test(sclass): dataframe.py auf 100% Coverage (+ parquet-Extra)

ci/local-ci.sh

@@ -28,7 +28,7 @@ fi
 
 echo "[ci] installiere/aktualisiere Abhängigkeiten (sdata[did] + Test-Tools)"
 "$PYBIN" -m pip install --quiet --upgrade pip
-"$PYBIN" -m pip install --quiet -e ".[did]" pytest coverage
+"$PYBIN" -m pip install --quiet -e ".[did,parquet]" pytest coverage
 
 # Testziel: durchgereichte Argumente oder – wenn keine – die komplette Suite.
 TARGETS=("$@")

setup.py

@@ -21,6 +21,7 @@
     'did': ['ecdsa>=0.18', 'base58>=2.1'],
     'hdf': ['tables'],
     'sql': ['sqlalchemy'],
+    'parquet': ['pyarrow'],   # sdata.sclass.DataFrame (Parquet-Serialisierung)
 }
 
 setup(

tests/test_sclass_dataframe_coverage.py

@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+"""Vollständige Abdeckung von sdata/sclass/dataframe.py."""
+import pandas as pd
+import pytest
+
+pytest.importorskip("pyarrow")          # Parquet-Backend
+
+from sdata.metadata import Metadata
+from sdata.sclass.dataframe import DataFrame
+
+
+def _df():
+    return pd.DataFrame({"weight": [10, 20, 30], "height": [1.5, 1.6, 1.7]})
+
+
+def test_init_variants():
+    cm = {"weight": {"label": "Gewicht", "unit": "kg"}}
+    a = DataFrame(df=_df(), column_metadata=cm, name="A")
+    assert isinstance(a.cmd, Metadata)
+    assert not a.cmdf.empty
+    # column_metadata als Metadata
+    b = DataFrame(df=_df(), column_metadata=a.cmd, name="B")
+    assert isinstance(b.column_metadata, Metadata)
+    # ungültiges column_metadata -> Warnung
+    c = DataFrame(df=_df(), column_metadata=123, name="C")
+    assert isinstance(c.column_metadata, Metadata)
+    # df=None
+    d = DataFrame(df=None, name="D")
+    assert d.df.empty
+
+
+def test_df_setter_index_name_and_columns():
+    sdf = DataFrame(name="x")
+    sdf.df = _df()
+    assert sdf.df.index.name == "index"
+    assert sdf.column_metadata.get("weight") is not None
+
+
+def test_to_from_dict_roundtrip():
+    sdf = DataFrame(df=_df(), name="rt", description="desc")
+    d = sdf.to_dict()
+    assert "parquet_bytes" in d["data"] and "column_metadata" in d["data"]
+    r = DataFrame.from_dict(d)
+    assert list(r.df.columns) == ["weight", "height"]
+
+
+def test_to_dataframe_attrs():
+    sdf = DataFrame(df=_df(), name="att", description="d")
+    out = sdf.to_dataframe()
+    assert "!sdata" in out.attrs
+
+
+def test_to_parquet_bytes_and_from_bytes():
+    sdf = DataFrame(df=_df(), name="pq")
+    raw = sdf.to_parquet()                      # ohne path -> bytes
+    assert isinstance(raw, (bytes, bytearray))
+    back = DataFrame.from_parquet_bytes(raw)    # attrs nicht erhalten -> except-Zweige
+    assert list(back.df.columns) == ["weight", "height"]
+
+
+def test_to_parquet_file_and_from_parquet(tmp_path):
+    sdf = DataFrame(df=_df(), name="onfile")
+    fp = sdf.to_parquet(path=str(tmp_path))     # schreibt <sname>.spq
+    assert fp.endswith(".spq")
+    loaded = DataFrame.from_parquet(fp)
+    assert list(loaded.df.columns) == ["weight", "height"]
+    # nicht existierende Datei -> Exception
+    with pytest.raises(Exception):
+        DataFrame.from_parquet(str(tmp_path / "nope.spq"))
+
+
+def test_from_parquet_bytes_without_sdata_attrs():
+    raw = _df().to_parquet()                    # plain, keine _sdata-attrs
+    back = DataFrame.from_parquet_bytes(raw)    # attrs None -> except-Zweige
+    assert list(back.df.columns) == ["weight", "height"]
+
+
+def test_from_parquet_without_sdata_attrs(tmp_path):
+    fp = str(tmp_path / "plain.spq")
+    _df().to_parquet(fp)
+    loaded = DataFrame.from_parquet(fp)         # attrs None -> except-Zweige
+    assert list(loaded.df.columns) == ["weight", "height"]