faststream
RabbitMQ
faststream | RabbitMQ | |
---|---|---|
13 | 95 | |
1,858 | 11,672 | |
9.8% | 1.6% | |
9.7 | 10.0 | |
1 day ago | 2 days ago | |
Python | Starlark | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
faststream
- FastStream v0.4.0: Introducing Confluent Kafka Integration with Async Support
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Show HN: Confluent Kafka support added to FastStream v0.4.0rc0
FastStream - https://github.com/airtai/faststream, a stream processing framework, already supports Kafka stream processing using the aiokafka library, as well as other brokers such as Redis, RabbitMQ, and NATS.
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Processing streaming messages from a Django service
FastStream is a powerful and easy-to-use FOSS framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ and NATS. It simplifies the process of writing producers and consumers for message queues, handling all the parsing, networking and documentation generation automatically.
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FastStream: Python's framework for Efficient Message Queue Handling
Ready to join the FastStream revolution? Head over to our GitHub repository and show your support by starring it. By doing so, you'll stay in the loop with the latest developments, updates, and enhancements as we continue to refine and expand FastStream.
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How we deprecated two successful projects and joined forces to create an even more successful one
After two months of hard work, we presented the newly released FastStream framework at Infobip Shift conference and got featured at ShiftMag. The framework now supports both Apache Kafka and RabbitMQ, but also NATS protocol with the plan to add more protocols in the near future. The overall code is much cleaner and the implementation is streamlined with abstractions covering the common functionality across the protocols. We deprecated both FastKafka and Propan, but promised to fix bugs as long as needed. However, it seems like the community already decided to switch over to gain new functionalities.
- FastStream 0.2.0 adds NATS support in addition to Apache Kafka and RabbitMQ. It is the easiest way to add broker-agnostic support for streaming protocols to your microservices.
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Generating production-level streaming microservices using GPT
faststream-gen(https://github.com/airtai/faststream-gen/) uses GPT models to automatically generate microservices using the FastStream(https://github.com/airtai/faststream) framework for Apache Kafka, RabbitMQ and NATS. Simply describe your microservice in plain English, and it will generate a production-level FastStream application ready to deploy in a few minutes and under $1 cost, together with unit and integration tests, documentation and Docker images.
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Generating production-level streaming microservices using AI
faststream-gen is a Python library that uses generative AI to automatically generate FastStream applications. Simply describe your microservice in plain English, and faststream-gen will generate a production-level FastStream application ready to deploy in a few minutes and under $1 cost.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
FastStream simplifies the process of writing producers and consumers for message queues, handling all the parsing, networking and documentation generation automatically. It is a new package based on the ideas and experiences gained from FastKafka and Propan. By joining our forces, we picked up the best from both packages and created a unified way to write services capable of processing streamed data regardless of the underlying protocol. We'll continue to maintain both packages, but new development will be in this project.
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FastStream: the easiest way to add Kafka and RabbitMQ support to FastAPI services
FastStream (https://github.com/airtai/faststream) is a new Python framework, born from Propan and FastKafka teams' collaboration (both are deprecated now). It extremely simplifies event-driven system development, handling all the parsing, networking, and documentation generation automatically. Now FastStream supports RabbitMQ and Kafka, but supported brokers are constantly growing (wait for NATS and Redis a bit). FastStream itself is a really great tool to build event-driven services. Also, it has a native FastAPI integration. Just create a StreamRouter (very close to APIRouter) and register event handlers the same with the regular HTTP-endpoints way:
RabbitMQ
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Building Llama as a Service (LaaS)
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.
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A Developer's Journal: Simplifying the Twelve-Factor App
Messaging/Queueing Systems (Amazon SQS, RabbitMQ, Beanstalkd)
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FastStream: Python's framework for Efficient Message Queue Handling
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.
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The Complete Microservices Guide
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.
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Project Structure Review [.Net] [Console]
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 😅
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The Role of Queues in Building Efficient Distributed Applications
RabbitMQ is a robust and highly configurable open-source message broker that implements the Advanced Message Queuing Protocol (AMQP).
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Should I chain calls in backend?
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.
- Node still seems better than python after all this time for web server speed but..
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Delayed events pattern, no more crons
The best technical solution to provide the event queues is to use a message-broker technology like RabbitMQ.
- RabbitMQ 3.12.0 Released
What are some alternatives?
Propan - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
Faust - Python Stream Processing
mosquitto - Eclipse Mosquitto - An open source MQTT broker
aiorabbit - An AsyncIO RabbitMQ client for Python 3
MediatR - Simple, unambitious mediator implementation in .NET
aiokafka - asyncio client for kafka
nsq - A realtime distributed messaging platform
cookiecutter-faststream - Cookiecutter template for FastStream apps
BeanstalkD - Beanstalk is a simple, fast work queue.
faststream-gen - The faststream-gen library uses advanced AI to generate FastStream code from user descriptions, speeding up FastStream app development.
rq - Simple job queues for Python