# Django Frozen Field
Django model custom field for storing a frozen snapshot of an object.
## Principles
* Behaves like a `ForeignKey` but the data is detached from the related object
* Transparent to the client - it looks like the original object
* The frozen object cannot be edited
* The frozen object cannot be saved
* Works even if original model is updated or deleted
### Why not use DRF / Django serializers?
This library has one specific requirement that makes using the existing
solutions hard - to be able to decouple the frozen data from the model,
such that the underlying model can be altered or even deleted, and the
data can still be used as it was at the point of freezing. We use the
model itself only once, when we first set the data - from that point on
the field has no dependency on the original model, using intermediate
dynamic dataclasses that represent the model as it was when the data was
saved. This package does reference a lot of the principles in both DRF
and Django itself - and the structure of the serialized data is similar
to that exported from the queryset serializer.
### Why not just store frozen data as JSON and be done with it?
This is probably a good / safe option for most codebases coming to the
freezing of data for the first time, and we have a lot of ephemeral data
stored in `JSONField` fields ourselves. However, migrating an existing
project from `ForeignKey` to `JSONField`, along with all references to
the data, templates, etc., is painful. This package is designed to make
the migration from 'fresh' to 'frozen' as simple as possible.
## Package internals
The package includes three core modules, `serializers`, `models`, and
`fields`, that together control the serialization process.
#### `frozen_field.models`
This module contains the engine of the package, which is a
`FrozenObjectMeta` dataclass that is responsible for parsing Django
model attributes, extracting data and and creating the dynamic
dataclasses used to represent a Django Model.
You should not need to use this module in your application.
#### `frozen_field.serializers`
This module contains the `freeze_object` and `unfreeze_object` functions
that are responsible for marshalling the serialized data between a
Django Model instance, a dynamic dataclass, and the serialized JSON..
On set:
# model >> dataclass
On save:
dataclass >> dict
On refresh:
dict >> dataclass
You should not need to use this module in your application.
#### `frozen_field.fields`
This module contains the `FrozenObjectField` itself - it is the only part of the
package that should need to use yourself.
#### Evolution of `FrozenObjectField`
The easiest way to understand why the field is structured as it is is to
follow the history:
1. The first implementation serialized just non-related object fields (i.e.
excluded `ForeignKey` and `OneToOneField` attrs)
1. The `include` and `exclude` arguments were added to control which fields were
serialized
1. The `select_related` argument was added to enable the serialization of
top-level related objects (`ForeignKey` / `OneToOneField`)
1. The `select_properties` argument was added to enable the serialization of
simple model properties (`@property`)
1. Support was added for ORM-style paths (using the `__` delimiter) to enable
deep serialization beyond the top-level
1. The `converters` argument was added to enable fine-tuning of the
deserialization process.
## Usage
A frozen field can be declared like a `ForeignKey`:
```python
class Profile(Model):
address = FrozenObjectField(
Address, # The model being frozen
include=[], # defaults to all
exclude=["line_2"], # defaults to none
select_related=[] # add related fields
select_properties=["attr_name"] # add model properties
converters={"field_name": func} # custom deserializer
)
...
>>> profile.address = Address.objects.get(...)
>>> type(profile.address)
types.FrozenAddress
>>> profile.save()
>>> profile.refresh_from_db()
>>> type(profile.address)
types.FrozenAddress
>>> profile.address.id
1
>>> profile.address.line_1
"29 Acacia Avenue"
>>> profile.address.since
datetime.date(2011, 6, 4)
>>> dataclasses.asdict(profile.address)
{
"_meta": {
"pk": 1,
"model": "Address",
"frozen_at": "2021-06-04T18:10:30.549Z",
"fields": {
"id": "django.db.models.AutoField",
"line_1": "django.db.models.CharField",
"since": "django.db.models.DateField"
},
"properties": ["attr_name"]
},
"id": 1,
"line_1": "29 Acacia Avenue",
"since": "2011-06-04T18:10:30.549Z"
"attr_name": "hello"
}
>>> profile.address.json_data()
{
"id": 1,
"line_1": "29 Acacia Avenue",
"since": "2011-06-04T18:10:30.549Z",
"attr_name": "hello"
}
>>> profile.address.id = 2
FrozenInstanceError: cannot assign to field 'id'
>>> profile.address.save()
AttributeError: 'FrozenAddress' object has no attribute 'save'
```
### Controlling serialization
By default only top-level attributes of an object are frozen - related
objects (`ForeignKey`, `OneToOneField`) are ignored. This is by design -
as deep serialization of recursive relationships can get very complex
very quickly, and a deep serialization of an object tree is not
recommended. This library is designed for the simple 'freezing' of basic
data. The recommended pattern is to flatten out the parts of the object
tree that you wish to record. You can control which top-level fields are
included in the frozen data using the `include` and `exclude` arguments.
Note that these are mutually exclusive - by default both are an empty
list, which results in all top-level non-related attributes being
serialized. If `included` is not empty, then *only* the fields in the
list are serialized. If `excluded` is not empty then all fields *except*
those in the list are serialized.
That said, there is support for related object capture using the
`select_related` argument.
The `select_properties` argument can be used to add model properties
(e.g. methods decorated with `@property`) to the serialization. NB this
currently does no casting of the value when deserialized (as it doesn't
know what the type is), so if your property is a date, it will come back
as a string (isoformat). If you want it to return a `date` you will want
to use converters.
The `converters` argument is used to override the default conversion of
the JSON back to something more appropriate. A typical use case would be
the casting of a property which has no default backing field to use. In
this case you could use the builtin Django `parse_date` function
```python
field = FrozenObjectField(
Profile,
include=[],
exclude=[],
select_related=[],
select_properties=["date_registered"],
converters={"date_registered": parse_date}
)
```
## How it works
The internal wrangling of a Django model to a JSON string is done using dynamic
dataclasses, created on the fly using the `dataclasses.make_dataclass` function.
The new dataclass contains one fixed property, `meta`, which is itself an
instance of a concrete dataclass, `FrozenObjectMeta`. This ensures that each
serialized blob contains enough original model field metadata to be able to
deserialize the JSONField back into something that resembles the original. This
is required because the process of serializing the data as JSON will convert
certain unsupported datatypes (e.g. `Decimal`, `float`, `date`, `datetime`,
`UUID`) to string equivalents, and in order to deserialize these values we need
to know what type the original value was. This is very similar to how Django's
own `django.core.serializers` work.
#### Running tests
The tests use `pytest` as the test runner. If you have installed the `poetry`
evironment, you can run them using:
```
$ poetry run pytest
```