Event Sourcing in Python¶
A library for event sourcing in Python.
Overview¶
What is event sourcing? One definition suggests the state of an event sourced application is determined by a sequence of events. Another definition has event sourcing as a persistence mechanism for domain driven design. In any case, it is common for the state of a software application to be distributed or partitioned across a set of entities or aggregates in a domain model.
Therefore, this library provides mechanisms useful in event sourced applications: a style for coding entity behaviours that emit events; and a way for the events of an entity to be stored and replayed to obtain the entities on demand.
This documentation provides instructions for installing the package, highlights the main features of the library, includes detailed examples of usage, describes the design of the software, and has some background information about the project.
This project is hosted on GitHub. Please register any issues, questions, and requests on GitHub.
Background¶
Although the event sourcing patterns are each quite simple, and they can be reproduced in code for each project, they do suggest cohesive mechanisms, for example applying and publishing the events generated within domain entities, storing and retrieving selections of the events in a highly scalable manner, replaying the stored events for a particular entity to obtain the current state, and projecting views of the event stream that are persisted in other models.
Therefore, quoting from Eric Evans’ book about domain-driven design:
“Partition a conceptually COHESIVE MECHANISM into a separate lightweight framework. Particularly watch for formalisms for well-documented categories of algorithms. Expose the capabilities of the framework with an INTENTION-REVEALING INTERFACE. Now the other elements of the domain can focus on expressing the problem (‘what’), delegating the intricacies of the solution (‘how’) to the framework.”
Inspiration:
- Martin Fowler’s article on event sourcing
- Greg Young’s discussions about event sourcing, and EventStore system
- Robert Smallshire’s brilliant example on Bitbucket
- Various professional projects that called for this approach, for which I didn’t want to rewrite the same things each time
See also:
- Evaluation of using NoSQL databases in an event sourcing system by Johan Rothsberg
- Object-relational impedance mismatch page on Wikipedia
- An introduction to event storming by a Steven Lowe, principal consultant developer at ThoughtWorks.
Quick start¶
This section shows how to write a very simple event sourced application using classes from the library. It shows the overall structure that is elaborated in the user guide.
Please use pip to install the library with the ‘sqlalchemy’ option.
pip install eventsourcing[sqlalchemy]
Domain¶
Firstly, import the example entity class Example
and its factory function create_new_example().
from eventsourcing.example.domainmodel import create_new_example, Example
These classes will be used as the domain model in this example.
Infrastructure¶
Next, setup an SQLite database in memory, using library classes
SQLAlchemyDatastore, with
SQLAlchemySettings and
IntegerSequencedItemRecord.
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
from eventsourcing.infrastructure.sqlalchemy.activerecords import IntegerSequencedItemRecord
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(IntegerSequencedItemRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Application¶
Finally, define an application object factory, that constructs an application object from library
class ApplicationWithPersistencePolicies.
The application class happens to take an active record strategy object and a session object.
The active record strategy is an instance of class
SQLAlchemyActiveRecordStrategy.
The session object is an argument of the application factory, and will be a normal
SQLAlchemy session object.
from eventsourcing.application.base import ApplicationWithPersistencePolicies
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sequenceditem import SequencedItem
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
def construct_application(session):
app = ApplicationWithPersistencePolicies(
entity_active_record_strategy=SQLAlchemyActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
session=session
)
)
app.example_repository = EventSourcedRepository(
event_store=app.entity_event_store,
mutator=Example._mutate,
)
return app
An example repository constructed from class
EventSourcedRepository,
and is assigned to the application object attribute example_repository. It is possible
to subclass the library application class, and extend it by constructing entity
repositories in the __init__(), we just didn’t do that here.
Run the code¶
Now, use the application to create, read, update, and delete “example” entities.
with construct_application(datastore.session) as app:
# Create.
example = create_new_example(foo='bar')
# Read.
assert example.id in app.example_repository
assert app.example_repository[example.id].foo == 'bar'
# Update.
example.foo = 'baz'
assert app.example_repository[example.id].foo == 'baz'
# Delete.
example.discard()
assert example.id not in app.example_repository
Installation¶
Use pip to install the library from the Python Package Index.
pip install eventsourcing
If you want to use SQLAlchemy, then please install the library with the ‘sqlalchemy’ option.
pip install eventsourcing[sqlalchemy]
Similarly, if you want to use Cassandra, please install with the ‘cassandra’ option.
pip install eventsourcing[cassandra]
If you want to use encryption, please install with the ‘crypto’ option.
pip install eventsourcing[crypto]
You can install combinations of options at the same time, for exampe the follow command will install dependencies for Cassandra and for encryption.
pip install eventsourcing[cassandra,crypto]
Running the install command with different options will just install the extra dependencies associated with that option. If you installed without any options, you can easily install optional dependencies later by running the install command again with the options you want.
Features¶
Generic event store — appends and retrieves domain events. The event store uses a sequenced item mapper with an active record strategy to map domain events to a database in ways that can be easily extended and replaced.
Snapshotting — avoids replaying an entire event stream to obtain the state of an entity. A snapshot strategy is included which reuses the capabilities of this library by implementing snapshots as events.
Application-level encryption — encrypts and decrypts stored events, using a cipher strategy passed as an option to the sequenced item mapper. Can be used to encrypt some events, or all events, or not applied at all (the default).
Optimistic concurrency control — can be used to ensure a distributed or horizontally scaled application doesn’t become inconsistent due to concurrent method execution. Leverages any optimistic concurrency controls in the database adapted by the active record strategy.
Abstract base classes — suggest how to structure an event sourced application. The library has base classes for application objects, domain entities, entity repositories, domain events of various types, mapping strategies, snapshotting strategies, cipher strategies, etc. They are well factored, relatively simple, and can be easily extended for your own purposes. If you wanted to create a domain model that is entirely stand-alone (recommended by purists for maximum longevity), you might start by replicating the library classes.
Worked examples — a simple example application, with an example entity class, example domain events, an example factory method, an example mutator function, and an example database table.
User guide¶
This guide describes how to write an event sourced application, using classes in this library.
In the first section, a stand-alone event sourced domain model is developed, along with an application object that has minimal dependencies on library infrastructure classes for storing events. In later sections, more use is made of library classes, in order to introduce the other capabilities of the library.
All the examples in this guide follow the layered architecture: application, domain, infrastructure. To create working programs, simply copy all the code snippets from a section into a Python file.
Please feel free to experiment by making variations. The code snippets in this guide are covered by a test case, so please expect everything to work as presented - raise an issue if something goes wrong.
Example application¶
Install the library with the ‘sqlalchemy’ option.
pip install eventsourcing[sqlalchemy]
In this section, an event sourced application is developed that has minimal dependencies on the library.
A stand-alone domain model is developed without library classes, which shows how event sourcing in Python can work. The stand-alone code examples here are simplified versions of the library classes. Infrastructure classes from the library are used explicitly to show the different components involved, so you can understand how to make variations.
Domain¶
Let’s start with the domain model. If the state of an event sourced application is determined by a sequence of events, then we need to define some events.
Domain events¶
You may wish to use a technique such as “event storming” to identify or decide what happens in your domain. In this example, for the sake of general familiarity let’s assume we have a domain in which things can be “created”, “changed”, and “discarded”. With that in mind, we can begin to write some domain event classes.
In the example below, there are three domain event classes: Created,
AttributeChanged, and Discarded. The common aspects of the domain
event classes have been pulled up to a layer supertype DomainEvent.
import time
class DomainEvent(object):
"""
Layer supertype.
"""
def __init__(self, originator_id, originator_version, **kwargs):
self.originator_id = originator_id
self.originator_version = originator_version
self.__dict__.update(kwargs)
class Created(DomainEvent):
"""
Published when an entity is created.
"""
def __init__(self, **kwargs):
super(Created, self).__init__(originator_version=0, **kwargs)
class AttributeChanged(DomainEvent):
"""
Published when an attribute value is changed.
"""
def __init__(self, name, value, **kwargs):
super(AttributeChanged, self).__init__(**kwargs)
self.name = name
self.value = value
class Discarded(DomainEvent):
"""
Published when an entity is discarded.
"""
Please note, the domain event classes above do not depend on the library. The library does
however contain a collection of different kinds of domain event classes that you can use
in your models, for example see
Created,
AttributeChanged, and
Discarded.
Publish-subscribe¶
Since we are dealing with events, let’s define a simple publish-subscribe mechanism for them.
subscribers = []
def publish(event):
for subscriber in subscribers:
subscriber(event)
def subscribe(subscriber):
subscribers.append(subscriber)
def unsubscribe(subscriber):
subscribers.remove(subscriber)
Domain entity¶
Now, let’s define a domain entity that publishes the event classes defined above.
The entity class Example below has an ID and a version number. It also
has a property foo with a “setter” method, and a method discard() to use
when the entity is no longer needed.
The entity methods follow a similar pattern. At some point, each
constructs an event that represents the result of the operation.
Then each uses a “mutator function” mutate() (see below) to
apply the event to the entity. Finally, each publishes the event
for the benefit of any subscribers, by using the function publish().
import uuid
class Example(object):
"""
Example domain entity.
"""
def __init__(self, originator_id, originator_version=0, foo=''):
self._id = originator_id
self._version = originator_version
self._is_discarded = False
self._foo = foo
@property
def id(self):
return self._id
@property
def version(self):
return self._version
@property
def foo(self):
return self._foo
@foo.setter
def foo(self, value):
assert not self._is_discarded
# Construct an 'AttributeChanged' event object.
event = AttributeChanged(
originator_id=self.id,
originator_version=self.version,
name='foo',
value=value,
)
# Apply the event to self.
mutate(self, event)
# Publish the event for others.
publish(event)
def discard(self):
assert not self._is_discarded
# Construct a 'Discarded' event object.
event = Discarded(
originator_id=self.id,
originator_version=self.version
)
# Apply the event to self.
mutate(self, event)
# Publish the event for others.
publish(event)
A factory can be used to create new “example” entities. The function
create_new_example() below works in a similar way to the entity
methods, creating new entities by firstly constructing a Created
event, then using the function mutate() (see below) to construct the entity
object, and finally publishing the event for others before returning
the new entity object to the caller.
def create_new_example(foo):
"""
Factory for Example entities.
"""
# Construct an entity ID.
entity_id = uuid.uuid4()
# Construct a 'Created' event object.
event = Created(
originator_id=entity_id,
foo=foo
)
# Use the mutator function to construct the entity object.
entity = mutate(None, event)
# Publish the event for others.
publish(event=event)
# Return the new entity.
return entity
The example entity class does not depend on the library. In particular, it doesn’t
inherit from a “magical” entity base class that makes everything work. The example
here just publishes events that it has applied to itself. The library does however
contain domain entity classes that you can use to build your domain model, for
example the class AggregateRoot.
The library classes are more developed than the examples here.
Mutator function¶
The mutator function mutate() below handles Created events by constructing
an object. It handles AttributeChanged events by setting an attribute value, and it
handles Discarded events by marking the entity as discarded. Each handler increases the
version of the entity, so that the version of the entity is always one plus the
the originator version of the last event that was applied.
When replaying a sequence of events, for example when reconstructing an entity from its domain events, the mutator function is called many times in order to apply each event in the sequence to an evolving initial state.
def mutate(entity, event):
"""
Mutator function for Example entities.
"""
# Handle "created" events by constructing the entity object.
if isinstance(event, Created):
entity = Example(**event.__dict__)
entity._version += 1
return entity
# Handle "value changed" events by setting the named value.
elif isinstance(event, AttributeChanged):
assert not entity._is_discarded
setattr(entity, '_' + event.name, event.value)
entity._version += 1
return entity
# Handle "discarded" events by returning 'None'.
elif isinstance(event, Discarded):
assert not entity._is_discarded
entity._version += 1
entity._is_discarded = True
return None
else:
raise NotImplementedError(type(event))
For the sake of simplicity in this example, we’ll use an if-else block to structure
the mutator function. The library has a function decorator
mutator() that allows handlers
for different types of event to be registered with a default mutator function,
just like singledispatch.
Run the code¶
Let’s firstly subscribe to receive the events that will be published, so we can see what happened.
# A list of received events.
received_events = []
# Subscribe to receive published events.
subscribe(lambda e: received_events.append(e))
With this stand-alone code, we can create a new example entity object. We can update its property
foo, and we can discard the entity using the discard() method.
# Create a new entity using the factory.
entity = create_new_example(foo='bar')
# Check the entity has an ID.
assert entity.id
# Check the entity has a version number.
assert entity.version == 1
# Check the received events.
assert len(received_events) == 1, received_events
assert isinstance(received_events[0], Created)
assert received_events[0].originator_id == entity.id
assert received_events[0].originator_version == 0
assert received_events[0].foo == 'bar'
# Check the value of property 'foo'.
assert entity.foo == 'bar'
# Update property 'foo'.
entity.foo = 'baz'
# Check the new value of 'foo'.
assert entity.foo == 'baz'
# Check the version number has increased.
assert entity.version == 2
# Check the received events.
assert len(received_events) == 2, received_events
assert isinstance(received_events[1], AttributeChanged)
assert received_events[1].originator_version == 1
assert received_events[1].name == 'foo'
assert received_events[1].value == 'baz'
Infrastructure¶
Since the application state is determined by a sequence of events, the application must somehow be able both to persist the events, and then recover the entities.
Please note, storing and replaying events to persist and to reconstruct the state of an application is the primary capability of this library. The domain and application and interface capabilities are offered as a supplement to the infrastructural capabilities, and have been added to the library partly as a way of shaping and validating the infrastructure, partly to demonstrate how the core capabilities may be applied, but also as a convenient way of reusing foundational code so that attention can remain on the problem domain (framework).
Database table¶
Let’s start by setting up a simple database table that can store sequences of items. We can use SQLAlchemy directly to define a database table that stores items in sequences, with a single identity for each sequence, and with each item positioned in its sequence by an integer index number.
from sqlalchemy.ext.declarative.api import declarative_base
from sqlalchemy.sql.schema import Column, Sequence, Index
from sqlalchemy.sql.sqltypes import BigInteger, Integer, String, Text
from sqlalchemy_utils import UUIDType
ActiveRecord = declarative_base()
class SequencedItemRecord(ActiveRecord):
__tablename__ = 'sequenced_items'
# Sequence ID (e.g. an entity or aggregate ID).
sequence_id = Column(UUIDType(), primary_key=True)
# Position (index) of item in sequence.
position = Column(BigInteger(), primary_key=True)
# Topic of the item (e.g. path to domain event class).
topic = Column(String(255))
# State of the item (serialized dict, possibly encrypted).
data = Column(Text())
__table_args__ = Index('index', 'sequence_id', 'position'),
The library has a class
IntegerSequencedItemRecord
which is very similar to the above.
Next, create the database table. For convenience, the SQLAlchemy objects can be adapted
with the class
SQLAlchemyDatastore, which
provides a simple interface for the two operations we require: setup_connection()
and setup_tables().
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
datastore = SQLAlchemyDatastore(
base=ActiveRecord,
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(SequencedItemRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
As you can see from the uri argument above, this example is using SQLite to manage
an in memory relational database. You can change uri to any valid connection string.
Here are some example connection strings: for an SQLite file; for a PostgreSQL database; and
for a MySQL database. See SQLAlchemy’s create_engine() documentation for details. You may need
to install drivers for your database management system.
sqlite:////tmp/mydatabase
postgresql://scott:tiger@localhost:5432/mydatabase
mysql://scott:tiger@hostname/dbname
Similar to the support for storing events in SQLAlchemy, there are classes in the library for Cassandra. The project djangoevents has support for storing events with this library using the Django ORM. Support for other databases such as DynamoDB is forthcoming.
Event store¶
To support different kinds of sequences in the domain model, and to allow for
different database schemas, the library has an event store class
EventStore that uses
a “sequenced item mapper” for mapping domain events to “sequenced items” - this
library’s archetype persistence model for storing events. The sequenced item
mapper derives the values of sequenced item fields from the attributes of domain
events.
The event store then uses an “active record strategy” to persist the sequenced items into a particular database management system. The active record strategy uses an active record class to manipulate records in a particular database table.
Hence you can use a different database table by substituting an alternative active record class. You can use a different database management system by substituting an alternative active record strategy.
from eventsourcing.infrastructure.eventstore import EventStore
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sequenceditemmapper import SequencedItemMapper
active_record_strategy = SQLAlchemyActiveRecordStrategy(
session=datastore.session,
active_record_class=SequencedItemRecord,
)
sequenced_item_mapper = SequencedItemMapper(
sequence_id_attr_name='originator_id',
position_attr_name='originator_version'
)
event_store = EventStore(
active_record_strategy=active_record_strategy,
sequenced_item_mapper=sequenced_item_mapper
)
In the code above, the sequence_id_attr_name value given to the sequenced item
mapper is the name of the domain events attribute that will be used as the ID
of the mapped sequenced item, The position_attr_name argument informs the
sequenced item mapper which event attribute should be used to position the item
in the sequence. The values originator_id and originator_version correspond
to attributes of the domain event classes we defined in the domain model section above.
Entity repository¶
It is common to retrieve entities from a repository. An event sourced repository
for the example entity class can be constructed directly using library class
EventSourcedRepository.
The repository is given the mutator function mutate() and the event store.
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
example_repository = EventSourcedRepository(
event_store=event_store,
mutator=mutate
)
Run the code¶
Now, let’s firstly write the events we received earlier into the event store.
# Put each received event into the event store.
for event in received_events:
event_store.append(event)
# Check the events exist in the event store.
stored_events = event_store.get_domain_events(entity.id)
assert len(stored_events) == 2, (received_events, stored_events)
The entity can now be retrieved from the repository, using its dictionary-like interface.
retrieved_entity = example_repository[entity.id]
assert retrieved_entity.foo == 'baz'
Sequenced items¶
Remember that we can always get the sequenced items directly from the active record
strategy. A sequenced item is tuple containing a serialised representation of the
domain event. The library class
SequencedItem is a Python namedtuple
with four fields: sequence_id, position, topic, and data.
In this example, an event’s originator_id attribute is mapped to the sequence_id
field, and the event’s originator_version attribute is mapped to the position
field. The topic field of a sequenced item is used to identify the event class, and
the data field represents the state of the event (normally a JSON string).
sequenced_items = event_store.active_record_strategy.get_items(entity.id)
assert len(sequenced_items) == 2
assert sequenced_items[0].sequence_id == entity.id
assert sequenced_items[0].position == 0
assert 'Created' in sequenced_items[0].topic
assert 'bar' in sequenced_items[0].data
assert sequenced_items[1].sequence_id == entity.id
assert sequenced_items[1].position == 1
assert 'AttributeChanged' in sequenced_items[1].topic
assert 'baz' in sequenced_items[1].data
These are just default names. If it matters in your context that the persistence model uses other names, then you can use a different sequenced item type which either extends or replaces the fields above.
Application¶
Although we can do everything at the module level, an application object brings
it all together. In the example below, the class ExampleApplication has an
event store, and an entity repository. The application also has a persistence policy.
Persistence Policy¶
The persistence policy below subscribes to receive events whenever they are published. It uses an event store to store events whenever they are received.
class PersistencePolicy(object):
def __init__(self, event_store):
self.event_store = event_store
subscribe(self.store_event)
def close(self):
unsubscribe(self.store_event)
def store_event(self, event):
self.event_store.append(event)
A slightly more developed class PersistencePolicy
is included in the library.
Application object¶
As a convenience, it is useful to make the application function as a Python context manager, so that the application can close the persistence policy, and unsubscribe from receiving further domain events.
class ExampleApplication(object):
def __init__(self, session):
# Construct event store.
self.event_store = EventStore(
active_record_strategy=SQLAlchemyActiveRecordStrategy(
active_record_class=SequencedItemRecord,
session=session,
),
sequenced_item_mapper=SequencedItemMapper(
sequence_id_attr_name='originator_id',
position_attr_name='originator_version'
)
)
# Construct persistence policy.
self.persistence_policy = PersistencePolicy(
event_store=self.event_store
)
# Construct example repository.
self.example_repository = EventSourcedRepository(
event_store=self.event_store,
mutator=mutate
)
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.persistence_policy.close()
A more developed class ExampleApplication
can be found in the library. It is used in later sections of this guide.
Run the code¶
With the application object, we can create more example entities and expect they will be available immediately in the repository.
Please note, an entity that has been discarded by using its discard() method
cannot subsequently be retrieved from the repository using its ID. In particular,
the repository’s dictionary-like interface will raise a Python KeyError
exception instead of returning an entity.
with ExampleApplication(datastore.session) as app:
# Create a new entity.
example = create_new_example(foo='bar')
# Read.
assert example.id in app.example_repository
assert app.example_repository[example.id].foo == 'bar'
# Update.
example.foo = 'baz'
assert app.example_repository[example.id].foo == 'baz'
# Delete.
example.discard()
assert example.id not in app.example_repository
Congratulations. You have created yourself an event sourced application.
Snapshotting¶
To enable snapshots to be used when recovering an entity from a repository, construct an entity repository that has a snapshot strategy object (see below). It is recommended to store snapshots in a dedicated table.
To automatically generate snapshots, you could perhaps define a snapshotting policy, to take snapshots whenever a particular condition occurs.
Domain¶
To avoid duplicating code from the previous section, let’s
use the example entity class Example
and its factory function create_new_example()
from the library.
from eventsourcing.example.domainmodel import Example, create_new_example
Infrastructure¶
It is recommended not to store snapshots within the entity’s sequence of events,
but in a dedicated table for snapshots. So let’s setup a dedicated table
for snapshots using the library class
SnapshotRecord,
as well as a table for the events of the entity.
from eventsourcing.infrastructure.sqlalchemy.activerecords import IntegerSequencedItemRecord, SnapshotRecord
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemyDatastore, SQLAlchemySettings
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(IntegerSequencedItemRecord, SnapshotRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Application¶
Policy¶
Now let’s define a snapshotting policy object, so that snapshots of example entities are taken every so many events.
The class ExampleSnapshottingPolicy below will take a snapshot of
the example entities every period number of events, so that there will
never be more than period number of events to replay when recovering the
entity. The default value of 2 is effective in the example below.
from eventsourcing.domain.model.events import subscribe, unsubscribe
class ExampleSnapshottingPolicy(object):
def __init__(self, example_repository, period=2):
self.example_repository = example_repository
self.period = period
subscribe(predicate=self.trigger, handler=self.take_snapshot)
def close(self):
unsubscribe(predicate=self.trigger, handler=self.take_snapshot)
def trigger(self, event):
return isinstance(event, Example.Event) and not (event.originator_version + 1) % self.period
def take_snapshot(self, event):
self.example_repository.take_snapshot(event.originator_id, lte=event.originator_version)
Because the event’s originator_version is passed to the method take_snapshot(),
with the argument lte, the snapshot will reflect the entity as it existed just after
the event was applied. Even if a different thread operates on the same entity before the
snapshot is taken, the resulting snapshot is the same as it would have been otherwise.
Application object¶
The application class below extends the library class
ApplicationWithPersistencePolicies,
which constructs the event stores and persistence policies we need. The supertype
has a policy to persist snapshots whenever they are taken. It also has as a policy
to persist the events of entities whenever they are published.
The example entity repository is constructed from library class
EventSourcedRepository
with a snapshot strategy, the integer sequenced event store, and a mutator function.
The snapshot strategy is constructed from library class
EventSourcedSnapshotStrategy
with an event store for snapshots that is provided by the supertype.
The application’s snapshotting policy is constructed with the example repository, which it needs in order to take snapshots.
from eventsourcing.application.base import ApplicationWithPersistencePolicies
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
from eventsourcing.infrastructure.snapshotting import EventSourcedSnapshotStrategy
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
class SnapshottedApplication(ApplicationWithPersistencePolicies):
def __init__(self, session):
# Construct event stores and persistence policies.
entity_active_record_strategy = SQLAlchemyActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
session=session,
)
snapshot_active_record_strategy = SQLAlchemyActiveRecordStrategy(
active_record_class=SnapshotRecord,
session=session,
)
super(SnapshottedApplication, self).__init__(
entity_active_record_strategy=entity_active_record_strategy,
snapshot_active_record_strategy=snapshot_active_record_strategy,
)
# Construct snapshot strategy.
self.snapshot_strategy = EventSourcedSnapshotStrategy(
event_store=self.snapshot_event_store
)
# Construct the entity repository, this time with the snapshot strategy.
self.example_repository = EventSourcedRepository(
event_store=self.entity_event_store,
mutator=Example._mutate,
snapshot_strategy=self.snapshot_strategy
)
# Construct the snapshotting policy.
self.snapshotting_policy = ExampleSnapshottingPolicy(
example_repository=self.example_repository,
)
def create_new_example(self, foo):
return create_new_example(foo=foo)
def close(self):
super(SnapshottedApplication, self).close()
self.snapshotting_policy.close()
Run the code¶
The application object can be used in the same way as before. Now snapshots of an example entity will be taken every second event.
with SnapshottedApplication(datastore.session) as app:
# Create an entity.
entity = app.create_new_example(foo='bar1')
# Check there's no snapshot, only one event so far.
snapshot = app.snapshot_strategy.get_snapshot(entity.id)
assert snapshot is None
# Change an attribute, generates a second event.
entity.foo = 'bar2'
# Check the snapshot.
snapshot = app.snapshot_strategy.get_snapshot(entity.id)
assert snapshot.state['_foo'] == 'bar2'
# Check can recover entity using snapshot.
assert entity.id in app.example_repository
assert app.example_repository[entity.id].foo == 'bar2'
# Check snapshot after five events.
entity.foo = 'bar3'
entity.foo = 'bar4'
entity.foo = 'bar5'
snapshot = app.snapshot_strategy.get_snapshot(entity.id)
assert snapshot.state['_foo'] == 'bar4'
# Check snapshot after seven events.
entity.foo = 'bar6'
entity.foo = 'bar7'
assert app.example_repository[entity.id].foo == 'bar7'
snapshot = app.snapshot_strategy.get_snapshot(entity.id)
assert snapshot.state['_foo'] == 'bar6'
# Check snapshot state is None after discarding the entity on the eighth event.
entity.discard()
assert entity.id not in app.example_repository
snapshot = app.snapshot_strategy.get_snapshot(entity.id)
assert snapshot.state is None
try:
app.example_repository[entity.id]
except KeyError:
pass
else:
raise Exception('KeyError was not raised')
# Get historical snapshots.
snapshot = app.snapshot_strategy.get_snapshot(entity.id, lte=2)
assert snapshot.state['_version'] == 2 # one behind
assert snapshot.state['_foo'] == 'bar2'
snapshot = app.snapshot_strategy.get_snapshot(entity.id, lte=3)
assert snapshot.state['_version'] == 4
assert snapshot.state['_foo'] == 'bar4'
# Get historical entities.
entity = app.example_repository.get_entity(entity.id, lte=0)
assert entity.version == 1
assert entity.foo == 'bar1', entity.foo
entity = app.example_repository.get_entity(entity.id, lte=1)
assert entity.version == 2
assert entity.foo == 'bar2', entity.foo
entity = app.example_repository.get_entity(entity.id, lte=2)
assert entity.version == 3
assert entity.foo == 'bar3', entity.foo
entity = app.example_repository.get_entity(entity.id, lte=3)
assert entity.version == 4
assert entity.foo == 'bar4', entity.foo
Aggregates in DDD¶
Eric Evans’ book Domain Driven Design describes an abstraction called “aggregate”:
“An aggregate is a cluster of associated objects that we treat as a unit for the purpose of data changes. Each aggregate has a root and a boundary.”
Therefore,
“Cluster the entities and value objects into aggregates and define boundaries around each. Choose one entity to be the root of each aggregate, and control all access to the objects inside the boundary through the root. Allow external objects to hold references to the root only.”
Which seems to suggest an event sourced aggregate must have a set of events and a mutator function that pertain to a cluster of objects within a boundary. Also an entity that can function as the root of the cluster of objects, with identity distinguishable across the application, and methods that exclusively operate on the objects of the aggregate.
Since one command may result in several events, it is also important never to persist only some events that result from executing a command. And so events must be appended to the event store in a single atomic transaction, so that if some of the events resulting from executing a command cannot be stored then none of them will be stored.
Aggregate root¶
Let’s define an aggregate root using class TimestampedVersionedEntity
from the library. The Example class used in the previous
section on snapshotting also derives from TimestampedVersionedEntity.
The example aggregate root class below defines (as as inner class) the
domain event class ExampleCreated which will be published by the aggregate
when creating “example” objects, and a method count_examples() that
can operate on all the “example” objects of the aggregate.
from eventsourcing.domain.model.entity import TimestampedVersionedEntity
class ExampleAggregateRoot(TimestampedVersionedEntity):
"""
Root entity of example aggregate.
"""
class Event(TimestampedVersionedEntity.Event):
"""Layer supertype."""
class Created(Event, TimestampedVersionedEntity.Created):
"""Published when aggregate is created."""
class Discarded(Event, TimestampedVersionedEntity.Discarded):
"""Published when aggregate is discarded."""
class ExampleCreated(Event):
"""Published when an "example" object in the aggregate is created."""
def __init__(self, **kwargs):
super(ExampleAggregateRoot, self).__init__(**kwargs)
self._pending_events = []
self._examples = {}
def count_examples(self):
return len(self._examples)
def create_new_example(self):
assert not self._is_discarded
event = ExampleAggregateRoot.ExampleCreated(
example_id=uuid.uuid4(),
originator_id=self.id,
originator_version=self.version,
)
mutate_aggregate(self, event)
self._publish(event)
def _publish(self, event):
self._pending_events.append(event)
def save(self):
publish(self._pending_events[:])
self._pending_events = []
class Example(object):
"""
Example entity, exists only within the example aggregate boundary.
"""
def __init__(self, example_id):
self._id = example_id
@property
def id(self):
return self._id
The methods of the aggregate, and the factory below, are similar to previous
examples. But instead of immediately publishing events using the publish()
function, the events are appended to an internal list of pending events
using the aggregate’s method _publish(). The aggregate then has a save()
method which is used to publish all the pending events in a single list using
the function publish().
As before, we’ll also need a factory and a mutator function. The factory function here works in the same way as before.
def create_example_aggregate():
"""
Factory function for example aggregate.
"""
# Construct event.
event = ExampleAggregateRoot.Created(originator_id=uuid.uuid4())
# Mutate aggregate.
aggregate = mutate_aggregate(aggregate=None, event=event)
# Publish event to internal list only.
aggregate._publish(event)
# Return the new aggregate object.
return aggregate
The mutator function mutate_aggregate() below handles events Created and
Discarded similarly to the previous examples. It also handles ExampleCreated,
by constructing an object class Example that it adds to the aggregate’s internal
collection of examples.
def mutate_aggregate(aggregate, event):
"""
Mutator function for example aggregate.
"""
# Handle "created" events by constructing the aggregate object.
if isinstance(event, ExampleAggregateRoot.Created):
aggregate = ExampleAggregateRoot(**event.__dict__)
aggregate._version += 1
return aggregate
# Handle "example entity created" events by adding a new entity
# to the aggregate's dict of entities.
elif isinstance(event, ExampleAggregateRoot.ExampleCreated):
aggregate._assert_not_discarded()
entity = Example(example_id=event.example_id)
aggregate._examples[str(entity.id)] = entity
aggregate._version += 1
aggregate._last_modified_on = event.timestamp
return aggregate
# Handle "discarded" events by returning 'None'.
elif isinstance(event, ExampleAggregateRoot.Discarded):
aggregate._assert_not_discarded()
aggregate._version += 1
aggregate._is_discarded = True
return None
else:
raise NotImplementedError(type(event))
Application and infrastructure¶
Set up a database table using library classes.
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
from eventsourcing.infrastructure.sqlalchemy.activerecords import IntegerSequencedItemRecord
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(IntegerSequencedItemRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Define an application class that uses the domain model code above, and infrastructure and policy classes from the library.
import uuid
import time
from eventsourcing.application.policies import PersistencePolicy
from eventsourcing.domain.model.events import publish
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
from eventsourcing.infrastructure.eventstore import EventStore
from eventsourcing.infrastructure.sequenceditemmapper import SequencedItemMapper
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
class ExampleDDDApplication(object):
def __init__(self, session):
self.event_store = EventStore(
active_record_strategy=SQLAlchemyActiveRecordStrategy(
session=session,
active_record_class=IntegerSequencedItemRecord,
),
sequenced_item_mapper=SequencedItemMapper(
sequence_id_attr_name='originator_id',
position_attr_name='originator_version',
)
)
self.aggregate_repository = EventSourcedRepository(
event_store=self.event_store,
mutator=mutate_aggregate,
)
self.persistence_policy = PersistencePolicy(
event_store=self.event_store,
event_type=ExampleAggregateRoot.Event
)
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.persistence_policy.close()
Run the code¶
The application can be used to create new aggregates, and aggregates can be used to
create new entities. Events are published in batches when the aggregate’s save()
method is called.
with ExampleDDDApplication(datastore.session) as app:
# Create a new aggregate.
aggregate = create_example_aggregate()
aggregate.save()
# Check it exists in the repository.
assert aggregate.id in app.aggregate_repository, aggregate.id
# Check the aggregate has zero entities.
assert aggregate.count_examples() == 0
# Check the aggregate has zero entities.
assert aggregate.count_examples() == 0
# Ask the aggregate to create an entity within itself.
aggregate.create_new_example()
# Check the aggregate has one entity.
assert aggregate.count_examples() == 1
# Check the aggregate in the repo still has zero entities.
assert app.aggregate_repository[aggregate.id].count_examples() == 0
# Call save().
aggregate.save()
# Check the aggregate in the repo now has one entity.
assert app.aggregate_repository[aggregate.id].count_examples() == 1
# Create two more entities within the aggregate.
aggregate.create_new_example()
aggregate.create_new_example()
# Save both "entity created" events in one atomic transaction.
aggregate.save()
# Check the aggregate in the repo now has three entities.
assert app.aggregate_repository[aggregate.id].count_examples() == 3
# Discard the aggregate, but don't call save() yet.
aggregate.discard()
# Check the aggregate still exists in the repo.
assert aggregate.id in app.aggregate_repository
# Call save().
aggregate.save()
# Check the aggregate no longer exists in the repo.
assert aggregate.id not in app.aggregate_repository
The library has an AggregateRoot
class that is slightly more developed than the code in this example.
Application-level encryption¶
Install the library with the ‘crypto’ option.
pip install eventsourcing[crypto]
To enable encryption, pass in a cipher strategy object when constructing
the sequenced item mapper, and set always_encrypt to a True value.
Cipher strategy¶
Let’s firstly construct a cipher strategy object. This example uses the
library AES cipher strategy AESCipher.
The library AES cipher strategy uses the AES cipher from the Python Cryptography Toolkit, by default in CBC mode with 128 bit blocksize and a 16 byte encryption key. It generates a unique 16 byte initialization vector for each encryption. In this cipher strategy, serialized event data is compressed before it is encrypted, which can mean application performance is improved when encryption is enabled.
With encryption enabled, event attribute values are encrypted inside the application before they are mapped to the database. The values are decrypted before domain events are replayed.
from eventsourcing.domain.services.aes_cipher import AESCipher
# Construct the cipher strategy.
aes_key = '0123456789abcdef'
cipher = AESCipher(aes_key)
Application and infrastructure¶
Set up infrastructure using library classes.
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
from eventsourcing.infrastructure.sqlalchemy.activerecords import IntegerSequencedItemRecord
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(IntegerSequencedItemRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Define a factory that uses library classes to construct an application object.
from eventsourcing.example.application import ExampleApplication
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sequenceditem import SequencedItem
def construct_example_application(session, always_encrypt=False, cipher=None):
active_record_strategy = SQLAlchemyActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
session=session
)
app = ExampleApplication(
entity_active_record_strategy=active_record_strategy,
always_encrypt=always_encrypt,
cipher=cipher,
)
return app
Run the code¶
Now construct an encrypted application with the cipher. Create an “example” with some “secret information”. Check the information is not visible in the database, as it is when the application is not encrypted.
# Create a new example entity using an encrypted application.
encrypted_app = construct_example_application(datastore.session, always_encrypt=True, cipher=cipher)
with encrypted_app as app:
secret_entity = app.create_new_example(foo='secret info')
# With encryption enabled, application state is not visible in the database.
event_store = app.entity_event_store
item2 = event_store.active_record_strategy.get_item(secret_entity.id, eq=0)
assert 'secret info' not in item2.data
# Events are decrypted inside the application.
retrieved_entity = app.example_repository[secret_entity.id]
assert 'secret info' in retrieved_entity.foo
# Create a new example entity using an unencrypted application object.
unencrypted_app = construct_example_application(datastore.session)
with unencrypted_app as app:
entity = app.create_new_example(foo='bar')
# Without encryption, application state is visible in the database.
event_store = app.entity_event_store
item1 = event_store.active_record_strategy.get_item(entity.id, 0)
assert 'bar' in item1.data
Optimistic concurrency control¶
Because of the unique constraint on the sequenced item table, it isn’t possible to branch the evolution of an entity and store two events at the same version. Hence, if the entity you are working on has been updated elsewhere, an attempt to update your object will raise a concurrency exception.
Application and infrastructure¶
Set up infrastructure using library classes.
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
from eventsourcing.infrastructure.sqlalchemy.activerecords import IntegerSequencedItemRecord
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(IntegerSequencedItemRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Define a factory that uses library classes to construct an application object.
from eventsourcing.example.application import ExampleApplication
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sequenceditem import SequencedItem
def construct_example_application(session):
active_record_strategy = SQLAlchemyActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
sequenced_item_class=SequencedItem,
session=session
)
app = ExampleApplication(
entity_active_record_strategy=active_record_strategy
)
return app
Run the code¶
Use the application to get two instances of the same entity, and try to change them independently.
from eventsourcing.exceptions import ConcurrencyError
with construct_example_application(datastore.session) as app:
entity = app.create_new_example(foo='bar1')
a = app.example_repository[entity.id]
b = app.example_repository[entity.id]
# Change the entity using instance 'a'.
a.foo = 'bar2'
# Because 'a' has been changed since 'b' was obtained,
# 'b' cannot be updated unless it is firstly refreshed.
try:
b.foo = 'bar3'
except ConcurrencyError:
pass
else:
raise Exception("Failed to control concurrency of 'b'.")
# Refresh object 'b', so that 'b' has the current state of the entity.
b = app.example_repository[entity.id]
assert b.foo == 'bar2'
# Changing the entity using instance 'b' now works because 'b' is up to date.
b.foo = 'bar3'
assert app.example_repository[entity.id].foo == 'bar3'
# Now 'a' does not have the current state of the entity, and cannot be changed.
try:
a.foo = 'bar4'
except ConcurrencyError:
pass
else:
raise Exception("Failed to control concurrency of 'a'.")
Cassandra¶
The Cassandra database management system, which implements the Paxos protocol, can (allegedly) accomplish linearly-scalable distributed optimistic concurrency control, guaranteeing sequential consistency of the events of an entity. It is also possible to serialize calls to the methods of an entity, but that is out of the scope of this package — if you wish to do that, perhaps something like Zookeeper might help.
Alternative schema¶
Stored event model¶
The database schema we have been using so far stores events in a sequence of “sequenced items”, and the names in the database schema reflect that design.
Let’s say we want instead our database records to called “stored events”.
It’s easy to do. Just define a new sequenced item class,
e.g. StoredEvent below, and then supply a suitable
active record class. As before, create the table using the
new active record class, and pass both to the active record
strategy when constructing the application object.
from collections import namedtuple
StoredEvent = namedtuple('StoredEvent', ['aggregate_id', 'aggregate_version', 'event_type', 'state'])
Then define a suitable active record class.
from sqlalchemy.ext.declarative.api import declarative_base
from sqlalchemy.sql.schema import Column, Sequence, Index
from sqlalchemy.sql.sqltypes import BigInteger, Integer, String, Text
from sqlalchemy_utils import UUIDType
Base = declarative_base()
class StoredEventRecord(Base):
__tablename__ = 'stored_events'
# Sequence ID (e.g. an entity or aggregate ID).
aggregate_id = Column(UUIDType(), primary_key=True)
# Position (timestamp) of item in sequence.
aggregate_version = Column(BigInteger(), primary_key=True)
# Type of the event (class name).
event_type = Column(String(100))
# State of the item (serialized dict, possibly encrypted).
state = Column(Text())
__table_args__ = Index('index', 'aggregate_id', 'aggregate_version'),
Application and infrastructure¶
Then redefine the application class to use the new sequenced item and active record classes.
from eventsourcing.application.policies import PersistencePolicy
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
from eventsourcing.infrastructure.eventstore import EventStore
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sequenceditem import SequencedItem
from eventsourcing.infrastructure.sequenceditemmapper import SequencedItemMapper
from eventsourcing.example.domainmodel import Example, create_new_example
class Application(object):
def __init__(self, session):
self.event_store = EventStore(
active_record_strategy=SQLAlchemyActiveRecordStrategy(
session=session,
active_record_class=StoredEventRecord,
sequenced_item_class=StoredEvent,
),
sequenced_item_mapper=SequencedItemMapper(
sequenced_item_class=StoredEvent,
sequence_id_attr_name='originator_id',
position_attr_name='originator_version',
)
)
self.example_repository = EventSourcedRepository(
event_store=self.event_store,
mutator=Example._mutate,
)
self.persistence_policy = PersistencePolicy(self.event_store, event_type=Example.Event)
def create_example(self, foo):
return create_new_example(foo=foo)
def close(self):
self.persistence_policy.close()
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
Set up the database.
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemySettings, SQLAlchemyDatastore
datastore = SQLAlchemyDatastore(
base=Base,
settings=SQLAlchemySettings(uri='sqlite:///:memory:'),
tables=(StoredEventRecord,),
)
datastore.setup_connection()
datastore.setup_tables()
Run the code¶
Then you can use the application to create, read, update, and discard. And your events will be stored as “stored events” rather than “sequenced items”.
with Application(datastore.session) as app:
# Create.
example = create_new_example(foo='bar')
# Read.
assert example.id in app.example_repository
assert app.example_repository[example.id].foo == 'bar'
# Update.
example.foo = 'baz'
assert app.example_repository[example.id].foo == 'baz'
# Delete.
example.discard()
assert example.id not in app.example_repository
Applause djangoevents project¶
It is possible to replace more aspects of the library, to make a more customized application. The excellent project djangoevents by Applause is a Django app that provides a neat way of taking an event sourcing approach in a Django project. It allows this library to be used seamlessly with Django, by using the Django ORM to store events. Using djangoevents is well documented in the README file. It adds some nice enhancements to the capabilities of this library, and shows how various components can be extended or replaced. Please note, the djangoevents project currently works with a previous version of this library.
Using Cassandra¶
Install the library with the ‘cassandra’ option.
pip install eventsourcing[cassandra]
Infrastructure¶
Set up the connection and the database tables, using the library classes for Cassandra.
If you are using default settings, make sure you have a Cassandra server available at
port 9042. Please investigate the library class
CassandraSettings for
information about configuring away from default settings.
from eventsourcing.infrastructure.cassandra.datastore import CassandraSettings, CassandraDatastore
from eventsourcing.infrastructure.cassandra.activerecords import IntegerSequencedItemRecord
cassandra_datastore = CassandraDatastore(
settings=CassandraSettings(),
tables=(IntegerSequencedItemRecord,),
)
cassandra_datastore.setup_connection()
cassandra_datastore.setup_tables()
Application object¶
Define a factory that uses library classes for Cassandra to construct an application object.
from eventsourcing.example.application import ExampleApplication
from eventsourcing.infrastructure.cassandra.activerecords import CassandraActiveRecordStrategy
def construct_application():
active_record_strategy = CassandraActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
)
app = ExampleApplication(
entity_active_record_strategy=active_record_strategy,
)
return app
Run the code¶
The application can be used to create, read, update, and delete entities in Cassandra.
with construct_application() as app:
# Create.
example = app.create_new_example(foo='bar')
# Read.
assert example.id in app.example_repository
assert app.example_repository[example.id].foo == 'bar'
# Update.
example.foo = 'baz'
assert app.example_repository[example.id].foo == 'baz'
# Delete.
example.discard()
assert example.id not in app.example_repository
Everything in one app¶
In this example, an application is developed that includes all of the aspects introduced in previous sections. The application has aggregates with a root entity that controls a cluster of entities and value objects, and which publishes events in batches. Aggregate events are stored using Cassandra, with application level encryption, and with snapshotting at regular intervals. The tests at the bottom demonstrate that it works.
Domain¶
Aggregate model¶
from eventsourcing.domain.model.decorators import attribute
from eventsourcing.domain.model.entity import TimestampedVersionedEntity
from eventsourcing.domain.model.events import publish, subscribe, unsubscribe
class ExampleAggregateRoot(TimestampedVersionedEntity):
"""
Root entity of example aggregate.
"""
class Event(TimestampedVersionedEntity.Event):
"""Layer supertype."""
class Created(Event, TimestampedVersionedEntity.Created):
"""Published when aggregate is created."""
class AttributeChanged(Event, TimestampedVersionedEntity.AttributeChanged):
"""Published when aggregate is changed."""
class Discarded(Event, TimestampedVersionedEntity.Discarded):
"""Published when aggregate is discarded."""
class ExampleCreated(Event):
"""Published when an "example" object in the aggregate is created."""
def __init__(self, foo, **kwargs):
super(ExampleAggregateRoot, self).__init__(**kwargs)
self._foo = foo
self._pending_events = []
self._examples = {}
@attribute
def foo(self):
pass
def count_examples(self):
return len(self._examples)
def create_new_example(self):
assert not self._is_discarded
event = ExampleAggregateRoot.ExampleCreated(
example_id=uuid.uuid4(),
originator_id=self.id,
originator_version=self.version,
)
self._apply_and_publish(event)
self._publish(event)
def _publish(self, event):
self._pending_events.append(event)
def save(self):
publish(self._pending_events[:])
self._pending_events = []
@classmethod
def _mutate(cls, initial, event):
return mutate_aggregate(initial or cls, event)
class Example(object):
"""
Example entity. Controlled by aggregate root.
Exists only within the aggregate boundary.
"""
def __init__(self, example_id):
self._id = example_id
@property
def id(self):
return self._id
Aggregate factory¶
def create_example_aggregate(foo):
"""
Factory function for example aggregate.
"""
# Construct event.
event = ExampleAggregateRoot.Created(originator_id=uuid.uuid4(), foo=foo)
# Mutate aggregate.
aggregate = mutate_aggregate(ExampleAggregateRoot, event)
# Publish event to internal list only.
aggregate._publish(event)
# Return the new aggregate object.
return aggregate
Mutator function¶
from eventsourcing.domain.model.decorators import mutator
from eventsourcing.domain.model.entity import mutate_entity
@mutator
def mutate_aggregate(aggregate, event):
"""
Mutator function for example aggregate.
"""
return mutate_entity(aggregate, event)
@mutate_aggregate.register(ExampleAggregateRoot.ExampleCreated)
def _(aggregate, event):
# Handle "ExampleCreated" events by adding a new entity to the aggregate's dict of entities.
try:
aggregate._assert_not_discarded()
except TypeError:
raise Exception(aggregate)
entity = Example(example_id=event.example_id)
aggregate._examples[str(entity.id)] = entity
aggregate._version += 1
aggregate._last_modified_on = event.timestamp
return aggregate
Infrastructure¶
from eventsourcing.infrastructure.cassandra.datastore import CassandraSettings, CassandraDatastore
from eventsourcing.infrastructure.cassandra.activerecords import IntegerSequencedItemRecord, SnapshotRecord
import uuid
cassandra_datastore = CassandraDatastore(
settings=CassandraSettings(),
tables=(IntegerSequencedItemRecord, SnapshotRecord),
)
cassandra_datastore.setup_connection()
cassandra_datastore.setup_tables()
Application¶
Cipher strategy¶
from eventsourcing.domain.services.aes_cipher import AESCipher
# Construct the cipher strategy.
aes_key = '0123456789abcdef'
cipher = AESCipher(aes_key)
Snapshotting policy¶
class ExampleSnapshottingPolicy(object):
def __init__(self, example_repository, period=2):
self.example_repository = example_repository
self.period = period
subscribe(predicate=self.trigger, handler=self.take_snapshot)
def close(self):
unsubscribe(predicate=self.trigger, handler=self.take_snapshot)
def trigger(self, event):
if isinstance(event, (list)):
return True
is_period = not (event.originator_version + 1) % self.period
is_type = isinstance(event, ExampleAggregateRoot.Event)
is_trigger = is_type and is_period
return is_trigger
def take_snapshot(self, event):
if isinstance(event, list):
for e in event:
if self.trigger(e):
self.take_snapshot(e)
else:
self.example_repository.take_snapshot(event.originator_id, lte=event.originator_version)
Application object¶
from eventsourcing.application.base import ApplicationWithPersistencePolicies
from eventsourcing.infrastructure.eventsourcedrepository import EventSourcedRepository
from eventsourcing.infrastructure.snapshotting import EventSourcedSnapshotStrategy
from eventsourcing.infrastructure.cassandra.activerecords import CassandraActiveRecordStrategy
class EverythingApplication(ApplicationWithPersistencePolicies):
def __init__(self, **kwargs):
# Construct event stores and persistence policies.
entity_active_record_strategy = CassandraActiveRecordStrategy(
active_record_class=IntegerSequencedItemRecord,
)
snapshot_active_record_strategy = CassandraActiveRecordStrategy(
active_record_class=SnapshotRecord,
)
super(EverythingApplication, self).__init__(
entity_active_record_strategy=entity_active_record_strategy,
snapshot_active_record_strategy=snapshot_active_record_strategy,
**kwargs
)
# Construct snapshot strategy.
self.snapshot_strategy = EventSourcedSnapshotStrategy(
event_store=self.snapshot_event_store
)
# Construct the entity repository, this time with the snapshot strategy.
self.example_repository = EventSourcedRepository(
event_store=self.entity_event_store,
mutator=ExampleAggregateRoot._mutate,
snapshot_strategy=self.snapshot_strategy
)
# Construct the snapshotting policy.
self.snapshotting_policy = ExampleSnapshottingPolicy(
example_repository=self.example_repository,
)
def close(self):
super(EverythingApplication, self).close()
self.snapshotting_policy.close()
Run the code¶
from eventsourcing.exceptions import ConcurrencyError
with EverythingApplication(cipher=cipher, always_encrypt=True) as app:
## Check encryption.
secret_aggregate = create_example_aggregate(foo='secret info')
secret_aggregate.save()
# With encryption enabled, application state is not visible in the database.
event_store = app.entity_event_store
item2 = event_store.active_record_strategy.get_item(secret_aggregate.id, eq=0)
assert 'secret info' not in item2.data
# Events are decrypted inside the application.
retrieved_entity = app.example_repository[secret_aggregate.id]
assert 'secret info' in retrieved_entity.foo
## Check concurrency control.
aggregate = create_example_aggregate(foo='bar1')
aggregate.create_new_example()
aggregate.save()
assert app.example_repository[aggregate.id].foo == 'bar1'
a = app.example_repository[aggregate.id]
b = app.example_repository[aggregate.id]
# Change the aggregate using instance 'a'.
a.foo = 'bar2'
a.save()
assert app.example_repository[aggregate.id].foo == 'bar2'
# Because 'a' has been changed since 'b' was obtained,
# 'b' cannot be updated unless it is firstly refreshed.
try:
b.foo = 'bar3'
b.save()
assert app.example_repository[aggregate.id].foo == 'bar3'
except ConcurrencyError:
pass
else:
raise Exception("Failed to control concurrency of 'b':".format(app.example_repository[aggregate.id]))
# Refresh object 'b', so that 'b' has the current state of the aggregate.
b = app.example_repository[aggregate.id]
assert b.foo == 'bar2'
# Changing the aggregate using instance 'b' now works because 'b' is up to date.
b.foo = 'bar3'
b.save()
assert app.example_repository[aggregate.id].foo == 'bar3'
# Now 'a' does not have the current state of the aggregate, and cannot be changed.
try:
a.foo = 'bar4'
a.save()
except ConcurrencyError:
pass
else:
raise Exception("Failed to control concurrency of 'a'.")
## Check snapshotting.
# Create an aggregate.
aggregate = create_example_aggregate(foo='bar1')
aggregate.save()
# Check there's no snapshot, only one event so far.
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id)
assert snapshot is None
# Change an attribute, generates a second event.
aggregate.foo = 'bar2'
aggregate.save()
# Check the snapshot.
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id)
assert snapshot.state['_foo'] == 'bar2'
# Check can recover aggregate using snapshot.
assert aggregate.id in app.example_repository
assert app.example_repository[aggregate.id].foo == 'bar2'
# Check snapshot after five events.
aggregate.foo = 'bar3'
aggregate.foo = 'bar4'
aggregate.foo = 'bar5'
aggregate.save()
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id)
assert snapshot.state['_foo'] == 'bar4', snapshot.state['_foo']
# Check snapshot after seven events.
aggregate.foo = 'bar6'
aggregate.foo = 'bar7'
aggregate.save()
assert app.example_repository[aggregate.id].foo == 'bar7'
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id)
assert snapshot.state['_foo'] == 'bar6'
# Check snapshot state is None after discarding the aggregate on the eighth event.
aggregate.discard()
aggregate.save()
assert aggregate.id not in app.example_repository
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id)
assert snapshot.state is None
try:
app.example_repository[aggregate.id]
except KeyError:
pass
else:
raise Exception('KeyError was not raised')
# Get historical snapshots.
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id, lte=2)
assert snapshot.state['_version'] == 2 # one behind
assert snapshot.state['_foo'] == 'bar2'
snapshot = app.snapshot_strategy.get_snapshot(aggregate.id, lte=3)
assert snapshot.state['_version'] == 4
assert snapshot.state['_foo'] == 'bar4'
# Get historical entities.
aggregate = app.example_repository.get_entity(aggregate.id, lte=0)
assert aggregate.version == 1
assert aggregate.foo == 'bar1', aggregate.foo
aggregate = app.example_repository.get_entity(aggregate.id, lte=1)
assert aggregate.version == 2
assert aggregate.foo == 'bar2', aggregate.foo
aggregate = app.example_repository.get_entity(aggregate.id, lte=2)
assert aggregate.version == 3
assert aggregate.foo == 'bar3', aggregate.foo
aggregate = app.example_repository.get_entity(aggregate.id, lte=3)
assert aggregate.version == 4
assert aggregate.foo == 'bar4', aggregate.foo
Projections and notifications¶
If a projection is just another mutator function that operates on a sequence of events, and a persistent projection is a snapshot of the resulting state, then the new thing we need for projections of the application state is a sequence of all the events of the application. This section introduces the notification log, and assumes your projections and your persistent projections can be coded using techniques for coding mutator functions and snapshots introduced in previous sections.
Synchronous update¶
In a simple situation, you may wish to update a view of an aggregate synchronously whenever there are changes. If each view model depends only on one aggregate, you may wish simply to subscribe to the events of the aggregate. Then, whenever an event occurs, the projection can be updated.
The library has a decorator function
subscribe_to()
that can be used for this purpose.
@subscribe_to(Todo.Created)
def new_todo_projection(event):
todo = TodoProjection(id=event.originator_id, title=event.title)
todo.save()
The view model could be saved as a normal record, or stored in a sequence that follows the event originator version numbers, perhaps as snapshots, so that concurrent handling of events will not lead to a later state being overwritten by an earlier state. Older versions of the view could be deleted later.
If the view fails to update after the domain event has been stored, then the view will become inconsistent. Since it is not desirable to delete the event once it has been stored, the command must return normally despite the view update failing, so that the command is not retried. The failure to update will need to be logged, or otherwise handled, in a similar way to failures of asynchronous updates.
The big issue with this approach is that if the first event of an aggregate is not processed, there is no way of knowing the aggregate exists, and so there is nothing that can be used to check for updates to that aggregate.
Asynchronous update¶
The fundamental concern is to accomplish high fidelity when propagating a stream of events, so that events are neither missed nor are they duplicated. Once the stream of events has been propagated faithfully, it can be republished and subscribers can execute commands as above.
As Vaughn Vernon suggests in his book Implementing Domain Driven Design:
“at least two mechanisms in a messaging solution must always be consistent with each other: the persistence store used by the domain model, and the persistence store backing the messaging infrastructure used to forward the Events published by the model. This is required to ensure that when the model’s changes are persisted, Event delivery is also guaranteed, and that if an Event is delivered through messaging, it indicates a true situation reflected by the model that published it. If either of these is out of lockstep with the other, it will lead to incorrect states in one or more interdependent models.”
There are three options, he continues. The first option is to have the messaging infrastructure and the domain model share the same persistence store, so changes to the model and insertion of new messages commit in the same local transaction. The second option is to have separate datastores for domain model and messaging but have a two phase commit, or global transaction, across the two.
The third option is to have the bounded context control notifications. Vaughn Vernon is his book Implementing Domain Driven Design relies on the simple logic of an ascending sequence of integers to allow others to progress along the event stream. That is the approach taken here.
A pull mechanism that allows others to pull events they don’t yet have can be used to allow remote components to catch up. The same mechanism can be used if a component is developed after the application has been deployed and so requires initialising from an established application stream, or otherwise needs to be reconstructed from scratch.
As we will see below, updates can be triggered by pushing the notifications to messaging infrastructure, and having the remote components subscribe. If anything goes wrong with messaging infrastructure, such that a notification is not received, remote components can detect they have missed a notification and pull the notifications they have missed.
Application log¶
In order to update a projection of more than one aggregate, or the application state as a whole, we need a single sequence to log all the events of the application.
We want an application log that follows an increasing sequence of integers. The application log must also be capable of storing a very large sequence of events, neither swamping an individual database partition nor distributing things across partitions without any particular order so that iterating through the sequence is slow and expensive. We also want the application log effectively to have constant time read and write operations.
The library class
BigArray satisfies these
requirements quite well. It is a tree of arrays, with a root array
that stores references to the current apex, with an apex that contains
references to arrays, which either contain references to lower arrays
or contain the items assigned to the big array. Each array uses one database
partition, and is limited is size (the array size) to ensure the partition
is never too large. The identity of each array can be calculated directly
from the index number, so it is possible to identify arrays directly
without traversing the tree to discover entity IDs. The capacity of base
arrays is the array size to the power of the array size. For a reasonable
size of array, it isn’t really possible to fill up the base of such an
array tree, but the slow growing properties of this tree mean that for
all imaginable scenarios, the performance will be approximately constant
as items are appended to the big array.
Items can be appended to a big array using the append() method.
The append() method identifies the next available index in the array,
and then assigns the item to that index in the array. A
ConcurrencyError will be raised if
the position is already taken.
The performance of the append() method is proportional to the log of the
index in the array, to the base of the array size used in the big array, rounded
up to the nearest integer, plus one (because of the root sequence that tracks
the apex). For example, if the sub-array size is 10,000, then it will take only 50%
longer to append the 100,000,000th item to the big array than the 1st one. By
the time the 1,000,000,000,000th index position is assigned to a big array, the
append() method will take only twice as long as the 1st.
That’s because the performance of the append() method is dominated by the
need to walk down the big array’s tree of arrays to find the highest assigned
index. Once the index of the next position is known, the item can be assigned
directly to an array.
from uuid import uuid4
from eventsourcing.domain.model.array import BigArray, ItemAssigned
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
from eventsourcing.infrastructure.sqlalchemy.activerecords import StoredEventRecord
from eventsourcing.infrastructure.sqlalchemy.datastore import SQLAlchemyDatastore, SQLAlchemySettings
from eventsourcing.infrastructure.eventstore import EventStore
from eventsourcing.infrastructure.repositories.array import BigArrayRepository
from eventsourcing.application.policies import PersistencePolicy
from eventsourcing.infrastructure.sequenceditem import StoredEvent
from eventsourcing.infrastructure.sequenceditemmapper import SequencedItemMapper
datastore = SQLAlchemyDatastore(
settings=SQLAlchemySettings(),
tables=[StoredEventRecord],
)
datastore.setup_connection()
datastore.setup_tables()
event_store = EventStore(
active_record_strategy=SQLAlchemyActiveRecordStrategy(
session=datastore.session,
active_record_class=StoredEventRecord,
sequenced_item_class=StoredEvent,
),
sequenced_item_mapper=SequencedItemMapper(
sequenced_item_class=StoredEvent,
)
)
persistence_policy = PersistencePolicy(
event_store=event_store,
event_type=ItemAssigned,
)
array_id = uuid4()
repo = BigArrayRepository(
event_store=event_store,
array_size=10000
)
application_log = repo[array_id]
application_log.append('event0')
application_log.append('event1')
application_log.append('event2')
application_log.append('event3')
Because there is a small duration of time between checking for the next
position and using it, another thread could jump in and use the position
first. If that happens, a ConcurrencyError
will be raised by the BigArray
object. In such a case, another attempt can be made to append the item.
Items can be assigned directly to a big array using an index number. If an item has already been assigned to the same position, a concurrency error will be raised, and the original item will remain in place. Items cannot be unassigned from an array, hence each position in the array can be assigned once only.
The average performance of assigning an item is a constant time. The worst case is the log of the index with base equal to the array size, which occurs when containing arrays are added, so that the last highest assigned index can be discovered. The probability of departing from average performance is inversely proportional to the array size, since the the larger the array size, the less often the base arrays fill up. For a decent array size, the probability of needing to build the tree is very low. And when the tree does need building, it doesn’t take very long (and most of it probably already exists).
from eventsourcing.exceptions import ConcurrencyError
assert application_log.get_next_position() == 4
application_log[4] = 'event4'
try:
application_log[4] = 'event4a'
except ConcurrencyError:
pass
else:
raise
If the next available position in the array must be identified
each time an item is assigned, the amount of contention will increase
as the number of threads increases. Using the append() method alone
will work if the time period of appending events is greater than the
time it takes to identify the next available index and assign to it.
At that rate, any contention will not lead to congestion. Different
nodes can take their chances assigning to what they believe is an
unassigned index, and if another has already taken that position,
the operation can be retried.
However, there will be an upper limit to the rate at which events can be appended, and contention will eventually lead to congestion that will cause requests to backup or be spilled.
The rate of assigning items to the big array can be greatly increased
by centralizing the generation of the sequence of integers. Instead of
discovering the next position from the array each time an item is assigned,
an integer sequence generator can be used to generate a contiguous sequence
of integers. This technique eliminates contention around assigning items to
the big array entirely. In consequence, the bandwidth of assigning to a big
array using an integer sequence generator is much greater than using the
append() method.
If the application is executed in only one process, the number generator can
be a simple Python object. The library class
SimpleIntegerSequenceGenerator
generates a contiguous sequence of integers that can be shared across multiple
threads in the same process.
from eventsourcing.infrastructure.integersequencegenerators.base import SimpleIntegerSequenceGenerator
integers = SimpleIntegerSequenceGenerator()
generated = []
for i in integers:
if i >= 5:
break
generated.append(i)
expected = list(range(5))
assert generated == expected, (generated, expected)
If the application is deployed across many nodes, an external integer sequence
generator can be used. There are many possible solutions. The library class
RedisIncr
uses Redis’ INCR command to generate a contiguous sequence of integers
that can be shared be processes running on different nodes.
Using Redis doesn’t necessarily create a single point of failure. Redundancy can be obtained using clustered Redis. Although there aren’t synchronous updates between nodes, so that the INCR command may issue the same numbers more than once, these numbers can only ever be used once. As failures are retried, the position will eventually reach an unassigned index position. Arrangements can be made to set the value from the highest assigned index. With care, the worst case will be an occasional slight delay in storing events, caused by switching to a new Redis node and catching up with the current index number. Please note, there is currently no code in the library to update or resync the Redis key used in the Redis INCR integer sequence generator.
from eventsourcing.infrastructure.integersequencegenerators.redisincr import RedisIncr
integers = RedisIncr()
generated = []
for i in integers:
generated.append(i)
if i >= 4:
break
expected = list(range(5))
assert generated == expected, (generated, expected)
The integer sequence generator can be used when assigning items to the application log.
application_log[next(integers)] = 'event5'
application_log[next(integers)] = 'event6'
assert application_log.get_next_position() == 7
Items can be read from the application log using an index or a slice.
The performance of reading an item at a given index is always constant time with respect to the number of the index. The base array ID, and the index of the item in the base array, can be calculated from the number of the index.
The performance of reading a slice of items is proportional to the size of the slice. Consecutive items in a base array are stored consecutively in the same database partition, and if the slice overlaps more than base array, the iteration proceeds to the next partition.
assert application_log[0] == 'event0'
assert list(application_log[5:7]) == ['event5', 'event6']
The application log can be written to by a persistence policy. References to events can be assigned to the application log before the domain event is written to the aggregate’s own sequence, so that it isn’t possible to store an event in the aggregate’s sequence that is not already in the application log.
Commands that fail to write to the aggregate’s sequence (due to an operation error or concurrency error) after the event has been logged in the application log should probably raise an exception, so that the command is seen to have failed and so may be retried. This leaves an item in the notification log, but not a domain event in the aggregate stream (a dangling reference, that may be satisfied later). If the command failed due to an operational error, the same event maybe published again, and so it would appear twice in the application log. And so whilst events in the application log that aren’t in the aggregate sequence can perhaps be ignored by consumers of the application log, care should be taken to deduplicate events.
If writing the event to its aggregate sequence is successful, then it is possible to push a notification about the event to a message queue. Failing to push the notification perhaps should not prevent the command returning normally. Push notifications could also be generated by another process, something that pulls from the application log, and pushes notifications for events that have not already been sent.
Notification log¶
As described in Implementing Domain Driven Design, a notification log is presented in linked sections. The “current section” is returned by default, and contains the very latest notification and some of the preceding notifications. There are also archived sections that contain all the earlier notifications. When the current section is full, it is considered to be an archived section that links to the new current section.
Readers can navigate the linked sections from the current section backwards until the archived section is reached that contains the last notification seen by the client. If the client has not yet seen any notifications, it will navigate back to the first section. Readers can then navigate forwards, revealing all existing notifications that have not yet been seen.
The library class NotificationLog
encapsulates the application log and presents linked sections. The library class
NotificationLogReader is an iterator
that yields notifications. It navigates the sections of the notification log, and
maintains position so that it can continue when there are further notifications.
The position can be set directly with the seek() method. The position is set
indirectly when a slice is taken with a start index. The position is set to zero
when the reader is constructed.
The notification log uses a big array object. In this example, the big array object is directly the application log above. It is possible to project the application log into a custom notification log, perhaps to deduplicate domain events, or to anonymise data, or to send messages to messaging infrastructure with more stateful control.
from eventsourcing.interface.notificationlog import NotificationLog, NotificationLogReader
# Construct notification log.
notification_log = NotificationLog(application_log, section_size=10)
# Get the "current "section from the notification log (numbering follows Vaughn Vernon's book)
section = notification_log['current']
assert section.section_id == '1,10'
assert len(section.items) == 7, section.items
assert section.previous_id == None
assert section.next_id == None
# Construct log reader.
reader = NotificationLogReader(notification_log)
# The position is zero by default.
assert reader.position == 0
# The position can be set directly.
reader.seek(10)
assert reader.position == 10
# Reset the position.
reader.seek(0)
# Read all existing notifications.
all_notifications = list(reader)
assert all_notifications == ['event0', 'event1', 'event2', 'event3', 'event4', 'event5', 'event6']
# Check the position has advanced.
assert reader.position == 7
# Read all subsequent notifications (should be none).
subsequent_notifications = list(reader)
assert subsequent_notifications == []
# Assign more events to the application log.
application_log[next(integers)] = 'event7'
application_log[next(integers)] = 'event8'
# Read all subsequent notifications (should be two).
subsequent_notifications = list(reader)
assert subsequent_notifications == ['event7', 'event8']
# Check the position has advanced.
assert reader.position == 9
# Read all subsequent notifications (should be none).
subsequent_notifications = list(reader)
assert subsequent_notifications == []
# Assign more events to the application log.
application_log[next(integers)] = 'event9'
application_log[next(integers)] = 'event10'
application_log[next(integers)] = 'event11'
# Read all subsequent notifications (should be two).
subsequent_notifications = list(reader)
assert subsequent_notifications == ['event9', 'event10', 'event11']
# Check the position has advanced.
assert reader.position == 12
# Read all subsequent notifications (should be none).
subsequent_notifications = list(reader)
assert subsequent_notifications == []
# Get the "current "section from the notification log (numbering follows Vaughn Vernon's book)
section = notification_log['current']
assert section.section_id == '11,20'
assert section.previous_id == '1,10'
assert section.next_id == None
assert len(section.items) == 2, len(section.items)
# Get the first section from the notification log (numbering follows Vaughn Vernon's book)
section = notification_log['1,10']
assert section.section_id == '1,10'
assert section.previous_id == None
assert section.next_id == '11,20'
assert len(section.items) == 10, section.items
The RESTful API design in Implementing Domain Driven Design suggests a good way to present the notification log, a way that is simple and can scale using established HTTP technology.
The library function present_section()
serializes sections from the notification log for use in a view.
import json
from eventsourcing.interface.notificationlog import present_section
content = present_section(application_log, '1,10', 10)
expected = {
"items": [
"event0",
"event1",
"event2",
"event3",
"event4",
"event5",
"event6",
"event7",
"event8",
"event9"
],
"next_id": "11,20",
"previous_id": None,
"section_id": "1,10"
}
assert json.loads(content) == expected
A Web application view can pick out from the request path the notification
log ID and the section ID, and return an HTTP response with the JSON content
that results from calling present_section().
The library class RemoteNotificationLog
issues HTTP requests to a RESTful API that presents sections from the notification log.
It has the same interface as NotificationLog
and so can be used by NotificationLogReader
progressively to obtain unseen notifications.
Todo: Pulling from remote notification log.
Todo: Publishing and subscribing to remote notification log.
Todo: Deduplicating domain events in receiving context. Events may appear twice in the notification log if there is contention over the command that generates the logged event, or if the event cannot be appended to the aggregate stream for whatever reason and then the command is retried successfully. So events need to be deduplicated. One approach is to have a UUID5 namespace for received events, and use concurrency control to make sure each event is acted on only once. That leads to the question of when to insert the event, before or after it is successfully applied to the context? If before, and the event is not successfully applied, then the event maybe lost. Does the context need to apply the events in order? It may help to to construct a sequenced command log, also using a big array, so that the command sequence can be constructed in a distributed manner. The command sequence can then be executed in a distributed manner. This approach would support creating another application log that is entirely correct.
Todo: Race conditions around reading events being assigned using central integer sequence generator, could potentially read when a later index has been assigned but a previous one has not yet been assigned. Reading the previous as None, when it just being assigned is an error. So perhaps something can wait until previous has been assigned, or until it can safely be assumed the integer was lost. If an item is None, perhaps the notification log could stall for a moment before yielding the item, to allow time for the race condition to pass. Perhaps it should only do it when the item has been assigned recently (timestamp of the ItemAdded event could be checked) or when there have been lots of event since (the highest assigned index could be checked). A permanent None value should be something that occurs very rarely, when an issued integer is not followed by a successful assignment to the big array. A permanent “None” will exist in the sequence if an integer is lost perhaps due to a database operation error that somehow still failed after many retries, or because the client process crashed before the database operation could be executed but after the integer had been issued, so the integer became lost. This needs code.
Todo: Automatic initialisation of the integer sequence generator RedisIncr from getting highest assigned index. Or perhaps automatic update with the current highest assigned index if there continues to be contention after a number of increments, indicating the issued values are far behind. If processes all reset the value whilst they are also incrementing it, then there will be a few concurrency errors, but it should level out quickly. This also needs code.
Todo: Use actual domain event objects, and log references to them. Have an iterator that returns actual domain events, rather than the logged references. Could log the domain events, but their variable size makes the application log less stable (predictable) in its usage of database partitions. Perhaps deferencing to real domain events could be an option of the notification log? Perhaps something could encapsulate the notification log and generate domain events?
Todo: Configuration of remote reader, to allow URL to be completely configurable.
Deployment¶
This section gives an overview of the concerns that arise when using an eventsourcing application in Web applications and task queue workers. There are many combinations of frameworks, databases, and process models. The complicated aspect is setting up the database configuration to work well with the framework. Your event sourcing application can be constructed just after the database is configured, and before requests are handled.
Please note, unlike the code snippets in the other sections of
the user guide, the snippets of code in this section are merely
suggestive, and do not form a complete working program.
For a working example using Flask and SQLAlchemy, please refer
to the library module eventsourcing.example.interface.flaskapp,
which is tested both stand-alone and with uWSGI.
Application object¶
In general you need one, and only one, instance of your application object in each process. If your eventsourcing application object has any policies, for example if is has a persistence policy that will persist events whenever they are published, then constructing more than one instance of the application causes the policy event handlers to be subscribed more than once, so for example more than one attempt will be made to save each event, which won’t work.
To make sure there is only one instance of your application object in each process, one possible arrangement (see below) is to have a module with two functions and a variable. The first function constructs an application object and assigns it to the variable, and can perhaps be called when a module is imported, or from a suitable hook or signal designed for setting things up before any requests are handled. A second function returns the application object assigned to the variable, and can be called by any views, or request or task handlers, that depend on the application’s services.
Although the first function below must be called only once, the second
function can be called many times. The example functions below have
been written relatively strictly so that, when it is called, the function
init_application() will raise an exception if it has already been
called, and get_application() will raise an exeception if
init_application() has not already been called.
# Your eventsourcing application.
class ExampleApplication(object):
def __init__(*args, **kwargs):
pass
def construct_application(**kwargs):
return ExampleApplication(**kwargs)
_application = None
def init_application(**kwargs):
global _application
if _application is not None:
raise AssertionError("init_application() has already been called")
_application = construct_application(**kwargs)
def get_application():
if application is None:
raise AssertionError("init_application() must be called first")
return application
As an aside, if you will use these function also in your test suite, and your
test suite needs to set up the application more than once, you will also need
a close_application() function that closes the application object,
unsubscribing any handlers, and resetting the module level variable so that
init_application() can be called again. If doesn’t really matter
if you don’t close your application at the end of the process lifetime, however
you may wish to close any database or other connections to network services.
def close_application():
global application
if application is not None:
application.close()
application = None
Lazy initialization¶
An alternative to having separate “init” and “get” functions is having one “get” function that does lazy initialization of the application object when first requested. With lazy initialization, the getter will first check if the object it needs to return has been constructed, and will then return the object. If the object hasn’t been constructed, before returning the object it will construct the object. So you could use a lock around the construction of the object, to make sure it only happens once. After the lock is obtained and before the object is constructed, it is recommended to check again that the object wasn’t constructed by another thread before the lock was acquired.
import threading
application = None
lock = threading.Lock()
def get_application():
global application
if application is None:
lock.acquire()
try:
# Check again to avoid a TOCTOU bug.
if application is None:
application = construct_application()
finally:
lock.release()
return application
Database connection¶
Typically, your eventsourcing application object will be constructed after its database connection has been configured, and before any requests are handled. Views or tasks can then safely use the already constructed application object.
If your eventsourcing application depends on receiving a database session object when it is constructed, for example if you are using the SQLAlchemy classes in this library, then you will need to create a correctly scoped session object first and use it to construct the application object.
On the other hand, if your eventsourcing application does not depend on receiving a database session object when it is constructed, for example if you are using the Cassandra classes in this library, then you may construct the application object before configuring the database connection - just be careful not to use the application object before the database connection is configured otherwise your queries just won’t work.
Setting up connections to databases is out of scope of the eventsourcing application classes, and should be set up in a “normal” way. The documentation for your Web or worker framework may describe when to set up database connections, and your database documentation may also have some suggestions. It is recommended to make use of any hooks or decorators or signals intended for the purpose of setting up the database connection also to construct the application once for the process. See below for some suggestions.
SQLAlchemy¶
SQLAlchemy has very good documentation about constructing sessions. If you are an SQLAlchemy user, it is well worth reading the documentation about sessions in full. Here’s a small quote:
Some web frameworks include infrastructure to assist in the task of aligning the lifespan of a Session with that of a web request. This includes products such as Flask-SQLAlchemy for usage in conjunction with the Flask web framework, and Zope-SQLAlchemy, typically used with the Pyramid framework. SQLAlchemy recommends that these products be used as available.
In those situations where the integration libraries are not provided or are insufficient, SQLAlchemy includes its own “helper” class known as scoped_session. A tutorial on the usage of this object is at Contextual/Thread-local Sessions. It provides both a quick way to associate a Session with the current thread, as well as patterns to associate Session objects with other kinds of scopes.
The important thing is to use a scoped session, and it is better to have the session scoped to the request or task, rather than the thread, but scoping to the thread is ok.
As soon as you have a scoped session object, you can construct your eventsourcing application.
Cassandra¶
Cassandra connections can be set up entirely independently of the application object. See the section about using Cassandra for more information.
Web interfaces¶
uWSGI¶
If you are running uWSGI in prefork mode, and not using a Web application framework, please note that uWSGI has a postfork decorator which may help.
Your “wsgi.py” file can have a module-level function decorated with the @postfork
decorator that initialises your eventsourcing application for the Web application process
after child workers have been forked.
from uwsgidecorators import postfork
@postfork
def init_process():
# Set up database connection.
database = {}
# Construct eventsourcing application.
init_application()
Other decorators are available.
Flask with Cassandra¶
The Cassandra Driver FAQ has a code snippet about establishing the connection with the uWSGI postfork decorator, when running in a forked mode.
from flask import Flask
from uwsgidecorators import postfork
from cassandra.cluster import Cluster
session = None
prepared = None
@postfork
def connect():
global session, prepared
session = Cluster().connect()
prepared = session.prepare("SELECT release_version FROM system.local WHERE key=?")
app = Flask(__name__)
@app.route('/')
def server_version():
row = session.execute(prepared, ('local',))[0]
return row.release_version
Flask-Cassandra¶
The Flask-Cassandra project serves a similar function to Flask-SQLAlchemy.
Flask-SQLAlchemy¶
If you wish to use eventsourcing with Flask and SQLAlchemy, then you may wish to use Flask-SQLAlchemy. You just need to define your active record class using the model classes from that library, and then use it instead of the library classes in your eventsourcing application object, along with the session object it provides.
The docs snippet below shows that it can work simply to construct the eventsourcing application in the same place as the Flask application object.
The Flask-SQLAlchemy class SQLAlchemy is used to set up a session object that is scoped to the request.
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy_utils.types.uuid import UUIDType
from eventsourcing.infrastructure.sqlalchemy.activerecords import SQLAlchemyActiveRecordStrategy
# Construct Flask application.
application = Flask(__name__)
# Construct Flask-SQLAlchemy object.
db = SQLAlchemy(application)
# Define database table using Flask-SQLAlchemy library.
class IntegerSequencedItem(db.Model):
__tablename__ = 'integer_sequenced_items'
# Sequence ID (e.g. an entity or aggregate ID).
sequence_id = db.Column(UUIDType(), primary_key=True)
# Position (index) of item in sequence.
position = db.Column(db.BigInteger(), primary_key=True)
# Topic of the item (e.g. path to domain event class).
topic = db.Column(db.String(255))
# State of the item (serialized dict, possibly encrypted).
data = db.Column(db.Text())
# Index.
__table_args__ = db.Index('index', 'sequence_id', 'position'),
# Construct eventsourcing application with db table and session.
init_application(
entity_active_record_strategy=SQLAlchemyActiveRecordStrategy(
active_record_class=IntegerSequencedItem,
session=db.session,
)
)
For a working example using Flask and SQLAlchemy, please
refer to the library module eventsourcing.example.interface.flaskapp,
which is tested both stand-alone and with uWSGI.
The Flask application method “before_first_request” is used to decorate an
application object constructor, just before a request is made, so that the
module can be imported by the test suite, without immediately constructing
the application.
Django-Cassandra¶
If you wish to use eventsourcing with Django and Cassandra, you may wish to use Django-Cassandra.
It’s also possible to use this library directly with Django and Cassandra. You just need to configure the connection and initialise the application before handling requests in a way that is correct for your configuration.
Django ORM¶
The excellent project djangoevents by Applause is a Django app that provides a neat way of taking an event sourcing approach in a Django project. It allows this library to be used seamlessly with Django, by using the Django ORM to store events. Using djangoevents is well documented in the README file. It adds some nice enhancements to the capabilities of this library, and shows how various components can be extended or replaced. Please note, the djangoevents project currently works with a previous version of this library.
Zope-SQLAlchemy¶
The Zope-SQLAlchemy project serves a similar function to Flask-SQLAlchemy.
Task queues¶
This section contains suggestions about using an eventsourcing application in task queue workers.
Celery¶
Celery has a worker_process_init signal decorator, which may be appropriate if you are running Celery workers in prefork mode. Other decorators are available.
Your Celery tasks or config module can have a module-level function decorated with
the @worker-process-init decorator that initialises your eventsourcing application
for the Celery worker process.
from celery.signals import worker_process_init
@worker_process_init.connect
def init_process(sender=None, conf=None, **kwargs):
# Set up database connection.
database = {}
# Construct eventsourcing application.
init_application()
As an alternative, it may work to use decorator @task_prerun
with a getter that supports lazy initialization.
from celery.signals import task_prerun
@task_prerun.connect
def init_process(*args, **kwargs):
get_appliation(lazy_init=True)
Once the application has been safely initialized once
in the process, your Celery tasks can use function get_application()
to complete their work. Of course, you could just call a getter with lazy
initialization from the tasks.
from celery import Celery
app = Celery()
# Use Celery app to route the task to the worker.
@app.task
def hello_world():
# Use eventsourcing app to complete the task.
app = get_application()
return "Hello World, {}".format(id(app))
Again, the most important thing is configuring the database, and making things work across all modes of execution, including your test suite.
Redis Queue¶
Redis queue workers are
quite similar to Celery workers. You can call get_application()
from within a job function. To fit with the style in the RQ
documentation, you could perhaps use your eventsourcing application
as a context manager, just like the Redis connection example.
Design¶
The design of the library follows the layered architecture: interfaces, application, domain, and infrastructure.
The domain layer contains a model of the supported domain, and services that depend on that model. The infrastructure layer encapsulates the infrastructural services required by the application.
The application is responsible for binding domain and infrastructure, and has policies such as the persistence policy, which stores domain events whenever they are published by the model.
The example application has an example respository, from which example entities can be retrieved. It also has a factory method to register new example entities. Each repository has an event player, which all share an event store with the persistence policy. The persistence policy uses the event store to store domain events, and the event players use the event store to retrieve the stored events. The event players also share with the model the mutator functions that are used to apply domain events to an initial state.
Functionality such as mapping events to a database, or snapshotting, is factored as strategy objects and injected into dependents by constructor parameter. Application level encryption is a mapping option.
The sequenced item persistence model allows domain events to be stored in wide variety of database services, and optionally makes use of any optimistic concurrency controls the database system may afford.
Release notes¶
It is the aim of the project that releases with the same major version number are backwards compatible.
Version 2.x series was a major rewrite that implemented two distinct kinds of sequences: events sequenced by integer version numbers and events sequenced in time, with an archetypal “sequenced item” persistence model for storing events.
Version 1.x series was an extension of the version 0.x series, and attempted to bridge between sequencing events with both timestamps and version numbers.
Version 0.x series was the initial cut of the code, all events were sequenced by timestamps, or TimeUUIDs in Cassandra, because the project originally emerged whilst working with Cassandra.
Reference¶
Modules¶
eventsourcing¶
Interface layer¶
eventsourcing.interface.notificationlog¶
-
class
eventsourcing.interface.notificationlog.AbstractNotificationLog[source]¶ Bases:
objectPresents a sequence of sections from a sequence of notifications.
-
class
eventsourcing.interface.notificationlog.NotificationLog(big_array, section_size)[source]¶ Bases:
eventsourcing.interface.notificationlog.AbstractNotificationLog
-
class
eventsourcing.interface.notificationlog.NotificationLogReader(notification_log)[source]¶ Bases:
object
-
class
eventsourcing.interface.notificationlog.RemoteNotificationLog(base_url, notification_log_id)[source]¶ Bases:
eventsourcing.interface.notificationlog.AbstractNotificationLog
-
class
eventsourcing.interface.notificationlog.Section(section_id, items, previous_id=None, next_id=None)[source]¶ Bases:
objectSection of a notification log.
Contains items, and has an ID.
May also have either IDs of previous and next sections of the notification log.
Application layer¶
eventsourcing.application.base¶
-
class
eventsourcing.application.base.ApplicationWithEventStores(entity_active_record_strategy=None, log_active_record_strategy=None, snapshot_active_record_strategy=None, always_encrypt=False, cipher=None)[source]¶ Bases:
object-
construct_event_store(event_sequence_id_attr, event_position_attr, active_record_strategy, always_encrypt=False, cipher=None)[source]¶
-
construct_sequenced_item_mapper(sequenced_item_class, event_sequence_id_attr, event_position_attr, json_encoder_class=<class 'eventsourcing.infrastructure.transcoding.ObjectJSONEncoder'>, json_decoder_class=<class 'eventsourcing.infrastructure.transcoding.ObjectJSONDecoder'>, always_encrypt=False, cipher=None)[source]¶
-
-
class
eventsourcing.application.base.ApplicationWithPersistencePolicies(**kwargs)[source]¶ Bases:
eventsourcing.application.base.ApplicationWithEventStores
Domain layer¶
eventsourcing.domain.model.aggregate¶
-
class
eventsourcing.domain.model.aggregate.AggregateRoot(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.TimestampedVersionedEntityRoot entity for an aggregate in a domain driven design.
-
class
AttributeChanged(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.aggregate.Event,eventsourcing.domain.model.entity.AttributeChangedPublished when an AggregateRoot is changed.
-
class
Created(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.aggregate.Event,eventsourcing.domain.model.entity.CreatedPublished when an AggregateRoot is created.
-
class
Discarded(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.aggregate.Event,eventsourcing.domain.model.entity.DiscardedPublished when an AggregateRoot is discarded.
-
class
eventsourcing.domain.model.array¶
-
class
eventsourcing.domain.model.array.AbstractArrayRepository(array_size=10000, *args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.AbstractEntityRepositoryRepository for sequence objects.
-
class
eventsourcing.domain.model.array.AbstractBigArrayRepository(*args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.AbstractEntityRepositoryRepository for compound sequence objects.
-
subrepo¶ Sub-sequence repository.
-
-
class
eventsourcing.domain.model.array.BigArray(array_id, repo)[source]¶ Bases:
eventsourcing.domain.model.array.ArrayA virtual array holding items in indexed positions, across a number of Array instances.
Getting and setting items at index position is supported. Slices are supported, and operate across the underlying arrays. Appending is also supported.
BigArray is designed to overcome the concern of needing a single large sequence that may not be suitably stored in any single partiton. In simple terms, if events of an aggregate can fit in a partition, we can use the same size partition to make a tree of arrays that will certainly be capable of sequencing all the events of the application in a single stream.
With normal size base arrays, enterprise applications can expect read and write time to be approximately constant with respect to the number of items in the array.
The array is composed of a tree of arrays, which gives the capacity equal to the size of each array to the power of the size of each array. If the arrays are limited to be about the maximum size of an aggregate event stream (a large number but not too many that would cause there to be too much data in any one partition, let’s say 1000s to be safe) then it would be possible to fit such a large number of aggregates in the corresponding BigArray, that we can be confident it would be full.
Write access time in the worst case, and the time to identify the index of the last item in the big array, is proportional to the log of the highest assigned index to the base of the underlying array size. Write time on average, and read time given an index, is contant with respect to the number of items in a BigArray.
Items can be appended in log time in a single thread. However, the time between reading the current last index and claiming the next position leads to contention and retries when there are lots of threads of execution all attempting to append items, which inherently limits throughput.
Todo: Not possible in Cassandra, but maybe do it in a transaction in SQLAlchemy?
An alternative to reading the last item before writing the next is to use an integer sequence generator to generate a stream of integers. Items can be assigned to index positions in a big array, according to the integers that are issued. Throughput will then be much better, and will be limited only by the rate at which the database can have events written to it (unless the number generator is quite slow).
An external integer sequence generator, such as Redis’ INCR command, or an auto-incrementing database column, may constitute a single point of failure.
eventsourcing.domain.model.decorators¶
-
eventsourcing.domain.model.decorators.attribute(getter)[source]¶ When used as a method decorator, returns a property object with the method as the getter and a setter defined to call instance method change_attribute(), which publishes an AttributeChanged event.
-
eventsourcing.domain.model.decorators.mutator(arg=None)[source]¶ Structures mutator functions by allowing handlers to be registered for different types of event. When the decorated function is called with an initial value and an event, it will call the handler that has been registered for that type of event.
It works like singledispatch, which it uses. The difference is that when the decorated function is called, this decorator dispatches according to the type of last call arg, which fits better with reduce(). The builtin Python function reduce() is used by the library to replay a sequence of events against an initial state. If a mutator function is given to reduce(), along with a list of events and an initializer, reduce() will call the mutator function once for each event in the list, but the initializer will be the first value, and the event will be the last argument, and we want to dispatch according to the type of the event. It happens that singledispatch is coded to switch on the type of the first argument, which makes it unsuitable for structuring a mutator function without the modifications introduced here.
The other aspect introduced by this decorator function is the option to set the type of the handled entity in the decorator. When an entity is replayed from scratch, in other words when all its events are replayed, the initial state is None. The handler which handles the first event in the sequence will probably construct an object instance. It is possible to write the type into the handler, but that makes the entity more difficult to subclass because you will also need to write a handler for it. If the decorator is invoked with the type, when the initial value passed as a call arg to the mutator function is None, the handler will instead receive the type of the entity, which it can use to construct the entity object.
class Entity(object): class Created(object): pass @mutator(Entity) def mutate(initial, event): raise NotImplementedError(type(event)) @mutate.register(Entity.Created) def _(initial, event): return initial(**event.__dict__) entity = mutate(None, Entity.Created())
-
eventsourcing.domain.model.decorators.random() → x in the interval [0, 1).¶
-
eventsourcing.domain.model.decorators.retry(exc=<class 'Exception'>, max_retries=1, wait=0)[source]¶
-
eventsourcing.domain.model.decorators.subscribe_to(event_class)[source]¶ Decorator for making a custom event handler function subscribe to a certain event type
event_class: DomainEvent class or its child classes that the handler function should subscribe to
The following example shows a custom handler that reacts to Todo.Created event and saves a projection of a Todo model object.
@subscribe_to(Todo.Created) def new_todo_projection(event): todo = TodoProjection(id=event.originator_id, title=event.title) todo.save()
eventsourcing.domain.model.entity¶
-
class
eventsourcing.domain.model.entity.AbstractEntityRepository(*args, **kwargs)[source]¶ Bases:
object-
event_store¶ Returns event store object used by this repository.
-
-
class
eventsourcing.domain.model.entity.DomainEntity(originator_id)[source]¶ Bases:
eventsourcing.domain.model.events.QualnameABC-
class
AttributeChanged(originator_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.events.AttributeChangedPublished when a DomainEntity is discarded.
-
class
Created(originator_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.events.CreatedPublished when a DomainEntity is created.
-
class
Discarded(originator_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.events.DiscardedPublished when a DomainEntity is discarded.
-
class
Event(originator_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.EventWithOriginatorID,eventsourcing.domain.model.events.DomainEventLayer supertype.
-
change_attribute(name, value, **kwargs)[source]¶ Changes given attribute of the entity, by constructing and applying an AttributeChanged event.
-
id¶
-
class
-
class
eventsourcing.domain.model.entity.TimestampedEntity(timestamp, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.DomainEntity-
class
AttributeChanged(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.AttributeChangedPublished when a TimestampedEntity is changed.
-
class
Created(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.CreatedPublished when a TimestampedEntity is created.
-
class
Discarded(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.DiscardedPublished when a TimestampedEntity is discarded.
-
class
Event(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.EventWithTimestamp,eventsourcing.domain.model.entity.EventLayer supertype.
-
created_on¶
-
last_modified_on¶
-
class
-
class
eventsourcing.domain.model.entity.TimestampedVersionedEntity(timestamp, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.TimestampedEntity,eventsourcing.domain.model.entity.VersionedEntity-
class
AttributeChanged(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.AttributeChanged,eventsourcing.domain.model.entity.AttributeChangedPublished when a TimestampedVersionedEntity is created.
-
class
Created(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.Created,eventsourcing.domain.model.entity.CreatedPublished when a TimestampedVersionedEntity is created.
-
class
-
class
eventsourcing.domain.model.entity.TimeuuidedEntity(event_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.DomainEntity-
created_on¶
-
last_modified_on¶
-
-
class
eventsourcing.domain.model.entity.TimeuuidedVersionedEntity(event_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.TimeuuidedEntity,eventsourcing.domain.model.entity.VersionedEntity
-
class
eventsourcing.domain.model.entity.VersionedEntity(originator_version, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.DomainEntity-
class
AttributeChanged(originator_version, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.AttributeChangedPublished when a VersionedEntity is changed.
-
class
Created(originator_version=0, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.CreatedPublished when a VersionedEntity is created.
-
class
Discarded(originator_version, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.Event,eventsourcing.domain.model.entity.DiscardedPublished when a VersionedEntity is discarded.
-
class
Event(originator_version, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.EventWithOriginatorVersion,eventsourcing.domain.model.entity.EventLayer supertype.
-
version¶
-
class
-
class
eventsourcing.domain.model.entity.WithReflexiveMutator(originator_id)[source]¶ Bases:
eventsourcing.domain.model.entity.DomainEntityImplements an entity mutator function by dispatching to the event itself all calls to mutate an entity with an event.
This is an alternative to using an independent mutator function implemented with the @mutator decorator, or an if-else block.
eventsourcing.domain.model.events¶
-
class
eventsourcing.domain.model.events.AttributeChanged(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventCan be published when an attribute of an entity is created.
-
name¶
-
value¶
-
-
class
eventsourcing.domain.model.events.Created(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventCan be published when an entity is created.
-
class
eventsourcing.domain.model.events.Discarded(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventPublished when something is discarded.
-
class
eventsourcing.domain.model.events.DomainEvent(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.QualnameABCBase class for domain events.
Implements methods to make instances read-only, comparable for equality, have recognisable representations, and hashable.
-
class
eventsourcing.domain.model.events.EventWithOriginatorID(originator_id, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEvent-
originator_id¶
-
-
class
eventsourcing.domain.model.events.EventWithOriginatorVersion(originator_version, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventFor events that have an originator version number.
-
originator_version¶
-
-
class
eventsourcing.domain.model.events.EventWithTimestamp(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventFor events that have a timestamp value.
-
timestamp¶
-
-
class
eventsourcing.domain.model.events.EventWithTimeuuid(event_id=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventFor events that have an UUIDv1 event ID.
-
event_id¶
-
-
class
eventsourcing.domain.model.events.Logged(**kwargs)[source]¶ Bases:
eventsourcing.domain.model.events.DomainEventPublished when something is logged.
-
class
eventsourcing.domain.model.events.QualnameABC[source]¶ Bases:
objectBase class that introduces __qualname__ for objects in Python 2.7.
-
class
eventsourcing.domain.model.events.QualnameABCMeta[source]¶ Bases:
abc.ABCMetaSupplies __qualname__ to object classes with this metaclass.
-
eventsourcing.domain.model.events.resolve_attr(obj, path)[source]¶ A recursive version of getattr for navigating dotted paths.
- Args:
- obj: An object for which we want to retrieve a nested attribute. path: A dot separated string containing zero or more attribute names.
- Returns:
- The attribute referred to by obj.a1.a2.a3…
- Raises:
- AttributeError: If there is no such attribute.
-
eventsourcing.domain.model.events.resolve_domain_topic(topic)[source]¶ Return domain class described by given topic.
- Args:
- topic: A string describing a domain class.
- Returns:
- A domain class.
- Raises:
- TopicResolutionError: If there is no such domain class.
eventsourcing.domain.model.snapshot¶
-
class
eventsourcing.domain.model.snapshot.AbstractSnapshop[source]¶ Bases:
object-
originator_id¶ ID of the snapshotted entity.
-
originator_version¶ Version of the last event applied to the entity.
-
state¶ State of the snapshotted entity.
-
topic¶ Path to the class of the snapshotted entity.
-
-
class
eventsourcing.domain.model.snapshot.Snapshot(originator_id, originator_version, topic, state)[source]¶ Bases:
eventsourcing.domain.model.events.EventWithTimestamp,eventsourcing.domain.model.events.EventWithOriginatorVersion,eventsourcing.domain.model.events.EventWithOriginatorID,eventsourcing.domain.model.snapshot.AbstractSnapshop-
state¶ State of the snapshotted entity.
-
topic¶ Path to the class of the snapshotted entity.
-
eventsourcing.domain.services.aes_cipher¶
Infrastructure layer¶
eventsourcing.infrastructure.eventsourcedrepository¶
-
class
eventsourcing.infrastructure.eventsourcedrepository.EventSourcedRepository(event_store, mutator=None, snapshot_strategy=None, use_cache=False, *args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.AbstractEntityRepository-
event_store¶
-
get_entity(entity_id, lt=None, lte=None)[source]¶ Returns entity with given ID, optionally until position.
-
mutator(initial, event)¶ Entity mutator function. Mutates initial state by the event.
Different handlers are registered for different types of event.
-
eventsourcing.infrastructure.eventplayer¶
-
class
eventsourcing.infrastructure.eventplayer.EventPlayer(event_store, mutator, page_size=None, is_short=False, snapshot_strategy=None)[source]¶ Bases:
objectReconstitutes domain entities from domain events retrieved from the event store, optionally with snapshots.
-
get_domain_events(entity_id, gt=None, gte=None, lt=None, lte=None, limit=None, is_ascending=True)[source]¶ Returns domain events for given entity ID.
-
get_most_recent_event(entity_id, lt=None, lte=None)[source]¶ Returns the most recent event for the given entity ID.
-
get_snapshot(entity_id, lt=None, lte=None)[source]¶ Returns a snapshot for given entity ID, according to the snapshot strategy.
-
replay_entity(entity_id, gt=None, gte=None, lt=None, lte=None, limit=None, initial_state=None, query_descending=False)[source]¶ Reconstitutes requested domain entity from domain events found in event store.
-
eventsourcing.infrastructure.snapshotting¶
-
class
eventsourcing.infrastructure.snapshotting.AbstractSnapshotStrategy[source]¶ Bases:
object-
get_snapshot(entity_id, lt=None, lte=None)[source]¶ Gets the last snapshot for entity, optionally until a particular version number.
Return type: Snapshot
-
take_snapshot(entity_id, entity, last_event_version)[source]¶ Takes a snapshot of entity, using given ID, state and version number.
Return type: AbstractSnapshop
-
-
class
eventsourcing.infrastructure.snapshotting.EventSourcedSnapshotStrategy(event_store)[source]¶ Bases:
eventsourcing.infrastructure.snapshotting.AbstractSnapshotStrategySnapshot strategy that uses an event sourced snapshot.
eventsourcing.infrastructure.eventstore¶
-
class
eventsourcing.infrastructure.eventstore.AbstractEventStore[source]¶ Bases:
object
-
class
eventsourcing.infrastructure.eventstore.EventStore(active_record_strategy, sequenced_item_mapper=None)[source]¶ Bases:
eventsourcing.infrastructure.eventstore.AbstractEventStore-
get_domain_events(originator_id, gt=None, gte=None, lt=None, lte=None, limit=None, is_ascending=True, page_size=None)[source]¶
-
iterator_class¶ alias of
SequencedItemIterator
-
eventsourcing.infrastructure.sequenceditem¶
-
class
eventsourcing.infrastructure.sequenceditem.SequencedItem(sequence_id, position, topic, data)¶ Bases:
tuple-
data¶ Alias for field number 3
-
position¶ Alias for field number 1
-
sequence_id¶ Alias for field number 0
-
topic¶ Alias for field number 2
-
eventsourcing.infrastructure.sequenceditemmapper¶
-
class
eventsourcing.infrastructure.sequenceditemmapper.AbstractSequencedItemMapper[source]¶ Bases:
object
-
class
eventsourcing.infrastructure.sequenceditemmapper.SequencedItemMapper(sequenced_item_class=<class 'eventsourcing.infrastructure.sequenceditem.SequencedItem'>, sequence_id_attr_name=None, position_attr_name=None, json_encoder_class=<class 'eventsourcing.infrastructure.transcoding.ObjectJSONEncoder'>, json_decoder_class=<class 'eventsourcing.infrastructure.transcoding.ObjectJSONDecoder'>, always_encrypt=False, cipher=None, other_attr_names=())[source]¶ Bases:
eventsourcing.infrastructure.sequenceditemmapper.AbstractSequencedItemMapperUses JSON to transcode domain events.
-
POSITION_FIELD_INDEX= 1¶
-
SEQUENCE_ID_FIELD_INDEX= 0¶
-
construct_item_args(domain_event)[source]¶ Constructs attributes of a sequenced item from the given domain event.
-
deserialize_event_attrs(event_attrs, is_encrypted)[source]¶ Deserialize event attributes from JSON, optionally with decryption.
-
eventsourcing.infrastructure.transcoding¶
eventsourcing.infrastructure.activerecord¶
-
class
eventsourcing.infrastructure.activerecord.AbstractActiveRecordStrategy(active_record_class, sequenced_item_class=<class 'eventsourcing.infrastructure.sequenceditem.SequencedItem'>)[source]¶ Bases:
object-
all_items()[source]¶ Returns all stored items from all sequences (possibly in chronological order, depending on database).
-
all_records(resume=None, *arg, **kwargs)[source]¶ Returns all records in the table (possibly in chronological order, depending on database).
-
eventsourcing.infrastructure.datastore¶
-
exception
eventsourcing.infrastructure.datastore.DatastoreConnectionError[source]¶ Bases:
eventsourcing.infrastructure.datastore.DatastoreError
-
class
eventsourcing.infrastructure.datastore.DatastoreSettings[source]¶ Bases:
objectBase class for settings for database connection used by a stored event repository.
-
exception
eventsourcing.infrastructure.datastore.DatastoreTableError[source]¶ Bases:
eventsourcing.infrastructure.datastore.DatastoreError
eventsourcing.infrastructure.cassandra.activerecords¶
eventsourcing.infrastructure.cassandra.datastore¶
eventsourcing.infrastructure.sqlalchemy.activerecords¶
eventsourcing.infrastructure.sqlalchemy.datastore¶
eventsourcing.infrastructure.iterators¶
-
class
eventsourcing.infrastructure.iterators.AbstractSequencedItemIterator(active_record_strategy, sequence_id, page_size=None, gt=None, gte=None, lt=None, lte=None, limit=None, is_ascending=True)[source]¶ Bases:
object-
DEFAULT_PAGE_SIZE= 1000¶
-
-
class
eventsourcing.infrastructure.iterators.GetEntityEventsThread(active_record_strategy, sequence_id, gt=None, gte=None, lt=None, lte=None, page_size=None, is_ascending=True, *args, **kwargs)[source]¶ Bases:
threading.Thread
-
class
eventsourcing.infrastructure.iterators.SequencedItemIterator(active_record_strategy, sequence_id, page_size=None, gt=None, gte=None, lt=None, lte=None, limit=None, is_ascending=True)[source]¶ Bases:
eventsourcing.infrastructure.iterators.AbstractSequencedItemIterator
-
class
eventsourcing.infrastructure.iterators.ThreadedSequencedItemIterator(active_record_strategy, sequence_id, page_size=None, gt=None, gte=None, lt=None, lte=None, limit=None, is_ascending=True)[source]¶ Bases:
eventsourcing.infrastructure.iterators.AbstractSequencedItemIterator
eventsourcing.infrastructure.repositories.array¶
-
class
eventsourcing.infrastructure.repositories.array.ArrayRepository(array_size=10000, *args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.array.AbstractArrayRepository,eventsourcing.infrastructure.eventsourcedrepository.EventSourcedRepository
-
class
eventsourcing.infrastructure.repositories.array.BigArrayRepository(base_size=10000, *args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.array.AbstractBigArrayRepository,eventsourcing.infrastructure.eventsourcedrepository.EventSourcedRepository-
subrepo¶
-
subrepo_class¶ alias of
ArrayRepository
-
eventsourcing.infrastructure.integersequencegenerators.base¶
-
class
eventsourcing.infrastructure.integersequencegenerators.base.AbstractIntegerSequenceGenerator[source]¶ Bases:
object
-
class
eventsourcing.infrastructure.integersequencegenerators.base.SimpleIntegerSequenceGenerator(i=0)[source]¶ Bases:
eventsourcing.infrastructure.integersequencegenerators.base.AbstractIntegerSequenceGenerator
eventsourcing.infrastructure.integersequencegenerators.redisincr¶
Exception classes¶
-
exception
eventsourcing.exceptions.ArrayIndexError[source]¶ Bases:
IndexError,eventsourcing.exceptions.EventSourcingErrorRaised when appending item to an array that is full.
-
exception
eventsourcing.exceptions.ConcurrencyError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when appending events at the wrong version to a versioned stream.
-
exception
eventsourcing.exceptions.ConsistencyError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when applying an event stream to a versioned entity.
-
exception
eventsourcing.exceptions.DatasourceSettingsError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when an error is detected in settings for a datasource.
-
exception
eventsourcing.exceptions.EntityIsDiscarded[source]¶ Bases:
AssertionErrorRaised when access to a recently discarded entity object is attempted.
-
exception
eventsourcing.exceptions.EntityVersionNotFound[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaise when accessing an entity version that does not exist.
-
exception
eventsourcing.exceptions.EventSourcingError[source]¶ Bases:
ExceptionBase eventsourcing exception.
-
exception
eventsourcing.exceptions.MismatchedOriginatorError[source]¶ Bases:
eventsourcing.exceptions.ConsistencyErrorRaised when applying an event to an inappropriate object.
-
exception
eventsourcing.exceptions.MismatchedOriginatorIDError[source]¶ Bases:
eventsourcing.exceptions.MismatchedOriginatorErrorRaised when applying an event to the wrong entity or aggregate.
-
exception
eventsourcing.exceptions.MismatchedOriginatorVersionError[source]¶ Bases:
eventsourcing.exceptions.MismatchedOriginatorErrorRaised when applying an event to the wrong version of an entity or aggregate.
-
exception
eventsourcing.exceptions.MutatorRequiresTypeNotInstance[source]¶ Bases:
eventsourcing.exceptions.ConsistencyErrorRaised when mutator function received a class rather than an entity.
-
exception
eventsourcing.exceptions.ProgrammingError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when programming errors are encountered.
-
exception
eventsourcing.exceptions.RepositoryKeyError[source]¶ Bases:
KeyError,eventsourcing.exceptions.EventSourcingErrorRaised when using entity repository’s dictionary like interface to get an entity that does not exist.
-
exception
eventsourcing.exceptions.SequencedItemError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when an integer sequence error occurs e.g. trying to save a version that already exists.
-
exception
eventsourcing.exceptions.TimeSequenceError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when a time sequence error occurs e.g. trying to save a timestamp that already exists.
-
exception
eventsourcing.exceptions.TopicResolutionError[source]¶ Bases:
eventsourcing.exceptions.EventSourcingErrorRaised when unable to resolve a topic to a Python class.
Example application¶
eventsourcing.example.interface.flaskapp¶
eventsourcing.example.application¶
-
class
eventsourcing.example.application.ExampleApplication(**kwargs)[source]¶ Bases:
eventsourcing.application.base.ApplicationWithPersistencePoliciesExample event sourced application with entity factory and repository.
-
eventsourcing.example.application.close_example_application()[source]¶ Shuts down single global instance of application.
To be called when tearing down, perhaps between tests, in order to allow a subsequent call to init_example_application().
-
eventsourcing.example.application.construct_example_application(**kwargs)[source]¶ Application object factory.
eventsourcing.example.domainmodel¶
-
class
eventsourcing.example.domainmodel.AbstractExampleRepository(*args, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.AbstractEntityRepository
-
class
eventsourcing.example.domainmodel.Example(foo='', a='', b='', **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.TimestampedVersionedEntityAn example event sourced domain model entity.
-
class
AttributeChanged(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.example.domainmodel.Event,eventsourcing.domain.model.entity.AttributeChangedPublished when an Example is created.
-
class
Created(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.example.domainmodel.Event,eventsourcing.domain.model.entity.CreatedPublished when an Example is created.
-
class
Discarded(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.example.domainmodel.Event,eventsourcing.domain.model.entity.DiscardedPublished when an Example is discarded.
-
class
Event(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.domain.model.entity.EventLayer supertype.
-
class
Heartbeat(timestamp=None, **kwargs)[source]¶ Bases:
eventsourcing.example.domainmodel.Event,eventsourcing.domain.model.entity.EventPublished when a heartbeat in the entity occurs (see below).
-
a¶ An example attribute.
-
b¶ Another example attribute.
-
foo¶ An example attribute.
-
class
eventsourcing.example.infrastructure¶
-
class
eventsourcing.example.infrastructure.ExampleRepository(event_store, mutator=None, snapshot_strategy=None, use_cache=False, *args, **kwargs)[source]¶ Bases:
eventsourcing.infrastructure.eventsourcedrepository.EventSourcedRepository,eventsourcing.example.domainmodel.AbstractExampleRepositoryEvent sourced repository for the Example domain model entity.
-
mutator(initial, event)¶
-