Update app.py

app.py

@@ -423,18 +423,27 @@ def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, com
                 if ra not in df_comp.columns: 
                     return pd.DataFrame({"Error": [f"비교 열(Anchor) '{ra}'이(가) 비교 데이터에 존재하지 않습니다. Table_Config를 확인하세요."]})
 
-            df_base['merge_key'] = df_base[real_anchors_b].apply(lambda row: '-'.join(row.values.astype(str)), axis=1).astype(str).str.replace(" ", "")
-            df_comp['merge_key'] = df_comp[real_anchors_c].apply(lambda row: '-'.join(row.values.astype(str)), axis=1).astype(str).str.replace(" ", "")
+            def clean_key_val(v):
+                s = str(v).strip()
+                if s.endswith('.0'): s = s[:-2] 
+                return s.replace(" ", "")
+
+            df_base['merge_key'] = df_base[real_anchors_b].apply(lambda row: '-'.join([clean_key_val(x) for x in row]), axis=1)
+            df_comp['merge_key'] = df_comp[real_anchors_c].apply(lambda row: '-'.join([clean_key_val(x) for x in row]), axis=1)
 
             conn_map = sqlite3.connect(os.path.join(UPLOAD_DIR, "mapping.db"))
             map_cols = pd.read_sql("PRAGMA table_info(Mapping_table)", conn_map)['name'].tolist()
+            map_cols_lower = [c.lower() for c in map_cols]
             
-            if 'Base_Type' in map_cols and 'Comp_Type' in map_cols:
-                q = "SELECT Base_section, Comp_section FROM Mapping_table WHERE TRIM(Base_std)=? AND TRIM(Base_ver)=? AND TRIM(Base_Type)=? AND TRIM(Comp_std)=? AND TRIM(Comp_ver)=? AND TRIM(Comp_Type)=?"
-                df_fw = pd.read_sql(q, conn_map, params=[base_std.strip(), base_ver.strip(), type_b, comp_std.strip(), comp_ver.strip(), type_c])
+            if 'base_type' in map_cols_lower and 'comp_type' in map_cols_lower:
+                b_col = map_cols[map_cols_lower.index('base_type')]
+                c_col = map_cols[map_cols_lower.index('comp_type')]
+                
+                q = f"SELECT Base_section, Comp_section FROM Mapping_table WHERE TRIM(Base_std)=? AND TRIM(Base_ver)=? AND UPPER(TRIM(IFNULL([{b_col}], 'Main')))=UPPER(?) AND TRIM(Comp_std)=? AND TRIM(Comp_ver)=? AND UPPER(TRIM(IFNULL([{c_col}], 'Main')))=UPPER(?)"
+                df_fw = pd.read_sql(q, conn_map, params=[base_std.strip(), base_ver.strip(), type_b.strip(), comp_std.strip(), comp_ver.strip(), type_c.strip()])
                 
-                q_rv = "SELECT Comp_section AS Base_section, Base_section AS Comp_section FROM Mapping_table WHERE TRIM(Comp_std)=? AND TRIM(Comp_ver)=? AND TRIM(Comp_Type)=? AND TRIM(Base_std)=? AND TRIM(Base_ver)=? AND TRIM(Base_Type)=?"
-                df_rv = pd.read_sql(q_rv, conn_map, params=[base_std.strip(), base_ver.strip(), type_b, comp_std.strip(), comp_ver.strip(), type_c])
+                q_rv = f"SELECT Comp_section AS Base_section, Base_section AS Comp_section FROM Mapping_table WHERE TRIM(Comp_std)=? AND TRIM(Comp_ver)=? AND UPPER(TRIM(IFNULL([{c_col}], 'Main')))=UPPER(?) AND TRIM(Base_std)=? AND TRIM(Base_ver)=? AND UPPER(TRIM(IFNULL([{b_col}], 'Main')))=UPPER(?)"
+                df_rv = pd.read_sql(q_rv, conn_map, params=[base_std.strip(), base_ver.strip(), type_b.strip(), comp_std.strip(), comp_ver.strip(), type_c.strip()])
             else:
                 q = "SELECT Base_section, Comp_section FROM Mapping_table WHERE TRIM(Base_std)=? AND TRIM(Base_ver)=? AND TRIM(Comp_std)=? AND TRIM(Comp_ver)=?"
                 df_fw = pd.read_sql(q, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
@@ -447,7 +456,9 @@ def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, com
                 df_mapping['Base_section'] = df_mapping['Base_section'].astype(str).str.replace('\n', ',').str.split(',')
                 df_mapping['Comp_section'] = df_mapping['Comp_section'].astype(str).str.replace('\n', ',').str.split(',')
                 df_mapping = df_mapping.explode('Base_section').explode('Comp_section')
-                df_mapping[['Base_section', 'Comp_section']] = df_mapping[['Base_section', 'Comp_section']].astype(str).apply(lambda x: x.str.strip().str.replace(" ", ""))
+                
+                df_mapping['Base_section'] = df_mapping['Base_section'].apply(clean_key_val)
+                df_mapping['Comp_section'] = df_mapping['Comp_section'].apply(clean_key_val)
                 df_mapping = df_mapping.dropna().drop_duplicates()
             else:
                 df_mapping = pd.DataFrame(columns=['Base_section', 'Comp_section'])