fields-of-gold 0.1.3
A Django library for providing useful DB model fields.
Keywords: Django, Pydantic, JSON, JSONField, Schema

Fields of Gold
==============

A Django library providing useful DB model fields.


Installation & setup
--------------------

1. `pip install fields-of-gold`
2. Add `"fields_of_gold"` to your `INSTALLED_APPS`.
3. Use the fields in your models.


Fields
------

### TypedJSONField

A JSONField which can have an enforced schema using [Pydantic](https://docs.pydantic.dev/) models.
The underlying storage uses the JSONField, but you can interact with the data via the declared Pydantic type.

Because the underlying storage is using JSON, you can swap out existing JSONFields for TypedJSONField without
having to perform any manipulation to the stored data, so long as the existing data conforms to your Pydantic schema.

#### Definition

```python
TypedJSONField(
    # The Pydantic model class of your data structure
    type: type[pydantic.BaseModel],

    # A JSON encoder class. The default uses `pydantic.BaseModel.model_dump(mode="json")`:
    encoder: type[json.JSONEncoder] = PydanticJSONEncoder,

    # Allows you to force validation of the data during save (rather than only during validation),
    # raising IntegrityError for invalid data:
    force_valid: bool = False,

    # The other standard field kwargs, such as `null`, etc
    **kwargs,
)
```

#### Example usage:

```python
from django.db import models
from fields_of_gold import TypedJSONField
from pydantic import BaseModel

class MyType(BaseModel):
    my_int: int
    my_str: str


class MyModel(models.Model):
    typed_field = TypedJSONField(type=MyType)


...

instance = MyModel(typed_field=MyType(my_int=1, my_str=2))
instance.full_clean()
instance.save()
```

#### Handling existing data

If you've already got data in your database which doesn't conform to the Pydantic model schema that
you've defined then when you fetch a Django model instance from the database the field value will
simply be set to the raw underlying JSON value rather than the Pydantic model instance.
This allows you to still fetch the objects from your DB, and to fix the data. Here an example
using the `MyType` and `MyModel` from above:

```python

obj = MyModel.objects.get()
if not isinstnce(obj.typed_field, MyType):
    # Invalid data, need to fix it:
    if isinstance(obj.typed_field, dict):
        if "my_int" not in obj.typed_field:
            obj.typed_field["my_int"] = 0
        if "my_str" not in obj.typed_field:
            obj.typed_field["my_str"] = ""
        # Note that leaving the data as a dict is fine, so long as it matches the schema of MyType
    elif isinstance(obj.typed_field, list):
        # Totally the wrong type of data
        obj.typed_field = MyType()
    obj.save()
```

You might want to handle existing invalid data in your model's `__init__` method.


### NullableOneToOneField

A modified OneToOneField which is unique but nullable.

In Django, using `ForeignKey(unique=True, null=True)` will raise a warning recommending that you should use
`OneToOneField` instead. But using `OneToOneField(null=True)` won't respect the null-able-ness, so trying to
access `obj.my_one_to_one_field` will raise `DoesNotExist`, and the same with the reverse lookup.

This field solves that problem by allowing the field to be nullable while still enforcing its uniqueness and
not giving you unnecessary warnings.