vidgear VS starlette

My experience that played out over the last few weeks lead me to a similar belief, somewhat. For rather uninteresting reasons I decided I wanted to create mp4 videos of an animation programmatically, from scratch.

The first solution suggested when googling around is to just create all the frames, save them to disk, and then let ffmpeg do its thing from there. I would have just gone with that for a one-off task, but it seems like a pretty bad solution if the video is long, or high res, or both. Plus, what I really wanted was to build something more "scalable/flexible".

Maybe I didn't know the right keywords to search for, but there really didn't seem to be many options for creating frames, piping them straight to an encoder, and writing just the final video file to disk. The only one I found that seemed like it could maybe do it the way I had in mind was VidGear[1] (Python). I had figured that with the popularity of streaming, and video in general on the web, there would be so much more tooling for these sorts of things.

I ended up digging way deeper into this than I had intended, and built myself something on top of Membrane[2] (Elixir)

[1] https://abhitronix.github.io/vidgear/

I've been googling and reading for a while but I'm very unsure about which tools I need, which tools will help me achieve what I want the easiest way. What about (pylivestream)[https://pypi.org/project/pylivestream/] for example? Will this do the job for me? What about a lower level approach including (pyopencv)[https://pypi.org/project/opencv-python/]? What about a higher level approach using (vidgear)[https://github.com/abhiTronix/vidgear], which seems promising but I don't feel confident in assessing if it's the tool I really need?

Vidgear and new deffcode library are my best. I bet you don't know none of them. But they're pretty awesome when it comes to video-processing and stuff.

Yes, fortunately I already resolved it in my previous(popular) library called vidgearthrough its WriteGear API: https://abhitronix.github.io/vidgear/latest/gears/writegear/compression/overview/

Code: https://github.com/abhiTronix/vidgear

Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.

The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.

Uvicorn + Starlette 8k requests/s

Starlette documentation

Same here, but without these weird utils it doesn't get any better.

I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.

Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.

https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...

In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.

Set up Starlette, a tool we'll use to make async requests

I never used websockets in FastAPI so I wouldn't know how to guide you more, but Middleware in Websockets are 100% supported by Starlette : https://github.com/encode/starlette/issues/641

Websockets are the way but I would not recommend django as it's still not fully async. I would go for other tools.