Django Styleguide

Django styleguide used in HackSoft projects.

Expect often updates as we discuss & decide upon different things.

Table of contents:

• Examples
• Overview
• Cookie Cutter
• Models
  • Custom validation
  • Properties
  • Methods
  • Testing
• Services
• Selectors
• APIs & Serializers
  • An example list API
  • An example detail API
  • An example create API
  • An example update API
  • Nested serializers
• Exception Handling
  • Raising Exceptions in Services
  • Handle Exceptions in APIs
• Inspiration

Examples

Most of the examples are taken from HackSoft's Learning Management System - Odin - https://github.com/HackSoftware/Odin

Overview

In Django, business logic should live in:

• Model properties (with some exceptions).
• Model clean method for additional validations (with some exceptions).
• Services - functions, that take care of code written to the database.
• Selectors - functions, that take care of code taken from the database.

In Django, business logic should not live in:

• APIs and Views.
• Serializers and Forms.
• Form tags.
• Model save method.

Model properties vs selectors:

• If the model property spans multiple relations, it should better be a selector.
• If a model property, added to some list API, will cause N + 1 problem that cannot be easily solved with select_related, it should better be a selector.

Cookie Cutter

We recommend starting every new project with cookiecutter-django

Once this is done, depending on the context, remove everything that's not needed.

The usual list is:

• allauth
• templates
• Settings for things that are not yet required (always add settings when necessary)

Models

Lets take a look at an example model:

class Course(models.Model):
    name = models.CharField(unique=True, max_length=255)

    start_date = models.DateField()
    end_date = models.DateField()

    attendable = models.BooleanField(default=True)

    students = models.ManyToManyField(
        Student,
        through='CourseAssignment',
        through_fields=('course', 'student')
    )

    teachers = models.ManyToManyField(
        Teacher,
        through='CourseAssignment',
        through_fields=('course', 'teacher')
    )

    slug_url = models.SlugField(unique=True)

    repository = models.URLField(blank=True)
    video_channel = models.URLField(blank=True, null=True)
    facebook_group = models.URLField(blank=True, null=True)

    logo = models.ImageField(blank=True, null=True)

    public = models.BooleanField(default=True)

    generate_certificates_delta = models.DurationField(default=timedelta(days=15))

    objects = CourseManager()

    def clean(self):
        if self.start_date > self.end_date:
            raise ValidationError("End date cannot be before start date!")

    def save(self, *args, **kwargs):
        self.full_clean()
        return super().save(*args, **kwargs)

    @property
    def visible_teachers(self):
        return self.teachers.filter(course_assignments__hidden=False).select_related('profile')

    @property
    def duration_in_weeks(self):
        weeks = rrule.rrule(
            rrule.WEEKLY,
            dtstart=self.start_date,
            until=self.end_date
        )
        return weeks.count()

    @property
    def has_started(self):
        now = get_now()

        return self.start_date <= now.date()

    @property
    def has_finished(self):
        now = get_now()

        return self.end_date <= now.date()

    @property
    def can_generate_certificates(self):
        now = get_now()

        return now.date() <= self.end_date + self.generate_certificates_delta

    def __str__(self) -> str:
        return self.name

Few things to spot here.

Custom validation:

• There's a custom model validation, defined in clean. This validation uses only model fields and no relations.
• This requires someone to call full_clean() on the model instance. The best place to do that is in the save() method of the model. Otherwise people can forget to call full_clean() in the respective service.

Properties:

• All properties, expect visible_teachers work directly on model fields.
• visible_teachers is a great candidate for a selector.

We have few general rules for custom validations & model properties / methods:

Custom validation

• If the custom validation depends only on the non-relational model fields, define it in clean and call full_clean in save.
• If the custom validation is more complex & spans relationships, do it in the service that creates the model.
• It's OK to combine both clean and additional validation in the service.

Properties

• If your model properties use only non-relational model fields, they are OK to stay as properties.
• If a property, such as visible_teachers starts spanning relationships, it's better to define a selector for that.

Methods

• If you need a method that updates several fields at once (for example - created_at and created_by when something happens), you can create a model method that does the job.
• Every model method should be wrapped in a service. There should be no model method calling outside a service.

Testing

Models need to be tested only if there's something additional to them - like custom validation or properties.

If we are strict & don't do custom validation / properties, then we can test the models without actually writing anything to the database => we are going to get quicker tests.

For example, if we want to test the custom validation, here's how a test could look like:

from datetime import timedelta

from django.test import TestCase
from django.core.exceptions import ValidationError

from odin.common.utils import get_now

from odin.education.factories import CourseFactory
from odin.education.models import Course


class CourseTests(TestCase):
    def test_course_end_date_cannot_be_before_start_date(self):
        start_date = get_now()
        end_date = get_now() - timedelta(days=1)

        course_data = CourseFactory.build()
        course_data['start_date'] = start_date
        course_data['end_date'] = end_date

        course = Course(**course_data)

        with self.assertRaises(ValidationError):
            course.full_clean()

There's a lot going on in this test:

• get_now() returns a timezone aware datetime.
• CourseFactory.build() will return a dictionary with all required fields for a course to exist.
• We replace the values for start_date and end_date.
• We assert that a validation error is going to be raised if we call full_clean.
• We are not hitting the database at all, since there's no need for that.

Here's how CourseFactory looks like:

class CourseFactory(factory.DjangoModelFactory):
    name = factory.Sequence(lambda n: f'{n}{faker.word()}')
    start_date = factory.LazyAttribute(
        lambda _: get_now()
    )
    end_date = factory.LazyAttribute(
        lambda _: get_now() + timedelta(days=30)
    )

    slug_url = factory.Sequence(lambda n: f'{n}{faker.slug()}')

    repository = factory.LazyAttribute(lambda _: faker.url())
    video_channel = factory.LazyAttribute(lambda _: faker.url())
    facebook_group = factory.LazyAttribute(lambda _: faker.url())

    class Meta:
        model = Course

    @classmethod
    def _build(cls, model_class, *args, **kwargs):
        return kwargs

    @classmethod
    def _create(cls, model_class, *args, **kwargs):
        return create_course(**kwargs)

Services

A service is a simple function that:

• Lives in your_app/services.py module
• Takes keyword-only arguments
• Is type-annotated (even if you are not using mypy at the moment)
• Works mostly with models & other services and selectors
• Does business logic - from simple model creation to complex cross-cutting concerns, to calling external services & tasks.

An example service that creates an user:

def create_user(
    *,
    email: str,
    name: str
) -> User:
    user = User(email=email)
    user.full_clean()
    user.save()

    create_profile(user=user, name=name)
    send_confirmation_email(user=user)

    return user

As you can see, this service calls 2 other services - create_profile and send_confirmation_email

Selectors

A selector is a simple function that:

• Lives in your_app/selectors.py module
• Takes keyword-only arguments
• Is type-annotated (even if you are not using mypy at the moment)
• Works mostly with models & other services and selectors
• Does business logic around fetching data from your database

An example selector that list users from the database:

def get_users(*, fetched_by: User) -> Iterable[User]:
    user_ids = get_visible_users_for(user=fetched_by)

    query = Q(id__in=user_ids)

    return User.objects.filter(query)

As you can see, get_visible_users_for is another selector.

APIs & Serializers

When using services & selectors, all of your APIs should look simple & the same.

General rules for an API is:

• Do 1 API per operation. For CRUD on a model, this means 4 APIs.
• Use the most simple APIView or GenericAPIView
• Use services / selectors & don't do business logic in your API.
• Use serializers for fetching objects from params - passed either via GET or POST
• Serializer should be nested in the API and be named either InputSerializer or OutputSerializer
  • OutputSerializer can subclass ModelSerializer, if needed.
  • InputSerializer should always be a plain Serializer
  • Reuse serializers as little as possible
  • If you need a nested serializer, use the inline_serializer util

An example list API

class CourseListApi(SomeAuthenticationMixin, APIView):
    class OutputSerializer(serializers.ModelSerializer):
        class Meta:
            model = Course
            fields = ('id', 'name', 'start_date', 'end_date')

    def get(self, request):
        courses = get_courses()

        data = self.OutputSerializer(courses, many=True)

        return Response(data)

An example detail API

class CourseDetailApi(SomeAuthenticationMixin, APIView):
    class OutputSerializer(serializers.ModelSerializer):
        class Meta:
            model = Course
            fields = ('id', 'name', 'start_date', 'end_date')

    def get(self, request, course_id):
        course = get_course(id=course_id)

        data = self.OutputSerializer(course)

        return Response(data)

An example create API

class CourseCreateApi(SomeAuthenticationMixin, APIView):
    class InputSerializer(serializers.Serializer):
        name = serializers.CharField()
        start_date = serializers.DateField()
        end_date = serializers.DateField()

    def post(self, request):
        serializer = self.InputSerializer(data=request.data)
        serializer.is_valid(raise_exception=True)

        create_course(**serializer.validated_data)

        return Response(status=status.HTTP_201_CREATED)

An example update API

class CourseUpdateApi(SomeAuthenticationMixin, APIView):
    class InputSerializer(serializers.Serializer):
        name = serializers.CharField(required=False)
        start_date = serializers.DateField(required=False)
        end_date = serializers.DateField(required=False)

    def post(self, request, course_id):
        serializer = self.InputSerializer(data=request.data)
        serializer.is_valid(raise_exception=True)

        update_course(course_id=course_id, **serializer.validated_data)

        return Response(status=status.HTTP_200_OK)

Nested serializers

In case you need to use a nested serializer, you can do the following thing:

class Serializer(serializers.Serializer):
    weeks = inline_serializer(many=True, fields={
        'id': serializers.IntegerField(),
        'number': serializers.IntegerField(),
    })

The implementation of inline_serializer can be found in utils.py in this repo.

Exception Handling

Raising Exceptions in Services / Selectors

Now we have separation between our HTTP interface & the core logic of our application.

In order to keep this separation of concerns, our services and selectors must not use the rest_framework.exception classes because they are bounded with HTTP status codes.

Our services and selectors must use one of:

• Python built-in exceptions
• Exceptions from django.core.exceptions
• Custom exceptions, inheriting from the ones above.

Here is a good example of service that preforms some validation and raises django.core.exceptions.ValidationError:

from django.core.exceptions import ValidationError

def create_topic(*, name: str, course: Course) -> Topic:
    if course.end_date < timezone.now():
       raise ValidationError('You can not create topics for course that has ended.')

    topic = Topic.objects.create(name=name, course=course)

    return topic

Handle Exceptions in APIs

In order to transform the exceptions raised in the services or selectors, to a standard HTTP response, you need to catch the exception and raise something that the rest framework understands.

The best place to do this is in the handle_exception method of the APIView.

There you can map your exception to DRF exception.

Here is an example:

from rest_framework import exceptions as rest_exceptions

from django.core.exceptions import ValidationError


class CourseCreateApi(SomeAuthenticationMixin, APIView):
    expected_exceptions = {
        ValidationError: rest_exceptions.ValidationError
    }

    class InputSerializer(serializers.Serializer):
        ...

    def post(self, request):
        serializer = self.InputSerializer(data=request.data)
        serializer.is_valid(raise_exception=True)

        create_course(**serializer.validated_data)

        return Response(status=status.HTTP_201_CREATED)

    def handle_exception(self, exc):
        if isinstance(exc, tuple(self.expected_exceptions.keys())):
            drf_exception_class = self.expected_exceptions[exc.__class__]
            drf_exception = drf_exception_class(get_error_message(exc))

            return super().handle_exception(drf_exception)

        return super().handle_exception(exc)

Here's the implementation of get_error_message:

def get_first_matching_attr(obj, *attrs, default=None):
    for attr in attrs:
        if hasattr(obj, attr):
            return getattr(obj, attr)

    return default


def get_error_message(exc):
    if hasattr(exc, 'message_dict'):
        return exc.message_dict
    error_msg = get_first_matching_attr(exc, 'message', 'messages')

    if isinstance(error_msg, list):
        error_msg = ', '.join(error_msg)

    if error_msg is None:
        error_msg = str(exc)

    return error_msg

You can move this code to a mixin and use it in every API to prevent code duplication.

We call this ExceptionHandlerMixin. Here's a sample implementation from one of our projects:

from rest_framework import exceptions as rest_exceptions

from django.core.exceptions import ValidationError

from project.common.utils import get_error_message


class ExceptionHandlerMixin:
    """
    Mixin that transforms Django and Python exceptions into rest_framework ones.
    without the mixin, they return 500 status code which is not desired.
    """
    expected_exceptions = {
        ValueError: rest_exceptions.ValidationError,
        ValidationError: rest_exceptions.ValidationError,
        PermissionError: rest_exceptions.PermissionDenied
    }

    def handle_exception(self, exc):
        if isinstance(exc, tuple(self.expected_exceptions.keys())):
            drf_exception_class = self.expected_exceptions[exc.__class__]
            drf_exception = drf_exception_class(get_error_message(exc))

            return super().handle_exception(drf_exception)

        return super().handle_exception(exc)

Having this mixin in mind, our API can be written like that:

class CourseCreateApi(
  SomeAuthenticationMixin,
  ExceptionHandlerMixin,
  APIView
):
    class InputSerializer(serializers.Serializer):
        ...

    def post(self, request):
        serializer = self.InputSerializer(data=request.data)
        serializer.is_valid(raise_exception=True)

        create_course(**serializer.validated_data)

        return Response(status=status.HTTP_201_CREATED)

All of code above can be found in utils.py in this repository.

Testing

In our Django projects, we split our tests depending on the type of code they represent.

Meaning, we generally have tests for models, services, selectors & APIs / views.

The file structure usually looks like this:

project_name
├── app_name
│   ├── __init__.py
│   └── tests
│       ├── __init__.py
│       ├── models
│       │   └── test_some_model_name.py
│       ├── selectors
│       │   └── test_some_selector_name.pyy
│       └── services
│           ├── __init__.py
│           └── test_some_service_name.py
└── __init__.py

Naming conventions

We follow 2 general naming conventions:

• The test file names should be test_the_name_of_the_thing_that_is_tested.py
• The test case shoud be class TheNameOfTheThingThatIsTestedTests(TestCase):

For example if we have:

def a_very_neat_service(*args, **kwargs):
    pass

We are going to have the following for file name:

project_name/app_name/tests/services/test_a_very_neat_service.py

And the following for test case:

class AVeryNeatServiceTests(TestCase):
    pass

For tests of utility functions, we follow a similiar pattern.

For example, if we have project_name/common/utils.py, then we are going to have project_name/common/tests/test_utils.py and place different test cases in that file.

If we are to split the utils.py module into submodules, the same will happen for the tests:

• project_name/common/utils/files.py
• project_name/common/tests/utils/test_files.py

We try to match the stucture of our modules with the structure of their respective tests.

Services

Service tests are the most important tests in the project. Usually, those are the heavier tests with most lines of code.

General rule of thumb for service tests:

• The tests should cover the business logic behind the services in an exhaustive manner.
• The tests should hit the database - creating & reading from it.
• The tests should mock async task calls & everything that goes outside the project.

When creating the required state for a given test, one can use a combination of:

• Fakes (We recommend using https://github.com/joke2k/faker)
• Other services, to create the required objects.
• Special test utility & helper methods.
• Factories (We recommend using factory_boy)

Lets see an example.

This is our service:

def buy_item(
    *,
    item: Item,
    user: User,
) -> Payment:
    if item in get_items_for_user(user=user):
        raise ValidationError(f'Item {item} already in {user} items.')

    payment = Payment.objects.create(
        item=item,
        user=user,
        successful=False
    )

    charge_payment.delay(payment_id=payment.id)

    return payment

The service:

• Calls a selector for validation
• Create ORM object
• Calls a task

Those are our tests:

class BuyItemTests(TestCase):
    def setUp(self):
        self.user = UserFactory()
        self.item = ItemFactory()

        self.service = buy_item

    @patch('project_name.app_name.services.payments.get_items_for_user')
    def test_buying_item_that_is_already_bought_fails(self, get_items_for_user_mock):
        """
        Since we already have tests for `get_items_for_user`,
        we can safely mock it here and give it a proper return value.
        """
        get_items_for_user_mock.return_value = [self.item]

        with self.assertRaises(ValidationError):
            self.service(user=self.user, item=self.item)

    @patch('project_name.app_name.services.payments.charge_payment.delay')
    def test_buying_item_creates_a_payment_and_calls_charge_task(
        self,
        charge_payment_mock
    ):
        self.assetEqual(0, Payment.objects.count())

        payment = self.service(user=self.user, item=self.item)

        self.assetEqual(1, Payment.objects.count())
        self.assertEqual(payment, Payment.objects.first())

        self.assertFalse(payment.successful)

        self.assert_called(charge_payment_mock)

Inspiration

The way we do Django is inspired by the following things:

• The general idea for separation of concerns
• Boundaries by Gary Bernhardt
• Rails service objects