django-cattrs-fields 0.0.3

django data type support for cattrs

django-cattrs-fields

Note: this is a very experimental project, I'm mostly navigating and discovering how this could work, as much as any help and feedback is appreciated, please do not use in a production environment.

Brings cattrs support to the django world.

this project is the first step of many, it is intended to be minimal, only adding data type support.

current data types

• BooleanField
• CharField
• DecimalField
• EmailField
• SlugField
• URLField
• UUIDField
• IntegerField
• FloatField
• DateField
• DateTimeField
• FileField
• TimeField
• EmptyField

installing

this is not packaged to PyPI yet, for using you need to clone the repository first.

then install the package by running uv sync or uv sync --extra <group name> where group name is one of optional-dependencies listed in pyproject.toml.

if you want a one-shot install use uv sync --all-extras

basic usage:

data model classes are attrs classes, so anything you find in attrs docs also applies here. we also follow cattrs, so anything in their docs also applies

import uuid
from datetime import date, datetime, time
from decimal import Decimal

from attrs import define

from django.core.files.uploadedfile import SimpleUploadedFile

from django-cattrs-fields.converters import converter
from django_cattrs_fields.fields import (
  BooleanField, 
  CharField, 
  DecimalField,
  EmailField, 
  SlugField, 
  URLField, 
  UUIDField, 
  IntegerField, 
  FloatField, 
  DateField,
  DateTimeField,
  TimeField,
)
from django_cattrs_fields.fields.files import FileField

@define
class Human:
    id: UUIDField
    username: CharField
    email: EmailField
    slug: SlugField
    website: URLField
    age: IntegerField
    salary: FloatField
    birth_date: DateField
    signup_date: DateTimeField
    picture: FileField
    accurate_salary: DecimalField
    lunch_time: TimeField


human = {
    "id": uuid.uuid4(),
    "username": "bob",
    "email": "[e-mail]",
    "slug": "bo-b",
    "website": "https://bob.com",
    "age": 25,
    "salary": 1000.43,
    "birth_date": date(year=2000, month=7, day=3),
    "signup_date": datetime.now(),
    "picture": SimpleUploadedFile(name="test_image.jpeg", content=b"wheeee", content_type="image/jpeg"),
    "accurate_salary": Decimal("1000.43"),
    "lunch_time": time(14, 30, 0),
}

structure = converter.structure(human, Human)  # runs structure hooks and validators, then creates an instance of `Human`
normal_data = converter.unstructure(structure)  # runs unstructure hooks, then makes a dict similar to `human` (or what you tell it to), no validators run.

list and querysets

when we are working with a list of multiple objects or a queryset that would contains multiple objects, we need to tell structure and unstructure that it's working with a list

@define
class FoodData:
    name: CharField
    rate: IntegerField


foods = [{"name": "pizza", "rate": 4}, {"name": "burger", "rate": 5}]
# or
foods = Food.objects.all()  # where Food is a django model

structure = converter.structure(foods, list[FoodData])  
unstructure = converter.unstructure(structure, list) # this will make a list[dict]

same logic applies to loads

dump = converter.dumps(structure)
load = converter.loads(dump, list[FoodData])

note that bson and toml don't support list serialization.

Comparison

in comparison with how django forms and DRF serializers work, see the examples below

in django forms we do:

form = MyForm(data)
form.is_valid()
clean_data = form.cleaned_data

in drf we do:

serializer = MySerializer(data)
serializer.is_valid()
clean_data = serializer.validated_data

# to serialize data
content = JSONRenderer().render(serializer.data)

the cattrs equivalent of forms is like this:

try:
    form = converter.structure(data, MyForm)  # where `MyForm` is a cattrs supported class (usually and attrs class)
except* ValueError:  # notice the `*`, this is an exception group (unless you configure cattrs otherwise)
    pass
clean_data = converter.unstructure(form)

or if working with json (or other formats)

try:
    form = converter.loads(data, MyForm)  # take a json data and load it to python
except* ValueError:  # notice the `*`, this is an exception group (unless you configure cattrs otherwise)
    pass
clean_data = converter.unstructure(form)

# to serialize data
data = converter.structure(clean_data, MyForm)  # to dump data, structure it first
content = converter.dumps(data)

structuring and loading also validates the data, so no need for the extra step.

note that converter.structure raises ValueError as an exception group.

Serializers

the basic converter you saw in basic usage section can only structure and unstructure, which is powerful, but we can do more.

cattrs comes with a set of preconfigured converters.

we ship our own version of these converters, which extends on top of cattrs' version, though we call them serializer to avoid some confusion. these are available in django_cattrs_fields.converters directory:

• django_cattrs_fields.converters.bson
• django_cattrs_fields.converters.cbor2
• django_cattrs_fields.converters.json
• django_cattrs_fields.converters.msgpack
• django_cattrs_fields.converters.msgspec
• django_cattrs_fields.converters.orjson
• django_cattrs_fields.converters.pyyaml
• django_cattrs_fields.converters.tomlkit
• django_cattrs_fields.converters.ujson

just import serializer from each of these modules:

from django_cattrs_fields.converters import converter
from django_cattrs_fields.converters.json import serializer


structure = converter.structure(human, Human)
dump: str | bytes = serializer.dumps(structure)  # takes an structured data, dumps a json string
load: Human = serializers.loads(dump, Human)  # takes a dumped data, and loads that as a structured data
data = converter.unstructure(load)  # a dictionary of the data, ready to be used.

it is important to note, while serializer objects also have structure and unstructure methods, they are considered internal API, since they are configured to feed encoding and decoding functionalities, they don't necessarily behave the way you would expect them to.

so in most scenarios you should import a converter and a serializer to handle their specific task, unless you are fully aware how your serializer behaves and can handle it yourself.

the only exception (currently) is the msgspec serializer, which doesn't implement any additional logic and works like a normal converter, tho if the need arises, this could change.

work with django views

you can use the data models you made with this package instead of django forms or serializers

from django_cattrs_fields.converters import converter
from django_cattrs_fields.converters.json import serializer


@define
class Human:
    id: UUIDField
    username: CharField
    email: EmailField
    slug: SlugField
    website: URLField
    age: IntegerField
    salary: FloatField
    birth_date: DateField
    signup_date: DateTimeField
    accurate_salary: DecimalField
    lunch_time: TimeField


def get_data(request):
    if request.method == "POST":
        if request.content_type in {"application/x-www-form-urlencoded", "multipart/form-data"}:
            structured_data = converter.structure({**request.POST.dict(), **request.FILES.dict()}, Human)  # handle html forms, and multipart data
        else:
            structured_data = serializer.loads(request.body, Human)  # handle json (or anything else)

        data: dict[str, Any] = converter.unstructure(structured_data)  # a dictionary of all the POST data (excluding data not covered by Human)

        return HttpResponse("done")

and just like that you have one view that handles html forms and json in one place

note that if POST data contains anything not in Human, it won't show up in the output data (such as csrf token, in this case)

also note that when working with APIs, depending on your client you might need to add csrf_exempt on you view.

saving to database

one you unstructure your data, you have a dictionary of cleaned data. then you can just pass that to your model and create your data

data: dict[str, Any] = converter.unstructure(structured_data)

# either
obj = HumanModel(**dict)
obj.save()

# or
HumanModel.objects.create(**dict)

nullable fields

by default all fields are required and passing a None value will raise an error to make a field nullable, you can use a union

@define
class Product:
    name: CharField  # required
    discount: FloatField | None  # optional

default values

to add a default value, the simplest way is to just add it via assignment

@define
class Product:
    name: CharField  # required
    discount: FloatField = 5.1

for more advanced use check default docs

field params

some fields like DecimalField can take some parameter about their data using typing.Annotated.

from typing import Annotated

from attrs import define

from django_cattrs_fields.fields import DecimalField, CharField, Params

@define
class Product:
  name: CharField
  discount: Annotated[DecimalField, Params(decimal_max_digits=5, decimal_places=3)]

the use case of params differs depending on the field, in the case of Decimal field, decimal_max_digits as equivalent to django's DecimalField's max_digits parameter and decimal_places is equivalent to decimal_places parameter, and are used when structuring the data to validate the decimal value.

like django, DecimalField's params are optional, some fields may require some params in the future.

EmptyField

EmptyField is useful when supporting PATCH requests.

if a field doesn't receive any data and has Empty as its value, it will be omitted when unstructuring.

from django_cattrs_fields.fields import CharField, EmptyField, Empty

@define
class Human:
  name: CharField 
  age: IntegerField | EmptyField = Empty  # default to Empty, or provide Empty manually


struct = converter.structure({"name": "bob"})
# Human(name='bob', age=Empty)
unstruct = converter.unstructure(struct)
# {'name': 'bob'}

as you can see, since age is Empty, it won't be included in the resulting dictionary.

Warning: at the moment, EmptyField is only supported in unions that have only one other type, tho None is also supported, so:

• CharField | EmptyField works.
• CharField | EmptyField | None works.
• CharField | IntegerField | EmptyField doesn't work.

if complex types are required, register your custom hooks until we can figure out how to properly support this. for inspiration, you can check django_cattrs_fields.hooks.empty_hooks to see how other hooks are made.

validation

by default this package runs some validation when you are structuring your data but to add any custom validators you can use attrs built-in validation mechanism.

note that the validations we run are baked in structure hooks, so they will run in any situation. these are validations that django also runs every time you use it's data fields. if you need to turn this off, just create a new converter

File Handling

this package comes with FileField you can use to work with files. when an uploaded file is passed to this field (e.g: user POSTs some file), it goes through validation, then an instance of django's UploadedFile is returned (usually a subclass of UploadedFile is used like InMemoryUploadedFile).

you can save this using the ORM or any other way you do with django.

when serving a File (e.g: user sends a GET request), an instance of django's FieldFile should be passed (django ORM does this automatically) in this case our hooks will return the url of the file.

note that this behavior is different in django and DRF django returns the whole FieldFile object (could be useful with templates), DRF is configurable, it either returns the url or the file name.

if you require a different behaviour, you can change this by hooking your logic and set DCF_FILE_HOOKS to False in your settings file, this will disable all file related hooks.

contribution

I appreciate any help with this project, but please follow Django's Code of Conduct if you have ideas or have found a bug please open an issue on github

to help with development follow these steps:

1. fork the repository from github.
2. clone the project from your fork.
3. install the package with one of the following commands:

• uv sync --group dev
• uv sync --group dev --group ipython
• uv sync --group dev --group prek
• uv sync --group dev --group test you can combine them together or just use uv sync --all-groups to one-shot.

4. run prek install or pre-commit install depending on your choice.

if you are contributing new code, please make sure to add some tests for it.