diff --git a/machine_learning/sequential_minimum_optimization.py b/machine_learning/sequential_minimum_optimization.py
index 625fc28fe60c..975a0172363d 100644
--- a/machine_learning/sequential_minimum_optimization.py
+++ b/machine_learning/sequential_minimum_optimization.py
@@ -451,7 +451,7 @@ def test_cancer_data():
     print("Hello!\nStart test SVM using the SMO algorithm!")
     # 0: download dataset and load into pandas' dataframe
     if not os.path.exists(r"cancer_data.csv"):
-        request = urllib.request.Request(  # noqa: S310
+        request = urllib.request.Request(  # noqa: S310, RUF100
             CANCER_DATASET_URL,
             headers={"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)"},
         )
diff --git a/sorts/radix_sort.py b/sorts/radix_sort.py
index 1dbf5fbd1365..47c5dd8720e3 100644
--- a/sorts/radix_sort.py
+++ b/sorts/radix_sort.py
@@ -21,7 +21,17 @@ def radix_sort(list_of_ints: list[int]) -> list[int]:
     True
     >>> radix_sort([1,100,10,1000]) == sorted([1,100,10,1000])
     True
+    >>> radix_sort([-1, 2, 3])
+    Traceback (most recent call last):
+    ...
+    ValueError: All elements in list_of_ints must be non-negative integers
     """
+    if not list_of_ints:
+        return []
+
+    if any(i < 0 for i in list_of_ints):
+        raise ValueError("All elements in list_of_ints must be non-negative integers")
+
     placement = 1
     max_digit = max(list_of_ints)
     while placement <= max_digit: