From 400cf12597142ac37b1aa5bcd9bd5b3352305c8f Mon Sep 17 00:00:00 2001
From: Alexander Beedie <alexander-beedie@users.noreply.github.com>
Date: Fri, 29 Sep 2023 12:48:47 +0400
Subject: [PATCH] fix(rust,python): Fix edge-case where the Array dtype could
 (internally) be considered numeric (#11398)

Co-authored-by: Stijn de Gooijer <stijn@degooijer.io>
---
 crates/polars-core/src/datatypes/dtype.rs    | 36 +++++++-------------
 py-polars/tests/unit/datatypes/test_array.py | 13 +++++++
 py-polars/tests/unit/test_interop.py         | 21 ++++++++----
 3 files changed, 40 insertions(+), 30 deletions(-)

diff --git a/crates/polars-core/src/datatypes/dtype.rs b/crates/polars-core/src/datatypes/dtype.rs
index 6043fa31504e..9866cb9456b7 100644
--- a/crates/polars-core/src/datatypes/dtype.rs
+++ b/crates/polars-core/src/datatypes/dtype.rs
@@ -163,29 +163,19 @@ impl DataType {
 
     /// Check if this [`DataType`] is a numeric type.
     pub fn is_numeric(&self) -> bool {
-        // allow because it cannot be replaced when object feature is activated
-        #[allow(clippy::match_like_matches_macro)]
-        match self {
-            DataType::Utf8
-            | DataType::List(_)
-            | DataType::Date
-            | DataType::Datetime(_, _)
-            | DataType::Duration(_)
-            | DataType::Time
-            | DataType::Boolean
-            | DataType::Unknown
-            | DataType::Null => false,
-            DataType::Binary => false,
-            #[cfg(feature = "object")]
-            DataType::Object(_) => false,
-            #[cfg(feature = "dtype-categorical")]
-            DataType::Categorical(_) => false,
-            #[cfg(feature = "dtype-struct")]
-            DataType::Struct(_) => false,
-            #[cfg(feature = "dtype-decimal")]
-            DataType::Decimal(_, _) => false,
-            _ => true,
-        }
+        matches!(
+            self,
+            DataType::UInt8
+                | DataType::UInt16
+                | DataType::UInt32
+                | DataType::UInt64
+                | DataType::Int8
+                | DataType::Int16
+                | DataType::Int32
+                | DataType::Int64
+                | DataType::Float32
+                | DataType::Float64
+        )
     }
 
     pub fn is_float(&self) -> bool {
diff --git a/py-polars/tests/unit/datatypes/test_array.py b/py-polars/tests/unit/datatypes/test_array.py
index 2eb2fedde73c..748ab37e261a 100644
--- a/py-polars/tests/unit/datatypes/test_array.py
+++ b/py-polars/tests/unit/datatypes/test_array.py
@@ -1,6 +1,7 @@
 import pytest
 
 import polars as pl
+from polars.exceptions import InvalidOperationError
 from polars.testing import assert_series_equal
 
 
@@ -79,6 +80,18 @@ def test_array_in_group_by() -> None:
         assert out.to_dict(False) == {"g": [1, 2], "a": [[[1, 2], [2, 2]], [[1, 4]]]}
 
 
+def test_array_invalid_operation() -> None:
+    s = pl.Series(
+        [[1, 2], [8, 9]],
+        dtype=pl.Array(width=2, inner=pl.Int32),
+    )
+    with pytest.raises(
+        InvalidOperationError,
+        match=r"`sign` operation not supported for dtype `array\[",
+    ):
+        s.sign()
+
+
 def test_array_concat() -> None:
     a_df = pl.DataFrame({"a": [[0, 1], [1, 0]]}).select(
         pl.col("a").cast(pl.Array(width=2, inner=pl.Int32))
diff --git a/py-polars/tests/unit/test_interop.py b/py-polars/tests/unit/test_interop.py
index f47da7d46f57..d3981cc8528a 100644
--- a/py-polars/tests/unit/test_interop.py
+++ b/py-polars/tests/unit/test_interop.py
@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import warnings
 from datetime import date, datetime, time
 from typing import Any, cast
 
@@ -121,13 +120,21 @@ def test_from_pandas() -> None:
     for col, dtype in overrides.items():
         assert out.schema[col] == dtype
 
-    # empty and/or all null values, no pandas dtype
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", Warning)
 
-        for nulls in ([], [None], [None, None], [None, None, None]):
-            srs = pl.from_pandas(pd.Series(nulls))
-            assert nulls == srs.to_list()
+@pytest.mark.parametrize(
+    "nulls",
+    [
+        [],
+        [None],
+        [None, None],
+        [None, None, None],
+    ],
+)
+def test_from_pandas_nulls(nulls: list[None]) -> None:
+    # empty and/or all null values, no pandas dtype
+    ps = pd.Series(nulls)
+    s = pl.from_pandas(ps)
+    assert nulls == s.to_list()
 
 
 def test_from_pandas_nan_to_null() -> None: