code: def test_extract_metrics_for_single_field(
      records, td_extractor: TextDescriptivesExtractor
  ) -> None:
      field_metrics = td_extractor._extract_metrics_for_single_field(
          records, "required-field"
      )
      assert field_metrics["required-field_n_tokens"].values[0] == 4
      assert len(field_metrics) == len(
          records
      )  # Assert the number of rows in the DataFrame
      assert isinstance(
          field_metrics, pd.DataFrame
      )  # Assert the data type of the DataFrame
      assert (
          "required-field_n_tokens" in field_metrics.columns
      )  # Assert the presence of the column
      assert (
          field_metrics["required-field_n_tokens"].values[0] == 4
      )  # Assert the value of the column
      assert (
          "required-field" not in field_metrics.columns
      )  # Assert that text column has been dropped
      assert (
          not field_metrics.isnull().values.any()
      )  # Assert no columns with NaN values
      assert "optional-field" not in field_metrics.columns
  
imports: from unittest.mock import MagicMock
  import pandas
  import pytest
  from argilla.client.feedback.dataset import FeedbackDataset
  from argilla.client.feedback.integrations.textdescriptives import TextDescriptivesExtractor
  from argilla.client.feedback.schemas.fields import TextField
  from argilla.client.feedback.schemas.metadata import FloatMetadataProperty, IntegerMetadataProperty, TermsMetadataProperty
  from argilla.client.feedback.schemas.questions import TextQuestion
  from argilla.client.feedback.schemas.records import FeedbackRecord
label_desc: Use image node_id 3 for calling a global function with example usage: test_extract_metrics_for_single_field(records, td_extractor) without return types