I am working on a Django project where I need to filter objects based on their status while excluding those that are already assigned in another model.
I have two models:
CartObject
– Stores all objects.OnGoingProcess
– Tracks objects that are currently assigned.Each OnGoingProcess
entry has a OneToOneField
relationship with CartObject
, meaning each object can only be assigned once.
My goal is to fetch all objects with a specific status but exclude those that are already assigned in OnGoingProcess
.
class CartObject(models.Model):
object_id = models.CharField(max_length=100, unique=True)
status = models.CharField(max_length=50, choices=[("pending", "Pending")])
# Other fields...
class OnGoingProcess(models.Model):
user = models.OneToOneField(DeliveryProfile, on_delete=models.CASCADE, related_name="ongoing_process")
associated_object = models.OneToOneField(CartObject, on_delete=models.CASCADE, related_name="associated_process", blank=True, null=True)
# Other fields...
@user_passes_test(lambda user: user.is_staff)
def process_manager_view(request):
# Get objects that are already assigned in OnGoingProcess
assigned_objects = OnGoingProcess.objects.values_list('associated_object', flat=True)
# Exclude objects that are already assigned
available_objects = CartObject.objects.filter(status="pending").exclude(id__in=assigned_objects).order_by("-id")
context = {
"available_objects": available_objects,
}
return render(request, "useradmin/available-objects.html", context)
values_list('associated_object', flat=True)
to extract the assigned object IDs.exclude(id__in=assigned_objects)
to filter out those objects.Subquery()
, isnull=False
, or any other approach for better performance?isnull=False
available_objects = CartObject.objects.filter(status="pending").exclude(associated_process__isnull=False)
Pros: Simple, avoids extra queries.
Cons: Not sure if it's the best approach for performance.
Subquery
from django.db.models import Subquery
assigned_objects = OnGoingProcess.objects.values('associated_object')
available_objects = CartObject.objects.filter(status="pending").exclude(id__in=Subquery(assigned_objects))
Pros: Optimized for large datasets.
Cons: More complex.
from django.db import connection
with connection.cursor() as cursor:
cursor.execute("""
SELECT id FROM useradmin_cartobject
WHERE status='pending'
AND id NOT IN (SELECT associated_object FROM useradmin_ongoingprocess)
ORDER BY id DESC
""")
result = cursor.fetchall()
available_objects = CartObject.objects.filter(id__in=[row[0] for row in result])
Pros: Performance boost for huge data.
Cons: Less readable, database-dependent.
What is the best and most efficient Django ORM approach to filter objects while excluding those that are already assigned?
Would values_list()
, isnull=False
, or Subquery()
be the recommended way?
Are there any performance considerations when working with large datasets?
Your query:
available_objects = (
CartObject.objects.filter(status='pending')
.exclude(id__in=assigned_objects)
.order_by('-id')
)
will use a subquery, so run as:
AND id NOT IN (SELECT associated_object FROM useradmin_ongoingprocess)
You can inspect it with:
print(available_objects.query)
But on databases like MySQL, this is not the most efficient one no.
For most databases:
available_objects = CartObject.objects.filter(status='pending').filter(
associated_process=None
)
will yield results efficiently. We can rewrite this to:
available_objects = CartObject.objects.filter(
status='pending', associated_process=None
)
this will generate the same query, but is a bit shorter in code.
This works based on the fact that a LEFT OUTER JOIN
includes a NULL
row for items for which there is no corresponding item at the table for the OnGoingProcess
model. Then we thus retrieve only the ones with NULL
, so only retain the CartObject
with no OnGoingProcess
.
As for raw queries, one usually uses this if there is no ORM-equivalent available, or when it is very cumbersome to construct it. Raw queries have additional disadvantages: a QuerySet
can be filtered, paginated, etc. whereas a raw query is an "end product": you can not manipulate it further, so limiting what you can do with it with Django. It also means that if you change the corresponding models, like adding a column, you will probably have to rewrite the raw queries that work with these models as well.