code: def test_huggingface_formatter_to_namespace_overview(
      get_content_mock,
  ):
      get_content_mock.return_value = "{}"
      namespace1 = "huggingface"
      datasets = [
          _create_dataset_package(namespace1, "ds1"),
          _create_dataset_package(namespace1, "ds2"),
      ]
      templates = _create_templates(
          dataset_details_template="{tfds_id}"
      )
      get_content_mock.return_value = "{}"
      formatter = build_community_catalog.HuggingfaceFormatter(
          namespace=namespace1,
          datasets=datasets,
          templates=templates,
          options=_create_options(),
      )
      assert (
          formatter.to_namespace_overview()
          == """\
  # Huggingface datasets
  
  Huggingface has forked TFDS and provides a lot of text datasets. See
  [here](https://huggingface.co/docs/datasets/) for more documentation.
  Next you can find the list of all the datasets that can be used with TFDS.
  
  
  *  [ds1](huggingface/ds1.md)
  *  [ds2](huggingface/ds2.md)
  """
      )
  
file_path: datasets/tensorflow_datasets/scripts/documentation/build_community_catalog_test.py
imports: from unittest import mock
  from etils import epath
  import tensorflow_datasets
  from tensorflow_datasets.core import naming
  from tensorflow_datasets.scripts.documentation import build_community_catalog
label_desc: Use image node_id 10 for calling a global function with example usage: test_huggingface_formatter_to_namespace_overview(get_content_mock) without return types