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Caching and QuerySets

That means the same database query will be executed twice, effectively doubling your database load. Also, there’s a possibility the two lists may not include the same database records, because an Entry may have been added or deleted in the split second between the two requests.

To avoid this problem, simply save the QuerySet and reuse it:

>>> queryset = Entry.objects.all()
>>> print([p.headline for p in queryset]) # Evaluate the query set.
>>> print([p.pub_date for p in queryset]) # Re-use the cache from the evaluation.

When QuerySets are not cached

Querysets do not always cache their results. When evaluating only part of the queryset, the cache is checked, but if it is not populated then the items returned by the subsequent query are not cached. Specifically, this means that limiting the queryset using an array slice or an index will not populate the cache.

For example, repeatedly getting a certain index in a queryset object will query the database each time:

>>> queryset = Entry.objects.all()
>>> print(queryset[5]) # Queries the database
>>> print(queryset[5]) # Queries the database again

However, if the entire queryset has already been evaluated, the cache will be checked instead:

>>> queryset = Entry.objects.all()
>>> [entry for entry in queryset] # Queries the database
>>> print(queryset[5]) # Uses cache
>>> print(queryset[5]) # Uses cache

Here are some examples of other actions that will result in the entire queryset being evaluated and therefore populate the cache:

>>> [entry for entry in queryset]
>>> bool(queryset)
>>> entry in queryse