Separation of Business Logic and Data Access in Django

Separation of business logic and data access in django

It seems like you are asking about the difference between the data model and the domain model – the latter is where you can find the business logic and entities as perceived by your end user, the former is where you actually store your data.

Furthermore, I've interpreted the 3rd part of your question as: how to notice failure to keep these models separate.

These are two very different concepts and it's always hard to keep them separate. However, there are some common patterns and tools that can be used for this purpose.

About the Domain Model

The first thing you need to recognize is that your domain model is not really about data; it is about actions and questions such as "activate this user", "deactivate this user", "which users are currently activated?", and "what is this user's name?". In classical terms: it's about queries and commands.

Thinking in Commands

Let's start by looking at the commands in your example: "activate this user" and "deactivate this user". The nice thing about commands is that they can easily be expressed by small given-when-then scenario's:

given an inactive user

when the admin activates this user

then the user becomes active

and a confirmation e-mail is sent to the user

and an entry is added to the system log

(etc. etc.)

Such scenario's are useful to see how different parts of your infrastructure can be affected by a single command – in this case your database (some kind of 'active' flag), your mail server, your system log, etc.

Such scenario's also really help you in setting up a Test Driven Development environment.

And finally, thinking in commands really helps you create a task-oriented application. Your users will appreciate this :-)

Expressing Commands

Django provides two easy ways of expressing commands; they are both valid options and it is not unusual to mix the two approaches.

The service layer

The service module has already been described by @Hedde. Here you define a separate module and each command is represented as a function.

services.py

def activate_user(user_id):
    user = User.objects.get(pk=user_id)

    # set active flag
    user.active = True
    user.save()

    # mail user
    send_mail(...)

    # etc etc

Using forms

The other way is to use a Django Form for each command. I prefer this approach, because it combines multiple closely related aspects:

• execution of the command (what does it do?)
• validation of the command parameters (can it do this?)
• presentation of the command (how can I do this?)

forms.py

class ActivateUserForm(forms.Form):

    user_id = IntegerField(widget = UsernameSelectWidget, verbose_name="Select a user to activate")
    # the username select widget is not a standard Django widget, I just made it up

    def clean_user_id(self):
        user_id = self.cleaned_data['user_id']
        if User.objects.get(pk=user_id).active:
            raise ValidationError("This user cannot be activated")
        # you can also check authorizations etc. 
        return user_id

    def execute(self):
        """
        This is not a standard method in the forms API; it is intended to replace the 
        'extract-data-from-form-in-view-and-do-stuff' pattern by a more testable pattern. 
        """
        user_id = self.cleaned_data['user_id']

        user = User.objects.get(pk=user_id)

        # set active flag
        user.active = True
        user.save()

        # mail user
        send_mail(...)

        # etc etc

Thinking in Queries

You example did not contain any queries, so I took the liberty of making up a few useful queries. I prefer to use the term "question", but queries is the classical terminology. Interesting queries are: "What is the name of this user?", "Can this user log in?", "Show me a list of deactivated users", and "What is the geographical distribution of deactivated users?"

Before embarking on answering these queries, you should always ask yourself this question, is this:

• a presentational query just for my templates, and/or
• a business logic query tied to executing my commands, and/or
• a reporting query.

Presentational queries are merely made to improve the user interface. The answers to business logic queries directly affect the execution of your commands. Reporting queries are merely for analytical purposes and have looser time constraints. These categories are not mutually exclusive.

The other question is: "do I have complete control over the answers?" For example, when querying the user's name (in this context) we do not have any control over the outcome, because we rely on an external API.

Making Queries

The most basic query in Django is the use of the Manager object:

User.objects.filter(active=True)

Of course, this only works if the data is actually represented in your data model. This is not always the case. In those cases, you can consider the options below.

Custom tags and filters

The first alternative is useful for queries that are merely presentational: custom tags and template filters.

template.html

<h1>Welcome, {{ user|friendly_name }}</h1>

template_tags.py

@register.filter
def friendly_name(user):
    return remote_api.get_cached_name(user.id)

Query methods

If your query is not merely presentational, you could add queries to your services.py (if you are using that), or introduce a queries.py module:

queries.py

def inactive_users():
    return User.objects.filter(active=False)

def users_called_publysher():
    for user in User.objects.all():
        if remote_api.get_cached_name(user.id) == "publysher":
            yield user 

Proxy models

Proxy models are very useful in the context of business logic and reporting. You basically define an enhanced subset of your model. You can override a Manager’s base QuerySet by overriding the Manager.get_queryset() method.

models.py

class InactiveUserManager(models.Manager):
    def get_queryset(self):
        query_set = super(InactiveUserManager, self).get_queryset()
        return query_set.filter(active=False)

class InactiveUser(User):
    """
    >>> for user in InactiveUser.objects.all():
    …        assert user.active is False 
    """

    objects = InactiveUserManager()
    class Meta:
        proxy = True

Query models

For queries that are inherently complex, but are executed quite often, there is the possibility of query models. A query model is a form of denormalization where relevant data for a single query is stored in a separate model. The trick of course is to keep the denormalized model in sync with the primary model. Query models can only be used if changes are entirely under your control.

models.py

class InactiveUserDistribution(models.Model):
    country = CharField(max_length=200)
    inactive_user_count = IntegerField(default=0)

The first option is to update these models in your commands. This is very useful if these models are only changed by one or two commands.

forms.py

class ActivateUserForm(forms.Form):
    # see above
   
    def execute(self):
        # see above
        query_model = InactiveUserDistribution.objects.get_or_create(country=user.country)
        query_model.inactive_user_count -= 1
        query_model.save()

A better option would be to use custom signals. These signals are of course emitted by your commands. Signals have the advantage that you can keep multiple query models in sync with your original model. Furthermore, signal processing can be offloaded to background tasks, using Celery or similar frameworks.

signals.py

user_activated = Signal(providing_args = ['user'])
user_deactivated = Signal(providing_args = ['user'])

forms.py

class ActivateUserForm(forms.Form):
    # see above
   
    def execute(self):
        # see above
        user_activated.send_robust(sender=self, user=user)

models.py

class InactiveUserDistribution(models.Model):
    # see above

@receiver(user_activated)
def on_user_activated(sender, **kwargs):
        user = kwargs['user']
        query_model = InactiveUserDistribution.objects.get_or_create(country=user.country)
        query_model.inactive_user_count -= 1
        query_model.save()
    

Keeping it clean

When using this approach, it becomes ridiculously easy to determine if your code stays clean. Just follow these guidelines:

• Does my model contain methods that do more than managing database state? You should extract a command.
• Does my model contain properties that do not map to database fields? You should extract a query.
• Does my model reference infrastructure that is not my database (such as mail)? You should extract a command.

The same goes for views (because views often suffer from the same problem).

• Does my view actively manage database models? You should extract a command.

Some References

Django documentation: proxy models

Django documentation: signals

Architecture: Domain Driven Design

Django separation of business logic and views logic

You could've just asked in the comments on the other question ;).

Business logic is anything that's related to how a "thing" works or operates. Take for example the following:

class Animal(Object):
    def speak(self, sound):
        print sound

class Duck(Animal):
    has_feathers = True

It would be incorrect to do something like:

>>> myduck = Duck()
>>> myduck.speak('Quack!')
Quack!

The fact that a duck makes the sound of 'Quack!' is business logic, and should be in the model:

class Duck(Animal):
    has_feathers = True
    makes_sound = 'Quack!'

    def speak(self):
        super(Duck, self).speak(self.makes_sound)

You don't necessarily need to understand all that; all we're doing is ensuring that when a Duck speaks it says 'Quack!':

>>> myduck = Duck()
>>> myduck.speak()
Quack!

View logic would be anything related to processing a request and returning some sort of response. Using the previous example, our view would contain the code to instantiate a Duck object and make it speak.

myduck = Duck()
myduck.speak()

The "response" would be the 'Quack!'.

Django: separating business logic from view logic

Depends, but if it's a logical unit, then a separate python module would be a good start and you would of course write its own unit tests for it (as opposed to Django's built-in integration tests with TestClient).

If it needs to work within the model, then a property on model would be a better place.

django models = business logic + data access? Or data access layer should be separated out from django model?

After three years of Django development, I've learned the following.

The ORM is the access layer. Nothing more is needed.

50% of the business logic goes in the model. Some of this is repeated or amplified in the Forms.

20% of the business logic goes in Forms. All data validation, for example, is in the forms. In some cases, the forms will narrow a general domain (allowed in the model) to some subset that's specific to the problem, the business or the industry.

20% of the business logic winds up in other modules in the application. These modules are above the models and forms, but below the view functions, RESTful web services and command-line apps.

10% of the business logic winds up in command-line apps using the management command interface. This is file loads, extracts, and random bulk changes.

It's very important that view functions and RESTful web services do approximately nothing. They use models, forms, and other modules as much as possible. The view functions and RESTful web services are limited to dealing with the vagaries of HTTP and the various data formats (JSON, HTML, XML, YAML, whatever.)

Trying to invent Yet Another Access Layer is a zero-value exercise.

business logic in Django

Short answer: Django is more of a MTV or MVT (Model / Template / View), as described in the official FAQ : https://docs.djangoproject.com/en/dev/faq/general/#django-appears-to-be-a-mvc-framework-but-you-call-the-controller-the-view-and-the-view-the-template-how-come-you-don-t-use-the-standard-names

The business logic has its place in your views, but nothing prevents you from putting it inside a "utils.py", "services.py" or anything to your liking.

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