drf-accelerator 0.1.0a1

A high-performance Rust-backed accelerator for Django Rest Framework.

DRF Accelerator

[!CAUTION] Experimental / Under Development This project is currently an experiment to improve DRF performance using Rust. It is NOT production-ready and has strict scope limitations.

A high-performance Rust-backed accelerator for Django Rest Framework.

Performance Benchmark

Method	Time (10k items)	Speedup
Standard DRF	0.3288s	1x
drf-accelerator	0.0389s	~8.45x

Benchmark run on 10,000 Product models with 5 primitive fields in the examples project.

Installation & Setup

For Users (Stable)

Currently, the package is in early development. To install it from source:

1. Prerequisites: Ensure you have Rust installed.
2. Clone the repository:

   git clone https://github.com/p-r-a-v-i-n/drf-accelerator.git
   cd drf-accelerator
   

3. Build and Install:

   pip install -e .
   

For Developers (Try it out)

If you want to run the benchmarks yourself:

1. Build the extension:

   cd drf_accelerator
   maturin develop --release
   cd ..
   

2. Setup and Run Benchmark:

   cd examples
   python manage.py migrate
   python bench.py
   

Usage

Simply inherit from FastSerializationMixin in your ModelSerializer:

from drf_accelerator import FastSerializationMixin
from rest_framework import serializers

class MySerializer(FastSerializationMixin, serializers.ModelSerializer):
    class Meta:
        model = MyModel
        fields = ["id", "title", "author", "is_published"]

Limitations (Strict)

To maintain high performance and safety, the following are not supported:

• Dotted Sources: source="user.profile.age" will error.
• Nested Serializers: Cannot be used inside an accelerated serializer.
• Method Fields: SerializerMethodField is not supported.
• Non-Primitives: Only int, str, float, bool, and None are supported. Non-primitive types (like Decimal or Date) will currently trigger a TypeError.

How it works

The Mixin swaps the standard DRF ListSerializer for a FastListSerializer that offloads the object-to-dict conversion loop to a Rust extension using PyO3. This significantly reduces Python interpreter overhead for large list responses.