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Lelit-Marax-Dashboard

This project was made to visualise data from the Lelit MaraX coffee machine.

Sources for this project :

Hardware

For this project you need at least :

  • USB to TTL com RS232 (got it from Amazon, with a PL2303TA chip)
  • Raspberry pi with wifi (I used a pi zero W + OTG USB type A to micro USB)

Connect the USB to TTL on your coffee Machine. Pin 0 (closer th the edge/outside) is not connected, then green to PIN 1 and white to PIN 2. image

Connect th USB to the rpi. You can see the raw data in /dev/ttyUSB0.

You can verify everything is correct with this command

~# tail -f /dev/ttyUSB0

image

Python

Create a virtual env and download the dependency.

  • ~# python -m venv /MYPATH/MyVenv
  • ~# source /MYPATH/MyVenv/bin/activate
  • ~# python -m pip install -r requirements.txt
  • ~# deactivate

Modify the first line of reporter.py and specify your virtual env.

  • #!/MYPATH/MyVenv/bin/python

Then you can make it executable and start it in background.

  • ~# chmod +x reporters.py
  • ~# nohup ./reporters.py >/dev/null 2>&1 &

System D

You can add a service to restart the script every day. It is also easier to restart the app if it crash.

Place the pyLelit.service file in /etc/systemd/system/

  • To see the status : systemctl status pyLelit
  • To restart : systemctl restart pyLelit

Docker

You can install docker on your raspberry pi, or use a server.

I used my nas to host thoses containers.

You can install InfluxDB and Grafana, bare metal, on your raspberry if you don't want docker.

Create docker Stack with docker compose :

By default, the docker compose create db0 database.

Chronograf can only by accessed by the host machine.

Influx db :

If you want to create a DB and user manually, connect to your container.

  • ~# docker container ls
  • ~# docker exec -it <CONTAINER_NAME> /bin/bash

Then you can create databases and users directly from the container.

  • ~# inlfux
  • > SHOW DATABASES

Dashboard Gafana :

In grafana add a datasource : InfluxDB

Specify your credentials here :

image

Then you can import the dashboard :

image

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