import os
from dataframer import Dataframer

client = Dataframer(
    api_key=os.environ.get("DATAFRAMER_API_KEY"),  # This is the default and can be omitted
)
evaluation = client.dataframer.evaluations.create(
    run_id="a98715da-921d-4326-bbf8-208f8bcc2956",
)
print(evaluation.id)

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "run_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "status": "PENDING",
  "conformance_score": 123,
  "conformance_explanation": "<string>",
  "distribution_analysis": [
    {
      "property_name": "<string>",
      "total_samples": 123,
      "requested_distributions": {
        "positive": 40,
        "negative": 30,
        "neutral": 30
      },
      "expected_distributions": {
        "positive": 42,
        "negative": 30,
        "neutral": 28
      },
      "evaluated_distributions": {
        "positive": 45,
        "negative": 28,
        "neutral": 27
      },
      "observed_distributions": {},
      "total_samples_analyzed": 123
    }
  ],
  "sample_classifications": [
    {
      "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "evaluation_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "sample_identifier": "<string>",
      "classifications": {
        "sentiment": "positive",
        "topic": "technology",
        "length": "medium"
      },
      "created_at": "2023-11-07T05:31:56Z"
    }
  ],
  "started_at": "2023-11-07T05:31:56Z",
  "completed_at": "2023-11-07T05:31:56Z",
  "error_message": "<string>",
  "created_by_email": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "duration_seconds": 123,
  "company_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "status_display": "<string>",
  "conformant_areas": "<string>",
  "non_conformant_areas": "<string>",
  "trace": {},
  "created_by": 123,
  "updated_at": "2023-11-07T05:31:56Z"
}