Bytewax

This guide demonstrates how to use Estuary Flow to stream data to Bytewax using the Kafka-compatible Dekaf API.

Bytewax is a Python framework for building scalable dataflow applications, designed for high-throughput, low-latency data processing tasks.

Connecting Estuary Flow to Bytewax

Generate a refresh token for the Bytewax connection from the Estuary Admin Dashboard.
Install Bytewax and the Kafka Python client:
```
pip install bytewax kafka-python
```

Create a Python script for your Bytewax dataflow, using the following template:

import json
from datetime import timedelta
from bytewax.dataflow import Dataflow
from bytewax.inputs import KafkaInputConfig
from bytewax.outputs import StdOutputConfig
from bytewax.window import TumblingWindowConfig, SystemClockConfig

# Estuary Flow Dekaf configuration
KAFKA_BOOTSTRAP_SERVERS = "dekaf.estuary.dev:9092"
KAFKA_TOPIC = "/full/nameof/your/collection"

# Parse incoming messages
def parse_message(msg):
    data = json.loads(msg)
    # Process your data here
    return data

# Define your dataflow
 src = KafkaSource(brokers=KAFKA_BOOTSTRAP_SERVERS, topics=[KAFKA_TOPIC], add_config={
     "security.protocol": "SASL_SSL",
     "sasl.mechanism": "PLAIN",
     "sasl.username": "{}",
     "sasl.password": os.getenv("DEKAF_TOKEN"),
 })
 
 flow = Dataflow()
 flow.input("input", src)
 flow.input("input", KafkaInputConfig(KAFKA_BOOTSTRAP_SERVERS, KAFKA_TOPIC))
 flow.map(parse_message)
 # Add more processing steps as needed
 flow.output("output", StdOutputConfig())

 if __name__ == "__main__":
     from bytewax.execution import run_main
     run_main(flow)

Replace "/full/nameof/your/collection" with your actual collection name from Estuary Flow.
Run your Bytewax dataflow:
```
python your_dataflow_script.py
```
Your Bytewax dataflow is now processing data from Estuary Flow in real-time.

Bytewax

Connecting Estuary Flow to Bytewax​

Connecting Estuary Flow to Bytewax