Concatenating the querysets into a list is the simplest approach. If the database will be hit for all querysets anyway (e.g. because the result needs to be sorted), this won’t add further cost.
from itertools import chain result_list = list(chain(page_list, article_list, post_list))
itertools.chain is faster than looping each list and appending elements one by one, since
itertools is implemented in C. It also consumes less memory than converting each queryset into a list before concatenating.
Now it’s possible to sort the resulting list e.g. by date (as requested in hasen j’s comment to another answer). The
sorted() function conveniently accepts a generator and returns a list:
result_list = sorted( chain(page_list, article_list, post_list), key=lambda instance: instance.date_created)
If you’re using Python 2.4 or later, you can use
attrgetter instead of a lambda. I remember reading about it being faster, but I didn’t see a noticeable speed difference for a million item list.
from operator import attrgetter result_list = sorted( chain(page_list, article_list, post_list), key=attrgetter('date_created'))