How can I build a scalable video platform with Python and JavaScript?

Question

I'm currently learning web development and I'm particularly interested in building a scalable video content platform using Python (possibly Django or Flask) and JavaScript (React or Vue).

I've been exploring sites like RBTV77 for inspiration — they seem lightweight but handle live video content well. From a technical perspective, what would be the best approach for someone starting out to handle video uploads, live streaming, and user interactions at scale?

Should I explore using WebRTC, HLS, or another protocol for real-time media? And how would I best integrate this into a Python backend with a JS frontend for performance and scalability?

Any advice or roadmap suggestions would be super helpful!

Answer 1

Since you're already learning Python and JavaScript, you're on the right track. For the backend, Django would be a strong choice for scalability and structure, especially with its built-in user authentication, admin panel, and REST API support (via Django REST Framework). If you prefer something lighter, Flask gives you more flexibility, but you’ll need to handle more things manually.

On the frontend, React or Vue are both great — React has a larger ecosystem, while Vue is slightly easier to start with.

🔹 For video uploads:

Start with file-based uploads using services like AWS S3, Cloudinary, or Firebase Storage — they handle storage, CDN delivery, and scaling better than hosting large files yourself.

🔹 For live streaming:

If you're aiming for real-time interactions (like video calls or low-latency streaming), WebRTC is the go-to protocol. But it’s complex for beginners and more suitable for peer-to-peer or small group streaming.

For one-to-many streaming (like YouTube or RBTV77), HLS (HTTP Live Streaming) is better. It’s supported widely and works well with CDNs. You can use tools like FFmpeg, Nginx with RTMP module, or Mux, Agora, or Livepeer to handle video encoding and delivery.

🔹 For user interaction:

Use WebSockets (with Django Channels or Flask-SocketIO) for real-time features like comments, likes, or viewer count updates. It blends well with a modern JS frontend.

🔹 Suggested roadmap:

1. Start small: Build a video upload and playback system using Django + React.
2. Add user accounts, likes, comments (basic social features).
3. Integrate cloud storage and delivery (S3 or Firebase).
4. Explore live streaming with HLS and test scalability using dummy traffic.
5. Add real-time interactions with WebSockets.
6. Once stable, explore deeper WebRTC use cases.

Answer 2

Hi Jeck,

Great question — building a scalable video platform using Python and JavaScript is a challenging but rewarding goal. If you're just getting started, I'd recommend using FastAPI for your Python backend (for performance and simplicity) or Django if you want built-in user management and a structured framework. For storing videos, don't save them directly on your server — instead, use cloud storage services like AWS S3, Google Cloud Storage, or Wasabi. You'll also want to integrate FFmpeg on the backend to convert uploaded videos into HLS format, which breaks videos into streamable chunks that work well with modern web players.

For playback and delivery, use HLS (HTTP Live Streaming) for on-demand video content, and consider WebRTC if you plan to support low-latency live streaming. Another common approach for live video is to stream via RTMP and then transcode to HLS for broader compatibility. Tools like Mux, Daily.co, or Agora can also help offload the complexity of video delivery while remaining scalable. On the frontend, whether you're using React or Vue, you can use libraries like Video.js or hls.js to handle video playback and stream integration smoothly. Connect your frontend to the backend using standard fetch() or libraries like Axios.

If you plan to incorporate real-time features like chat or viewer reactions, consider using WebSockets — these can be implemented via Django Channels or FastAPI with Socket.IO, and scaled using Redis for pub/sub messaging. For production readiness and scalability, use a CDN (like Cloudflare or AWS CloudFront) to serve video segments, and offload background jobs like encoding or notifications using Celery with Redis. Finally, containerize your app with Docker, and deploy on scalable platforms like Kubernetes, Render, or Railway for long-term growth.

Let me know if you’d like help setting up an MVP stack or want to see example repositories for inspiration!

Best regards,

Sid Bhatia