You can grab energy data with the library, for example:
python3 -m myPyllant.export email@example.com password vaillant --country country -d --start 2023-01-01 --end 2023-09-01 -r DAY > data.json
…which gives you JSON in the data.json file, for example:
...
{
"operation_mode": "HEATING",
"device": {
"system_id": "",
"device_uuid": "",
"ebus_id": "VWZ02",
"article_number": "0010023609",
"device_serial_number": "",
"type": "electric_backup_heater",
"device_type": "ELECTRIC_AUXILIARY_HEATER",
"first_data": "2022-10-11 16:16:40",
"last_data": "2023-11-15 19:46:33",
"brand": "vaillant",
"name": null,
"product_name": "hydraulic station",
"spn": 351,
"bus_coupler_address": 0,
"emf_valid": true,
"operational_data": {},
"data": [
{
"operation_mode": "DOMESTIC_HOT_WATER",
"device": null,
"data_from": "2022-10-11 16:16:40",
"data_to": "2023-11-15 19:46:33",
"start_date": null,
"end_date": null,
"resolution": null,
"energy_type": null,
"value_type": "CONSUMED_ELECTRICAL_ENERGY",
"calculated": false,
"data": []
},
{
"operation_mode": "HEATING",
"device": null,
"data_from": "2022-10-11 16:16:40",
"data_to": "2023-11-15 19:46:33",
"start_date": null,
"end_date": null,
"resolution": null,
"energy_type": null,
"value_type": "CONSUMED_ELECTRICAL_ENERGY",
"calculated": false,
"data": []
}
],
"properties": [],
"diagnostic_trouble_codes": []
},
"data_from": null,
"data_to": null,
"start_date": "2023-01-01 00:00:00",
"end_date": "2023-09-01 00:00:00",
"resolution": "DAY",
"energy_type": "CONSUMED_ELECTRICAL_ENERGY",
"value_type": null,
"calculated": null,
"data": [
{
"start_date": "2023-01-01 00:00:00",
"end_date": "2023-01-02 00:00:00",
"value": 0.0
},
...
{
"start_date": "2023-01-21 00:00:00",
"end_date": "2023-01-22 00:00:00",
"value": 1000.0
}
...
You could then take the relevant portions from data and paste it into JSON To CSV Converter