code: def test_push_to_huggingface_and_from_huggingface(
      mocked_client: "SecuredClient",
      monkeypatch: pytest.MonkeyPatch,
      feedback_dataset_guidelines: str,
      feedback_dataset_fields: List["AllowedFieldTypes"],
      feedback_dataset_questions: List["AllowedQuestionTypes"],
      feedback_dataset_records: List[FeedbackRecord],
  ) -> None:
      argilla.client.singleton.active_api()
      argilla.client.singleton.init(api_key="argilla.apikey")
  
      dataset = FeedbackDataset(
          guidelines=feedback_dataset_guidelines,
          fields=feedback_dataset_fields,
          questions=feedback_dataset_questions,
      )
      dataset.add_records(records=feedback_dataset_records)
  
      monkeypatch.setattr(
          "datasets.arrow_dataset.Dataset.push_to_hub",
          lambda *args, **kwargs: None,
      )
      monkeypatch.setattr(
          "huggingface_hub.hf_api.HfApi.upload_file",
          lambda *args, **kwargs: None,
      )
      monkeypatch.setattr(
          "huggingface_hub.repocard.RepoCard.push_to_hub",
          lambda *args, **kwargs: None,
      )
  
      dataset.push_to_huggingface(
          repo_id="test-dataset", generate_card=True
      )
  
      with tempfile.NamedTemporaryFile(
          mode="w", suffix=".yaml", delete=False
      ) as f:
          f.write(
              DatasetConfig(
                  fields=feedback_dataset_fields,
                  questions=feedback_dataset_questions,
                  guidelines=feedback_dataset_guidelines,
              ).to_yaml()
          )
          config_file = f.name
  
      monkeypatch.setattr(
          "huggingface_hub.hf_hub_download",
          lambda *args, **kwargs: config_file,
      )
      monkeypatch.setattr(
          "datasets.load_dataset",
          lambda *args, **kwargs: dataset.format_as("datasets"),
      )
  
      dataset_from_huggingface = FeedbackDataset.from_huggingface(
          repo_id="test-dataset"
      )
      assert isinstance(dataset_from_huggingface, FeedbackDataset)
      assert dataset_from_huggingface.guidelines == dataset.guidelines
      assert len(dataset_from_huggingface.fields) == len(dataset.fields)
      assert all(
          original_field in dataset_from_huggingface.fields
          for original_field in dataset.fields
      )
      assert len(dataset_from_huggingface.questions) == len(
          dataset.questions
      )
      assert all(
          original_question in dataset_from_huggingface.questions
          for original_question in dataset.questions
      )
  
      for hf_record, record in zip(
          dataset_from_huggingface.records, dataset.records
      ):
          assert hf_record.fields == record.fields
          assert hf_record.metadata == record.metadata
          assert len(hf_record.responses) == len(record.responses)
          assert all(
              hf_response.dict() == response.dict()
              for hf_response, response in zip(
                  hf_record.responses, record.responses
              )
          )
  
      dataset.add_records(
          records=[
              FeedbackRecord(
                  fields={
                      "text": "This is a negative example",
                      "label": "negative",
                  },
                  responses=[
                      {
                          "values": {
                              "question-1": {
                                  "value": "This is a response to question 1"
                              },
                              "question-2": {"value": 0},
                              "question-3": {"value": "b"},
                              "question-4": {"value": ["b", "c"]},
                              "question-5": {
                                  "value": [
                                      {"rank": 1, "value": "a"},
                                      {"rank": 2, "value": "b"},
                                  ]
                              },
                          },
                          "status": "submitted",
                      },
                      {
                          "values": {
                              "question-1": {
                                  "value": "This is a response to question 1"
                              },
                              "question-2": {"value": 0},
                              "question-3": {"value": "b"},
                              "question-4": {"value": ["b", "c"]},
                              "question-5": {
                                  "value": [
                                      {"rank": 1, "value": "a"},
                                      {"rank": 2, "value": "b"},
                                  ]
                              },
                          },
                          "status": "submitted",
                      },
                  ],
              ),
          ],
      )
  
      monkeypatch.setattr(
          "datasets.arrow_dataset.Dataset.push_to_hub",
          lambda *args, **kwargs: None,
      )
      monkeypatch.setattr(
          "huggingface_hub.hf_api.HfApi.upload_file",
          lambda *args, **kwargs: None,
      )
      monkeypatch.setattr(
          "huggingface_hub.repocard.RepoCard.push_to_hub",
          lambda *args, **kwargs: None,
      )
  
      dataset.push_to_huggingface(
          repo_id="test-dataset", generate_card=True
      )
  
      monkeypatch.setattr(
          "huggingface_hub.hf_hub_download",
          lambda *args, **kwargs: config_file,
      )
      monkeypatch.setattr(
          "datasets.load_dataset",
          lambda *args, **kwargs: dataset.format_as("datasets"),
      )
  
      with pytest.warns(
          UserWarning, match="Found more than one user without ID"
      ):
          dataset_from_huggingface = FeedbackDataset.from_huggingface(
              repo_id="test-dataset"
          )
  
imports: import tempfile
  from typing import TYPE_CHECKING, List, Type, Union
  import argilla.client.singleton
  import datasets
  import pytest
  from argilla import User, Workspace
  from argilla.client.feedback.config import DatasetConfig
  from argilla.client.feedback.dataset import FeedbackDataset
  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
  from argilla.client.feedback.schemas.remote.records import RemoteSuggestionSchema
  from argilla.client.feedback.schemas.vector_settings import VectorSettings
  from argilla.client.feedback.training.schemas.base import TrainingTask
  from argilla.client.models import Framework
label_desc: Use image node_id 6 for calling a global function with example usage: test_push_to_huggingface_and_from_huggingface(mocked_client, monkeypatch, feedback_dataset_guidelines, feedback_dataset_fields, feedback_dataset_questions, feedback_dataset_records) without return types