def update_records(self, model, qs, batch_size=1000, **kwargs):
        """
        Updates multiple records.

        This method is optimized for speed. It takes a QuerySet and the same
        arguments as QuerySet.update(). Optionally, you can specify the size
        of the batch send to Algolia with batch_size (default to 1000).

        >>> from algoliasearch_django import update_records
        >>> qs = MyModel.objects.filter(myField=False)
        >>> update_records(MyModel, qs, myField=True)
        >>> qs.update(myField=True)
        """
        adapter = self.get_adapter(model)
        adapter.update_records(qs, batch_size=batch_size, **kwargs)
def update_records(self, model, qs, batch_size=1000, **kwargs):
        """
        Updates multiple records.

        This method is optimized for speed. It takes a QuerySet and the same
        arguments as QuerySet.update(). Optionally, you can specify the size
        of the batch send to Algolia with batch_size (default to 1000).

        >>> from algoliasearch_django import update_records
        >>> qs = MyModel.objects.filter(myField=False)
        >>> update_records(MyModel, qs, myField=True)
        >>> qs.update(myField=True)
        """
        adapter = self.get_adapter(model)
        adapter.update_records(qs, batch_size=batch_size, **kwargs)
def update_records ( self , model , qs , batch_size = 1000 , * * kwargs ) : adapter = self . get_adapter ( model ) adapter . update_records ( qs , batch_size = batch_size , * * kwargs )
Updates multiple records.

        This method is optimized for speed. It takes a QuerySet and the same
        arguments as QuerySet.update(). Optionally, you can specify the size
        of the batch send to Algolia with batch_size (default to 1000).

        >>> from algoliasearch_django import update_records
        >>> qs = MyModel.objects.filter(myField=False)
        >>> update_records(MyModel, qs, myField=True)
        >>> qs.update(myField=True)
Updates multiple records .