Function test_is_dataframe_like

dask/dataframe/tests/test_utils_dataframe.py:530–587

(monkeypatch, frame_value_counts)

@pytest.mark.parametrize("frame_value_counts", [True, False])
def test_is_dataframe_like(monkeypatch, frame_value_counts):
    # When we drop support for pandas 1.0, this compat check can
    # be dropped
    if frame_value_counts:
        monkeypatch.setattr(pd.DataFrame, "value_counts", lambda x: None, raising=False)

    df = pd.DataFrame({"x": [1, 2, 3]})
    ddf = dd.from_pandas(df, npartitions=1)

    assert is_dataframe_like(df)
    assert is_dataframe_like(ddf)
    assert not is_dataframe_like(df.x)
    assert not is_dataframe_like(ddf.x)
    assert not is_dataframe_like(df.index)
    assert not is_dataframe_like(ddf.index)
    assert not is_dataframe_like(pd.DataFrame)

    assert not is_series_like(df)
    assert not is_series_like(ddf)
    assert is_series_like(df.x)
    assert is_series_like(ddf.x)
    assert not is_series_like(df.index)
    assert not is_series_like(ddf.index)
    assert not is_series_like(pd.Series)

    assert not is_index_like(df)
    assert not is_index_like(ddf)
    assert not is_index_like(df.x)
    assert not is_index_like(ddf.x)
    assert is_index_like(df.index)
    assert is_index_like(ddf.index)
    assert not is_index_like(pd.Index)

    # The following checks support of class wrappers, which
    # requires the comparisons of `x.__class__` instead of `type(x)`
    class DataFrameWrapper:
        __class__ = pd.DataFrame

    wrap = DataFrameWrapper()
    wrap.dtypes = None
    wrap.columns = None
    assert is_dataframe_like(wrap)

    class SeriesWrapper:
        __class__ = pd.Series

    wrap = SeriesWrapper()
    wrap.dtype = None
    wrap.name = None
    assert is_series_like(wrap)

    class IndexWrapper:
        __class__ = pd.Index

    wrap = IndexWrapper()
    wrap.dtype = None
    wrap.name = None
    assert is_index_like(wrap)