Django Remote Queryset (a.k.a. DRQ) is a library to execute rich ORM queries from client-side using the same interface of Django ORM.

DRQ defines a JSON syntax to call all Django's Queryset methods.

Consider this example:

 from myapp.models import MyModel not_null_title = MyModel.objects.filter(title__isnull=False) 

DRQ query syntax for the previous filter is the following

 { "_query_class" : "filter", "_condition" : "title__isnull", "_value" : false }

DRQ supports Django Rest Framework and automatically decodes and applies this filter to any GET request.

DRQ is distrubuted through pypi

 $ pip install django-remote-queryset 

1. Add django_remote_queryset to your INSTALLED_APPS:

 INSTALLED_APPS = [ ... 'rest_framework', 'django_remote_queryset', ... ]

Django rest_framework is strongly recommended but if you prefer to use DRQ without it you can see Advanced Usage section.

2. Extend DRQModelViewSet for your model:

 from django_remote_queryset.viewset import DRQModelViewSet class MyModelModelViewSet(DRQModelViewSet): queryset = MyModel.objects.all() serializer_class = MyModelModelSerializer

And use it like any other Django REST Framework ViewSet!

3. Enjoy filtering from your browser!

 GET: http://yourdomain/my_model_rest_path/?query= query = { "_query_class" : "filter", "_condition" : "title__isnull", "_value" : false } 

For further informations on DRF ViewSets see Django Rest Framework documentation.

This repository contains a example_django_project folder. Try it doing the following:

 $ cd example_django_app # Install site dependencies $ pip install -r requirements.txt # Create sqlite database $ python manage.py migrate # Create demo data $ python manage.py create_demo_data # Run the server $ python manage.py runserver

Then:

1. Go to http://localhost:8000 and you should see the usual Django Rest Framework page.
2. Go to http://localhost:8000/polls and you should see the list of all polls available
3. Go to http://localhost:8000/polls/?query={"_query_class":"filter","_condition":"title__icontains","_value":"DRQ"}

It's possible to extend/customize DRQ using it in your extisting ViewSets or integrating it in your own custom Views/Django code.

DRQ is implemented using DRF's filter_backends, you can add it to your ModelViewSet easily

 from django_remote_queryset.backend import DRQFilterBackend class AnotherModelViewSet(ModelViewSet): filter_backends = ( ..., DRQFilterBackend, ...)

You can use directly the QueryDecoder to decode and apply the json_query to any queryset

 from django_remote_queryset.queries import QueryDecoder ... original_queryset = MyModel.objects.all() json_query = { "_query_class" : "filter", "_condition" : "title__isnull", "_value" : false } query = QueryDecoder \ .decodeJSONQuery(json_query) if query is not None: filtered_queryset = query.applyOnQuerySet(original_queryset)

DRQ Queries are built using the Composite Pattern. Several queries are already available and the Framework could be extended with custom ones. All the queries are contained in django_remote_queryset.queries module.

This is the abstract one, defines the interface for every child.

 class Query(): def __init__(self, json_query): """  Initializes the sub_tree of this query starting from the json_query parameter  :param json_query: dict  """ pass def applyOnQuerySet(self, queryset): """  Applies the sub_tree of this query to the queryset passed as parameter  :param queryset: Queryset  :return: Queryset  """ return queryset 

It's JSON syntax is the following

 { "_query_class":"query" }

This query applies the .filter( ... ) method on the queryset

It's JSON syntax is the following

 { "_query_class": "filter", "_condition": [string] | string, "_value": [*] | *  }

Examples:

1. Single lookup

 Person.filter(age__gte=4)

 { "_query_class": "filter", "_condition": "age__gte", "_value": 4 }

2. Multiple lookups

 Person.filter(age__gte=4, name__icontains='Nic')

 { "_query_class": "filter", "_condition": ["age__gte","name__icontains"], "_value": [4,"Nic"] }

This query applies the .exclude( ... ) method on the queryset

It's JSON syntax is the following

 { "_query_class": "exclude", "_condition": [string] | string, "_value": [*] | *  }

Examples:

1. Single lookup

 Person.exclude(age__gte=4)

 { "_query_class": "exclude", "_condition": "age__gte", "_value": 4 }

2. Multiple lookups

 Person.exclude(age__gte=4, name__icontains='Nic')

 { "_query_class": "exclude", "_condition": ["age__gte","name__icontains"], "_value": [4,"Nic"] }

This query creates a chain of subqueries applying all it's sub_tree on the queryset.

It's JSON syntax is the following

 { "_query_class": "compositequery", "_sub_queries":[ ... other queries ... ] }

The subqueries are applied as a chain.

 for query in self._sub_queries: queryset = query.applyOnQuerySet(queryset)

Examples:

1. Chained filters

 Person.objects.filter(age__gte=4).filter(name__icontains='Nic')

 { "_query_class": "compositequery", "_sub_queries":[ { "_query_class": "filter", "_condition": "age__gte", "_value": 4 }, { "_query_class": "filter", "_condition": "name__icontains", "_value": "Nic" } ] }

2. Chained mixed queries

 Person.objects.filter(age__gte=4).exclude(name__icontains='Nic')

 { "_query_class": "compositequery", "_sub_queries":[ { "_query_class": "filter", "_condition": "age__gte", "_value": 4 }, { "_query_class": "exclude", "_condition": "name__icontains", "_value": "Nic" } ] }