fix(setup): restore security stamp filtering

code/file_setup/setup_utils.py

@@ -194,13 +194,36 @@ def filter_dataframe(df: pd.DataFrame, banned_cards: List[str]) -> pd.DataFrame:
         filtered_df = df.copy()
         filter_config: FilterConfig = FILTER_CONFIG  # Type hint for configuration
         for field, rules in filter_config.items():
+            if field not in filtered_df.columns:
+                logger.warning('Skipping filter for missing field %s', field)
+                continue
+
             for rule_type, values in rules.items():
+                if not values:
+                    continue
+
                 if rule_type == 'exclude':
                     for value in values:
-                        filtered_df = filtered_df[~filtered_df[field].str.contains(value, na=False)]
+                        mask = filtered_df[field].astype(str).str.contains(
+                            value,
+                            case=False,
+                            na=False,
+                            regex=False
+                        )
+                        filtered_df = filtered_df[~mask]
                 elif rule_type == 'require':
                     for value in values:
-                        filtered_df = filtered_df[filtered_df[field].str.contains(value, na=False)]
+                        mask = filtered_df[field].astype(str).str.contains(
+                            value,
+                            case=False,
+                            na=False,
+                            regex=False
+                        )
+                        filtered_df = filtered_df[mask]
+                else:
+                    logger.warning('Unknown filter rule type %s for field %s', rule_type, field)
+                    continue
+
                 logger.debug(f'Applied {rule_type} filter for {field}: {values}')
         
         # Remove illegal sets

code/tests/test_setup_filters.py

@@ -0,0 +1,40 @@
+import pandas as pd
+
+from file_setup.setup_utils import filter_dataframe
+
+
+def _record(name: str, security_stamp: str) -> dict[str, object]:
+    return {
+        "name": name,
+        "faceName": name,
+        "edhrecRank": 100,
+        "colorIdentity": "G",
+        "colors": "G",
+        "manaCost": "{G}",
+        "manaValue": 1,
+        "type": "Creature",
+        "layout": "normal",
+        "text": "",
+        "power": "1",
+        "toughness": "1",
+        "keywords": "",
+        "side": "a",
+        "availability": "paper,arena",
+        "promoTypes": "",
+        "securityStamp": security_stamp,
+        "printings": "RNA",
+    }
+
+
+def test_filter_dataframe_removes_acorn_and_heart_security_stamps() -> None:
+    df = pd.DataFrame(
+        [
+            _record("Acorn Card", "Acorn"),
+            _record("Heart Card", "heart"),
+            _record("Legal Card", ""),
+        ]
+    )
+
+    filtered = filter_dataframe(df, banned_cards=[])
+
+    assert list(filtered["name"]) == ["Legal Card"]