Periodically remove data from your Django app.
Project description
django-data-purger
Periodically remove data from your Django app.
Getting Started
- Install django-data-purger
Use Poetry to add the package
$ poetry add django-data-purger
- Add
django_data_purgertoINSTALLED_APPS
Update your INSTALLED_APP setting:
INSTALLED_APPS = [
'django...',
...
'django_data_purger',
]
- Create a data purger in the Django app you want to clean periodically
Example:
# data_purger.py
from django_data_purger.data_purger import DataPurger, PurgeResult
from app.models import DataModel
from datetime import datetime, timedelta
class PurgeDataModel(DataPurger):
expected_delete_models = ("app.DataModel",)
def run(self, *, now: datetime) -> list[PurgeResult]:
old_threshold = now - timedelta(weeks=6)
entries = DataModel.objects.filter(
created_time__lte=old_threshold,
)
return self._delete_queryset_in_batch(
entries, batch_size=DataPurger.BATCH_SIZE_LARGE
)
- Register the data purger in the
DATA_PURGERSsetting
Add the purger to your settings:
DATA_PURGERS = [
"app.data_purger.PurgeDataModel",
]
- Run the management command to purge old data
Configure this command to run periodically using a scheduler like cron:
$ python manage.py run_data_purgers --force
Settings
| Setting name | Type | Default | Description |
|---|---|---|---|
DATA_PURGERS |
list[str] |
[] |
Array with import strings to data purgers in your project. |
The DataPurger Class
The DataPurger class can be used to UPDATE or DELETE models. It runs within a transaction and ensures that updates or deletions are only applied to whitelisted models.
Update Model Instances
class PurgeDataModel(DataPurger):
expected_update_models = ("app.DataModel",)
def run(self, *, now: datetime) -> list[PurgeResult]:
old_threshold = now - timedelta(weeks=6)
entries = DataModel.objects.filter(
created_time__lte=old_threshold,
)
return self._update_queryset_in_batch(
entries, updates={"is_deleted": True}, batch_size=DataPurger.BATCH_SIZE_MEDIUM
)
Delete Model Instances
class PurgeDataModel(DataPurger):
expected_delete_models = ("app.DataModel",)
def run(self, *, now: datetime) -> list[PurgeResult]:
old_threshold = now - timedelta(weeks=6)
entries = DataModel.objects.filter(
created_time__lte=old_threshold,
)
return self._delete_queryset_in_batch(
entries, batch_size=DataPurger.BATCH_SIZE_LARGE
)
Planning for Model Instance Deletion
Models often depend on each other via ForeignKey or ManyToManyField relationships. It can be challenging to determine the correct order for deleting models without causing unexpected cascading deletions or errors from on_delete=models.PROTECT.
django-data-purger includes a tool to explore model dependencies. ✅ and 🛑 icons indicate whether a data purger for the model is already defined.
Example:
$ poetry run python manage.py calculate_model_dependencies --model app.DataModel
The following models depend on app.DataModel:
- ...
The following models depend on ...:
- ...
==============
2 models depend on app.DataModel.
==============
The models need to be deleted in the following order to safely delete app.DataModel:
(Models in the same batch can be deleted in any order.)
Batch 1:
- ✅ ...
- 🛑 ...
Batch 2:
- ✅ ...
Listing Models with Enabled Data Purgers
To view all models with a configured data purger:
$ python manage.py print_data_purging_enabled_tables --action delete
- app.DataModel
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