Open Data Schema for Energy
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Quickstart

Install ODS-E, transform one OEM file, and validate the output. Takes about 2 minutes.

Step 1: Install

pip install odse

Step 2: Transform OEM Data

Transform a Huawei FusionSolar CSV into standardized ODS-E records:

from odse import transform

csv_data = """timestamp,power,inverter_state,run_state
2026-02-09 12:00:00,5000,512,1
2026-02-09 12:05:00,4800,512,1
"""

rows = transform(csv_data, source="huawei")
print(rows[0])

Output:

{
  "timestamp": "2026-02-09T12:00:00Z",
  "kWh": 416.67,
  "error_type": "normal",
  "error_code": "512"
}

The same transform() function works for all 10 supported OEMs:

rows = transform(enphase_json, source="enphase", expected_devices=10)
rows = transform(solaredge_csv, source="solaredge")
rows = transform(solarman_csv, source="solarman")

Step 3: Validate

Check that the transformed records conform to the ODS-E schema:

from odse import validate

result = validate({
    "timestamp": "2026-02-09T14:00:00Z",
    "kWh": 847.5,
    "error_type": "normal"
})

print(result.is_valid)   # True
print(result.errors)     # []

You now have normalized, validated energy data from an OEM source.

What’s Next

You’ve completed the basic transform-validate pipeline. From here: