Getting Started

Start your Kafka instance. Example using Docker:

docker run -p 9092:9092 -e ADV_HOST=127.0.0.1 lensesio/fast-data-dev

Define your KQ `worker.py module:

import logging

from kafka import KafkaConsumer
from kq import Worker

# Set up logging.
formatter = logging.Formatter('[%(levelname)s] %(message)s')
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(formatter)
logger = logging.getLogger('kq.worker')
logger.setLevel(logging.DEBUG)
logger.addHandler(stream_handler)

# Set up a Kafka consumer.
consumer = KafkaConsumer(
    bootstrap_servers='127.0.0.1:9092',
    group_id='group',
    auto_offset_reset='latest'
)

# Set up a worker.
worker = Worker(topic='topic', consumer=consumer)
worker.start()

Start the worker:

python my_worker.py
[INFO] Starting Worker(hosts=127.0.0.1:9092 topic=topic, group=group) ...

Enqueue a function call:

import requests

from kafka import KafkaProducer
from kq import Queue

# Set up a Kafka producer.
producer = KafkaProducer(bootstrap_servers='127.0.0.1:9092')

# Set up a queue.
queue = Queue(topic='topic', producer=producer)

# Enqueue a function call.
job = queue.enqueue(requests.get, 'https://google.com')

# You can also specify the job timeout, Kafka message key and partition.
job = queue.using(timeout=5, key=b'foo', partition=0).enqueue(requests.get, 'https://google.com')

Let the worker process it in the background:

python my_worker.py
[INFO] Starting Worker(hosts=127.0.0.1:9092, topic=topic, group=group) ...
[INFO] Processing Message(topic=topic, partition=0, offset=0) ...
[INFO] Executing job c7bf2359: requests.api.get('https://www.google.com')
[INFO] Job c7bf2359 returned: <Response [200]>