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, which offers various useful managers, services, 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, agetorn, afilter, aset, aadd, arelated
Decorators 🎀
-
aforce_data
The
aforce_data
decorator combines data from theGET
,POST
andJSON
body request inrequest.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 usehandle
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
- These decorators automatically catch uncaught exceptions and log if the logger is configured
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
andCelery 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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