Skip to main content
GET
/
api
/
dataframer
/
anonymization-runs
Python
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_runs = client.dataframer.anonymization_runs.list()
print(anonymization_runs)
[
  {
    "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "status": "PENDING",
    "dataset_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "dataset_name": "<string>",
    "detection_method": "<string>",
    "pii_types": [
      "<string>"
    ],
    "llm_model_name": "<string>",
    "created_by_email": "[email protected]",
    "completed_at": "2023-11-07T05:31:56Z",
    "created_at": "2023-11-07T05:31:56Z"
  }
]

Authorizations

​
Authorization
string
header
required

API Key authentication. Format: "Bearer YOUR_API_KEY"

Response

List of anonymization runs

​
id
string<uuid>

Unique identifier for the anonymization run.

​
status
enum<string>

Current status of the anonymization run.

Available options:
PENDING,
PROCESSING,
SUCCEEDED,
FAILED
​
dataset_id
string<uuid> | null

UUID of the seed dataset being anonymized.

​
dataset_name
string | null

Name of the seed dataset.

​
detection_method
string

Entity detection method used.

​
pii_types
string[]

List of PII/PHI entity types being detected.

​
llm_model_name
string | null

LLM model name (when detection_method includes llm).

​
created_by_email
string<email> | null

Email of the user who created this run.

​
completed_at
string<date-time> | null

When the run completed.

​
created_at
string<date-time>

When the run was created.