SQLAlchemy 2.0 Documentation
SQLAlchemy ORM
- ORM Quick Start
- ORM Mapped Class Configuration
- Relationship Configuration
- ORM Querying Guide
- Using the Session
- Session Basics
- State Management
- Cascades
- Transactions and Connection Management
- Additional Persistence Techniques
- Contextual/Thread-local Sessions
- Tracking queries, object and Session Changes with Events¶
- Session API
- Events and Internals
- ORM Extensions
- ORM Examples
Project Versions
Tracking queries, object and Session Changes with Events¶
SQLAlchemy features an extensive Event Listening system used throughout the Core and ORM. Within the ORM, there are a wide variety of event listener hooks, which are documented at an API level at ORM Events. This collection of events has grown over the years to include lots of very useful new events as well as some older events that aren’t as relevant as they once were. This section will attempt to introduce the major event hooks and when they might be used.
Execute Events¶
New in version 1.4: The Session
now features a single
comprehensive hook designed to intercept all SELECT statements made
on behalf of the ORM as well as bulk UPDATE and DELETE statements.
This hook supersedes the previous QueryEvents.before_compile()
event as well QueryEvents.before_compile_update()
and
QueryEvents.before_compile_delete()
.
Session
features a comprehensive system by which all queries
invoked via the Session.execute()
method, which includes all
SELECT statements emitted by Query
as well as all SELECT
statements emitted on behalf of column and relationship loaders, may
be intercepted and modified. The system makes use of the
SessionEvents.do_orm_execute()
event hook as well as the
ORMExecuteState
object to represent the event state.
Basic Query Interception¶
SessionEvents.do_orm_execute()
is firstly useful for any kind of
interception of a query, which includes those emitted by
Query
with 1.x style as well as when an ORM-enabled
2.0 style select()
,
update()
or delete()
construct is delivered to
Session.execute()
. The ORMExecuteState
construct
provides accessors to allow modifications to statements, parameters, and
options:
Session = sessionmaker(engine)
@event.listens_for(Session, "do_orm_execute")
def _do_orm_execute(orm_execute_state):
if orm_execute_state.is_select:
# add populate_existing for all SELECT statements
orm_execute_state.update_execution_options(populate_existing=True)
# check if the SELECT is against a certain entity and add an
# ORDER BY if so
col_descriptions = orm_execute_state.statement.column_descriptions
if col_descriptions[0]["entity"] is MyEntity:
orm_execute_state.statement = statement.order_by(MyEntity.name)
The above example illustrates some simple modifications to SELECT statements.
At this level, the SessionEvents.do_orm_execute()
event hook intends
to replace the previous use of the QueryEvents.before_compile()
event,
which was not fired off consistently for various kinds of loaders; additionally,
the QueryEvents.before_compile()
only applies to 1.x style
use with Query
and not with 2.0 style use of
Session.execute()
.
Adding global WHERE / ON criteria¶
One of the most requested query-extension features is the ability to add WHERE
criteria to all occurrences of an entity in all queries. This is achievable
by making use of the with_loader_criteria()
query option, which
may be used on its own, or is ideally suited to be used within the
SessionEvents.do_orm_execute()
event:
from sqlalchemy.orm import with_loader_criteria
Session = sessionmaker(engine)
@event.listens_for(Session, "do_orm_execute")
def _do_orm_execute(orm_execute_state):
if (
orm_execute_state.is_select
and not orm_execute_state.is_column_load
and not orm_execute_state.is_relationship_load
):
orm_execute_state.statement = orm_execute_state.statement.options(
with_loader_criteria(MyEntity.public == True)
)
Above, an option is added to all SELECT statements that will limit all queries
against MyEntity
to filter on public == True
. The criteria
will be applied to all loads of that class within the scope of the
immediate query. The with_loader_criteria()
option by default
will automatically propagate to relationship loaders as well, which will
apply to subsequent relationship loads, which includes
lazy loads, selectinloads, etc.
For a series of classes that all feature some common column structure,
if the classes are composed using a declarative mixin,
the mixin class itself may be used in conjunction with the with_loader_criteria()
option by making use of a Python lambda. The Python lambda will be invoked at
query compilation time against the specific entities which match the criteria.
Given a series of classes based on a mixin called HasTimestamp
:
import datetime
class HasTimestamp:
timestamp = mapped_column(DateTime, default=datetime.datetime.now)
class SomeEntity(HasTimestamp, Base):
__tablename__ = "some_entity"
id = mapped_column(Integer, primary_key=True)
class SomeOtherEntity(HasTimestamp, Base):
__tablename__ = "some_entity"
id = mapped_column(Integer, primary_key=True)
The above classes SomeEntity
and SomeOtherEntity
will each have a column
timestamp
that defaults to the current date and time. An event may be used
to intercept all objects that extend from HasTimestamp
and filter their
timestamp
column on a date that is no older than one month ago:
@event.listens_for(Session, "do_orm_execute")
def _do_orm_execute(orm_execute_state):
if (
orm_execute_state.is_select
and not orm_execute_state.is_column_load
and not orm_execute_state.is_relationship_load
):
one_month_ago = datetime.datetime.today() - datetime.timedelta(months=1)
orm_execute_state.statement = orm_execute_state.statement.options(
with_loader_criteria(
HasTimestamp,
lambda cls: cls.timestamp >= one_month_ago,
include_aliases=True,
)
)
Warning
The use of a lambda inside of the call to
with_loader_criteria()
is only invoked once per unique class.
Custom functions should not be invoked within this lambda. See
Using Lambdas to add significant speed gains to statement production for an overview of the “lambda SQL” feature,
which is for advanced use only.
See also
ORM Query Events - includes working examples of the
above with_loader_criteria()
recipes.
Re-Executing Statements¶
Deep Alchemy
the statement re-execution feature involves a slightly intricate recursive sequence, and is intended to solve the fairly hard problem of being able to re-route the execution of a SQL statement into various non-SQL contexts. The twin examples of “dogpile caching” and “horizontal sharding”, linked below, should be used as a guide for when this rather advanced feature is appropriate to be used.
The ORMExecuteState
is capable of controlling the execution of
the given statement; this includes the ability to either not invoke the
statement at all, allowing a pre-constructed result set retrieved from a cache to
be returned instead, as well as the ability to invoke the same statement
repeatedly with different state, such as invoking it against multiple database
connections and then merging the results together in memory. Both of these
advanced patterns are demonstrated in SQLAlchemy’s example suite as detailed
below.
When inside the SessionEvents.do_orm_execute()
event hook, the
ORMExecuteState.invoke_statement()
method may be used to invoke
the statement using a new nested invocation of Session.execute()
,
which will then preempt the subsequent handling of the current execution
in progress and instead return the Result
returned by the
inner execution. The event handlers thus far invoked for the
SessionEvents.do_orm_execute()
hook within this process will
be skipped within this nested call as well.
The ORMExecuteState.invoke_statement()
method returns a
Result
object; this object then features the ability for it to
be “frozen” into a cacheable format and “unfrozen” into a new
Result
object, as well as for its data to be merged with
that of other Result
objects.
E.g., using SessionEvents.do_orm_execute()
to implement a cache:
from sqlalchemy.orm import loading
cache = {}
@event.listens_for(Session, "do_orm_execute")
def _do_orm_execute(orm_execute_state):
if "my_cache_key" in orm_execute_state.execution_options:
cache_key = orm_execute_state.execution_options["my_cache_key"]
if cache_key in cache:
frozen_result = cache[cache_key]
else:
frozen_result = orm_execute_state.invoke_statement().freeze()
cache[cache_key] = frozen_result
return loading.merge_frozen_result(
orm_execute_state.session,
orm_execute_state.statement,
frozen_result,
load=False,
)
With the above hook in place, an example of using the cache would look like:
stmt = (
select(User).where(User.name == "sandy").execution_options(my_cache_key="key_sandy")
)
result = session.execute(stmt)
Above, a custom execution option is passed to
Select.execution_options()
in order to establish a “cache key” that
will then be intercepted by the SessionEvents.do_orm_execute()
hook. This
cache key is then matched to a FrozenResult
object that may be
present in the cache, and if present, the object is re-used. The recipe makes
use of the Result.freeze()
method to “freeze” a
Result
object, which above will contain ORM results, such that
it can be stored in a cache and used multiple times. In order to return a live
result from the “frozen” result, the merge_frozen_result()
function is used to merge the “frozen” data from the result object into the
current session.
The above example is implemented as a complete example in Dogpile Caching.
The ORMExecuteState.invoke_statement()
method may also be called
multiple times, passing along different information to the
ORMExecuteState.invoke_statement.bind_arguments
parameter such
that the Session
will make use of different
Engine
objects each time. This will return a different
Result
object each time; these results can be merged together
using the Result.merge()
method. This is the technique employed
by the Horizontal Sharding extension; see the source code to
familiarize.
Persistence Events¶
Probably the most widely used series of events are the “persistence” events, which correspond to the flush process. The flush is where all the decisions are made about pending changes to objects and are then emitted out to the database in the form of INSERT, UPDATE, and DELETE statements.
before_flush()
¶
The SessionEvents.before_flush()
hook is by far the most generally
useful event to use when an application wants to ensure that
additional persistence changes to the database are made when a flush proceeds.
Use SessionEvents.before_flush()
in order to operate
upon objects to validate their state as well as to compose additional objects
and references before they are persisted. Within this event,
it is safe to manipulate the Session’s state, that is, new objects
can be attached to it, objects can be deleted, and individual attributes
on objects can be changed freely, and these changes will be pulled into
the flush process when the event hook completes.
The typical SessionEvents.before_flush()
hook will be tasked with
scanning the collections Session.new
, Session.dirty
and
Session.deleted
in order to look for objects
where something will be happening.
For illustrations of SessionEvents.before_flush()
, see
examples such as Versioning with a History Table and
Versioning using Temporal Rows.
after_flush()
¶
The SessionEvents.after_flush()
hook is called after the SQL has been
emitted for a flush process, but before the state of the objects that
were flushed has been altered. That is, you can still inspect
the Session.new
, Session.dirty
and
Session.deleted
collections to see what was just flushed, and
you can also use history tracking features like the ones provided
by AttributeState
to see what changes were just persisted.
In the SessionEvents.after_flush()
event, additional SQL can be emitted
to the database based on what’s observed to have changed.
after_flush_postexec()
¶
SessionEvents.after_flush_postexec()
is called soon after
SessionEvents.after_flush()
, but is invoked after the state of
the objects has been modified to account for the flush that just took place.
The Session.new
, Session.dirty
and
Session.deleted
collections are normally completely empty here.
Use SessionEvents.after_flush_postexec()
to inspect the identity map
for finalized objects and possibly emit additional SQL. In this hook,
there is the ability to make new changes on objects, which means the
Session
will again go into a “dirty” state; the mechanics of the
Session
here will cause it to flush again if new changes
are detected in this hook if the flush were invoked in the context of
Session.commit()
; otherwise, the pending changes will be bundled
as part of the next normal flush. When the hook detects new changes within
a Session.commit()
, a counter ensures that an endless loop in this
regard is stopped after 100 iterations, in the case that an
SessionEvents.after_flush_postexec()
hook continually adds new state to be flushed each time it is called.
Mapper-level Flush Events¶
In addition to the flush-level hooks, there is also a suite of hooks that are more fine-grained, in that they are called on a per-object basis and are broken out based on INSERT, UPDATE or DELETE within the flush process. These are the mapper persistence hooks, and they too are very popular, however these events need to be approached more cautiously, as they proceed within the context of the flush process that is already ongoing; many operations are not safe to proceed here.
The events are:
Note
It is important to note that these events apply only to the
session flush operation , and not to the
ORM-level INSERT/UPDATE/DELETE functionality described at
ORM-Enabled INSERT, UPDATE, and DELETE statements. To intercept ORM-level DML, use the
SessionEvents.do_orm_execute()
event.
Each event is passed the Mapper
,
the mapped object itself, and the Connection
which is being
used to emit an INSERT, UPDATE or DELETE statement. The appeal of these
events is clear, in that if an application wants to tie some activity to
when a specific type of object is persisted with an INSERT, the hook is
very specific; unlike the SessionEvents.before_flush()
event,
there’s no need to search through collections like Session.new
in order to find targets. However, the flush plan which
represents the full list of every single INSERT, UPDATE, DELETE statement
to be emitted has already been decided when these events are called,
and no changes may be made at this stage. Therefore the only changes that are
even possible to the given objects are upon attributes local to the
object’s row. Any other change to the object or other objects will
impact the state of the Session
, which will fail to function
properly.
Operations that are not supported within these mapper-level persistence events include:
Mapped collection append, add, remove, delete, discard, etc.
Mapped relationship attribute set/del events, i.e.
someobject.related = someotherobject
The reason the Connection
is passed is that it is encouraged that
simple SQL operations take place here, directly on the Connection
,
such as incrementing counters or inserting extra rows within log tables.
There are also many per-object operations that don’t need to be handled
within a flush event at all. The most common alternative is to simply
establish additional state along with an object inside its __init__()
method, such as creating additional objects that are to be associated with
the new object. Using validators as described in Simple Validators is
another approach; these functions can intercept changes to attributes and
establish additional state changes on the target object in response to the
attribute change. With both of these approaches, the object is in
the correct state before it ever gets to the flush step.
Object Lifecycle Events¶
Another use case for events is to track the lifecycle of objects. This refers to the states first introduced at Quickie Intro to Object States.
All the states above can be tracked fully with events. Each event
represents a distinct state transition, meaning, the starting state
and the destination state are both part of what are tracked. With the
exception of the initial transient event, all the events are in terms of
the Session
object or class, meaning they can be associated either
with a specific Session
object:
from sqlalchemy import event
from sqlalchemy.orm import Session
session = Session()
@event.listens_for(session, "transient_to_pending")
def object_is_pending(session, obj):
print("new pending: %s" % obj)
Or with the Session
class itself, as well as with a specific
sessionmaker
, which is likely the most useful form:
from sqlalchemy import event
from sqlalchemy.orm import sessionmaker
maker = sessionmaker()
@event.listens_for(maker, "transient_to_pending")
def object_is_pending(session, obj):
print("new pending: %s" % obj)
The listeners can of course be stacked on top of one function, as is likely to be common. For example, to track all objects that are entering the persistent state:
@event.listens_for(maker, "pending_to_persistent")
@event.listens_for(maker, "deleted_to_persistent")
@event.listens_for(maker, "detached_to_persistent")
@event.listens_for(maker, "loaded_as_persistent")
def detect_all_persistent(session, instance):
print("object is now persistent: %s" % instance)
Transient¶
All mapped objects when first constructed start out as transient.
In this state, the object exists alone and doesn’t have an association with
any Session
. For this initial state, there’s no specific
“transition” event since there is no Session
, however if one
wanted to intercept when any transient object is created, the
InstanceEvents.init()
method is probably the best event. This
event is applied to a specific class or superclass. For example, to
intercept all new objects for a particular declarative base:
from sqlalchemy.orm import DeclarativeBase
from sqlalchemy import event
class Base(DeclarativeBase):
pass
@event.listens_for(Base, "init", propagate=True)
def intercept_init(instance, args, kwargs):
print("new transient: %s" % instance)
Transient to Pending¶
The transient object becomes pending when it is first associated
with a Session
via the Session.add()
or Session.add_all()
method. An object may also become part of a Session
as a result
of a “cascade” from a referencing object that was
explicitly added. The transient to pending transition is detectable using
the SessionEvents.transient_to_pending()
event:
@event.listens_for(sessionmaker, "transient_to_pending")
def intercept_transient_to_pending(session, object_):
print("transient to pending: %s" % object_)
Pending to Persistent¶
The pending object becomes persistent when a flush
proceeds and an INSERT statement takes place for the instance. The object
now has an identity key. Track pending to persistent with the
SessionEvents.pending_to_persistent()
event:
@event.listens_for(sessionmaker, "pending_to_persistent")
def intercept_pending_to_persistent(session, object_):
print("pending to persistent: %s" % object_)
Pending to Transient¶
The pending object can revert back to transient if the
Session.rollback()
method is called before the pending object
has been flushed, or if the Session.expunge()
method is called
for the object before it is flushed. Track pending to transient with the
SessionEvents.pending_to_transient()
event:
@event.listens_for(sessionmaker, "pending_to_transient")
def intercept_pending_to_transient(session, object_):
print("transient to pending: %s" % object_)
Loaded as Persistent¶
Objects can appear in the Session
directly in the persistent
state when they are loaded from the database. Tracking this state transition
is synonymous with tracking objects as they are loaded, and is synonymous
with using the InstanceEvents.load()
instance-level event. However, the
SessionEvents.loaded_as_persistent()
event is provided as a
session-centric hook for intercepting objects as they enter the persistent
state via this particular avenue:
@event.listens_for(sessionmaker, "loaded_as_persistent")
def intercept_loaded_as_persistent(session, object_):
print("object loaded into persistent state: %s" % object_)
Persistent to Transient¶
The persistent object can revert to the transient state if the
Session.rollback()
method is called for a transaction where the
object was first added as pending. In the case of the ROLLBACK, the
INSERT statement that made this object persistent is rolled back, and
the object is evicted from the Session
to again become transient.
Track objects that were reverted to transient from
persistent using the SessionEvents.persistent_to_transient()
event hook:
@event.listens_for(sessionmaker, "persistent_to_transient")
def intercept_persistent_to_transient(session, object_):
print("persistent to transient: %s" % object_)
Persistent to Deleted¶
The persistent object enters the deleted state when an object
marked for deletion is deleted from the database within the flush
process. Note that this is not the same as when the Session.delete()
method is called for a target object. The Session.delete()
method only marks the object for deletion; the actual DELETE statement
is not emitted until the flush proceeds. It is subsequent to the flush
that the “deleted” state is present for the target object.
Within the “deleted” state, the object is only marginally associated
with the Session
. It is not present in the identity map
nor is it present in the Session.deleted
collection that refers
to when it was pending for deletion.
From the “deleted” state, the object can go either to the detached state when the transaction is committed, or back to the persistent state if the transaction is instead rolled back.
Track the persistent to deleted transition with
SessionEvents.persistent_to_deleted()
:
@event.listens_for(sessionmaker, "persistent_to_deleted")
def intercept_persistent_to_deleted(session, object_):
print("object was DELETEd, is now in deleted state: %s" % object_)
Deleted to Detached¶
The deleted object becomes detached when the session’s transaction
is committed. After the Session.commit()
method is called, the
database transaction is final and the Session
now fully discards
the deleted object and removes all associations to it. Track
the deleted to detached transition using SessionEvents.deleted_to_detached()
:
@event.listens_for(sessionmaker, "deleted_to_detached")
def intercept_deleted_to_detached(session, object_):
print("deleted to detached: %s" % object_)
Note
While the object is in the deleted state, the InstanceState.deleted
attribute, accessible using inspect(object).deleted
, returns True. However
when the object is detached, InstanceState.deleted
will again
return False. To detect that an object was deleted, regardless of whether
or not it is detached, use the InstanceState.was_deleted
accessor.
Persistent to Detached¶
The persistent object becomes detached when the object is de-associated
with the Session
, via the Session.expunge()
,
Session.expunge_all()
, or Session.close()
methods.
Note
An object may also become implicitly detached if its owning
Session
is dereferenced by the application and discarded due to
garbage collection. In this case, no event is emitted.
Track objects as they move from persistent to detached using the
SessionEvents.persistent_to_detached()
event:
@event.listens_for(sessionmaker, "persistent_to_detached")
def intercept_persistent_to_detached(session, object_):
print("object became detached: %s" % object_)
Detached to Persistent¶
The detached object becomes persistent when it is re-associated with a
session using the Session.add()
or equivalent method. Track
objects moving back to persistent from detached using the
SessionEvents.detached_to_persistent()
event:
@event.listens_for(sessionmaker, "detached_to_persistent")
def intercept_detached_to_persistent(session, object_):
print("object became persistent again: %s" % object_)
Deleted to Persistent¶
The deleted object can be reverted to the persistent
state when the transaction in which it was DELETEd was rolled back
using the Session.rollback()
method. Track deleted objects
moving back to the persistent state using the
SessionEvents.deleted_to_persistent()
event:
@event.listens_for(sessionmaker, "deleted_to_persistent")
def intercept_deleted_to_persistent(session, object_):
print("deleted to persistent: %s" % object_)
Transaction Events¶
Transaction events allow an application to be notified when transaction
boundaries occur at the Session
level as well as when the
Session
changes the transactional state on Connection
objects.
SessionEvents.after_transaction_create()
,SessionEvents.after_transaction_end()
- these events track the logical transaction scopes of theSession
in a way that is not specific to individual database connections. These events are intended to help with integration of transaction-tracking systems such aszope.sqlalchemy
. Use these events when the application needs to align some external scope with the transactional scope of theSession
. These hooks mirror the “nested” transactional behavior of theSession
, in that they track logical “subtransactions” as well as “nested” (e.g. SAVEPOINT) transactions.SessionEvents.before_commit()
,SessionEvents.after_commit()
,SessionEvents.after_begin()
,SessionEvents.after_rollback()
,SessionEvents.after_soft_rollback()
- These events allow tracking of transaction events from the perspective of database connections.SessionEvents.after_begin()
in particular is a per-connection event; aSession
that maintains more than one connection will emit this event for each connection individually as those connections become used within the current transaction. The rollback and commit events then refer to when the DBAPI connections themselves have received rollback or commit instructions directly.
Attribute Change Events¶
The attribute change events allow interception of when specific attributes
on an object are modified. These events include AttributeEvents.set()
,
AttributeEvents.append()
, and AttributeEvents.remove()
. These
events are extremely useful, particularly for per-object validation operations;
however, it is often much more convenient to use a “validator” hook, which
uses these hooks behind the scenes; see Simple Validators for
background on this. The attribute events are also behind the mechanics
of backreferences. An example illustrating use of attribute events
is in Attribute Instrumentation.
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