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faststream
spec | faststream | |
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42 | 13 | |
3,868 | 1,802 | |
1.7% | 7.0% | |
7.9 | 9.7 | |
7 days ago | 7 days ago | |
JavaScript | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
spec
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10 realtime data sources you won't believe are free!
AsyncAPI: Interested in how to define your WebSocket APIs? One of the most advanced realtime specifications is the AsyncAPI specification, which comes with various generators for code and documentation, as well as renderers for the specifications.
- Comunicar microservicios con: ¿Kafka, RabbitMQ u otro? ¿Por qué?
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FastStream: Python's framework for Efficient Message Queue Handling
Our journey with FastStream started when we needed to integrate our machine learning models into a customer's Apache Kafka environment. To streamline this process, we created FastKafka using AIOKafka, AsyncAPI, and asyncio. It was our first step in making message queue management easier.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
Automatic Docs: Stay ahead with automatic AsyncAPI documentation
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FastStream: the easiest way to add Kafka and RabbitMQ support to FastAPI services
FastStream supports in-memory testing, AsyncAPI schema generation and more... If you are interested, please support our project by giving a GH start and joining our discord server.
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An AsyncAPI Example: Building Your First Event-driven API
However, in order for the system to work effectively, there must be a common understanding between the components regarding events and their data structures. This is where AsyncAPI comes in; it helps define a contract that describes how the components communicate and behave effectively.
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Is this a viable approach to a chat microservice?
You can also take a look at https://www.asyncapi.com/ (a spec for asynchronous APIs). It's useful for this use case, that is, building a well structured websocket interface with pub/sub.
- OpenAPI v4 Proposal
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Propan 0.1.2 - new way to interact Kafka from Python
Sure! Next step I am working on AsyncAPI scheme generation by your application code. It's also includes a project generation from scheme, scheme web view (lika the Swagger for OpanAPI), etc. It will a much difficult than just another broker implementation...
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Make API product lifecycle management easy
Onboarding - Enable developers to quickly learn how to consume the exposed APIs. For example, offer OpenAPI or AsyncAPI documentation and provide a portal and sandbox.
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:
What are some alternatives?
springdoc-openapi - Library for OpenAPI 3 with spring-boot
Propan - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker
WatermelonDB - 🍉 Reactive & asynchronous database for powerful React and React Native apps ⚡️
Faust - Python Stream Processing
asyncapi-react - React component for rendering documentation from your specification in real-time in the browser. It also provides a WebComponent and bundle for Angular and Vue
aiorabbit - An AsyncIO RabbitMQ client for Python 3
mqtt-venstar-bridge - Simple MQTT bridge to the venstar HTTP API
aiokafka - asyncio client for kafka
eventbridge-atlas - Open-source tool to document, discover, and share your Amazon EventBridge schemas.
cookiecutter-faststream - Cookiecutter template for FastStream apps
Flask-SocketIO - Socket.IO integration for Flask applications.
faststream-gen - The faststream-gen library uses advanced AI to generate FastStream code from user descriptions, speeding up FastStream app development.