Research
Security News
Kill Switch Hidden in npm Packages Typosquatting Chalk and Chokidar
Socket researchers found several malicious npm packages typosquatting Chalk and Chokidar, targeting Node.js developers with kill switches and data theft.
.. image:: https://badges.gitter.im/Join%20Chat.svg :alt: Join the chat at https://gitter.im/romgar/django-dirtyfields :target: https://gitter.im/romgar/django-dirtyfields?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge .. image:: https://img.shields.io/pypi/v/django-dirtyfields.svg :alt: Published PyPI version :target: https://pypi.org/project/django-dirtyfields/ .. image:: https://github.com/romgar/django-dirtyfields/actions/workflows/tests.yml/badge.svg :alt: Github Actions Test status :target: https://github.com/romgar/django-dirtyfields/actions/workflows/tests.yml .. image:: https://coveralls.io/repos/github/romgar/django-dirtyfields/badge.svg?branch=develop :alt: Coveralls code coverage status :target: https://coveralls.io/github/romgar/django-dirtyfields?branch=develop .. image:: https://readthedocs.org/projects/django-dirtyfields/badge/?version=latest :alt: Read the Docs documentation status :target: https://django-dirtyfields.readthedocs.io/en/latest/
Tracking dirty fields on a Django model instance. Dirty means that field in-memory and database values are different.
This package is compatible and tested with the following Python & Django versions:
+------------------------+-----------------------------------+ | Django | Python | +========================+===================================+ | 2.2, 3.0, 3.1 | 3.9 | +------------------------+-----------------------------------+ | 3.2, 4.0 | 3.9, 3.10 | +------------------------+-----------------------------------+ | 4.1 | 3.9, 3.10, 3.11 | +------------------------+-----------------------------------+ | 4.2 | 3.9, 3.10, 3.11, 3.12 | +------------------------+-----------------------------------+ | 5.0 | 3.10, 3.11, 3.12 | +------------------------+-----------------------------------+ | 5.1 | 3.10, 3.11, 3.12, 3.13 | +------------------------+-----------------------------------+
.. code-block:: bash
$ pip install django-dirtyfields
To use django-dirtyfields
, you need to:
DirtyFieldsMixin
in the Django model you want to track... code-block:: python
from django.db import models
from dirtyfields import DirtyFieldsMixin
class ExampleModel(DirtyFieldsMixin, models.Model):
"""A simple example model to test dirty fields mixin with"""
boolean = models.BooleanField(default=True)
characters = models.CharField(blank=True, max_length=80)
Use one of these 2 functions on a model instance to know if this instance is dirty, and get the dirty fields:
is_dirty()
get_dirty_fields()
.. code-block:: python
>>> model = ExampleModel.objects.create(boolean=True,characters="first value")
>>> model.is_dirty()
False
>>> model.get_dirty_fields()
{}
>>> model.boolean = False
>>> model.characters = "second value"
>>> model.is_dirty()
True
>>> model.get_dirty_fields()
{'boolean': True, "characters": "first_value"}
Consult the full documentation <https://django-dirtyfields.readthedocs.io/>
_ for more information.
FAQs
Tracking dirty fields on a Django model instance.
We found that django-dirtyfields demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
Socket researchers found several malicious npm packages typosquatting Chalk and Chokidar, targeting Node.js developers with kill switches and data theft.
Security News
pnpm 10 blocks lifecycle scripts by default to improve security, addressing supply chain attack risks but sparking debate over compatibility and workflow changes.
Product
Socket now supports uv.lock files to ensure consistent, secure dependency resolution for Python projects and enhance supply chain security.