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Write the Python client code

In this part you write a command-line program to read the CPU load of your laptop, and publish that data to Quix.

Add the Python code

Using your editor of choice, create a file called Add the following code:

import psutil
import os
import time
import json
from quixstreams import Application

from dotenv import load_dotenv

def get_cpu_load():
    cpu_load = psutil.cpu_percent(interval=1)
    return cpu_load

app = Application()
output_topic = app.topic(os.environ["output"])

def main():
    with app.get_producer() as producer:
        while True:        
            cpu_load = get_cpu_load()
            print("CPU load: ", cpu_load)
            timestamp = int(time.time_ns()) # Quix timestamp is nano seconds
            message = {"timestamp": timestamp, "cpu_load": cpu_load}


if __name__ == '__main__':
    except KeyboardInterrupt:
        print('Exiting due to keyboard interrupt')

Get your SDK token

To obtain your token, go to Settings in your default environment, and then click on the APIs and tokens tab. You can obtain the Streaming Token (SDK Token) from there.

Set your token

You need to set the Quix__Sdk__Token environment variable.

Make a directory for your project and in it create a .env file:

Quix__Sdk__Token="<your SDK token>"


The SDK token and streaming token are the same thing. The SDK token is now called the streaming token in the UI.

Run the code

Run the code using a command similar to the following (the exact command you use depends on your Python set up):


When you run this, the topic cpu-load is created for you. If your code exits before the topic is created, simply run the code again.

Here, you're creating a simple JSON object containing a Unix timestamp in nano seconds, and the CPU load (as a percentage). This is then published to the output topic.


The timestamp is added here for convenience - it could have been added later in the pipeline. The Quix data format that can optionally be used expects a timestamp in nano seconds.

If you're monitoring many CPUs, you could use the stream ID to identify the source, in this case the stream ID is set to server-1-cpu.

🏃‍♀️ Next step

Part 2 - Add External source