fix: refactor column selection logic for Polars

docs/blog/polars-styling/index.qmd

@@ -198,12 +198,12 @@ gt_with_spanners = (
 
     # Table column spanners ----
     .tab_spanner(
-        label = "Time",
-        columns = time_cols
+        label="Time",
+        columns=time_cols
     )
     .tab_spanner(
-        label = "Measurement",
-        columns = cs.all().exclude(time_cols)
+        label="Measurement",
+        columns=cs.exclude(time_cols)
     )
 )
 

docs/blog/superbowl-squares/_code.py

@@ -45,7 +45,7 @@ def team_final_digits(game: pl.DataFrame, team_code: str) -> pl.DataFrame:
     .with_columns(joint=pl.col("prop") * pl.col("prop_right"))
     .sort("final_digit", "final_digit_right")
     .pivot(values="joint", columns="final_digit_right", index="final_digit")
-    .with_columns((cs.all().exclude("final_digit") * 100).round(1))
+    .with_columns((cs.exclude("final_digit") * 100).round(1))
 )
 
 # Display -----

docs/get-started/basic-styling.qmd

@@ -222,7 +222,7 @@ import polars.selectors as cs
 gt_pl_air.tab_style(
     style=style.fill(color="yellow"),
     locations=loc.body(
-        columns=cs.all().exclude(["Month", "Day"]),
+        columns=cs.exclude(["Month", "Day"]),
         rows=pl.col("Temp") == pl.col("Temp").max()
     )
 )

great_tables/_tbl_data.py

@@ -307,26 +307,47 @@ def _(
 def _(data: PlDataFrame, expr: Union[list[str], _selector_proxy_], strict: bool = True) -> _NamePos:
     # TODO: how to annotate type of a polars selector?
     # Seems to be polars.selectors._selector_proxy_.
+    import polars.selectors as cs
+
+    from functools import reduce
+    from operator import or_
     from polars import Expr
-    from polars import selectors
 
     if isinstance(expr, (str, int)):
         expr = [expr]
 
+    if isinstance(expr, list):
+        all_selectors = [
+            cs.by_name(x) if isinstance(x, str) else cs.by_index(x) if isinstance(x, int) else x
+            for x in expr
+        ]
+
+        _validate_selector_list(all_selectors)
+
+        expr = reduce(or_, all_selectors, cs.by_name())
+
     col_pos = {k: ii for ii, k in enumerate(data.columns)}
 
     # just in case _selector_proxy_ gets renamed or something
     # it inherits from Expr, so we can just use that in a pinch
-    cls_selector = getattr(selectors, "_selector_proxy_", Expr)
+    cls_selector = getattr(cs, "_selector_proxy_", Expr)
 
-    if not isinstance(expr, (list, cls_selector)):
+    if not isinstance(expr, cls_selector):
         raise TypeError(f"Unsupported selection expr type: {type(expr)}")
 
     # I don't think there's a way to get the columns w/o running the selection
-    final_columns = selectors.expand_selector(data, expr)
+    final_columns = cs.expand_selector(data, expr)
     return [(col, col_pos[col]) for col in final_columns]
 
 
+def _validate_selector_list(selectors: list):
+    from polars.selectors import is_selector
+
+    for ii, sel in enumerate(selectors):
+        if not is_selector(sel):
+            raise TypeError(f"Expected a list of selectors, but entry {ii} is type: {type(sel)}.")
+
+
 def _eval_select_from_list(
     columns: list[str], expr: list[Union[str, int]]
 ) -> list[tuple[str, int]]:

tests/test_formats.py

@@ -79,7 +79,7 @@ def test_format_repr_snap(snapshot):
     assert_repr_html(snapshot, new_gt)
 
 
-@pytest.mark.parametrize("expr", [[0, -1], pl.selectors.all().exclude("y")])
+@pytest.mark.parametrize("expr", [[0, -1], pl.selectors.exclude("y")])
 def test_format_col_selection_multi(expr: Any):
     df = pd.DataFrame({"x": [1], "y": [2], "z": [3]})
 

tests/test_tbl_data.py

@@ -70,14 +70,61 @@ def test_reorder(df: DataFrameLike):
     assert_frame_equal(res, dst)
 
 
-@pytest.mark.parametrize(
-    "expr", [["col2", "col1"], [1, 0], ["col2", 0], pl.selectors.all().exclude("col3")]
-)
+@pytest.mark.parametrize("expr", [["col2", "col1"], [1, 0], ["col2", 0], [1, "col1"]])
 def test_eval_select_with_list(df: DataFrameLike, expr):
-    sel = eval_select(df, ["col2", "col1"])
+    sel = eval_select(df, expr)
     assert sel == [("col2", 1), ("col1", 0)]
 
 
+@pytest.mark.parametrize(
+    "expr",
+    [
+        pl.selectors.exclude("col3"),
+        pl.selectors.starts_with("col1") | pl.selectors.starts_with("col2"),
+    ],
+)
+def test_eval_select_with_list_pl_selector(expr):
+    df = pl.DataFrame({"col1": [1, 2, 3], "col2": ["a", "b", "c"], "col3": [4.0, 5.0, 6.0]})
+    sel = eval_select(df, expr)
+    assert sel == [("col1", 0), ("col2", 1)]
+
+
+@pytest.mark.parametrize("expr", [["col2", 1.2]])
+def test_eval_select_pandas_raises1(expr):
+    df = pd.DataFrame({"col1": [1, 2, 3], "col2": ["a", "b", "c"], "col3": [4.0, 5.0, 6.0]})
+    with pytest.raises(TypeError) as exc_info:
+        eval_select(df, expr)
+
+    assert "Only int and str are supported." in str(exc_info.value.args[0])
+
+
+@pytest.mark.parametrize("expr", [3.45, {"col2"}, ("col2",)])
+def test_eval_select_pandas_raises2(expr):
+    df = pd.DataFrame({"col1": [1, 2, 3], "col2": ["a", "b", "c"], "col3": [4.0, 5.0, 6.0]})
+    with pytest.raises(NotImplementedError) as exc_info:
+        eval_select(df, expr)
+
+    assert "Unsupported selection expr: " in str(exc_info.value.args[0])
+
+
+@pytest.mark.parametrize("expr", [3.45, {6}, (7.8,)])
+def test_eval_select_polars_raises(expr):
+    df = pl.DataFrame({"col1": [1, 2, 3], "col2": ["a", "b", "c"], "col3": [4.0, 5.0, 6.0]})
+    with pytest.raises(TypeError) as exc_info:
+        eval_select(df, expr)
+
+    assert "Unsupported selection expr type:" in str(exc_info.value.args[0])
+
+
+def test_eval_selector_polars_list_raises():
+    expr = ["col1", 1.2]
+    df = pl.DataFrame({"col1": [], "col2": [], "col3": []})
+    with pytest.raises(TypeError) as exc_info:
+        eval_select(df, expr)
+
+    assert "entry 1 is type: <class 'float'>" in str(exc_info.value.args[0])
+
+
 def test_create_empty_frame(df: DataFrameLike):
     res = create_empty_frame(df)
     col = [None] * 3