LinkyStat

Data pipeline · Time-series · Long-term

GitHub

Capture, store and visualise electricity consumption from the Linky meter.

Role

Design & dev

Stack

Python · MySQL · Grafana

Status

Archived

The problem

A Linky meter, "connected". You've got my attention. Connected how, exactly?

The Enedis TIC spec, fine. A little USB key from hallard.me to read the serial frame, and now I'm on home ground: software. I can read the telemetry (TIC). One frame, one checksum to validate. I've got my first data.

Drop it all into a database, Grafana on top, and let it accumulate. Not a real-time gadget: long memory, usable over years.

FIG. 01 LinkyStat dashboard in Grafana: real-time, monthly and yearly history.

What worked

7 years, zero downtime

In continuous production since day one. Unbroken history until the switch to Home Assistant.

MySQL over the hype

A plain relational schema: no cardinality blow-up, no complex retention (full real-time for 2 days, hourly history for 7 years), queries still readable years later.

Dashboards that last

The same Grafana views still answer the questions I started with: short, medium and long-term views. Value compounded over time.

Simple backup

7 years of data in a single 1 MB dump. Automated via GitHub Actions. Restore takes seconds.

Why it's archived

Home Assistant made it obsolete. Once per-appliance power sensors were in place (smart plugs, TIC interface), HA aggregates everything natively — long-term history included — without a dedicated stack.

7 years of data were migrated into Home Assistant as HP/HC energy statistics — fully visible in the HA energy dashboard, no data loss. The code stays on GitHub. The Grafana/MySQL instance is gone: no point running a separate stack when the IoT platform does the same job, better.

What broke

Pricing. Tariff tables (peak/off-peak, standing charge, taxes) change often, and are only published as PDFs.

I tried to auto-download and parse those PDFs. The tables were too irregular: parsing broke on every tariff revision.

I ended up hard-coding prices. Simple and robust, but wrong the moment a rate moves. A conscious trade-off: I'd rather have accurate kWh than a fake cost.

Results

7 yrs

in production, no interruption

8300 → 4500

kWh / yr, 46% total consumption drop

300 → 120 W

permanent standby identified and cut

1 MB

final backup with 7 years of complete history

The next question

I could see total consumption falling. But what was actually using power? Impossible to know from a single meter.

I needed to go further: measure appliances individually. With a proper IoT platform, a community, serious hardware.

Enter Home Assistant.

Move to Home Assistant →

References

[01]
Teleinfo Client (TIC) Specification, Enedis
The official spec for the serial protocol emitted by the Linky meter: frames, fields, legacy and standard modes. Without it, the signal is undecipherable.
[02]
hallard.me, Charles-Henri Hallard
The maker behind the PiTInfo / LibTeleinfo USB key. Where I bought the hardware and found the community that actually reads TIC frames in France. One of the few places where electronics and software meet on this topic.