django-qp 0.1.0

Django query parameter validation using Pydantic, inspired by FastAPI

Are you tired of accessing Django query parameters like this?

# Traditional Django view
class MyView(View):
    def get(self, request):
        name = request.GET.get("name")
        age = int(request.GET.get("age", 0))
        # ...manual validation, type conversion, error handling...

Now, with django-qp, you can harness the power of Pydantic validation:

from pydantic import BaseModel, Field
from django_qp import QueryParamsMixinView

class UserParams(BaseModel):
    name: str
    age: int = Field(ge=0)

# Use generic type parameter for IDE autocompletion
class MyView(QueryParamsMixinView[UserParams], View):
    validated_params_model = UserParams

    def get(self, request):
        params = self.validated_params  # Validated Pydantic model with IDE autocompletion!
        return JsonResponse({"name": params.name, "age": params.age})

---

Django QP

A lightweight library for Django and Django Rest Framework that enables validation of query parameters using Pydantic models, inspired by FastAPI's approach.

Requirements

• Python >= 3.10, < 3.15
• Django >= 3.2, < 7.0
• Pydantic >= 2.0
• Django REST Framework >= 3.15.2 (optional)

Why use this library?

• No more manual parsing or type conversion: Query parameters are validated and converted to Python types automatically.
• Clear, maintainable code: Use Pydantic models to define your expected query parameters.
• Consistent error handling: Get structured error responses for invalid input.
• Works with Django, DRF, class-based and function-based views.
• Supports action-specific validation for ViewSets.
• Supports method-specific validation for function-based views.
• Customizable error messages and status codes.
• Type hints for IDE autocompletion: Get full IntelliSense/autocomplete in your IDE.

Features

• Validate query parameters using Pydantic models
• Type conversion and validation
• Support for Django views and DRF (APIView, ViewSet)
• Class-based mixins and function-based decorators
• Support for comma-separated list parameters
• Action-specific models for ViewSets
• Method-specific models for function-based views
• Custom error messages and status codes
• Generic type annotations for IDE autocompletion
• Enhanced type hints for request objects in function-based views

Installation

pip install django-qp

With DRF support:

pip install django-qp[drf]

Or with uv:

uv pip install django-qp        # Django only
uv pip install django-qp[drf]   # with DRF support

Usage

1. Define your Pydantic model

from pydantic import BaseModel, Field

class ProductFilterParams(BaseModel):
    category: str | None = None
    min_price: float = Field(default=0, ge=0)
    max_price: float | None = None
    in_stock: bool = False
    tags: list[str] | None = None  # Will parse comma-separated values

List parameters: Fields typed as list[...] support two patterns that can be combined:

• Comma-separated: ?tags=python,django → ["python", "django"]
• Repeated keys: ?tags=python&tags=django → ["python", "django"]
• Combined: ?tags=python,django&tags=fastapi → ["python", "django", "fastapi"]

2. Use with Django class-based views

from django.views import View
from django.http import JsonResponse
from django_qp import QueryParamsMixinView

# Specify the model as a generic parameter for IDE autocompletion
class ProductListView(QueryParamsMixinView[ProductFilterParams], View):
    validated_params_model = ProductFilterParams

    def get(self, request):
        params = self.validated_params  # IDE will now recognize type as ProductFilterParams
        return JsonResponse({
            "category": params.category,
            "min_price": params.min_price
        })

Important: QueryParamsMixinView must appear before the view class in the inheritance list. A TypeError is raised at class definition time if the order is wrong.

# Correct
class MyView(QueryParamsMixinView[MyParams], View): ...

# Wrong — raises TypeError
class MyView(View, QueryParamsMixinView[MyParams]): ...

3. Use with Django Rest Framework views

Requires pip install django-qp[drf].

from rest_framework.views import APIView
from rest_framework.response import Response
from django_qp import QueryParamsMixinView

class ProductAPIView(QueryParamsMixinView[ProductFilterParams], APIView):
    validated_params_model = ProductFilterParams

    def get(self, request):
        params = self.validated_params
        return Response({
            "result": "success",
            "tags": params.tags
        })

4. Use with ViewSets for action-specific validation

Override get_query_params_class to return different models per action (similar to DRF's get_serializer_class):

from rest_framework.viewsets import ModelViewSet
from rest_framework.decorators import action
from rest_framework.response import Response
from django_qp import QueryParamsMixinView
from typing import cast

class ProductViewSet(QueryParamsMixinView[ProductFilterParams], ModelViewSet):
    queryset = Product.objects.all()
    serializer_class = ProductSerializer

    def get_query_params_class(self, action):
        if action == "list":
            return ProductFilterParams
        elif action == "export":
            return ExportParams
        return None  # No validation for other actions

    def list(self, request):
        params = cast(ProductFilterParams, self.validated_params)
        filtered_products = self.queryset.filter(
            category=params.category,
            price__gte=params.min_price
        )
        # ...

    @action(detail=False, methods=["get"])
    def export(self, request):
        params = cast(ExportParams, self.validated_params)
        return Response({
            "export_format": params.format,
            "with_details": params.include_details
        })

5. Use with function-based views

Simple validation with a single model

from django.http import JsonResponse
from django_qp import validate_query_params, EnhancedHttpRequest

@validate_query_params(ProductFilterParams)
def product_list(request: EnhancedHttpRequest[ProductFilterParams]):
    params = request.validated_params  # IDE autocomplete works here!
    return JsonResponse({"category": params.category})

Method-specific validation

Provide different validation models for different HTTP methods using a dict with lowercase method names:

from django.http import JsonResponse, HttpRequest
from django_qp import validate_query_params

class GetParams(BaseModel):
    filter: str
    sort_by: str | None = None

class PostParams(BaseModel):
    data: str
    priority: int = Field(ge=1, le=5)

# Dictionary mapping HTTP methods to models
@validate_query_params({
    "get": GetParams,
    "post": PostParams,
    "": DefaultParams,  # Optional fallback for unmapped methods
})
def products_api(request: HttpRequest):
    params = request.validated_params

    if request.method == "GET":
        params: GetParams
        return JsonResponse({
            "filter": params.filter,
            "sort_by": params.sort_by
        })
    elif request.method == "POST":
        params: PostParams
        return JsonResponse({
            "data": params.data,
            "priority": params.priority
        })

Dynamic model selection

For more complex scenarios, use a resolver function:

from django.http import JsonResponse
from django_qp import validate_query_params, EnhancedHttpRequest

def get_model_for_request(request):
    if request.GET.get("export") == "true":
        return ExportParams
    return StandardParams

@validate_query_params(get_model_for_request)
def dynamic_api(request: EnhancedHttpRequest[ExportParams | StandardParams]):
    params = request.validated_params

    if hasattr(params, "format"):
        return JsonResponse({"format": params.format})
    else:
        return JsonResponse({"query": params.query})

Customizing Error Messages and Status Codes

You can provide custom error messages and status codes for specific fields and error types:

class CustomView(QueryParamsMixinView[ProductFilterParams], APIView):
    validated_params_model = ProductFilterParams
    field_error_messages = {
        "min_price": {
            "greater_than_equal": "Minimum price must be non-negative.",
            "__all__": "Invalid price provided."
        },
        "category": {
            "type_error": "Category must be a string."
        }
    }
    field_error_status_codes = {
        "min_price": 400,
        "category": 404,
    }

Advanced: Direct parameter validation

from django_qp import process_query_params, QueryParamsError

def custom_view(request):
    try:
        params = cast(
            ProductFilterParams,
            process_query_params(request, ProductFilterParams)
        )
    except QueryParamsError as e:
        return JsonResponse({"error": e.detail}, status=400)
    # ...

Type Hints for Function-Based Views

For better IDE support and type checking in function-based views, use the EnhancedHttpRequest generic type:

from django_qp import validate_query_params, EnhancedHttpRequest
from pydantic import BaseModel

class UserParams(BaseModel):
    name: str
    age: int

@validate_query_params(UserParams)
def my_view(request: EnhancedHttpRequest[UserParams]):
    # Your IDE now knows that:
    params = request.validated_params  # This is a UserParams instance
    name = params.name  # This is a string
    age = params.age    # This is an int

    return HttpResponse(f"Hello {name}, you are {age} years old")

Handling Dynamic Models with Type Casting

When working with dynamic models (such as when using a resolver function), you can use Python's cast() function for better type safety:

from typing import cast
from django_qp import validate_query_params, EnhancedHttpRequest

# Define a resolver function that returns different models
def get_model_for_request(request):
    if request.GET.get("use_detailed") == "true":
        return DetailedParams
    return SimpleParams

@validate_query_params(get_model_for_request)
def dynamic_view(request: EnhancedHttpRequest[SimpleParams | DetailedParams]):
    params = request.validated_params

    # Option 1: Type narrowing with isinstance
    if isinstance(params, DetailedParams):
        # IDE knows this is DetailedParams
        return JsonResponse({"details": params.details})

    # Option 2: Type narrowing with attribute check + cast
    if hasattr(params, "details"):
        # Use cast to tell the type checker what type this is
        detailed_params = cast(DetailedParams, params)
        return JsonResponse({"details": detailed_params.details})

    # Now IDE knows this must be SimpleParams
    return JsonResponse({"name": params.name})

This approach gives you the full benefits of type checking while still supporting dynamic model selection.

Running Tests

uv run pytest

License

MIT