Event Sourcing in Python

A library for event sourcing in Python.

"totally amazing and a pleasure to use"

"very clean and intuitive"

"a huge help and time saver"

Please read the docs. See also extension projects.

Installation

Use pip to install the stable distribution from the Python Package Index.

$ pip install eventsourcing

Please note, it is recommended to install Python packages into a Python virtual environment.

Synopsis

Define aggregates with the Aggregate class and the @event decorator.

from eventsourcing.domain import Aggregate, event

class Dog(Aggregate):
    @event('Registered')
    def __init__(self, name):
        self.name = name
        self.tricks = []

    @event('TrickAdded')
    def add_trick(self, trick):
        self.tricks.append(trick)

Define application objects with the Application class.

from eventsourcing.application import Application

class DogSchool(Application):
    def register_dog(self, name):
        dog = Dog(name)
        self.save(dog)
        return dog.id

    def add_trick(self, dog_id, trick):
        dog = self.repository.get(dog_id)
        dog.add_trick(trick)
        self.save(dog)

    def get_dog(self, dog_id):
        dog = self.repository.get(dog_id)
        return {'name': dog.name, 'tricks': tuple(dog.tricks)}

Write a test.

def test_dog_school():
    # Construct application object.
    school = DogSchool()

    # Evolve application state.
    dog_id = school.register_dog('Fido')
    school.add_trick(dog_id, 'roll over')
    school.add_trick(dog_id, 'play dead')

    # Query application state.
    dog = school.get_dog(dog_id)
    assert dog['name'] == 'Fido'
    assert dog['tricks'] == ('roll over', 'play dead')

    # Select notifications.
    notifications = school.notification_log.select(start=1, limit=10)
    assert len(notifications) == 3

Run the test with the default persistence module. Events are stored in memory using Python objects.

test_dog_school()

Configure the application to run with an SQLite database. Other persistence modules are available.

import os

os.environ["PERSISTENCE_MODULE"] = 'eventsourcing.sqlite'
os.environ["SQLITE_DBNAME"] = 'dog-school.db'

Run the test with SQLite.

test_dog_school()

See the documentation for more information.

Features

Aggregates and applications — base classes for event-sourced aggregates and applications. Suggests how to structure an event-sourced application. All classes are fully type-hinted to guide developers in using the library.

Flexible event store — flexible persistence of aggregate events. Combines an event mapper and an event recorder in ways that can be easily extended. Mapper uses a transcoder that can be easily extended to support custom model object types. Recorders supporting different databases can be easily substituted and configured with environment variables.

Application-level encryption and compression — encrypts and decrypts events inside the application. This means data will be encrypted in transit across a network ("on the wire") and at disk level including backups ("at rest"), which is a legal requirement in some jurisdictions when dealing with personally identifiable information (PII) for example the EU's GDPR. Compression reduces the size of stored aggregate events and snapshots, usually by around 25% to 50% of the original size. Compression reduces the size of data in the database and decreases transit time across a network.

Snapshotting — reduces access-time for aggregates that have many events.

Versioning - allows changes to be introduced after an application has been deployed. Both aggregate events and aggregate snapshots can be versioned.

Optimistic concurrency control — ensures a distributed or horizontally scaled application doesn't become inconsistent due to concurrent method execution. Leverages optimistic concurrency controls in adapted database management systems.

Notifications and projections — reliable propagation of application events with pull-based notifications allows the application state to be projected accurately into replicas, indexes, view models, and other applications. Supports materialized views and CQRS.

Event-driven systems — reliable event processing. Event-driven systems can be defined independently of particular persistence infrastructure and mode of running.

Detailed documentation — documentation provides general overview, introduction of concepts, explanation of usage, and detailed descriptions of library classes. All code is annotated with type hints.

Worked examples — includes examples showing how to develop aggregates, applications and systems.

Extensions

The GitHub organisation Event Sourcing in Python hosts extension projects for the Python eventsourcing library. There are projects that adapt popular ORMs such as Django and SQLAlchemy. There are projects that adapt specialist event stores such as Axon Server and EventStoreDB. There are projects that support popular NoSQL databases such as DynamoDB. There are also projects that provide examples of using the library with web frameworks such as FastAPI and Flask, and for serving applications and running systems with efficient inter-process communication technologies like gRPC. And there are examples of event-sourced applications and systems of event-sourced applications, such as the Paxos system, which is used as the basis for a replicated state machine, which is used as the basis for a distributed key-value store.