import os
from dataframer import Dataframer

client = Dataframer(
    api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
)
anonymization_run = client.dataframer.anonymization_runs.create(
    dataset_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e",
    detection_method="aimon_pii_m1",
    pii_types=["string"],
)
print(anonymization_run.id)

curl --request POST \
  --url https://df-api.dataframer.ai/api/dataframer/anonymization-runs/ \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "dataset_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "pii_types": [
    "<string>"
  ],
  "llm_model_name": "<string>",
  "mask_config": {},
  "threshold": 0.3
}
'

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "dataset_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "dataset_name": "<string>",
  "pii_types": [
    "<string>"
  ],
  "detection_method": "<string>",
  "llm_model_name": "<string>",
  "created_by_email": "[email protected]",
  "duration_seconds": 123,
  "results": {
    "entity_summary": {},
    "samples_processed": 123,
    "entities_found": [
      {
        "start": 123,
        "end": 123,
        "label": "<string>",
        "score": 123
      }
    ],
    "error": "<string>"
  },
  "anonymized_files": [
    {
      "id": "<string>",
      "path": "<string>",
      "size_in_bytes": 123,
      "content_type": "<string>"
    }
  ],
  "completed_at": "2023-11-07T05:31:56Z",
  "created_at": "2023-11-07T05:31:56Z"
}