SQLAlchemy 2.1 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¶
- Summary of Relationship Loading Styles
- Configuring Loader Strategies at Mapping Time
- Relationship Loading with Loader Options
- Lazy Loading
- Joined Eager Loading
- Select IN loading
- Subquery Eager Loading
- What Kind of Loading to Use ?
- Polymorphic Eager Loading
- Wildcard Loading Strategies
- Routing Explicit Joins/Statements into Eagerly Loaded Collections
- Relationship Loader API
contains_eager()
defaultload()
immediateload()
joinedload()
lazyload()
Load
Load.contains_eager()
Load.defaultload()
Load.defer()
Load.get_children()
Load.immediateload()
Load.inherit_cache
Load.joinedload()
Load.lazyload()
Load.load_only()
Load.noload()
Load.options()
Load.process_compile_state()
Load.process_compile_state_replaced_entities()
Load.propagate_to_loaders
Load.raiseload()
Load.selectin_polymorphic()
Load.selectinload()
Load.subqueryload()
Load.undefer()
Load.undefer_group()
Load.with_expression()
noload()
raiseload()
selectinload()
subqueryload()
- ORM API Features for Querying
- Legacy Query API
- Using the Session
- Events and Internals
- ORM Extensions
- ORM Examples
Project Versions
- Previous: Column Loading Options
- Next: ORM API Features for Querying
- Up: Home
- On this page:
- Relationship Loading Techniques
- Summary of Relationship Loading Styles
- Configuring Loader Strategies at Mapping Time
- Relationship Loading with Loader Options
- Lazy Loading
- Joined Eager Loading
- Select IN loading
- Subquery Eager Loading
- What Kind of Loading to Use ?
- Polymorphic Eager Loading
- Wildcard Loading Strategies
- Routing Explicit Joins/Statements into Eagerly Loaded Collections
- Relationship Loader API
contains_eager()
defaultload()
immediateload()
joinedload()
lazyload()
Load
Load.contains_eager()
Load.defaultload()
Load.defer()
Load.get_children()
Load.immediateload()
Load.inherit_cache
Load.joinedload()
Load.lazyload()
Load.load_only()
Load.noload()
Load.options()
Load.process_compile_state()
Load.process_compile_state_replaced_entities()
Load.propagate_to_loaders
Load.raiseload()
Load.selectin_polymorphic()
Load.selectinload()
Load.subqueryload()
Load.undefer()
Load.undefer_group()
Load.with_expression()
noload()
raiseload()
selectinload()
subqueryload()
Relationship Loading Techniques¶
About this Document
This section presents an in-depth view of how to load related objects. Readers should be familiar with Relationship Configuration and basic use.
Most examples here assume the “User/Address” mapping setup similar to the one illustrated at setup for selects.
A big part of SQLAlchemy is providing a wide range of control over how related
objects get loaded when querying. By “related objects” we refer to collections
or scalar associations configured on a mapper using relationship()
.
This behavior can be configured at mapper construction time using the
relationship.lazy
parameter to the relationship()
function, as well as by using ORM loader options with
the Select
construct.
The loading of relationships falls into three categories; lazy loading, eager loading, and no loading. Lazy loading refers to objects that are returned from a query without the related objects loaded at first. When the given collection or reference is first accessed on a particular object, an additional SELECT statement is emitted such that the requested collection is loaded.
Eager loading refers to objects returned from a query with the related collection or scalar reference already loaded up front. The ORM achieves this either by augmenting the SELECT statement it would normally emit with a JOIN to load in related rows simultaneously, or by emitting additional SELECT statements after the primary one to load collections or scalar references at once.
“No” loading refers to the disabling of loading on a given relationship, either that the attribute is empty and is just never loaded, or that it raises an error when it is accessed, in order to guard against unwanted lazy loads.
Summary of Relationship Loading Styles¶
The primary forms of relationship loading are:
lazy loading - available via
lazy='select'
or thelazyload()
option, this is the form of loading that emits a SELECT statement at attribute access time to lazily load a related reference on a single object at a time. Lazy loading is the default loading style for allrelationship()
constructs that don’t otherwise indicate therelationship.lazy
option. Lazy loading is detailed at Lazy Loading.select IN loading - available via
lazy='selectin'
or theselectinload()
option, this form of loading emits a second (or more) SELECT statement which assembles the primary key identifiers of the parent objects into an IN clause, so that all members of related collections / scalar references are loaded at once by primary key. Select IN loading is detailed at Select IN loading.joined loading - available via
lazy='joined'
or thejoinedload()
option, this form of loading applies a JOIN to the given SELECT statement so that related rows are loaded in the same result set. Joined eager loading is detailed at Joined Eager Loading.raise loading - available via
lazy='raise'
,lazy='raise_on_sql'
, or theraiseload()
option, this form of loading is triggered at the same time a lazy load would normally occur, except it raises an ORM exception in order to guard against the application making unwanted lazy loads. An introduction to raise loading is at Preventing unwanted lazy loads using raiseload.subquery loading - available via
lazy='subquery'
or thesubqueryload()
option, this form of loading emits a second SELECT statement which re-states the original query embedded inside of a subquery, then JOINs that subquery to the related table to be loaded to load all members of related collections / scalar references at once. Subquery eager loading is detailed at Subquery Eager Loading.write only loading - available via
lazy='write_only'
, or by annotating the left side of theRelationship
object using theWriteOnlyMapped
annotation. This collection-only loader style produces an alternative attribute instrumentation that never implicitly loads records from the database, instead only allowingWriteOnlyCollection.add()
,WriteOnlyCollection.add_all()
andWriteOnlyCollection.remove()
methods. Querying the collection is performed by invoking a SELECT statement which is constructed using theWriteOnlyCollection.select()
method. Write only loading is discussed at Write Only Relationships.dynamic loading - available via
lazy='dynamic'
, or by annotating the left side of theRelationship
object using theDynamicMapped
annotation. This is a legacy collection-only loader style which produces aQuery
object when the collection is accessed, allowing custom SQL to be emitted against the collection’s contents. However, dynamic loaders will implicitly iterate the underlying collection in various circumstances which makes them less useful for managing truly large collections. Dynamic loaders are superseded by “write only” collections, which will prevent the underlying collection from being implicitly loaded under any circumstances. Dynamic loaders are discussed at Dynamic Relationship Loaders.
Configuring Loader Strategies at Mapping Time¶
The loader strategy for a particular relationship can be configured
at mapping time to take place in all cases where an object of the mapped
type is loaded, in the absence of any query-level options that modify it.
This is configured using the relationship.lazy
parameter to
relationship()
; common values for this parameter
include select
, selectin
and joined
.
The example below illustrates the relationship example at
One To Many, configuring the Parent.children
relationship to use Select IN loading when a SELECT
statement for Parent
objects is emitted:
from typing import List
from sqlalchemy import ForeignKey
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy.orm import Mapped
from sqlalchemy.orm import mapped_column
from sqlalchemy.orm import relationship
class Base(DeclarativeBase):
pass
class Parent(Base):
__tablename__ = "parent"
id: Mapped[int] = mapped_column(primary_key=True)
children: Mapped[List["Child"]] = relationship(lazy="selectin")
class Child(Base):
__tablename__ = "child"
id: Mapped[int] = mapped_column(primary_key=True)
parent_id: Mapped[int] = mapped_column(ForeignKey("parent.id"))
Above, whenever a collection of Parent
objects are loaded, each
Parent
will also have its children
collection populated, using
the "selectin"
loader strategy that emits a second query.
The default value of the relationship.lazy
argument is
"select"
, which indicates Lazy Loading.
Relationship Loading with Loader Options¶
The other, and possibly more common way to configure loading strategies
is to set them up on a per-query basis against specific attributes using the
Select.options()
method. Very detailed
control over relationship loading is available using loader options;
the most common are
joinedload()
, selectinload()
and lazyload()
. The option accepts a class-bound attribute
referring to the specific class/attribute that should be targeted:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
# set children to load lazily
stmt = select(Parent).options(lazyload(Parent.children))
from sqlalchemy.orm import joinedload
# set children to load eagerly with a join
stmt = select(Parent).options(joinedload(Parent.children))
The loader options can also be “chained” using method chaining to specify how loading should occur further levels deep:
from sqlalchemy import select
from sqlalchemy.orm import joinedload
stmt = select(Parent).options(
joinedload(Parent.children).subqueryload(Child.subelements)
)
Chained loader options can be applied against a “lazy” loaded collection. This means that when a collection or association is lazily loaded upon access, the specified option will then take effect:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
stmt = select(Parent).options(lazyload(Parent.children).subqueryload(Child.subelements))
Above, the query will return Parent
objects without the children
collections loaded. When the children
collection on a particular
Parent
object is first accessed, it will lazy load the related
objects, but additionally apply eager loading to the subelements
collection on each member of children
.
Adding Criteria to loader options¶
The relationship attributes used to indicate loader options include the
ability to add additional filtering criteria to the ON clause of the join
that’s created, or to the WHERE criteria involved, depending on the loader
strategy. This can be achieved using the PropComparator.and_()
method which will pass through an option such that loaded results are limited
to the given filter criteria:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
stmt = select(A).options(lazyload(A.bs.and_(B.id > 5)))
When using limiting criteria, if a particular collection is already loaded it won’t be refreshed; to ensure the new criteria takes place, apply the Populate Existing execution option:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
stmt = (
select(A)
.options(lazyload(A.bs.and_(B.id > 5)))
.execution_options(populate_existing=True)
)
In order to add filtering criteria to all occurrences of an entity throughout
a query, regardless of loader strategy or where it occurs in the loading
process, see the with_loader_criteria()
function.
New in version 1.4.
Specifying Sub-Options with Load.options()¶
Using method chaining, the loader style of each link in the path is explicitly
stated. To navigate along a path without changing the existing loader style
of a particular attribute, the defaultload()
method/function may be used:
from sqlalchemy import select
from sqlalchemy.orm import defaultload
stmt = select(A).options(defaultload(A.atob).joinedload(B.btoc))
A similar approach can be used to specify multiple sub-options at once, using
the Load.options()
method:
from sqlalchemy import select
from sqlalchemy.orm import defaultload
from sqlalchemy.orm import joinedload
stmt = select(A).options(
defaultload(A.atob).options(joinedload(B.btoc), joinedload(B.btod))
)
See also
Using load_only() on related objects and collections - illustrates examples of combining relationship and column-oriented loader options.
Note
The loader options applied to an object’s lazy-loaded collections are “sticky” to specific object instances, meaning they will persist upon collections loaded by that specific object for as long as it exists in memory. For example, given the previous example:
stmt = select(Parent).options(lazyload(Parent.children).subqueryload(Child.subelements))
if the children
collection on a particular Parent
object loaded by
the above query is expired (such as when a Session
object’s
transaction is committed or rolled back, or Session.expire_all()
is
used), when the Parent.children
collection is next accessed in order to
re-load it, the Child.subelements
collection will again be loaded using
subquery eager loading. This stays the case even if the above Parent
object is accessed from a subsequent query that specifies a different set of
options. To change the options on an existing object without expunging it
and re-loading, they must be set explicitly in conjunction using the
Populate Existing execution option:
# change the options on Parent objects that were already loaded
stmt = (
select(Parent)
.execution_options(populate_existing=True)
.options(lazyload(Parent.children).lazyload(Child.subelements))
.all()
)
If the objects loaded above are fully cleared from the Session
,
such as due to garbage collection or that Session.expunge_all()
were used, the “sticky” options will also be gone and the newly created
objects will make use of new options if loaded again.
A future SQLAlchemy release may add more alternatives to manipulating the loader options on already-loaded objects.
Lazy Loading¶
By default, all inter-object relationships are lazy loading. The scalar or
collection attribute associated with a relationship()
contains a trigger which fires the first time the attribute is accessed. This
trigger typically issues a SQL call at the point of access
in order to load the related object or objects:
>>> spongebob.addresses
SELECT
addresses.id AS addresses_id,
addresses.email_address AS addresses_email_address,
addresses.user_id AS addresses_user_id
FROM addresses
WHERE ? = addresses.user_id
[5]
[<Address(u'spongebob@google.com')>, <Address(u'j25@yahoo.com')>]
The one case where SQL is not emitted is for a simple many-to-one relationship, when
the related object can be identified by its primary key alone and that object is already
present in the current Session
. For this reason, while lazy loading
can be expensive for related collections, in the case that one is loading
lots of objects with simple many-to-ones against a relatively small set of
possible target objects, lazy loading may be able to refer to these objects locally
without emitting as many SELECT statements as there are parent objects.
This default behavior of “load upon attribute access” is known as “lazy” or “select” loading - the name “select” because a “SELECT” statement is typically emitted when the attribute is first accessed.
Lazy loading can be enabled for a given attribute that is normally
configured in some other way using the lazyload()
loader option:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
# force lazy loading for an attribute that is set to
# load some other way normally
stmt = select(User).options(lazyload(User.addresses))
Preventing unwanted lazy loads using raiseload¶
The lazyload()
strategy produces an effect that is one of the most
common issues referred to in object relational mapping; the
N plus one problem, which states that for any N objects loaded,
accessing their lazy-loaded attributes means there will be N+1 SELECT
statements emitted. In SQLAlchemy, the usual mitigation for the N+1 problem
is to make use of its very capable eager load system. However, eager loading
requires that the attributes which are to be loaded be specified with the
Select
up front. The problem of code that may access other attributes
that were not eagerly loaded, where lazy loading is not desired, may be
addressed using the raiseload()
strategy; this loader strategy
replaces the behavior of lazy loading with an informative error being
raised:
from sqlalchemy import select
from sqlalchemy.orm import raiseload
stmt = select(User).options(raiseload(User.addresses))
Above, a User
object loaded from the above query will not have
the .addresses
collection loaded; if some code later on attempts to
access this attribute, an ORM exception is raised.
raiseload()
may be used with a so-called “wildcard” specifier to
indicate that all relationships should use this strategy. For example,
to set up only one attribute as eager loading, and all the rest as raise:
from sqlalchemy import select
from sqlalchemy.orm import joinedload
from sqlalchemy.orm import raiseload
stmt = select(Order).options(joinedload(Order.items), raiseload("*"))
The above wildcard will apply to all relationships not just on Order
besides items
, but all those on the Item
objects as well. To set up
raiseload()
for only the Order
objects, specify a full
path with Load
:
from sqlalchemy import select
from sqlalchemy.orm import joinedload
from sqlalchemy.orm import Load
stmt = select(Order).options(joinedload(Order.items), Load(Order).raiseload("*"))
Conversely, to set up the raise for just the Item
objects:
stmt = select(Order).options(joinedload(Order.items).raiseload("*"))
The raiseload()
option applies only to relationship attributes. For
column-oriented attributes, the defer()
option supports the
defer.raiseload
option which works in the same way.
Tip
The “raiseload” strategies do not apply
within the unit of work flush process. That means if the
Session.flush()
process needs to load a collection in order
to finish its work, it will do so while bypassing any raiseload()
directives.
Joined Eager Loading¶
Joined eager loading is the oldest style of eager loading included with the SQLAlchemy ORM. It works by connecting a JOIN (by default a LEFT OUTER join) to the SELECT statement emitted, and populates the target scalar/collection from the same result set as that of the parent.
At the mapping level, this looks like:
class Address(Base):
# ...
user: Mapped[User] = relationship(lazy="joined")
Joined eager loading is usually applied as an option to a query, rather than
as a default loading option on the mapping, in particular when used for
collections rather than many-to-one-references. This is achieved
using the joinedload()
loader option:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import joinedload
>>> stmt = select(User).options(joinedload(User.addresses)).filter_by(name="spongebob")
>>> spongebob = session.scalars(stmt).unique().all()
SELECT
addresses_1.id AS addresses_1_id,
addresses_1.email_address AS addresses_1_email_address,
addresses_1.user_id AS addresses_1_user_id,
users.id AS users_id, users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
LEFT OUTER JOIN addresses AS addresses_1
ON users.id = addresses_1.user_id
WHERE users.name = ?
['spongebob']
Tip
When including joinedload()
in reference to a one-to-many or
many-to-many collection, the Result.unique()
method must be
applied to the returned result, which will uniquify the incoming rows by
primary key that otherwise are multiplied out by the join. The ORM will
raise an error if this is not present.
This is not automatic in modern SQLAlchemy, as it changes the behavior
of the result set to return fewer ORM objects than the statement would
normally return in terms of number of rows. Therefore SQLAlchemy keeps
the use of Result.unique()
explicit, so there’s no ambiguity
that the returned objects are being uniqified on primary key.
The JOIN emitted by default is a LEFT OUTER JOIN, to allow for a lead object
that does not refer to a related row. For an attribute that is guaranteed
to have an element, such as a many-to-one
reference to a related object where the referencing foreign key is NOT NULL,
the query can be made more efficient by using an inner join; this is available
at the mapping level via the relationship.innerjoin
flag:
class Address(Base):
# ...
user_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
user: Mapped[User] = relationship(lazy="joined", innerjoin=True)
At the query option level, via the joinedload.innerjoin
flag:
from sqlalchemy import select
from sqlalchemy.orm import joinedload
stmt = select(Address).options(joinedload(Address.user, innerjoin=True))
The JOIN will right-nest itself when applied in a chain that includes an OUTER JOIN:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import joinedload
>>> stmt = select(User).options(
... joinedload(User.addresses).joinedload(Address.widgets, innerjoin=True)
... )
>>> results = session.scalars(stmt).unique().all()
SELECT
widgets_1.id AS widgets_1_id,
widgets_1.name AS widgets_1_name,
addresses_1.id AS addresses_1_id,
addresses_1.email_address AS addresses_1_email_address,
addresses_1.user_id AS addresses_1_user_id,
users.id AS users_id, users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
LEFT OUTER JOIN (
addresses AS addresses_1 JOIN widgets AS widgets_1 ON
addresses_1.widget_id = widgets_1.id
) ON users.id = addresses_1.user_id
Tip
If using database row locking techniques when emitting the SELECT,
meaning the Select.with_for_update()
method is being used
to emit SELECT..FOR UPDATE, the joined table may be locked as well,
depending on the behavior of the backend in use. It’s not recommended
to use joined eager loading at the same time as SELECT..FOR UPDATE
for this reason.
The Zen of Joined Eager Loading¶
Since joined eager loading seems to have many resemblances to the use of
Select.join()
, it often produces confusion as to when and how it should
be used. It is critical to understand the distinction that while
Select.join()
is used to alter the results of a query, joinedload()
goes through great lengths to not alter the results of the query, and
instead hide the effects of the rendered join to only allow for related objects
to be present.
The philosophy behind loader strategies is that any set of loading schemes can
be applied to a particular query, and the results don’t change - only the
number of SQL statements required to fully load related objects and collections
changes. A particular query might start out using all lazy loads. After using
it in context, it might be revealed that particular attributes or collections
are always accessed, and that it would be more efficient to change the loader
strategy for these. The strategy can be changed with no other modifications
to the query, the results will remain identical, but fewer SQL statements would
be emitted. In theory (and pretty much in practice), nothing you can do to the
Select
would make it load a different set of primary or related
objects based on a change in loader strategy.
How joinedload()
in particular achieves this result of not impacting
entity rows returned in any way is that it creates an anonymous alias of the
joins it adds to your query, so that they can’t be referenced by other parts of
the query. For example, the query below uses joinedload()
to create a
LEFT OUTER JOIN from users
to addresses
, however the ORDER BY
added
against Address.email_address
is not valid - the Address
entity is not
named in the query:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import joinedload
>>> stmt = (
... select(User)
... .options(joinedload(User.addresses))
... .filter(User.name == "spongebob")
... .order_by(Address.email_address)
... )
>>> result = session.scalars(stmt).unique().all()
SELECT
addresses_1.id AS addresses_1_id,
addresses_1.email_address AS addresses_1_email_address,
addresses_1.user_id AS addresses_1_user_id,
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
LEFT OUTER JOIN addresses AS addresses_1
ON users.id = addresses_1.user_id
WHERE users.name = ?
ORDER BY addresses.email_address <-- this part is wrong !
['spongebob']
Above, ORDER BY addresses.email_address
is not valid since addresses
is not in the
FROM list. The correct way to load the User
records and order by email
address is to use Select.join()
:
>>> from sqlalchemy import select
>>> stmt = (
... select(User)
... .join(User.addresses)
... .filter(User.name == "spongebob")
... .order_by(Address.email_address)
... )
>>> result = session.scalars(stmt).unique().all()
SELECT
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
JOIN addresses ON users.id = addresses.user_id
WHERE users.name = ?
ORDER BY addresses.email_address
['spongebob']
The statement above is of course not the same as the previous one, in that the
columns from addresses
are not included in the result at all. We can add
joinedload()
back in, so that there are two joins - one is that which we
are ordering on, the other is used anonymously to load the contents of the
User.addresses
collection:
>>> stmt = (
... select(User)
... .join(User.addresses)
... .options(joinedload(User.addresses))
... .filter(User.name == "spongebob")
... .order_by(Address.email_address)
... )
>>> result = session.scalars(stmt).unique().all()
SELECT
addresses_1.id AS addresses_1_id,
addresses_1.email_address AS addresses_1_email_address,
addresses_1.user_id AS addresses_1_user_id,
users.id AS users_id, users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users JOIN addresses
ON users.id = addresses.user_id
LEFT OUTER JOIN addresses AS addresses_1
ON users.id = addresses_1.user_id
WHERE users.name = ?
ORDER BY addresses.email_address
['spongebob']
What we see above is that our usage of Select.join()
is to supply JOIN
clauses we’d like to use in subsequent query criterion, whereas our usage of
joinedload()
only concerns itself with the loading of the
User.addresses
collection, for each User
in the result. In this case,
the two joins most probably appear redundant - which they are. If we wanted to
use just one JOIN for collection loading as well as ordering, we use the
contains_eager()
option, described in Routing Explicit Joins/Statements into Eagerly Loaded Collections below. But
to see why joinedload()
does what it does, consider if we were
filtering on a particular Address
:
>>> stmt = (
... select(User)
... .join(User.addresses)
... .options(joinedload(User.addresses))
... .filter(User.name == "spongebob")
... .filter(Address.email_address == "someaddress@foo.com")
... )
>>> result = session.scalars(stmt).unique().all()
SELECT
addresses_1.id AS addresses_1_id,
addresses_1.email_address AS addresses_1_email_address,
addresses_1.user_id AS addresses_1_user_id,
users.id AS users_id, users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users JOIN addresses
ON users.id = addresses.user_id
LEFT OUTER JOIN addresses AS addresses_1
ON users.id = addresses_1.user_id
WHERE users.name = ? AND addresses.email_address = ?
['spongebob', 'someaddress@foo.com']
Above, we can see that the two JOINs have very different roles. One will match
exactly one row, that of the join of User
and Address
where
Address.email_address=='someaddress@foo.com'
. The other LEFT OUTER JOIN
will match all Address
rows related to User
, and is only used to
populate the User.addresses
collection, for those User
objects that are
returned.
By changing the usage of joinedload()
to another style of loading, we
can change how the collection is loaded completely independently of SQL used to
retrieve the actual User
rows we want. Below we change joinedload()
into selectinload()
:
>>> stmt = (
... select(User)
... .join(User.addresses)
... .options(selectinload(User.addresses))
... .filter(User.name == "spongebob")
... .filter(Address.email_address == "someaddress@foo.com")
... )
>>> result = session.scalars(stmt).all()
SELECT
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
JOIN addresses ON users.id = addresses.user_id
WHERE
users.name = ?
AND addresses.email_address = ?
['spongebob', 'someaddress@foo.com']
# ... selectinload() emits a SELECT in order
# to load all address records ...
When using joined eager loading, if the query contains a modifier that impacts the rows returned externally to the joins, such as when using DISTINCT, LIMIT, OFFSET or equivalent, the completed statement is first wrapped inside a subquery, and the joins used specifically for joined eager loading are applied to the subquery. SQLAlchemy’s joined eager loading goes the extra mile, and then ten miles further, to absolutely ensure that it does not affect the end result of the query, only the way collections and related objects are loaded, no matter what the format of the query is.
Select IN loading¶
In most cases, selectin loading is the most simple and efficient way to eagerly load collections of objects. The only scenario in which selectin eager loading is not feasible is when the model is using composite primary keys, and the backend database does not support tuples with IN, which currently includes SQL Server.
“Select IN” eager loading is provided using the "selectin"
argument to
relationship.lazy
or by using the selectinload()
loader
option. This style of loading emits a SELECT that refers to the primary key
values of the parent object, or in the case of a many-to-one
relationship to the those of the child objects, inside of an IN clause, in
order to load related associations:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import selectinload
>>> stmt = (
... select(User)
... .options(selectinload(User.addresses))
... .filter(or_(User.name == "spongebob", User.name == "ed"))
... )
>>> result = session.scalars(stmt).all()
SELECT
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
WHERE users.name = ? OR users.name = ?
('spongebob', 'ed')
SELECT
addresses.id AS addresses_id,
addresses.email_address AS addresses_email_address,
addresses.user_id AS addresses_user_id
FROM addresses
WHERE addresses.user_id IN (?, ?)
(5, 7)
Above, the second SELECT refers to addresses.user_id IN (5, 7)
, where the
“5” and “7” are the primary key values for the previous two User
objects loaded; after a batch of objects are completely loaded, their primary
key values are injected into the IN
clause for the second SELECT.
Because the relationship between User
and Address
has a simple
primary join condition and provides that the
primary key values for User
can be derived from Address.user_id
, the
statement has no joins or subqueries at all.
For simple many-to-one loads, a JOIN is also not needed as the foreign key value from the parent object is used:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import selectinload
>>> stmt = select(Address).options(selectinload(Address.user))
>>> result = session.scalars(stmt).all()
SELECT
addresses.id AS addresses_id,
addresses.email_address AS addresses_email_address,
addresses.user_id AS addresses_user_id
FROM addresses
SELECT
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
WHERE users.id IN (?, ?)
(1, 2)
Tip
by “simple” we mean that the relationship.primaryjoin
condition expresses an equality comparison between the primary key of the
“one” side and a straight foreign key of the “many” side, without any
additional criteria.
Select IN loading also supports many-to-many relationships, where it currently will JOIN across all three tables to match rows from one side to the other.
Things to know about this kind of loading include:
The strategy emits a SELECT for up to 500 parent primary key values at a time, as the primary keys are rendered into a large IN expression in the SQL statement. Some databases like Oracle have a hard limit on how large an IN expression can be, and overall the size of the SQL string shouldn’t be arbitrarily large.
As “selectin” loading relies upon IN, for a mapping with composite primary keys, it must use the “tuple” form of IN, which looks like
WHERE (table.column_a, table.column_b) IN ((?, ?), (?, ?), (?, ?))
. This syntax is not currently supported on SQL Server and for SQLite requires at least version 3.15. There is no special logic in SQLAlchemy to check ahead of time which platforms support this syntax or not; if run against a non-supporting platform, the database will return an error immediately. An advantage to SQLAlchemy just running the SQL out for it to fail is that if a particular database does start supporting this syntax, it will work without any changes to SQLAlchemy (as was the case with SQLite).
Subquery Eager Loading¶
Legacy Feature
The subqueryload()
eager loader is mostly legacy
at this point, superseded by the selectinload()
strategy
which is of much simpler design, more flexible with features such as
Yield Per, and emits more efficient SQL
statements in most cases. As subqueryload()
relies upon
re-interpreting the original SELECT statement, it may fail to work
efficiently when given very complex source queries.
subqueryload()
may continue to be useful for the specific
case of an eager loaded collection for objects that use composite primary
keys, on the Microsoft SQL Server backend that continues to not have
support for the “tuple IN” syntax.
Subquery loading is similar in operation to selectin eager loading, however the SELECT statement which is emitted is derived from the original statement, and has a more complex query structure as that of selectin eager loading.
Subquery eager loading is provided using the "subquery"
argument to
relationship.lazy
or by using the subqueryload()
loader
option.
The operation of subquery eager loading is to emit a second SELECT statement for each relationship to be loaded, across all result objects at once. This SELECT statement refers to the original SELECT statement, wrapped inside of a subquery, so that we retrieve the same list of primary keys for the primary object being returned, then link that to the sum of all the collection members to load them at once:
>>> from sqlalchemy import select
>>> from sqlalchemy.orm import subqueryload
>>> stmt = select(User).options(subqueryload(User.addresses)).filter_by(name="spongebob")
>>> results = session.scalars(stmt).all()
SELECT
users.id AS users_id,
users.name AS users_name,
users.fullname AS users_fullname,
users.nickname AS users_nickname
FROM users
WHERE users.name = ?
('spongebob',)
SELECT
addresses.id AS addresses_id,
addresses.email_address AS addresses_email_address,
addresses.user_id AS addresses_user_id,
anon_1.users_id AS anon_1_users_id
FROM (
SELECT users.id AS users_id
FROM users
WHERE users.name = ?) AS anon_1
JOIN addresses ON anon_1.users_id = addresses.user_id
ORDER BY anon_1.users_id, addresses.id
('spongebob',)
Things to know about this kind of loading include:
The SELECT statement emitted by the “subquery” loader strategy, unlike that of “selectin”, requires a subquery, and will inherit whatever performance limitations are present in the original query. The subquery itself may also incur performance penalties based on the specifics of the database in use.
“subquery” loading imposes some special ordering requirements in order to work correctly. A query which makes use of
subqueryload()
in conjunction with a limiting modifier such asSelect.limit()
, orSelect.offset()
should always includeSelect.order_by()
against unique column(s) such as the primary key, so that the additional queries emitted bysubqueryload()
include the same ordering as used by the parent query. Without it, there is a chance that the inner query could return the wrong rows:# incorrect, no ORDER BY stmt = select(User).options(subqueryload(User.addresses).limit(1)) # incorrect if User.name is not unique stmt = select(User).options(subqueryload(User.addresses)).order_by(User.name).limit(1) # correct stmt = ( select(User) .options(subqueryload(User.addresses)) .order_by(User.name, User.id) .limit(1) )
See also
Why is ORDER BY recommended with LIMIT (especially with subqueryload())? - detailed example
“subquery” loading also incurs additional performance / complexity issues when used on a many-levels-deep eager load, as subqueries will be nested repeatedly.
“subquery” loading is not compatible with the “batched” loading supplied by Yield Per, both for collection and scalar relationships.
For the above reasons, the “selectin” strategy should be preferred over “subquery”.
See also
What Kind of Loading to Use ?¶
Which type of loading to use typically comes down to optimizing the tradeoff between number of SQL executions, complexity of SQL emitted, and amount of data fetched.
One to Many / Many to Many Collection - The selectinload()
is
generally the best loading strategy to use. It emits an additional SELECT
that uses as few tables as possible, leaving the original statement unaffected,
and is most flexible for any kind of
originating query. Its only major limitation is when using a table with
composite primary keys on a backend that does not support “tuple IN”, which
currently includes SQL Server and very old SQLite versions; all other included
backends support it.
Many to One - The joinedload()
strategy is the most general
purpose strategy. In special cases, the immediateload()
strategy may
also be useful, if there are a very small number of potential related values,
as this strategy will fetch the object from the local Session
without emitting any SQL if the related object is already present.
Polymorphic Eager Loading¶
Specification of polymorphic options on a per-eager-load basis is supported.
See the section Eager Loading of Polymorphic Subtypes for examples
of the PropComparator.of_type()
method in conjunction with the
with_polymorphic()
function.
Wildcard Loading Strategies¶
Each of joinedload()
, subqueryload()
, lazyload()
,
selectinload()
, and raiseload()
can be used to set the default
style of relationship()
loading
for a particular query, affecting all relationship()
-mapped
attributes not otherwise
specified in the statement. This feature is available by passing
the string '*'
as the argument to any of these options:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
stmt = select(MyClass).options(lazyload("*"))
Above, the lazyload('*')
option will supersede the lazy
setting
of all relationship()
constructs in use for that query,
with the exception of those that use lazy='write_only'
or lazy='dynamic'
.
If some relationships specify
lazy='joined'
or lazy='selectin'
, for example,
using lazyload('*')
will unilaterally
cause all those relationships to use 'select'
loading, e.g. emit a
SELECT statement when each attribute is accessed.
The option does not supersede loader options stated in the
query, such as joinedload()
,
selectinload()
, etc. The query below will still use joined loading
for the widget
relationship:
from sqlalchemy import select
from sqlalchemy.orm import lazyload
from sqlalchemy.orm import joinedload
stmt = select(MyClass).options(lazyload("*"), joinedload(MyClass.widget))
While the instruction for joinedload()
above will take place regardless
of whether it appears before or after the lazyload()
option,
if multiple options that each included "*"
were passed, the last one
will take effect.
Per-Entity Wildcard Loading Strategies¶
A variant of the wildcard loader strategy is the ability to set the strategy
on a per-entity basis. For example, if querying for User
and Address
,
we can instruct all relationships on Address
to use lazy loading,
while leaving the loader strategies for User
unaffected,
by first applying the Load
object, then specifying the *
as a
chained option:
from sqlalchemy import select
from sqlalchemy.orm import Load
stmt = select(User, Address).options(Load(Address).lazyload("*"))
Above, all relationships on Address
will be set to a lazy load.
Routing Explicit Joins/Statements into Eagerly Loaded Collections¶
The behavior of joinedload()
is such that joins are
created automatically, using anonymous aliases as targets, the results of which
are routed into collections and
scalar references on loaded objects. It is often the case that a query already
includes the necessary joins which represent a particular collection or scalar
reference, and the joins added by the joinedload feature are redundant - yet
you’d still like the collections/references to be populated.
For this SQLAlchemy supplies the contains_eager()
option. This option is used in the same manner as the
joinedload()
option except it is assumed that the
Select
object will explicitly include the appropriate joins,
typically using methods like Select.join()
.
Below, we specify a join between User
and Address
and additionally establish this as the basis for eager loading of User.addresses
:
from sqlalchemy.orm import contains_eager
stmt = select(User).join(User.addresses).options(contains_eager(User.addresses))
If the “eager” portion of the statement is “aliased”, the path
should be specified using PropComparator.of_type()
, which allows
the specific aliased()
construct to be passed:
# use an alias of the Address entity
adalias = aliased(Address)
# construct a statement which expects the "addresses" results
stmt = (
select(User)
.outerjoin(User.addresses.of_type(adalias))
.options(contains_eager(User.addresses.of_type(adalias)))
)
# get results normally
r = session.scalars(stmt).unique().all()
SELECT
users.user_id AS users_user_id,
users.user_name AS users_user_name,
adalias.address_id AS adalias_address_id,
adalias.user_id AS adalias_user_id,
adalias.email_address AS adalias_email_address,
(...other columns...)
FROM users
LEFT OUTER JOIN email_addresses AS email_addresses_1
ON users.user_id = email_addresses_1.user_id
The path given as the argument to contains_eager()
needs
to be a full path from the starting entity. For example if we were loading
Users->orders->Order->items->Item
, the option would be used as:
stmt = select(User).options(contains_eager(User.orders).contains_eager(Order.items))
Using contains_eager() to load a custom-filtered collection result¶
When we use contains_eager()
, we are constructing ourselves the
SQL that will be used to populate collections. From this, it naturally follows
that we can opt to modify what values the collection is intended to store,
by writing our SQL to load a subset of elements for collections or
scalar attributes.
Tip
SQLAlchemy now has a much simpler way to do this, by allowing
WHERE criteria to be added directly to loader options such as
joinedload()
and selectinload()
using PropComparator.and_()
. See
the section Adding Criteria to loader options for examples.
The techniques described here still apply if the related collection is to be queried using SQL criteria or modifiers more complex than a simple WHERE clause.
As an example, we can load a User
object and eagerly load only particular
addresses into its .addresses
collection by filtering the joined data,
routing it using contains_eager()
, also using
Populate Existing to ensure any already-loaded collections
are overwritten:
stmt = (
select(User)
.join(User.addresses)
.filter(Address.email_address.like("%@aol.com"))
.options(contains_eager(User.addresses))
.execution_options(populate_existing=True)
)
The above query will load only User
objects which contain at
least Address
object that contains the substring 'aol.com'
in its
email
field; the User.addresses
collection will contain only
these Address
entries, and not any other Address
entries that are
in fact associated with the collection.
Tip
In all cases, the SQLAlchemy ORM does not overwrite already loaded
attributes and collections unless told to do so. As there is an
identity map in use, it is often the case that an ORM query is
returning objects that were in fact already present and loaded in memory.
Therefore, when using contains_eager()
to populate a collection
in an alternate way, it is usually a good idea to use
Populate Existing as illustrated above so that an
already-loaded collection is refreshed with the new data.
The populate_existing
option will reset all attributes that were
already present, including pending changes, so make sure all data is flushed
before using it. Using the Session
with its default behavior
of autoflush is sufficient.
Note
The customized collection we load using contains_eager()
is not “sticky”; that is, the next time this collection is loaded, it will
be loaded with its usual default contents. The collection is subject
to being reloaded if the object is expired, which occurs whenever the
Session.commit()
, Session.rollback()
methods are used
assuming default session settings, or the Session.expire_all()
or Session.expire()
methods are used.
See also
Adding Criteria to loader options - modern API allowing WHERE criteria directly within any relationship loader option
Relationship Loader API¶
Object Name | Description |
---|---|
contains_eager(*keys, **kw) |
Indicate that the given attribute should be eagerly loaded from columns stated manually in the query. |
defaultload(*keys) |
Indicate an attribute should load using its predefined loader style. |
immediateload(*keys, [recursion_depth]) |
Indicate that the given attribute should be loaded using an immediate load with a per-attribute SELECT statement. |
joinedload(*keys, **kw) |
Indicate that the given attribute should be loaded using joined eager loading. |
lazyload(*keys) |
Indicate that the given attribute should be loaded using “lazy” loading. |
Represents loader options which modify the state of a
ORM-enabled |
|
noload(*keys) |
Indicate that the given relationship attribute should remain unloaded. |
raiseload(*keys, **kw) |
Indicate that the given attribute should raise an error if accessed. |
selectinload(*keys, [recursion_depth]) |
Indicate that the given attribute should be loaded using SELECT IN eager loading. |
subqueryload(*keys) |
Indicate that the given attribute should be loaded using subquery eager loading. |
- function sqlalchemy.orm.contains_eager(*keys: Literal['*'] | QueryableAttribute[Any], **kw: Any) → _AbstractLoad¶
Indicate that the given attribute should be eagerly loaded from columns stated manually in the query.
This function is part of the
Load
interface and supports both method-chained and standalone operation.The option is used in conjunction with an explicit join that loads the desired rows, i.e.:
sess.query(Order).join(Order.user).options( contains_eager(Order.user) )
The above query would join from the
Order
entity to its relatedUser
entity, and the returnedOrder
objects would have theOrder.user
attribute pre-populated.It may also be used for customizing the entries in an eagerly loaded collection; queries will normally want to use the Populate Existing execution option assuming the primary collection of parent objects may already have been loaded:
sess.query(User).join(User.addresses).filter( Address.email_address.like("%@aol.com") ).options(contains_eager(User.addresses)).populate_existing()
See the section Routing Explicit Joins/Statements into Eagerly Loaded Collections for complete usage details.
- function sqlalchemy.orm.defaultload(*keys: Literal['*'] | QueryableAttribute[Any]) → _AbstractLoad¶
Indicate an attribute should load using its predefined loader style.
The behavior of this loading option is to not change the current loading style of the attribute, meaning that the previously configured one is used or, if no previous style was selected, the default loading will be used.
This method is used to link to other loader options further into a chain of attributes without altering the loader style of the links along the chain. For example, to set joined eager loading for an element of an element:
session.query(MyClass).options( defaultload(MyClass.someattribute).joinedload( MyOtherClass.someotherattribute ) )
defaultload()
is also useful for setting column-level options on a related class, namely that ofdefer()
andundefer()
:session.scalars( select(MyClass).options( defaultload(MyClass.someattribute) .defer("some_column") .undefer("some_other_column") ) )
- function sqlalchemy.orm.immediateload(*keys: Literal['*'] | QueryableAttribute[Any], recursion_depth: int | None = None) → _AbstractLoad¶
Indicate that the given attribute should be loaded using an immediate load with a per-attribute SELECT statement.
The load is achieved using the “lazyloader” strategy and does not fire off any additional eager loaders.
The
immediateload()
option is superseded in general by theselectinload()
option, which performs the same task more efficiently by emitting a SELECT for all loaded objects.This function is part of the
Load
interface and supports both method-chained and standalone operation.- Parameters:
recursion_depth¶ –
optional int; when set to a positive integer in conjunction with a self-referential relationship, indicates “selectin” loading will continue that many levels deep automatically until no items are found.
Note
The
immediateload.recursion_depth
option currently supports only self-referential relationships. There is not yet an option to automatically traverse recursive structures with more than one relationship involved.Warning
This parameter is new and experimental and should be treated as “alpha” status
New in version 2.0: added
immediateload.recursion_depth
- function sqlalchemy.orm.joinedload(*keys: Literal['*'] | QueryableAttribute[Any], **kw: Any) → _AbstractLoad¶
Indicate that the given attribute should be loaded using joined eager loading.
This function is part of the
Load
interface and supports both method-chained and standalone operation.examples:
# joined-load the "orders" collection on "User" select(User).options(joinedload(User.orders)) # joined-load Order.items and then Item.keywords select(Order).options( joinedload(Order.items).joinedload(Item.keywords) ) # lazily load Order.items, but when Items are loaded, # joined-load the keywords collection select(Order).options( lazyload(Order.items).joinedload(Item.keywords) )
- Parameters:
innerjoin¶ –
if
True
, indicates that the joined eager load should use an inner join instead of the default of left outer join:select(Order).options(joinedload(Order.user, innerjoin=True))
In order to chain multiple eager joins together where some may be OUTER and others INNER, right-nested joins are used to link them:
select(A).options( joinedload(A.bs, innerjoin=False).joinedload( B.cs, innerjoin=True ) )
The above query, linking A.bs via “outer” join and B.cs via “inner” join would render the joins as “a LEFT OUTER JOIN (b JOIN c)”. When using older versions of SQLite (< 3.7.16), this form of JOIN is translated to use full subqueries as this syntax is otherwise not directly supported.
The
innerjoin
flag can also be stated with the term"unnested"
. This indicates that an INNER JOIN should be used, unless the join is linked to a LEFT OUTER JOIN to the left, in which case it will render as LEFT OUTER JOIN. For example, supposingA.bs
is an outerjoin:select(A).options( joinedload(A.bs).joinedload(B.cs, innerjoin="unnested") )
The above join will render as “a LEFT OUTER JOIN b LEFT OUTER JOIN c”, rather than as “a LEFT OUTER JOIN (b JOIN c)”.
Note
The “unnested” flag does not affect the JOIN rendered from a many-to-many association table, e.g. a table configured as
relationship.secondary
, to the target table; for correctness of results, these joins are always INNER and are therefore right-nested if linked to an OUTER join.Note
The joins produced by
joinedload()
are anonymously aliased. The criteria by which the join proceeds cannot be modified, nor can the ORM-enabledSelect
or legacyQuery
refer to these joins in any way, including ordering. See The Zen of Joined Eager Loading for further detail.To produce a specific SQL JOIN which is explicitly available, use
Select.join()
andQuery.join()
. To combine explicit JOINs with eager loading of collections, usecontains_eager()
; see Routing Explicit Joins/Statements into Eagerly Loaded Collections.
- function sqlalchemy.orm.lazyload(*keys: Literal['*'] | QueryableAttribute[Any]) → _AbstractLoad¶
Indicate that the given attribute should be loaded using “lazy” loading.
This function is part of the
Load
interface and supports both method-chained and standalone operation.
- class sqlalchemy.orm.Load¶
Represents loader options which modify the state of a ORM-enabled
Select
or a legacyQuery
in order to affect how various mapped attributes are loaded.The
Load
object is in most cases used implicitly behind the scenes when one makes use of a query option likejoinedload()
,defer()
, or similar. It typically is not instantiated directly except for in some very specific cases.See also
Per-Entity Wildcard Loading Strategies - illustrates an example where direct use of
Load
may be usefulMembers
contains_eager(), defaultload(), defer(), get_children(), immediateload(), inherit_cache, joinedload(), lazyload(), load_only(), noload(), options(), process_compile_state(), process_compile_state_replaced_entities(), propagate_to_loaders, raiseload(), selectin_polymorphic(), selectinload(), subqueryload(), undefer(), undefer_group(), with_expression()
Class signature
class
sqlalchemy.orm.Load
(sqlalchemy.orm.strategy_options._AbstractLoad
)-
method
sqlalchemy.orm.Load.
contains_eager(attr: _AttrType, alias: _FromClauseArgument | None = None, _is_chain: bool = False, _propagate_to_loaders: bool = False) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.contains_eager
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thecontains_eager()
option applied.See
contains_eager()
for usage examples.
-
method
sqlalchemy.orm.Load.
defaultload(attr: Literal['*'] | QueryableAttribute[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.defaultload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thedefaultload()
option applied.See
defaultload()
for usage examples.
-
method
sqlalchemy.orm.Load.
defer(key: Literal['*'] | QueryableAttribute[Any], raiseload: bool = False) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.defer
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thedefer()
option applied.See
defer()
for usage examples.
-
method
sqlalchemy.orm.Load.
get_children(*, omit_attrs: Tuple[str, ...] = (), **kw: Any) → Iterable[HasTraverseInternals]¶ inherited from the
HasTraverseInternals.get_children()
method ofHasTraverseInternals
Return immediate child
HasTraverseInternals
elements of thisHasTraverseInternals
.This is used for visit traversal.
**kw may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).
-
method
sqlalchemy.orm.Load.
immediateload(attr: Literal['*'] | QueryableAttribute[Any], recursion_depth: int | None = None) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.immediateload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theimmediateload()
option applied.See
immediateload()
for usage examples.
-
attribute
sqlalchemy.orm.Load.
inherit_cache: bool | None = None¶ inherited from the
HasCacheKey.inherit_cache
attribute ofHasCacheKey
Indicate if this
HasCacheKey
instance should make use of the cache key generation scheme used by its immediate superclass.The attribute defaults to
None
, which indicates that a construct has not yet taken into account whether or not its appropriate for it to participate in caching; this is functionally equivalent to setting the value toFalse
, except that a warning is also emitted.This flag can be set to
True
on a particular class, if the SQL that corresponds to the object does not change based on attributes which are local to this class, and not its superclass.See also
Enabling Caching Support for Custom Constructs - General guideslines for setting the
HasCacheKey.inherit_cache
attribute for third-party or user defined SQL constructs.
-
method
sqlalchemy.orm.Load.
joinedload(attr: Literal['*'] | QueryableAttribute[Any], innerjoin: bool | None = None) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.joinedload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thejoinedload()
option applied.See
joinedload()
for usage examples.
-
method
sqlalchemy.orm.Load.
lazyload(attr: Literal['*'] | QueryableAttribute[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.lazyload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thelazyload()
option applied.See
lazyload()
for usage examples.
-
method
sqlalchemy.orm.Load.
load_only(*attrs: Literal['*'] | QueryableAttribute[Any], raiseload: bool = False) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.load_only
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theload_only()
option applied.See
load_only()
for usage examples.
-
method
sqlalchemy.orm.Load.
noload(attr: Literal['*'] | QueryableAttribute[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.noload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thenoload()
option applied.See
noload()
for usage examples.
-
method
sqlalchemy.orm.Load.
options(*opts: _AbstractLoad) → Self¶ Apply a series of options as sub-options to this
Load
object.E.g.:
query = session.query(Author) query = query.options( joinedload(Author.book).options( load_only(Book.summary, Book.excerpt), joinedload(Book.citations).options( joinedload(Citation.author) ) ) )
- Parameters:
*opts¶ – A series of loader option objects (ultimately
Load
objects) which should be applied to the path specified by thisLoad
object.
New in version 1.3.6.
-
method
sqlalchemy.orm.Load.
process_compile_state(compile_state: ORMCompileState) → None¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.process_compile_state
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Apply a modification to a given
ORMCompileState
.This method is part of the implementation of a particular
CompileStateOption
and is only invoked internally when an ORM query is compiled.
-
method
sqlalchemy.orm.Load.
process_compile_state_replaced_entities(compile_state: ORMCompileState, mapper_entities: Sequence[_MapperEntity]) → None¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.process_compile_state_replaced_entities
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Apply a modification to a given
ORMCompileState
, given entities that were replaced by with_only_columns() or with_entities().This method is part of the implementation of a particular
CompileStateOption
and is only invoked internally when an ORM query is compiled.New in version 1.4.19.
-
attribute
sqlalchemy.orm.Load.
propagate_to_loaders: bool¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.propagate_to_loaders
attribute ofsqlalchemy.orm.strategy_options._AbstractLoad
if True, indicate this option should be carried along to “secondary” SELECT statements that occur for relationship lazy loaders as well as attribute load / refresh operations.
-
method
sqlalchemy.orm.Load.
raiseload(attr: Literal['*'] | QueryableAttribute[Any], sql_only: bool = False) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.raiseload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theraiseload()
option applied.See
raiseload()
for usage examples.
-
method
sqlalchemy.orm.Load.
selectin_polymorphic(classes: Iterable[Type[Any]]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.selectin_polymorphic
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theselectin_polymorphic()
option applied.See
selectin_polymorphic()
for usage examples.
-
method
sqlalchemy.orm.Load.
selectinload(attr: Literal['*'] | QueryableAttribute[Any], recursion_depth: int | None = None) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.selectinload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theselectinload()
option applied.See
selectinload()
for usage examples.
-
method
sqlalchemy.orm.Load.
subqueryload(attr: Literal['*'] | QueryableAttribute[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.subqueryload
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thesubqueryload()
option applied.See
subqueryload()
for usage examples.
-
method
sqlalchemy.orm.Load.
undefer(key: Literal['*'] | QueryableAttribute[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.undefer
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theundefer()
option applied.See
undefer()
for usage examples.
-
method
sqlalchemy.orm.Load.
undefer_group(name: str) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.undefer_group
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with theundefer_group()
option applied.See
undefer_group()
for usage examples.
-
method
sqlalchemy.orm.Load.
with_expression(key: _AttrType, expression: _ColumnExpressionArgument[Any]) → Self¶ inherited from the
sqlalchemy.orm.strategy_options._AbstractLoad.with_expression
method ofsqlalchemy.orm.strategy_options._AbstractLoad
Produce a new
Load
object with thewith_expression()
option applied.See
with_expression()
for usage examples.
-
method
- function sqlalchemy.orm.noload(*keys: Literal['*'] | QueryableAttribute[Any]) → _AbstractLoad¶
Indicate that the given relationship attribute should remain unloaded.
The relationship attribute will return
None
when accessed without producing any loading effect.This function is part of the
Load
interface and supports both method-chained and standalone operation.noload()
applies torelationship()
attributes only.Legacy Feature
The
noload()
option is legacy. As it forces collections to be empty, which invariably leads to non-intuitive and difficult to predict results. There are no legitimate uses for this option in modern SQLAlchemy.See also
- function sqlalchemy.orm.raiseload(*keys: Literal['*'] | QueryableAttribute[Any], **kw: Any) → _AbstractLoad¶
Indicate that the given attribute should raise an error if accessed.
A relationship attribute configured with
raiseload()
will raise anInvalidRequestError
upon access. The typical way this is useful is when an application is attempting to ensure that all relationship attributes that are accessed in a particular context would have been already loaded via eager loading. Instead of having to read through SQL logs to ensure lazy loads aren’t occurring, this strategy will cause them to raise immediately.raiseload()
applies torelationship()
attributes only. In order to apply raise-on-SQL behavior to a column-based attribute, use thedefer.raiseload
parameter on thedefer()
loader option.- Parameters:
sql_only¶ – if True, raise only if the lazy load would emit SQL, but not if it is only checking the identity map, or determining that the related value should just be None due to missing keys. When False, the strategy will raise for all varieties of relationship loading.
This function is part of the
Load
interface and supports both method-chained and standalone operation.
- function sqlalchemy.orm.selectinload(*keys: Literal['*'] | QueryableAttribute[Any], recursion_depth: int | None = None) → _AbstractLoad¶
Indicate that the given attribute should be loaded using SELECT IN eager loading.
This function is part of the
Load
interface and supports both method-chained and standalone operation.examples:
# selectin-load the "orders" collection on "User" select(User).options(selectinload(User.orders)) # selectin-load Order.items and then Item.keywords select(Order).options( selectinload(Order.items).selectinload(Item.keywords) ) # lazily load Order.items, but when Items are loaded, # selectin-load the keywords collection select(Order).options( lazyload(Order.items).selectinload(Item.keywords) )
- Parameters:
recursion_depth¶ –
optional int; when set to a positive integer in conjunction with a self-referential relationship, indicates “selectin” loading will continue that many levels deep automatically until no items are found.
Note
The
selectinload.recursion_depth
option currently supports only self-referential relationships. There is not yet an option to automatically traverse recursive structures with more than one relationship involved.Additionally, the
selectinload.recursion_depth
parameter is new and experimental and should be treated as “alpha” status for the 2.0 series.New in version 2.0: added
selectinload.recursion_depth
- function sqlalchemy.orm.subqueryload(*keys: Literal['*'] | QueryableAttribute[Any]) → _AbstractLoad¶
Indicate that the given attribute should be loaded using subquery eager loading.
This function is part of the
Load
interface and supports both method-chained and standalone operation.examples:
# subquery-load the "orders" collection on "User" select(User).options(subqueryload(User.orders)) # subquery-load Order.items and then Item.keywords select(Order).options( subqueryload(Order.items).subqueryload(Item.keywords) ) # lazily load Order.items, but when Items are loaded, # subquery-load the keywords collection select(Order).options( lazyload(Order.items).subqueryload(Item.keywords) )
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