Skip to main content

Build simple kafka streams applications

Project description

Kstreams

kstreams is a library/micro framework to use with kafka. It has simple kafka streams implementation that gives certain guarantees, see below.

Build status codecov python version


Documentation: https://kpn.github.io/kstreams/


Installation

pip install kstreams

You will need a worker, we recommend aiorun

pip install aiorun

Usage

import aiorun
from kstreams import create_engine, ConsumerRecord


stream_engine = create_engine(title="my-stream-engine")

@stream_engine.stream("local--kstream")
async def consume(cr: ConsumerRecord):
    print(f"Event consumed: headers: {cr.headers}, payload: {cr.value}")


async def produce():
    payload = b'{"message": "Hello world!"}'

    for i in range(5):
        metadata = await stream_engine.send("local--kstreams", value=payload)
        print(f"Message sent: {metadata}")


async def start():
    await stream_engine.start()
    await produce()


async def shutdown(loop):
    await stream_engine.stop()


if __name__ == "__main__":
    aiorun.run(start(), stop_on_unhandled_errors=True, shutdown_callback=shutdown)

Features

  • Produce events
  • Consumer events with Streams
  • Subscribe to topics by pattern
  • Prometheus metrics and custom monitoring
  • TestClient
  • Custom Serialization and Deserialization
  • Easy to integrate with any async framework. No tied to any library!!
  • Yield events from streams
  • Opentelemetry Instrumentation
  • Middlewares
  • Hooks (on_startup, on_stop, after_startup, after_stop)
  • Store (kafka streams pattern)
  • Stream Join
  • Windowing

Development

This repo requires the use of poetry instead of pip. Note: If you want to have the virtualenv in the same path as the project first you should run poetry config --local virtualenvs.in-project true

To install the dependencies just execute:

poetry install

Then you can activate the virtualenv with

poetry shell

Run test:

./scripts/test

Run code formatting with ruff:

./scripts/format

Commit messages

We use conventional commits for the commit message.

The use of commitizen is recommended. Commitizen is part of the dev dependencies.

cz commit

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kstreams-0.24.1.tar.gz (29.1 kB view details)

Uploaded Source

Built Distribution

kstreams-0.24.1-py3-none-any.whl (35.8 kB view details)

Uploaded Python 3

File details

Details for the file kstreams-0.24.1.tar.gz.

File metadata

  • Download URL: kstreams-0.24.1.tar.gz
  • Upload date:
  • Size: 29.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.6 Linux/6.8.0-1014-azure

File hashes

Hashes for kstreams-0.24.1.tar.gz
Algorithm Hash digest
SHA256 63200d93f83a372809aece9987aa7fde5423d7bc1e0179ac53bac6c46c7c0303
MD5 2c24a278acf430a5eefb600ff8fd439b
BLAKE2b-256 43eba77de85c20ef7b31ea8d8af65284deab6a10a8bd39555bd76f24f96f739a

See more details on using hashes here.

File details

Details for the file kstreams-0.24.1-py3-none-any.whl.

File metadata

  • Download URL: kstreams-0.24.1-py3-none-any.whl
  • Upload date:
  • Size: 35.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.12.6 Linux/6.8.0-1014-azure

File hashes

Hashes for kstreams-0.24.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f5b15ba45ae802c6e5a7e2bc724498e47bf05b950dc809e3a682e21b4da6d8ed
MD5 38ba5d48d0c5f047a446e3ef74a6d3a1
BLAKE2b-256 0003ca6bfb308dc7a999197b894ef7088da62ba2601a074203d455a699ce8810

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page