Add missing requests dependency

leakpro/synthetic_data_attacks/anomalies.py

@@ -11,7 +11,7 @@ def encode_categorical_columns(*, df: pd.DataFrame, threshold_one_hot_encoding:
     df_encoded = df.copy()
     # Iterate through each column in the DataFrame
     for column in df_encoded.columns:
-        if df_encoded[column].dtype == "object":
+        if pd.api.types.is_string_dtype(df_encoded[column]):
             unique_values = df_encoded[column].nunique()
             if unique_values <= threshold_one_hot_encoding:
                 # Perform one-hot encoding

leakpro/tests/tests_synthetic_data_attacks/test_anomalies.py

@@ -12,7 +12,11 @@
 
 def test_encode_categorical_columns() -> None:
     """Assert results for encode_categorical_columns function with simple input."""
-    assert list(df.dtypes) == [np.dtype("int64"), np.dtype("bool"), np.dtype("O"), np.dtype("O")]
+    # Check dtypes - newer pandas may use StringDtype instead of object
+    assert df["non_cat"].dtype == np.dtype("int64")
+    assert df["cat_bool"].dtype == np.dtype("bool")
+    assert pd.api.types.is_string_dtype(df["cat_less_threshold"])
+    assert pd.api.types.is_string_dtype(df["cat_more_threshold"])
     df_encoded = anom.encode_categorical_columns(df=df)
     assert list(df_encoded.columns) == ["non_cat", "cat_bool", "cat_more_threshold", "cat_less_threshold_True"]
     assert df_encoded[["non_cat", "cat_bool"]].equals(df[["non_cat", "cat_bool"]])

pyproject.toml

@@ -48,6 +48,7 @@ dev = [
   "kornia", # from minv
   "albumentations", # federated example
   "transformers", # federated example
+  "requests", 
 ]
 
 [tool.setuptools]