https://github.com/cloudblue/django-cqrs
django-cqrs is an Django application, that implements CQRS data synchronization between several Django micro-services
https://github.com/cloudblue/django-cqrs
cqrs django django-cqrs highload microservices python rabbitmq
Last synced: 2 months ago
JSON representation
django-cqrs is an Django application, that implements CQRS data synchronization between several Django micro-services
- Host: GitHub
- URL: https://github.com/cloudblue/django-cqrs
- Owner: cloudblue
- License: apache-2.0
- Created: 2020-05-27T08:19:10.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2026-03-25T16:10:51.000Z (3 months ago)
- Last Synced: 2026-03-26T18:04:36.097Z (3 months ago)
- Topics: cqrs, django, django-cqrs, highload, microservices, python, rabbitmq
- Language: Python
- Homepage: https://django-cqrs.readthedocs.io/en/latest/
- Size: 1.01 MB
- Stars: 128
- Watchers: 6
- Forks: 26
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
Django CQRS
===========
[](https://readthedocs.org/projects/django-cqrs)
[](https://sonarcloud.io/dashboard?id=django-cqrs)
[](https://pypi.python.org/pypi/django-cqrs/)
[](https://sonarcloud.io/dashboard?id=django-cqrs)
[](https://pypi.org/project/django-cqrs/)
`django-cqrs` is an Django application, that implements CQRS data synchronisation between several Django microservices.
CQRS
----
In Connect we have a rather complex Domain Model. There are many microservices, that are [decomposed by subdomain](https://microservices.io/patterns/decomposition/decompose-by-subdomain.html) and which follow [database-per-service](https://microservices.io/patterns/data/database-per-service.html) pattern. These microservices have rich and consistent APIs. They are deployed in cloud k8s cluster and scale automatically under load. Many of these services aggregate data from other ones and usually [API Composition](https://microservices.io/patterns/data/api-composition.html) is totally enough. But, some services are working too slowly with API JOINS, so another pattern needs to be applied.
The pattern, that solves this issue is called [CQRS - Command Query Responsibility Segregation](https://microservices.io/patterns/data/cqrs.html). Core idea behind this pattern is that view databases (replicas) are defined for efficient querying and DB joins. Applications keep their replicas up to data by subscribing to [Domain events](https://microservices.io/patterns/data/domain-event.html) published by the service that owns the data. Data is [eventually consistent](https://en.wikipedia.org/wiki/Eventual_consistency) and that's okay for non-critical business transactions.
Documentation
=============
Full documentation is available at [https://django-cqrs.readthedocs.org](https://django-cqrs.readthedocs.org).
Examples
========
You can find an example project [here](examples/demo_project/README.md)
Integration
-----------
* Setup `RabbitMQ`
* Install `django-cqrs`
* Apply changes to master service, according to RabbitMQ settings
```python
# models.py
from django.db import models
from dj_cqrs.mixins import MasterMixin, RawMasterMixin
class Account(MasterMixin, models.Model):
CQRS_ID = 'account'
CQRS_PRODUCE = True # set this to False to prevent sending instances to Transport
class Author(MasterMixin, models.Model):
CQRS_ID = 'author'
CQRS_SERIALIZER = 'app.api.AuthorSerializer'
# For cases of Diamond Multi-inheritance or in case of Proxy Django-models the following approach could be used:
from mptt.models import MPTTModel
from dj_cqrs.metas import MasterMeta
class ComplexInheritanceModel(MPTTModel, RawMasterMixin):
CQRS_ID = 'diamond'
class BaseModel(RawMasterMixin):
CQRS_ID = 'base'
class ProxyModel(BaseModel):
class Meta:
proxy = True
MasterMeta.register(ComplexInheritanceModel)
MasterMeta.register(BaseModel)
```
```python
# settings.py
CQRS = {
'transport': 'dj_cqrs.transport.rabbit_mq.RabbitMQTransport',
'host': RABBITMQ_HOST,
'port': RABBITMQ_PORT,
'user': RABBITMQ_USERNAME,
'password': RABBITMQ_PASSWORD,
}
```
* Apply changes to replica service, according to RabbitMQ settings
```python
from django.db import models
from dj_cqrs.mixins import ReplicaMixin
class AccountRef(ReplicaMixin, models.Model):
CQRS_ID = 'account'
id = models.IntegerField(primary_key=True)
class AuthorRef(ReplicaMixin, models.Model):
CQRS_ID = 'author'
CQRS_CUSTOM_SERIALIZATION = True
@classmethod
def cqrs_create(cls, sync, mapped_data, previous_data=None, meta=None):
# Override here
pass
def cqrs_update(self, sync, mapped_data, previous_data=None, meta=None):
# Override here
pass
```
```python
# settings.py
CQRS = {
'transport': 'dj_cqrs.transport.RabbitMQTransport',
'queue': 'account_replica',
'host': RABBITMQ_HOST,
'port': RABBITMQ_PORT,
'user': RABBITMQ_USERNAME,
'password': RABBITMQ_PASSWORD,
}
```
* Apply migrations on both services
* Run consumer worker on replica service. Management command: `python manage.py cqrs_consume -w 2`
Notes
-----
* When there are master models with related entities in CQRS_SERIALIZER, it's important to have operations within atomic transactions. CQRS sync will happen on transaction commit.
* Please, avoid saving different instances of the same entity within transaction to reduce syncing and potential racing on replica side.
* Updating of related model won't trigger CQRS automatic synchronization for master model. This needs to be done manually.
* By default `update_fields` doesn't trigger CQRS logic, but it can be overridden for the whole application in settings:
```python
settings.CQRS = {
...
'master': {
'CQRS_AUTO_UPDATE_FIELDS': True,
},
...
}
```
or a special flag can be used in each place, where it's required to trigger CQRS flow:
```python
instance.save(update_fields=['name'], update_cqrs_fields=True)
```
* When only needed instances need to be synchronized, there is a method `is_sync_instance` to set filtering rule.
It's important to understand, that CQRS counting works even without syncing and rule is applied every time model is updated.
Example:
```python
class FilteredSimplestModel(MasterMixin, models.Model):
CQRS_ID = 'filter'
name = models.CharField(max_length=200)
def is_sync_instance(self):
return len(str(self.name)) > 2
```
Django Admin
-----------
Add action to synchronize master items from Django Admin page.
```python
from django.db import models
from django.contrib import admin
from dj_cqrs.admin_mixins import CQRSAdminMasterSyncMixin
class AccountAdmin(CQRSAdminMasterSyncMixin, admin.ModelAdmin):
...
admin.site.register(models.Account, AccountAdmin)
```
* If necessary, override ```_cqrs_sync_queryset``` from ```CQRSAdminMasterSyncMixin``` to adjust the QuerySet and use it for synchronization.
Utilities
---------
Bulk synchronizer without transport (usage example: it may be used for initial configuration). May be used at planned downtime.
* On master service: `python manage.py cqrs_bulk_dump --cqrs-id=author` -> `author.dump`
* On replica service: `python manage.py cqrs_bulk_load -i=author.dump`
Filter synchronizer over transport (usage example: sync some specific records to a given replica). Can be used dynamically.
* To sync all replicas: `python manage.py cqrs_sync --cqrs-id=author -f={"id__in": [1, 2]}`
* To sync all instances only with one replica: `python manage.py cqrs_sync --cqrs-id=author -f={} -q=replica`
Set of diff synchronization tools:
* To get diff and synchronize master service with replica service in K8S:
```bash
kubectl exec -i MASTER_CONTAINER -- python manage.py cqrs_diff_master --cqrs-id=author |
kubectl exec -i REPLICA_CONTAINER -- python manage.py cqrs_diff_replica |
kubectl exec -i MASTER_CONTAINER -- python manage.py cqrs_diff_sync
```
* If it's important to check sync and clean up deleted objects within replica service in K8S:
```bash
kubectl exec -i REPLICA_CONTAINER -- python manage.py cqrs_deleted_diff_replica --cqrs-id=author |
kubectl exec -i MASTER_CONTAINER -- python manage.py cqrs_deleted_diff_master |
kubectl exec -i REPLICA_CONTAINER -- python manage.py cqrs_deleted_sync_replica
```
Development
===========
1. Python >= 3.10
2. Install dependencies `requirements/dev.txt`
3. We use `isort` library to order and format our imports, and `black` - to format the code.
We check it using `flake8-isort` and `flake8-black` libraries (automatically on `flake8` run).
For convenience you may run `isort . && black .` to format the code.
Testing
=======
Unit testing
------
1. Python >= 3.10
2. Install dependencies `requirements/test.txt`
3. `export PYTHONPATH=/your/path/to/django-cqrs/`
Run tests with various RDBMS:
- `cd integration_tests`
- `DB=postgres docker compose -f docker-compose.yml -f rdbms.yml run app_test`
- `DB=mysql docker compose -f docker-compose.yml -f rdbms.yml run app_test`
Check code style: `flake8`
Run tests: `pytest`
Tests reports are generated in `tests/reports`.
* `out.xml` - JUnit test results
* `coverage.xml` - Coverage xml results
To generate HTML coverage reports use:
`--cov-report html:tests/reports/cov_html`
Integrational testing
------
1. docker compose
2. `cd integration_tests`
3. `docker compose run master`