
[...] (2,)
Sandy Cheeks ['A Nut Like No Other', 'Geodesic Domes: A Retrospective', 'Rocketry for Squirrels']
Using defer()
to omit specific columns¶
The defer()
loader option is a more fine grained alternative to
load_only()
, which allows a single specific column to be marked as
“dont load”. In the example below, defer()
is applied directly to the
.cover_photo
column, leaving the behavior of all other columns
unchanged:
>>> from sqlalchemy.orm import defer
>>> stmt = select(Book).where(Book.owner_id == 2).options(defer(Book.cover_photo))
>>> books = session.scalars(stmt).all()
SELECT book.id, book.owner_id, book.title, book.summary
FROM book
WHERE book.owner_id = ?
[...] (2,)
>>> for book in books:
... print(f"{book.title}: {book.summary}")
A Nut Like No Other: some long summary
Geodesic Domes: A Retrospective: another long summary
Rocketry for Squirrels: yet another summary
As is the case with load_only()
, unloaded columns by default
will load themselves when accessed using lazy loading:
>>> img_data = books[0].cover_photo
SELECT book.cover_photo AS book_cover_photo
FROM book
WHERE book.id = ?
[...] (4,)
Multiple defer()
options may be used in one statement in order to
mark several columns as deferred.
As is the case with load_only()
, the defer()
option
also includes the ability to have a deferred attribute raise an exception on
access rather than lazy loading. This is illustrated in the section
Using raiseload to prevent deferred column loads.
Using raiseload to prevent deferred column loads¶
When using the load_only()
or defer()
loader options,
attributes marked as deferred on an object have the default behavior that when
first accessed, a SELECT statement will be emitted within the current
transaction in order to load their value. It is often necessary to prevent this
load from occurring, and instead raise an exception when the attribute is
accessed, indicating that the need to query the database for this column was
not expected. A typical scenario is an operation where objects are loaded with
all the columns that are known to be required for the operation to proceed,
which are then passed onto a view layer. Any further SQL operations that emit
within the view layer should be caught, so that the up-front loading operation
can be adjusted to accommodate for that additional data up front, rather than
incurring additional lazy loading.
For this use case the defer()
and load_only()
options
include a boolean parameter defer.raiseload
, which when set to
True
will cause the affected attributes to raise on access. In the
example below, the deferred column .cover_photo
will disallow attribute
access:
>>> book = session.scalar(
... select(Book).options(defer(Book.cover_photo, raiseload=True)).where(Book.id == 4)
... )
SELECT book.id, book.owner_id, book.title, book.summary
FROM book
WHERE book.id = ?
[...] (4,)
>>> book.cover_photo
Traceback (most recent call last):
...
sqlalchemy.exc.InvalidRequestError: 'Book.cover_photo' is not available due to raiseload=True
When using load_only()
to name a specific set of non-deferred
columns, raiseload
behavior may be applied to the remaining columns
using the load_only.raiseload
parameter, which will be applied
to all deferred attributes:
>>> session.expunge_all()
>>> book = session.scalar(
... select(Book).options(load_only(Book.title, raiseload=True)).where(Book.id == 5)
... )
SELECT book.id, book.title
FROM book
WHERE book.id = ?
[...] (5,)
>>> book.summary
Traceback (most recent call last):
...
sqlalchemy.exc.InvalidRequestError: 'Book.summary' is not available due to raiseload=True
Note
It is not yet possible to mix load_only()
and defer()
options which refer to the same entity together in one statement in order
to change the raiseload
behavior of certain attributes; currently,
doing so will produce undefined loading behavior of attributes.
See also
The defer.raiseload
feature is the column-level version
of the same “raiseload” feature that’s available for relationships.
For “raiseload” with relationships, see
Preventing unwanted lazy loads using raiseload in the
Relationship Loading Techniques section of this guide.
Configuring Column Deferral on Mappings¶
The functionality of defer()
is available as a default behavior for
mapped columns, as may be appropriate for columns that should not be loaded
unconditionally on every query. To configure, use the
mapped_column.deferred
parameter of
mapped_column()
. The example below illustrates a mapping for
Book
which applies default column deferral to the summary
and
cover_photo
columns:
>>> class Book(Base):
... __tablename__ = "book"
... id: Mapped[int] = mapped_column(primary_key=True)
... owner_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"))
... title: Mapped[str]
... summary: Mapped[str] = mapped_column(Text, deferred=True)
... cover_photo: Mapped[bytes] = mapped_column(LargeBinary, deferred=True)
...
... def __repr__(self) -> str:
... return f"Book(id={self.id!r}, title={self.title!r})"
Using the above mapping, queries against Book
will automatically not
include the summary
and cover_photo
columns:
>>> book = session.scalar(select(Book).where(Book.id == 2))
SELECT book.id, book.owner_id, book.title
FROM book
WHERE book.id = ?
[...] (2,)
As is the case with all deferral, the default behavior when deferred attributes on the loaded object are first accessed is that they will lazy load their value:
>>> img_data = book.cover_photo
SELECT book.cover_photo AS book_cover_photo
FROM book
WHERE book.id = ?
[...] (2,)
As is the case with the defer()
and load_only()
loader options, mapper level deferral also includes an option for raiseload
behavior to occur, rather than lazy loading, when no other options are
present in a statement. This allows a mapping where certain columns
will not load by default and will also never load lazily without explicit
directives used in a statement. See the section
Configuring mapper-level “raiseload” behavior for background on how to
configure and use this behavior.
Using deferred()
for imperative mappers, mapped SQL expressions¶
The deferred()
function is the earlier, more general purpose
“deferred column” mapping directive that precedes the introduction of the
mapped_column()
construct in SQLAlchemy.
deferred()
is used when configuring ORM mappers, and accepts
arbitrary SQL expressions or
Column
objects. As such it’s suitable to be used with
non-declarative imperative mappings, passing it
to the map_imperatively.properties
dictionary:
from sqlalchemy import Blob
from sqlalchemy import Column
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import String
from sqlalchemy import Table
from sqlalchemy import Text
from sqlalchemy.orm import registry
mapper_registry = registry()
book_table = Table(
"book",
mapper_registry.metadata,
Column("id", Integer, primary_key=True),
Column("title", String(50)),
Column("summary", Text),
Column("cover_image", Blob),
)
class Book:
pass
mapper_registry.map_imperatively(
Book,
book_table,
properties={
"summary": deferred(book_table.c.summary),
"cover_image": deferred(book_table.c.cover_image),
},
)
deferred()
may also be used in place of column_property()
when mapped SQL expressions should be loaded on a deferred basis:
from sqlalchemy.orm import deferred
class User(Base):
__tablename__ = "user"
id: Mapped[int] = mapped_column(primary_key=True)
firstname: Mapped[str] = mapped_column()
lastname: Mapped[str] = mapped_column()
fullname: Mapped[str] = deferred(firstname + " " + lastname)
See also
Using column_property - in the section SQL Expressions as Mapped Attributes
Applying Load, Persistence and Mapping Options for Imperative Table Columns - in the section Table Configuration with Declarative
Using undefer()
to “eagerly” load deferred columns¶
With columns configured on mappings to defer by default, the
undefer()
option will cause any column that is normally deferred
to be undeferred, that is, to load up front with all the other columns
of the mapping. For example we may apply undefer()
to the
Book.summary
column, which is indicated in the previous mapping
as deferred:
>>> from sqlalchemy.orm import undefer
>>> book = session.scalar(select(Book).where(Book.id == 2).options(undefer(Book.summary)))
SELECT book.id, book.owner_id, book.title, book.summary
FROM book
WHERE book.id = ?
[...] (2,)
The Book.summary
column was now eagerly loaded, and may be accessed without
additional SQL being emitted:
>>> print(book.summary)
another long summary
Loading deferred columns in groups¶
Normally when a column is mapped with mapped_column(deferred=True)
, when
the deferred attribute is accessed on an object, SQL will be emitted to load
only that specific column and no others, even if the mapping has other columns
that are also marked as deferred. In the common case that the deferred
attribute is part of a group of attributes that should all load at once, rather
than emitting SQL for each attribute individually, the
mapped_column.deferred_group
parameter may be used, which
accepts an arbitrary string which will define a common group of columns to be
undeferred:
>>> class Book(Base):
... __tablename__ = "book"
... id: Mapped[int] = mapped_column(primary_key=True)
... owner_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"))
... title: Mapped[str]
... summary: Mapped[str] = mapped_column(
... Text, deferred=True, deferred_group="book_attrs"
... )
... cover_photo: Mapped[bytes] = mapped_column(
... LargeBinary, deferred=True, deferred_group="book_attrs"
... )
...
... def __repr__(self) -> str:
... return f"Book(id={self.id!r}, title={self.title!r})"
Using the above mapping, accessing either summary
or cover_photo
will load both columns at once using just one SELECT statement:
>>> book = session.scalar(select(Book).where(Book.id == 2))
SELECT book.id, book.owner_id, book.title
FROM book
WHERE book.id = ?
[...] (2,)
>>> img_data, summary = book.cover_photo, book.summary
SELECT book.summary AS book_summary, book.cover_photo AS book_cover_photo
FROM book
WHERE book.id = ?
[...] (2,)
Undeferring by group with undefer_group()
¶
If deferred columns are configured with mapped_column.deferred_group
as introduced in the preceding section, the
entire group may be indicated to load eagerly using the undefer_group()
option, passing the string name of the group to be eagerly loaded:
>>> from sqlalchemy.orm import undefer_group
>>> book = session.scalar(
... select(Book).where(Book.id == 2).options(undefer_group("book_attrs"))
... )
SELECT book.id, book.owner_id, book.title, book.summary, book.cover_photo
FROM book
WHERE book.id = ?
[...] (2,)
Both summary
and cover_photo
are available without additional loads:
>>> img_data, summary = book.cover_photo, book.summary
Undeferring on wildcards¶
Most ORM loader options accept a wildcard expression, indicated by
"*"
, which indicates that the option should be applied to all relevant
attributes. If a mapping has a series of deferred columns, all such
columns can be undeferred at once, without using a group name, by indicating
a wildcard:
>>> book = session.scalar(select(Book).where(Book.id == 3).options(undefer("*")))
SELECT book.id, book.owner_id, book.title, book.summary, book.cover_photo
FROM book
WHERE book.id = ?
[...] (3,)
Configuring mapper-level “raiseload” behavior¶
The “raiseload” behavior first introduced at Using raiseload to prevent deferred column loads may
also be applied as a default mapper-level behavior, using the
mapped_column.deferred_raiseload
parameter of
mapped_column()
. When using this parameter, the affected columns
will raise on access in all cases unless explicitly “undeferred” using
undefer()
or load_only()
at query time:
>>> class Book(Base):
... __tablename__ = "book"
... id: Mapped[int] = mapped_column(primary_key=True)
... owner_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"))
... title: Mapped[str]
... summary: Mapped[str] = mapped_column(Text, deferred=True, deferred_raiseload=True)
... cover_photo: Mapped[bytes] = mapped_column(
... LargeBinary, deferred=True, deferred_raiseload=True
... )
...
... def __repr__(self) -> str:
... return f"Book(id={self.id!r}, title={self.title!r})"
Using the above mapping, the .summary
and .cover_photo
columns are
by default not loadable:
>>> book = session.scalar(select(Book).where(Book.id == 2))
SELECT book.id, book.owner_id, book.title
FROM book
WHERE book.id = ?
[...] (2,)
>>> book.summary
Traceback (most recent call last):
...
sqlalchemy.exc.InvalidRequestError: 'Book.summary' is not available due to raiseload=True
Only by overriding their behavior at query time, typically using
undefer()
or undefer_group()
, or less commonly
defer()
, may the attributes be loaded. The example below applies
undefer('*')
to undefer all attributes, also making use of
Populate Existing to refresh the already-loaded object’s loader options:
>>> book = session.scalar(
... select(Book)
... .where(Book.id == 2)
... .options(undefer("*"))
... .execution_options(populate_existing=True)
... )
SELECT book.id, book.owner_id, book.title, book.summary, book.cover_photo
FROM book
WHERE book.id = ?
[...] (2,)
>>> book.summary
'another long summary'
Loading Arbitrary SQL Expressions onto Objects¶
As discussed Selecting ORM Entities and Attributes and elsewhere,
the select()
construct may be used to load arbitrary SQL expressions
in a result set. Such as if we wanted to issue a query that loads
User
objects, but also includes a count of how many books
each User
owned, we could use func.count(Book.id)
to add a “count”
column to a query which includes a JOIN to Book
as well as a GROUP BY
owner id. This will yield Row
objects that each contain two
entries, one for User
and one for func.count(Book.id)
:
>>> from sqlalchemy import func
>>> stmt = select(User, func.count(Book.id)).join_from(User, Book).group_by(Book.owner_id)
>>> for user, book_count in session.execute(stmt):
... print(f"Username: {user.name} Number of books: {book_count}")
SELECT user_account.id, user_account.name, user_account.fullname,
count(book.id) AS count_1
FROM user_account JOIN book ON user_account.id = book.owner_id
GROUP BY book.owner_id
[...] ()
Username: spongebob Number of books: 3
Username: sandy Number of books: 3
In the above example, the User
entity and the “book count” SQL expression
are returned separately. However, a popular use case is to produce a query that
will yield User
objects alone, which can be iterated for example using
Session.scalars()
, where the result of the func.count(Book.id)
SQL expression is applied dynamically to each User
entity. The end result
would be similar to the case where an arbitrary SQL expression were mapped to
the class using column_property()
, except that the SQL expression
can be modified at query time. For this use case SQLAlchemy provides the
with_expression()
loader option, which when combined with the mapper
level query_expression()
directive may produce this result.
To apply with_expression()
to a query, the mapped class must have
pre-configured an ORM mapped attribute using the query_expression()
directive; this directive will produce an attribute on the mapped
class that is suitable for receiving query-time SQL expressions. Below
we add a new attribute User.book_count
to User
. This ORM mapped attribute
is read-only and has no default value; accessing it on a loaded instance will
normally produce None
:
>>> from sqlalchemy.orm import query_expression
>>> class User(Base):
... __tablename__ = "user_account"
... id: Mapped[int] = mapped_column(primary_key=True)
... name: Mapped[str]
... fullname: Mapped[Optional[str]]
... book_count: Mapped[int] = query_expression()
...
... def __repr__(self) -> str:
... return f"User(id={self.id!r}, name={self.name!r}, fullname={self.fullname!r})"
With the User.book_count
attribute configured in our mapping, we may populate
it with data from a SQL expression using the
with_expression()
loader option to apply a custom SQL expression
to each User
object as it’s loaded:
>>> from sqlalchemy.orm import with_expression
>>> stmt = (
... select(User)
... .join_from(User, Book)
... .group_by(Book.owner_id)
... .options(with_expression(User.book_count, func.count(Book.id)))
... )
>>> for user in session.scalars(stmt):
... print(f"Username: {user.name} Number of books: {user.book_count}")
SELECT count(book.id) AS count_1, user_account.id, user_account.name,
user_account.fullname
FROM user_account JOIN book ON user_account.id = book.owner_id
GROUP BY book.owner_id
[...] ()
Username: spongebob Number of books: 3
Username: sandy Number of books: 3
Above, we moved our func.count(Book.id)
expression out of the columns
argument of the select()
construct and into the with_expression()
loader option. The ORM then considers this to be a special column load
option that’s applied dynamically to the statement.
The query_expression()
mapping has these caveats:
On an object where
with_expression()
were not used to populate the attribute, the attribute on an object instance will have the valueNone
, unless on the mapping thequery_expression.default_expr
parameter is set to a default SQL expression.The
with_expression()
value does not populate on an object that is already loaded, unless Populate Existing is used. The example below will not work, as theA
object is already loaded:# load the first A obj = session.scalars(select(A).order_by(A.id)).first() # load the same A with an option; expression will **not** be applied # to the already-loaded object obj = session.scalars(select(A).options(with_expression(A.expr, some_expr))).first()
To ensure the attribute is re-loaded on an existing object, use the Populate Existing execution option to ensure all columns are re-populated:
obj = session.scalars( select(A) .options(with_expression(A.expr, some_expr)) .execution_options(populate_existing=True) ).first()
The
with_expression()
SQL expression is lost when the object is expired. Once the object is expired, either viaSession.expire()
or via the expire_on_commit behavior ofSession.commit()
, the SQL expression and its value is no longer associated with the attribute and will returnNone
on subsequent access.with_expression()
, as an object loading option, only takes effect on the outermost part of a query and only for a query against a full entity, and not for arbitrary column selects, within subqueries, or the elements of a compound statement such as a UNION. See the next section Using with_expression() with UNIONs, other subqueries for an example.The mapped attribute cannot be applied to other parts of the query, such as the WHERE clause, the ORDER BY clause, and make use of the ad-hoc expression; that is, this won’t work:
# can't refer to A.expr elsewhere in the query stmt = ( select(A) .options(with_expression(A.expr, A.x + A.y)) .filter(A.expr > 5) .order_by(A.expr) )
The
A.expr
expression will resolve to NULL in the above WHERE clause and ORDER BY clause. To use the expression throughout the query, assign to a variable and use that:# assign desired expression up front, then refer to that in # the query a_expr = A.x + A.y stmt = ( select(A) .options(with_expression(A.expr, a_expr)) .filter(a_expr > 5) .order_by(a_expr) )
See also
The with_expression()
option is a special option used to
apply SQL expressions to mapped classes dynamically at query time.
For ordinary fixed SQL expressions configured on mappers,
see the section SQL Expressions as Mapped Attributes.
Using with_expression()
with UNIONs, other subqueries¶
The with_expression()
construct is an ORM loader option, and as
such may only be applied to the outermost level of a SELECT statement which
is to load a particular ORM entity. It does not have any effect if used
inside of a select()
that will then be used as a subquery or
as an element within a compound statement such as a UNION.
In order to use arbitrary SQL expressions in subqueries, normal Core-style
means of adding expressions should be used. To assemble a subquery-derived
expression onto the ORM entity’s query_expression()
attributes,
with_expression()
is used at the top layer of ORM object loading,
referencing the SQL expression within the subquery.
In the example below, two select()
constructs are used against
the ORM entity A
with an additional SQL expression labeled in
expr
, and combined using union_all()
. Then, at the topmost
layer, the A
entity is SELECTed from this UNION, using the
querying technique described at Selecting Entities from UNIONs and other set operations, adding an
option with with_expression()
to extract this SQL expression
onto newly loaded instances of A
:
>>> from sqlalchemy import union_all
>>> s1 = (
... select(User, func.count(Book.id).label("book_count"))
... .join_from(User, Book)
... .where(User.name == "spongebob")
... )
>>> s2 = (
... select(User, func.count(Book.id).label("book_count"))
... .join_from(User, Book)
... .where(User.name == "sandy")
... )
>>> union_stmt = union_all(s1, s2)
>>> orm_stmt = (
... select(User)
... .from_statement(union_stmt)
... .options(with_expression(User.book_count, union_stmt.selected_columns.book_count))
... )
>>> for user in session.scalars(orm_stmt):
... print(f"Username: {user.name} Number of books: {user.book_count}")
SELECT user_account.id, user_account.name, user_account.fullname, count(book.id) AS book_count
FROM user_account JOIN book ON user_account.id = book.owner_id
WHERE user_account.name = ?
UNION ALL
SELECT user_account.id, user_account.name, user_account.fullname, count(book.id) AS book_count
FROM user_account JOIN book ON user_account.id = book.owner_id
WHERE user_account.name = ?
[...] ('spongebob', 'sandy')
Username: spongebob Number of books: 3
Username: sandy Number of books: 3
Column Loading API¶
Object Name | Description |
---|---|
defer(key, *addl_attrs, [raiseload]) |
Indicate that the given column-oriented attribute should be deferred, e.g. not loaded until accessed. |
deferred(column, *additional_columns, [group, raiseload, comparator_factory, init, repr, default, default_factory, compare, kw_only, hash, active_history, expire_on_flush, info, doc]) |
Indicate a column-based mapped attribute that by default will not load unless accessed. |
load_only(*attrs, [raiseload]) |
Indicate that for a particular entity, only the given list of column-based attribute names should be loaded; all others will be deferred. |
query_expression([default_expr], *, [repr, compare, expire_on_flush, info, doc]) |
Indicate an attribute that populates from a query-time SQL expression. |
undefer(key, *addl_attrs) |
Indicate that the given column-oriented attribute should be undeferred, e.g. specified within the SELECT statement of the entity as a whole. |
undefer_group(name) |
Indicate that columns within the given deferred group name should be undeferred. |
with_expression(key, expression) |
Apply an ad-hoc SQL expression to a “deferred expression” attribute. |
- function sqlalchemy.orm.defer(key: Literal['*'] | QueryableAttribute[Any], *addl_attrs: Literal['*'] | QueryableAttribute[Any], raiseload: bool = False) → _AbstractLoad¶
Indicate that the given column-oriented attribute should be deferred, e.g. not loaded until accessed.
This function is part of the
Load
interface and supports both method-chained and standalone operation.e.g.:
from sqlalchemy.orm import defer session.query(MyClass).options( defer(MyClass.attribute_one), defer(MyClass.attribute_two) )
To specify a deferred load of an attribute on a related class, the path can be specified one token at a time, specifying the loading style for each link along the chain. To leave the loading style for a link unchanged, use
defaultload()
:session.query(MyClass).options( defaultload(MyClass.someattr).defer(RelatedClass.some_column) )
Multiple deferral options related to a relationship can be bundled at once using
Load.options()
:select(MyClass).options( defaultload(MyClass.someattr).options( defer(RelatedClass.some_column), defer(RelatedClass.some_other_column), defer(RelatedClass.another_column) ) )
- Parameters:
key¶ – Attribute to be deferred.
raiseload¶ – raise
InvalidRequestError
rather than lazy loading a value when the deferred attribute is accessed. Used to prevent unwanted SQL from being emitted.
New in version 1.4.
- function sqlalchemy.orm.deferred(column: _ORMColumnExprArgument[_T], *additional_columns: _ORMColumnExprArgument[Any], group: str | None = None, raiseload: bool = False, comparator_factory: Type[PropComparator[_T]] | None = None, init: _NoArg | bool = _NoArg.NO_ARG, repr: _NoArg | bool = _NoArg.NO_ARG, default: Any | None = _NoArg.NO_ARG, default_factory: _NoArg | Callable[[], _T] = _NoArg.NO_ARG, compare: _NoArg | bool = _NoArg.NO_ARG, kw_only: _NoArg | bool = _NoArg.NO_ARG, hash: _NoArg | bool | None = _NoArg.NO_ARG, active_history: bool = False, expire_on_flush: bool = True, info: _InfoType | None = None, doc: str | None = None) → MappedSQLExpression[_T]¶
Indicate a column-based mapped attribute that by default will not load unless accessed.
When using
mapped_column()
, the same functionality as that ofdeferred()
construct is provided by using themapped_column.deferred
parameter.- Parameters:
*columns¶ – columns to be mapped. This is typically a single
Column
object, however a collection is supported in order to support multiple columns mapped under the same attribute.raiseload¶ –
boolean, if True, indicates an exception should be raised if the load operation is to take place.
New in version 1.4.
Additional arguments are the same as that of
column_property()
.
- function sqlalchemy.orm.query_expression(default_expr: _ORMColumnExprArgument[_T] = <sqlalchemy.sql.elements.Null object>, *, repr: Union[_NoArg, bool] = _NoArg.NO_ARG, compare: Union[_NoArg, bool] = _NoArg.NO_ARG, expire_on_flush: bool = True, info: Optional[_InfoType] = None, doc: Optional[str] = None) → MappedSQLExpression[_T]¶
Indicate an attribute that populates from a query-time SQL expression.
- Parameters:
default_expr¶ – Optional SQL expression object that will be used in all cases if not assigned later with
with_expression()
.
New in version 1.2.
See also
Loading Arbitrary SQL Expressions onto Objects - background and usage examples
- function sqlalchemy.orm.load_only(*attrs: Literal['*'] | QueryableAttribute[Any], raiseload: bool = False) → _AbstractLoad¶
Indicate that for a particular entity, only the given list of column-based attribute names should be loaded; all others will be deferred.
This function is part of the
Load
interface and supports both method-chained and standalone operation.Example - given a class
User
, load only thename
andfullname
attributes:session.query(User).options(load_only(User.name, User.fullname))
Example - given a relationship
User.addresses -> Address
, specify subquery loading for theUser.addresses
collection, but on eachAddress
object load only theemail_address
attribute:session.query(User).options( subqueryload(User.addresses).load_only(Address.email_address) )
For a statement that has multiple entities, the lead entity can be specifically referred to using the
Load
constructor:stmt = ( select(User, Address) .join(User.addresses) .options( Load(User).load_only(User.name, User.fullname), Load(Address).load_only(Address.email_address), ) )
When used together with the populate_existing execution option only the attributes listed will be refreshed.
- Parameters:
*attrs¶ – Attributes to be loaded, all others will be deferred.
raiseload¶ –
raise
InvalidRequestError
rather than lazy loading a value when a deferred attribute is accessed. Used to prevent unwanted SQL from being emitted.New in version 2.0.
See also
Limiting which Columns Load with Column Deferral - in the ORM Querying Guide
- Parameters:
*attrs¶ – Attributes to be loaded, all others will be deferred.
raiseload¶ –
raise
InvalidRequestError
rather than lazy loading a value when a deferred attribute is accessed. Used to prevent unwanted SQL from being emitted.New in version 2.0.
- function sqlalchemy.orm.undefer(key: Literal['*'] | QueryableAttribute[Any], *addl_attrs: Literal['*'] | QueryableAttribute[Any]) → _AbstractLoad¶
Indicate that the given column-oriented attribute should be undeferred, e.g. specified within the SELECT statement of the entity as a whole.
The column being undeferred is typically set up on the mapping as a
deferred()
attribute.This function is part of the
Load
interface and supports both method-chained and standalone operation.Examples:
# undefer two columns session.query(MyClass).options( undefer(MyClass.col1), undefer(MyClass.col2) ) # undefer all columns specific to a single class using Load + * session.query(MyClass, MyOtherClass).options( Load(MyClass).undefer("*") ) # undefer a column on a related object select(MyClass).options( defaultload(MyClass.items).undefer(MyClass.text) )
- Parameters:
key¶ – Attribute to be undeferred.
- function sqlalchemy.orm.undefer_group(name: str) → _AbstractLoad¶
Indicate that columns within the given deferred group name should be undeferred.
The columns being undeferred are set up on the mapping as
deferred()
attributes and include a “group” name.E.g:
session.query(MyClass).options(undefer_group("large_attrs"))
To undefer a group of attributes on a related entity, the path can be spelled out using relationship loader options, such as
defaultload()
:select(MyClass).options( defaultload("someattr").undefer_group("large_attrs") )
See also
Limiting which Columns Load with Column Deferral - in the ORM Querying Guide
- function sqlalchemy.orm.with_expression(key: _AttrType, expression: _ColumnExpressionArgument[Any]) → _AbstractLoad¶
Apply an ad-hoc SQL expression to a “deferred expression” attribute.
This option is used in conjunction with the
query_expression()
mapper-level construct that indicates an attribute which should be the target of an ad-hoc SQL expression.E.g.:
stmt = select(SomeClass).options( with_expression(SomeClass.x_y_expr, SomeClass.x + SomeClass.y) )
New in version 1.2.
See also
Loading Arbitrary SQL Expressions onto Objects - background and usage examples
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