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A library with many features for interacting with Django

Project description

🚀 ADjango

Sometimes I use this in different projects, so I decided to put it on pypi

ADjango is a convenient library for simplifying work with Django DRF and other, which offers various useful managers, services, serializers, decorators, utilities for asynchronous programming, a task scheduler for Celery, working with transactions and much more.

Installation 🛠️

pip install adjango

Settings ⚙️

  • Add the application to the project.

    INSTALLED_APPS = [
        # ...
        'adjango',
    ]
    
  • In settings.py set the params

    # settings.py
    # None of the parameters are required.  
    
    # For usage @a/controller decorators
    LOGIN_URL = '/login/' 
    
    # optional
    ADJANGO_BACKENDS_APPS = BASE_DIR / 'apps' # for management commands
    ADJANGO_FRONTEND_APPS = BASE_DIR.parent / 'frontend' / 'src' / 'apps' # for management commands
    ADJANGO_APPS_PREPATH = 'apps.'  # if apps in BASE_DIR/apps/app1,app2...
    ADJANGO_UNCAUGHT_EXCEPTION_HANDLING_FUNCTION = ... # Read about @acontroller, @controller
    ADJANGO_CONTROLLERS_LOGGER_NAME = 'global' # only for usage @a/controller decorators
    ADJANGO_CONTROLLERS_LOGGING = True # only for usage @a/controller decorators
    ADJANGO_EMAIL_LOGGER_NAME = 'email' # for send_emails_task logging
    
    MIDDLEWARE = [
        ...
        # add request.ip in views if u need
        'adjango.middleware.IPAddressMiddleware',  
        ...
    ]
    

Overview

Most functions, if available in asynchronous form, are also available in synchronous form.

Manager & Services 🛎️

A simple example and everything is immediately clear...

from adjango.fields import AManyToManyField
from adjango.managers.base import AManager
from adjango.services.base import ABaseService
from adjango.models import AModel
from adjango.polymorphic_models import APolymorphicModel


class User(AbstractUser, ABaseService):
    objects = AManager()


# Its equal with...
class User(AbstractUser, AModel): pass


class Product(APolymorphicModel):
    # APolymorphicManager() of course here already exists
    name = CharField(max_length=100)


class Order(AModel):
    user = ForeignKey(User, CASCADE)
    products = AManyToManyField(Product)


# The following is now possible...
products = await Product.objects.aall()
products = await Product.objects.afilter(name='name')
# Returns an object or None if not found
order = await Order.objects.agetorn(id=69)  # aget or none
if not order: raise

# We install products in the order
await order.products.aset(products)
# Or queryset right away...
await order.products.aset(
    Product.objects.filter(name='name')
)
await order.products.aadd(products[0])

# We get the order again without associated objects
order: Order = await Order.objects.aget(id=69)
# Retrieve related objects asynchronously.
order.user = await order.related('user')
products = await order.products.aall()
# Works the same with intermediate processing/query filters
orders = await Order.objects.prefetch_related('products').aall()
for o in orders:
    for p in o.products.all():
        print(p.id)
# thk u

Utils 🔧

aall, afilter, arelated, и так далее доступны как отдельные функции

from adjango.utils.funcs import aall, getorn, agetorn, afilter, aset, aadd, arelated

Decorators 🎀

  • aforce_data

    The aforce_data decorator combines data from the GET, POST and JSON body request in request.data. This makes it easy to access all request data in one place.

  • atomic

    An asynchronous decorator that wraps function into a transactional context. If an exception occurs, all changes are rolled back.

  • acontroller/controller

    An asynchronous decorator that wraps function into a transactional context. If an exception occurs, all changes are rolled back.

    from adjango.adecorators import acontroller
    
    @acontroller(name='My View', logger='custom_logger', log_name=True, log_time=True)
    async def my_view(request):
        pass
    
    @acontroller('One More View')
    async def my_view_one_more(request):
        pass
    
    • These decorators automatically catch uncaught exceptions and log if the logger is configured ADJANGO_CONTROLLERS_LOGGER_NAME ADJANGO_CONTROLLERS_LOGGING.
    • You can also implement the interface:
      class IHandlerControllerException(ABC):
          @staticmethod
          @abstractmethod
          def handle(fn_name: str, request: WSGIRequest | ASGIRequest, e: Exception, *args, **kwargs) -> None:
              """
              An example of an exception handling function.
      
              :param fn_name: The name of the function where the exception occurred.
              :param request: The request object (WSGIRequest or ASGIRequest).
              :param e: The exception to be handled.
              :param args: Positional arguments passed to the function.
              :param kwargs: Named arguments passed to the function.
      
              :return: None
              """
              pass
      
      and use handle to get an uncaught exception:
      # settings.py
      from adjango.handlers import HCE # use my example if u need
      ADJANGO_UNCAUGHT_EXCEPTION_HANDLING_FUNCTION = HCE.handle
      

Serializers 🔧

ADjango extends Django REST Framework serializers to support asynchronous operations, making it easier to handle data in async views. Support methods like adata, avalid_data, ais_valid, and asave.

from adjango.querysets.base import AQuerySet
from adjango.aserializers import (
    AModelSerializer, ASerializer, AListSerializer
)
from adjango.serializers import create_dynamic_serializer

...


class ConsultationPublicSerializer(AModelSerializer):
    clients = UserPublicSerializer(many=True, read_only=True)
    psychologists = UserPsyPublicSerializer(many=True, read_only=True)
    config = ConsultationConfigSerializer(read_only=True)

    class Meta:
        model = Consultation
        fields = '__all__'


# From the complete serializer we cut off the pieces into smaller ones
ConsultationSerializerTier1 = create_dynamic_serializer(
    ConsultationPublicSerializer, ('id', 'date',)
)
ConsultationSerializerTier2 = create_dynamic_serializer(
    ConsultationPublicSerializer, (
        'id', 'date', 'psychologists', 'clients', 'config'
    ), {
        'psychologists': UserPublicSerializer(many=True),  # overridden
    }
)


# Use it, in compact format
@acontroller('Completed Consultations')
@api_view(('GET',))
@permission_classes((IsAuthenticated,))
async def consultations_completed(request):
    page = int(request.query_params.get('page', 1))
    page_size = int(request.query_params.get('page_size', 10))
    return Response({
        'results': await ConsultationSerializerTier2(
            await request.user.completed_consultations[
                  (page - 1) * page_size:page * page_size
                  ].aall(),
            many=True,
            context={'request': request}
        ).adata
    }, status=200)


...


class UserService:
    ...

    @property
    def completed_consultations(self: 'User') -> AQuerySet['Consultation']:
        """
        Returns an optimized AQuerySet of all completed consultations of the user
        (both psychologist and client).
        """
        from apps.psychology.models import Consultation
        now_ = now()
        return Consultation.objects.defer(
            'communication_type',
            'language',
            'reserved_by',
            'notifies',
            'cancel_initiator',
            'original_consultation',
            'consultations_feedbacks',
        ).select_related(
            'config',
            'conference',
        ).prefetch_related(
            'clients',
            'psychologists',
        ).filter(
            Q(
                Q(clients=self) | Q(psychologists=self),
                status=Consultation.Status.PAID,
                date__isnull=False,
                date__lt=now_,
                consultations_feedbacks__user=self,
            ) |
            Q(
                Q(clients=self) | Q(psychologists=self),
                status=Consultation.Status.CANCELLED,
                date__isnull=False,
            )
        ).distinct().order_by('-updated_at')

    ...

Management

  • copy_project Documentation in the py module itself - copy_project

Other

  • AsyncAtomicContextManager🧘

    An asynchronous context manager for working with transactions, which ensures the atomicity of operations.

    from adjango.utils.base import AsyncAtomicContextManager
    
    async def some_function():
        async with AsyncAtomicContextManager():
            ...  
    
  • Tasker📋

    The Tasker class provides methods for scheduling tasks in Celery and Celery Beat.

    from adjango.utils.tasks import Tasker
    
    task_id = Tasker.put(
        task=my_celery_task,
        param1='value1',
        param2='value2',
        countdown=60 # The task will be completed in 60 seconds
    )
    
    from adjango.utils.tasks import Tasker
    from datetime import datetime
    
    # One-time task via Celery Beat
    Tasker.beat(
        task=my_celery_task,
        name='one_time_task',
        schedule_time=datetime(2024, 10, 10, 14, 30), # Start the task on October 10, 2024 at 14:30
        param1='value1',
        param2='value2'
    )
    
    # Periodic task via Celery Beat (every hour)
    Tasker.beat(
        task=my_celery_task,
        name='hourly_task',
        interval=3600, # The task runs every hour
        param1='value1',
        param2='value2'
    )
    
  • send_emails

    Allows you to send emails using templates and context rendering.

    from adjango.utils.mail import send_emails
    
    send_emails(
        subject='Welcome!',
        emails=('user1@example.com', 'user2@example.com'),
        template='emails/welcome.html',
        context={'user': 'John Doe'}
    )
    
    from adjango.tasks import send_emails_task
    from adjango.utils.tasks import Tasker
    
    send_emails_task.delay(
        subject='Hello!',
        emails=('user@example.com',),
        template='emails/hello.html',
        context={'message': 'Welcome to our service!'}
    )
    # or
    Tasker.put(
        task=send_emails_task,
        subject='Hello!',
        emails=('user@example.com',),
        template='emails/hello.html',
        context={'message': 'Welcome to our service!'},
        countdown=60 # The task will be completed in 5 seconds
    )
    

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