Handling Multiple Image Uploads to AWS S3 with Django Rest Framework AP

Introduction

At Optitech Inc., we faced a challenge: enabling users to upload multiple images to AWS S3 through our Django Rest Framework (DRF) API using JSON requests. This guide details how we tackled this problem, blending technical rigor with practical application—a skill set I’m eager to expand upon in the HNG Internship.

Step-by-Step Solution

1. Setting Up AWS S3 Integration in Django

Begin by configuring Django to interact with AWS S3 for file storage.

Setup Steps:

• Install Required Packages: Boto3 for AWS interactions and Django Storages for S3 integration.

  pip install boto3 django-storages

• Configure Django Settings: Add S3 configuration in settings.py.

    pythonCopy code# settings.py
    AWS_ACCESS_KEY_ID = 'your_access_key_id'
    AWS_SECRET_ACCESS_KEY = 'your_secret_access_key'
    AWS_STORAGE_BUCKET_NAME = 'your_bucket_name'
    AWS_S3_REGION_NAME = 'your_region'
  
    DEFAULT_FILE_STORAGE = 'storages.backends.s3boto3.S3Boto3Storage'
  

Tools Used:

• Boto3: AWS SDK for Python.

• Django Storages: Backend for managing file storage.

2. Creating the Model and Serializer

Define a Django model and serializer to handle image uploads and store metadata.

Model Example:

pythonCopy codefrom django.db import models

class Image(models.Model):
    file = models.ImageField(upload_to='images/')
    uploaded_at = models.DateTimeField(auto_now_add=True)

    def __str__(self):
        return self.file.name

Serializer Example:

pythonCopy codefrom rest_framework import serializers
from .models import Image

class ImageSerializer(serializers.ModelSerializer):
    class Meta:
        model = Image
        fields = ('id', 'file', 'uploaded_at')

Tools Used:

• Django Models: Database schema definition.

• DRF Serializers: Validation and serialization of data.

3. Creating the API View for File Uploads

Develop a DRF API view to handle JSON requests for multiple image uploads and save metadata to the database.

API View Example:

pythonCopy codefrom rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework import status
import boto3
from django.conf import settings
from .serializers import ImageSerializer

class MultipleImageUploadView(APIView):
    def post(self, request, *args, **kwargs):
        serializer = ImageSerializer(data=request.data.getlist('images'), many=True)
        if serializer.is_valid():
            s3_client = boto3.client('s3', region_name=settings.AWS_S3_REGION_NAME)
            uploaded_files = []

            for file_data in request.data.getlist('images'):
                s3_client.upload_fileobj(
                    file_data,
                    settings.AWS_STORAGE_BUCKET_NAME,
                    file_data.name,
                    ExtraArgs={'ContentType': file_data.content_type}
                )
                image = Image(file=file_data)
                image.save()
                uploaded_files.append({
                    'file_name': file_data.name,
                    'url': f"https://{settings.AWS_STORAGE_BUCKET_NAME}.s3.amazonaws.com/{file_data.name}"
                })

            return Response({"uploaded_files": uploaded_files}, status=status.HTTP_201_CREATED)
        return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)

Tools Used:

• DRF Views: Handling HTTP methods and requests.

• Boto3: AWS S3 file upload.

4. Handling File Uploads in JSON Request

Ensure the client-side JSON request correctly formats the file data as multipart/form-data.

Example JSON Request (using Python Requests library):

pythonCopy codeimport requests

url = 'http://your-api-endpoint.com/api/upload/'
files = {
    'images': ('image1.jpg', open('image1.jpg', 'rb'), 'image/jpeg'),
    ('images', ('image2.jpg', open('image2.jpg', 'rb'), 'image/jpeg'))
}

response = requests.post(url, files=files)
print(response.json())

Tools Used:

• Python Requests: Sending HTTP requests.

5. Testing the API

Verify functionality by testing the API endpoint with multiple image uploads.

API Test Example:

pythonCopy codefrom rest_framework.test import APITestCase
from rest_framework import status
from io import BytesIO
from PIL import Image
from .models import Image

class MultipleImageUploadTest(APITestCase):
    def test_upload_multiple_images(self):
        image1 = BytesIO()
        image2 = BytesIO()
        Image.new('RGB', (100, 100)).save(image1, format='JPEG')
        Image.new('RGB', (100, 100)).save(image2, format='JPEG')
        image1.seek(0)
        image2.seek(0)

        files = {
            'images': [image1, image2]
        }

        response = self.client.post('/api/upload/', files, format='multipart')
        self.assertEqual(response.status_code, status.HTTP_201_CREATED)
        self.assertIn('uploaded_files', response.data)
        self.assertEqual(Image.objects.count(), 2)

Tools Used:

• PIL (Pillow): Generating test images.

• DRF Test Framework: Testing API endpoints.

6. Deploying and Monitoring

Deploy the solution and monitor AWS S3 activity and application logs for performance and errors.

Monitoring Tools:

• AWS CloudWatch: Monitoring AWS S3 and application performance.

• Logging: Capturing detailed logs for debugging and analysis.

Tools Used:

• AWS CloudWatch: Monitoring AWS services.

• Logging: Recording application events.

Conclusion

Implementing multiple image uploads to AWS S3 via DRF API with JSON request handling enhances system efficiency and user experience. This solution demonstrates robust backend development practices and prepares for challenges in the HNG Internship and beyond.