## Get evaluation results for a dataset

`datasets.get_evaluation(strdataset_id)  -> DatasetGetEvaluationResponse`

**get** `/api/v1/datasets/{dataset_id}/evaluation`

Get evaluation results for a dataset

### Parameters

- `dataset_id: str`

### Returns

- `class DatasetGetEvaluationResponse: …`

  - `dataset_id: str`

    Dataset ID

  - `quality: Optional[Quality]`

    Structured quality metrics. Null until evaluation completes.

    - `grade_after: Optional[str]`

      Letter grade (A-E) after augmentation

    - `grade_before: Optional[str]`

      Letter grade (A-E) before augmentation

    - `improvement_percent: Optional[float]`

      Relative quality improvement as a percentage

    - `percentile_after: Optional[float]`

      Percentile rank (0-100) after augmentation

    - `score_after: Optional[float]`

      Quality score (0-10) after augmentation

    - `score_before: Optional[float]`

      Quality score (0-10) before augmentation

  - `raw_results: Optional[Dict[str, object]]`

    Raw evaluation results payload for advanced use. Null until evaluation completes.

  - `status: Optional[str]`

    Evaluation pipeline status: pending | running | succeeded | failed | skipped

### Example

```python
import os
from adaption import Adaption

client = Adaption(
    api_key=os.environ.get("ADAPTION_API_KEY"),  # This is the default and can be omitted
)
response = client.datasets.get_evaluation(
    "dataset_id",
)
print(response.dataset_id)
```

#### Response

```json
{
  "dataset_id": "dataset_id",
  "quality": {
    "grade_after": "A",
    "grade_before": "C",
    "improvement_percent": 37.1,
    "percentile_after": 92.3,
    "score_after": 8.5,
    "score_before": 6.2
  },
  "raw_results": {
    "foo": "bar"
  },
  "status": "succeeded"
}
```