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adjango
Advanced tools
📊 Coverage 70%
Sometimes I use this in different projects, so I decided to put it on pypi
ADjango is a comprehensive library that enhances Django development with Django REST Framework (DRF) and Celery
integration. It provides essential tools including
asynchronous services, serializers, decorators, exceptions and more utilities for async
programming, Celery task scheduling, transaction management, and much more to streamline your Django DRF Celery
development workflow.
pip install adjango
INSTALLED_APPS = [
# ...
'adjango',
]
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',
...
]
Most functions, if available in asynchronous form, are also available in synchronous form.
A simple example and everything is immediately clear...
from django.contrib.auth.models import AbstractUser
from django.db.models import CASCADE, CharField, ForeignKey, ManyToManyField
from adjango.models import Model
from adjango.models.polymorphic import PolymorphicModel
from adjango.services.base import BaseService
from adjango.utils.funcs import aadd, aall, afilter, aset
...
... # Service layer usage
...
# services/user.py
if TYPE_CHECKING:
from apps.core.models import User
class UserService(BaseService):
def __init__(self, obj: 'User') -> None:
self.user = obj
def get_full_name(self) -> str:
return f"{self.user.first_name} {self.user.last_name}"
# models/user.py (User redefinition)
class User(AbstractUser):
...
@property
def service(self) -> UserService:
return UserService(self)
# and u can use:
full_name = user.service.get_full_name()
...
... # Other best features
...
# models/commerce.py
class Product(PolymorphicModel):
name = CharField(max_length=100)
class Order(Model):
user = ForeignKey(User, CASCADE)
products = ManyToManyField(Product)
# The following is now possible...
products = await afilter(Product.objects, name='name')
# Returns an object or None if not found
order = await BaseService.agetorn(Order.objects, id=69) # aget or none
if not order: raise
# We install products in the order
await aset(order.products, products)
# Or queryset right away...
await aset(
order.products,
Product.objects.filter(name='name')
)
await aadd(order.products, 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.arelated('user')
products = await aall(order.products)
# Works the same with intermediate processing/query filters
orders = await aall(Order.objects.prefetch_related('products'))
for o in orders:
for p in o.products.all():
print(p.id)
# thk u
aall, afilter, arelated, and so on are available as individual functions
from adjango.utils.funcs import (
aall, afilter, aset, aadd, arelated
)
ATextChoices and AIntegerChoices extend Django TextChoices / IntegerChoices
with helpers:
get_label(value) -> label or Nonehas_value(value) -> boolas_dict() -> {value: label}values and labels are available as standard Django choices attributes.from adjango.models.choices import AIntegerChoices, ATextChoices
class OrderStatus(ATextChoices):
NEW = 'new', 'New'
PAID = 'paid', 'Paid'
class Priority(AIntegerChoices):
LOW = 1, 'Low'
HIGH = 2, 'High'
OrderStatus.get_label('new') # 'New'
OrderStatus.get_label(OrderStatus.PAID) # 'Paid'
OrderStatus.get_label('unknown') # None
OrderStatus.has_value('new') # True
Priority.as_dict() # {1: 'Low', 2: 'High'}
Priority.values # [1, 2]
Priority.labels # ['Low', 'High']
from adjango.models.mixins import (
CreatedAtMixin, CreatedAtIndexedMixin, CreatedAtEditableMixin,
UpdatedAtMixin, UpdatedAtIndexedMixin,
CreatedUpdatedAtMixin, CreatedUpdatedAtIndexedMixin
)
class EventProfile(CreatedUpdatedAtIndexedMixin):
event = ForeignKey('events.Event', CASCADE, 'members', verbose_name=_('Event'))
@property
def service(self) -> EventProfileService:
return EventProfileService(self)
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.
aatomic
An asynchronous decorator that wraps function into a transactional context using AsyncAtomicContextManager. If an
exception occurs, all database changes are rolled back.
acontroller/controller
Decorators that provide automatic logging and exception handling for views. The acontroller is for async
views, controller is for sync views. They do NOT wrap functions in transactions (use @aatomic for that).
from adjango.adecorators import acontroller
from adjango.decorators import controller
@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
@controller(name='Sync View', auth_required=True, log_time=True)
def my_sync_view(request):
pass
These decorators automatically catch uncaught exceptions and log them if the logger is configured
via ADJANGO_CONTROLLERS_LOGGER_NAME and ADJANGO_CONTROLLERS_LOGGING.
The controller decorator also supports authentication checking with auth_required parameter.
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
ADjango provides convenient classes for generating API exceptions with proper HTTP statuses and structured error
messages.
from adjango.exceptions.base import (
ApiExceptionGenerator,
ModelApiExceptionGenerator,
ModelApiExceptionBaseVariant as MAEBV
)
# General API exceptions
raise ApiExceptionGenerator('Special error', 500)
raise ApiExceptionGenerator('Special error', 500, 'special_error')
raise ApiExceptionGenerator(
'Wrong data',
400,
extra={'field': 'email'}
)
# Model exceptions
from apps.commerce.models import Order
raise ModelApiExceptionGenerator(Order, MAEBV.DoesNotExist)
raise ModelApiExceptionGenerator(
Order,
MAEBV.AlreadyExists,
code="order_exists",
extra={"id": 123}
)
# Available exception variants for models:
# DoesNotExist, AlreadyExists, InvalidData, AccessDenied,
# NotAcceptable, Expired, InternalServerError, AlreadyUsed,
# NotUsed, NotAvailable, TemporarilyUnavailable,
# ConflictDetected, LimitExceeded, DependencyMissing, Deprecated
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.aserializers import (
AModelSerializer, ASerializer, AListSerializer
)
from adjango.serializers import dynamic_serializer
from adjango.services.base import BaseService
from adjango.utils.funcs import aall
from django.db.models import QuerySet
...
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 = dynamic_serializer(
ConsultationPublicSerializer, ('id', 'date',)
)
ConsultationSerializerTier2 = 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 aall(
request.user.service.completed_consultations[
(page - 1) * page_size:page * page_size
]
),
many=True,
context={'request': request}
).adata
}, status=200)
...
class UserService(BaseService):
...
@property
def completed_consultations(self) -> QuerySet['Consultation']:
"""
Returns an optimized QuerySet 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.user) | Q(psychologists=self.user),
status=Consultation.Status.PAID,
date__isnull=False,
date__lt=now_,
consultations_feedbacks__user=self.user,
) |
Q(
Q(clients=self) | Q(psychologists=self.user),
status=Consultation.Status.CANCELLED,
date__isnull=False,
)
).distinct().order_by('-updated_at')
...
copy_project
Documentation in the py module itself - copy_projectADjango ships with extra management commands to speed up project scaffolding.
astartproject — clones the adjango-template
into the given directory and strips its Git history.
django-admin astartproject myproject
astartup — creates an app skeleton inside apps/ and registers it in
INSTALLED_APPS.
python manage.py astartup blog
After running the command you will have the following structure:
apps/
blog/
controllers/base.py
models/base.py
services/base.py
serializers/base.py
tests/base.py
newentities — generates empty exception, model, service, serializer and
test stubs for the specified models in the target app.
python manage.py newentities order apps.commerce Order,Product,Price
Or create a single model:
python manage.py newentities order apps.commerce Order
ADjango provides convenient tools for working with Celery: management commands, decorators, and task scheduler.
For Celery configuration in Django, refer to the official Celery documentation.
celeryworker — starts Celery Worker with default settings
python manage.py celeryworker
python manage.py celeryworker --pool=solo --loglevel=info -E
python manage.py celeryworker --concurrency=4 --queues=high_priority,default
celerybeat — starts Celery Beat scheduler for periodic tasks
python manage.py celerybeat
python manage.py celerybeat --loglevel=debug
celerypurge — clears Celery queues from unfinished tasks
python manage.py celerypurge # clear all queues
python manage.py celerypurge --queue=high # clear specific queue
The @task decorator automatically logs Celery task execution, including errors:
from celery import shared_task
from adjango.decorators import task
@shared_task
@task(logger="global")
def my_background_task(param1: str, param2: int) -> bool:
"""
Task with automatic execution logging.
"""
# your code here
return True
What the decorator provides:
The Tasker class provides convenient methods for scheduling and managing Celery tasks:
from adjango.utils.celery.tasker import Tasker
# Immediate execution
task_id = Tasker.put(task=my_task, param1='value')
# Delayed execution (in 60 seconds)
task_id = Tasker.put(task=my_task, countdown=60, param1='value')
# Execution at specific time
from datetime import datetime
task_id = Tasker.put(
task=my_task,
eta=datetime(2024, 12, 31, 23, 59),
param1='value'
)
# Cancel task by ID
Tasker.cancel_task(task_id)
# One-time task via Celery Beat (sync)
Tasker.beat(
task=my_task,
name='one_time_task',
schedule_time=datetime(2024, 10, 10, 14, 30),
param1='value'
)
# Periodic task via Celery Beat (sync)
Tasker.beat(
task=my_task,
name='hourly_cleanup',
interval=3600, # every hour in seconds
param1='value'
)
# Crontab schedule via Celery Beat (sync)
Tasker.beat(
task=my_task,
name='daily_report',
crontab={'hour': 7, 'minute': 30}, # every day at 7:30 AM
param1='value'
)
# Async version of beat is also available
await Tasker.abeat(
task=my_task,
name='async_task',
interval=1800, # every 30 minutes
param1='value'
)
ADjango includes a ready-to-use task for sending emails with templates:
from adjango.tasks import send_emails_task
from adjango.utils.mail import send_emails
# Synchronous sending
send_emails(
subject='Welcome!',
emails=('user@example.com',),
template='emails/welcome.html',
context={'user': 'John Doe'}
)
# Asynchronous sending via Celery
send_emails_task.delay(
subject='Hello!',
emails=('user@example.com',),
template='emails/hello.html',
context={'message': 'Welcome to our service!'}
)
# Via Tasker with delayed execution
Tasker.put(
task=send_emails_task,
subject='Reminder',
emails=('user@example.com',),
template='emails/reminder.html',
context={'deadline': '2024-12-31'},
countdown=3600 # send in an hour
)
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():
...
FAQs
A library with many features for interacting with Django
We found that adjango demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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