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README.rst

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+Django Dharma
+=============
+
+Django Dharma is a Django library designed to facilitate running checks
+on models. It provides a structured way to perform and manage checks on
+your Django models.
+
+Why Use Django Dharma?
+----------------------
+
+Django Dharma is useful in scenarios where you need to validate data
+after it has been entered into your system. For example, if you are
+importing data from an external source without validating it during the
+import process (maybe you want to get them in your system as they are),
+you might want to perform validation checks afterward. With Django
+Dharma, you can execute checks such as:
+
+-  How many records have been inserted?
+-  Does the ``foo`` column contain values other than ``bar``?
+
+You can save the results of these checks and then analyze them or take
+necessary precautions based on the findings.
+
+Project Structure
+-----------------
+
+The project consists of two main components:
+
+-  ``django_dharma/``: The core library containing logic for running
+   model checks.
+-  ``test_project/``: A test Django project used to perform migrations
+   and test the library with different Django versions.
+
+Installation
+------------
+
+To install Django Dharma, you can use ``pip``:
+
+#. **Install the package:**
+
+   ``bash pip install django-dharma``
+
+#. **Add ``django_dharma`` to your Django project's ``INSTALLED_APPS``
+   in ``settings.py``:**
+
+   ``python INSTALLED_APPS = [     # ... other installed apps     'django_dharma', ]``
+
+Usage
+-----
+
+To use Django Dharma, you need to run the ``perform_checks`` management
+command to execute the checks on your models. This command will collect
+all implementations of the specified protocol and run the checks, saving
+any anomalies to the ``Anomaly`` model.
+
+#. **Run migrations:**
+
+   \```bash python manage.py migrate
+
+   \``\`
+
+#. **Create a check:**
+
+   To create a check, define a class that implements the
+   ``CheckProtocol``. The class should include a ``run_checks`` method
+   and an attribute ``model`` of type ``models.MyModel``. Here is an
+   example:
+
+   \```python from datetime import datetime from django\ *dharma.base
+   import count*\ check from myapp import models
+
+   class MyModelCheck: model = models.MyModel
+
+   ::
+
+      def run_checks(self) -> None:
+           """
+           Verifies that the 'foo' column contains only 'biz' and 'foo' values.
+           """
+           allowed_values = {'biz', 'foo'}
+
+           # Get distinct values in the 'foo' column
+           distinct_values = set(self.model.objects.values_list('foo', flat=True).distinct())
+
+           # Check if all distinct values are in the allowed_values set
+           assert distinct_values.issubset(allowed_values), (
+               f"Column 'foo' contains unexpected values: {distinct_values - allowed_values}"
+           )
+
+
+           """
+           Some example checks are included in this package.
+           Please contribute if you have useful checks to share!
+           This check verifies that there are at least 30 records in the MyModel model for today.
+           """
+           count_check(model=self.model, filters={"date": datetime.today().date()}, count=30)
+
+           print("All checks passed!")
+
+   \``\`
+
+#. **Run the checks:**
+
+   ``bash python manage.py perform_checks``
+
+Contributing
+------------
+
+If you would like to contribute to the project, please follow these
+steps:
+
+#. **Fork the repository.**
+
+#. **Create a branch for your change:**
+
+   ``bash git checkout -b my-feature``
+
+#. **Add and commit your changes:**
+
+   ``bash git add . git commit -m "Add a new feature"``
+
+#. **Push your branch and open a pull request.**
+
+Testing
+-------
+
+The project uses ``flake8`` for linting, ``black`` for code formatting,
+and ``isort`` for import sorting. You can run linting and formatting
+checks with the following commands:
+
+``bash poetry run flake8 django_dharma/ poetry run black --check django_dharma/ poetry run isort --check-only django_dharma/``