Stores P1 port data in a InfluxDB database, to visualize with Grafana.

Inspired by psy0rz/p1_dsmr_to_influxdb. Uses ndokter/dsmr_parser to read the P1 port data.

NOTE: I switched to PostgreSQL with TimescaleDB for performance, stability and flexibility reasons. This repo is not maintained. See mhvis/p1postgres.

With Docker Compose:

1. Copy or download compose.yaml to a desired location: wget https://github.com/mhvis/dsmr2influx/raw/master/compose.yaml.
2. Modify the configuration as required.
3. Run docker compose up -d.
4. To see if the containers have started correctly, use docker compose logs -f.

Steps after deployment:

• Open Grafana and add a data source for InfluxDB.
• Create a new dashboard or import the sample at ... .

The Docker image is only for amd64 platforms. To run this image on an arm platform, build it yourself. (TODO: add arm image.)

This command imports data from DSMR-reader into your InfluxDB instance. It requires that the DSMR-reader API is enabled and accessible via the container.

docker compose run app python dsmrreaderimport.py <api-url> <api-key>

Note: when using localhost as url, because the command runs in a Docker container, localhost does not refer to the Docker host. Instead use 172.17.0.1.

When the InfluxDB instance already contains measurements, existing measurements with the same timestamp get overridden. So it is safe to import multiple times.

Each telegram is stored as a telegram measurement in InfluxDB, and each field in the telegram is a field on the measurement. Field keys are the same as OBIS names, but in lowercase, for instance electricity_used_tariff_1 and instantaneous_voltage_l1.

Gas meter readings are stored in a separate measurement named gas_meter, because they update less frequent, often every 5 minutes or every hour. The measurement time is taken from the telegram. The field reading contains the value.