ListSerializer.to_representation cuts data and KeyError is raised if the queryset used has been modified

[MattBlack85]

I discovered this problem after upgrading to 3.1, after 86c5fa2 if a QuerySet is passed as iterable data.all() will be called. That's fine until we start to add extra data to the QS and use normal serializers for output.
Case:

objs = Model.objects.filter(x=y)
for obj in objs:
    obj.update(extra_dict)
serializer = MySerializer(objs, many=True)

serializer.data will contain only data from QS, ignoring totally the other portion of data added later and ending with a KeyError because we're missing fields that are declared on serializer, this wasn't happening before since data.all() wasn't called while passing QS around.

[xordoquy]

It's the second time we are bitten by the QS reevaluation in the ListSerializer (previous was #2704).
I'm really not convinced 86c5fa2 was a good idea after all.

[mcbhenwood]

Seconded. This is currently causing some grief to me as well. @bakaat suggested this quick fix:

Serializer(instance=list(objs), many=True)

which "works" in terms of the data you get out, but isn't desirable for large querysets

[bakaat]

Indeed it's not. And it would possibly require you to rewrite all calls to serializer.

While that's what I suggested, I actually worked around it by subclassing Serializer (We've got our own base class extending the ModelSerializer anyways)

from rest_framework import serializers

class ModelSerializer(serializers.ModelSerializer):
    def __new__(cls, *args, **kwargs):
        if 'many' in kwargs and isinstance(
                kwargs.get('instance', None), QuerySet):
            kwargs['instance'] = (x for x in kwargs['instance'])
        return super(ModelSerializer, cls).__new__(cls, *args, **kwargs)

Generator should be more efficient than list and still prevents reevalution. This said it still remains a quick fix

[tomchristie]

That's fine until we start to add extra data to the QS

@MattBlack85 (or anyone else)

On further review I didn't fully understand this.
What exactly did you mean here - what kind of extra data, and added how? could you give an example?

[tomchristie]

Closing as a duplicate of #2704, but it'd be useful to know if there are other types of "extra data" along with prefetch_related that also demonstrate the issue.

[bakaat]

@tomchristie In my situation it was something like

qs = Abc.objects.all()[:10]
for o in qs:
    o.additional_attr = 'abc'
Serializer(instance=qs, many=True)

This actually causes the items in qs to be re-fetched from the db and additional_attr to be lost in the process (as far as I recall at this moment)

[tomchristie]

Okay. That's (arguably) a slightly quirky thing to do, but it is at least a very simple demonstration of the issue! :) Thank you.

[bakaat]

Yup :)

[MattBlack85]

My case regards fetching data from another service, having then those data in a dict I was trying to update every object in my QS with that dictionary I got from the service:

fetched_data = {'x': {'attr_a': 'some', ...},...}
qs = Model.objects.all().values()
for obj in qs:
    obj.update(fetched_data.get(obj['id']), {})

almost the same