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from contextlib import suppress
import pytest
import zarr
import h5py
import pandas as pd
from anndata.compat import _clean_uns
from anndata._io.utils import report_read_key_on_error, AnnDataReadError
@pytest.mark.parametrize(
"group_fn",
[
pytest.param(lambda _: zarr.group(), id="zarr"),
pytest.param(lambda p: h5py.File(p / "test.h5", mode="a"), id="h5py"),
],
)
def test_key_error(tmp_path, group_fn):
@report_read_key_on_error
def read_attr(_):
raise NotImplementedError()
group = group_fn(tmp_path)
with group if hasattr(group, "__enter__") else suppress():
group["X"] = [1, 2, 3]
group.create_group("group")
with pytest.raises(AnnDataReadError) as e:
read_attr(group["X"])
assert "'/X'" in str(e.value)
with pytest.raises(AnnDataReadError) as e:
read_attr(group["group"])
assert "'/group'" in str(e.value)
def test_clean_uns():
d = dict(
uns=dict(species_categories=["a", "b"]),
obs=dict(species=pd.Series([0, 1, 0])),
var=dict(species=pd.Series([0, 1, 0, 2])),
)
_clean_uns(d)
assert "species_categories" not in d["uns"]
assert isinstance(d["obs"]["species"], pd.Categorical)
assert d["obs"]["species"].tolist() == ["a", "b", "a"]
# var’s categories were overwritten by obs’s,
# which we can detect here because var has too high codes
assert isinstance(d["var"]["species"], pd.Series)
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