RabbitMQ VS FFmpeg

Although they did not make it into production, I experimented with the RabbitMQ message broker, Python (Django, Flask), Kubernetes + minikube, JWT, and NGINX. This was a hobby project, but I intended to learn about microservices along the way.

Messaging/Queueing Systems (Amazon SQS, RabbitMQ, Beanstalkd)

Later, we discovered Propan, a library created by Nikita Pastukhov, which solved similar problems but for RabbitMQ. Recognizing the potential for collaboration, we joined forces with Nikita to build a unified library that could work seamlessly with both Kafka and RabbitMQ. And that's how FastStream came to be—a solution born out of the need for simplicity and efficiency in microservices development.

Inter-Service Communication: Middleware provides communication channels and protocols that enable microservices to communicate with each other. This can include message brokers like RabbitMQ, Apache Kafka, RPC frameworks like gRPC, or RESTful APIs.

This is an implementation of pub/sub. The publisher is on a separate project. The message broker is Azure Service Bus. We use NServiceBus for code implementation. I use rabbitMQ broker for local tests. Nothing I can do about the tech stack. This is more of a high level single project structure review 😅

RabbitMQ is a robust and highly configurable open-source message broker that implements the Advanced Message Queuing Protocol (AMQP).

When using third-party services, especially within a "transaction", it's often a good idea to use a persistent Message Queue (MQ) system like RabbitMQ. Go through all their tutorials to get a really good understanding of how message queues work and how they can be used to solve your problem.

The best technical solution to provide the event queues is to use a message-broker technology like RabbitMQ.

GPL2

Since FFmpeg is GPL2, doesn’t that require CompressX to disclose its source code?

IANAL, apologies if I miss understand license requirements.

https://github.com/FFmpeg/FFmpeg?tab=License-1-ov-file

This turns out to be a lot of assembly macros to help write one x86 assembly. https://github.com/FFmpeg/FFmpeg/blob/master/libavutil/x86/x...

The sibling comment recommending compiler intrinsics is probably the best way to go for writing SIMD code. A mixture of `` style types and intrinsics to specify instructions is a solid 90% solution compared to assembly.

If you want that last 10%, I think macros are putting the emphasis in the wrong place. They're a somewhat easy way to build up a language abstraction which will work if held carefully, but I'm confident the dev experience using this abstraction when you write invalid code will be deeply confusing.

I would suggest to write a parser instead of the macros. That'll tell you clearly when the syntax is invalid (though possibly not with much precision) and it'll give you a place to put semantic analysis for where valid syntax encodes nonsense. Do the equivalent of the macro expansions on the parsed tree instead of on the text. Emit asm as the "back end".

You might have heard of FFMPEG or ImageMagick for image and video edition in a programmatic way. MoviePy is a Python module for video editing (Python wrapper for FFMPEG and ImageMagick). It provides functions for cutting, concatenations, title insertions, video compositing, video processing, and the creation of custom effects. It can read and write common video and audio formats and be run on any platform with Python 2.7 or 3+.

There are many cloud-based tools and websites that can convert your images, but the problem with these tools is that you usually have to upload the files for them to be processed, and some of their services are not free. In this article, I'd like to introduce a piece of software called FFmpeg, which allows you convert the images locally with one simple command.

To run the demo locally, be sure to have Python 3.11 and FFmpeg installed.