Update app.py

app.py

@@ -425,33 +425,52 @@ def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, com
 
             def clean_key_val(v):
                 s = str(v).strip()
-                if s.endswith('.0'): s = s[:-2] 
+                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_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')]
+            # 1. 예전 코드로 롤백: 일단 매핑 데이터를 전부 다 가져옵니다. (DB 조건 오류 원천 차단)
+            q_fw = "SELECT * 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_fw, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
+            
+            q_rv = "SELECT * FROM Mapping_table WHERE TRIM(Comp_std)=? AND TRIM(Comp_ver)=? AND TRIM(Base_std)=? AND TRIM(Base_ver)=?"
+            df_rv = pd.read_sql(q_rv, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
+            conn_map.close()
+
+            # 2. 파이썬(Pandas)에서 Type을 정확하고 안전하게 필터링합니다.
+            cols_fw_lower = {c.lower(): c for c in df_fw.columns}
+            
+            if 'base_type' in cols_fw_lower and 'comp_type' in cols_fw_lower:
+                b_col = cols_fw_lower['base_type']
+                c_col = cols_fw_lower['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()])
+                # 정방향 필터
+                df_fw[b_col] = df_fw[b_col].fillna('Main').astype(str).str.strip().str.upper()
+                df_fw[c_col] = df_fw[c_col].fillna('Main').astype(str).str.strip().str.upper()
+                df_fw = df_fw[(df_fw[b_col] == type_b.strip().upper()) & (df_fw[c_col] == type_c.strip().upper())]
                 
-                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()])
+                # 역방향 필터 (DB의 Comp가 내 Base, DB의 Base가 내 Comp)
+                if not df_rv.empty:
+                    df_rv[b_col] = df_rv[b_col].fillna('Main').astype(str).str.strip().str.upper()
+                    df_rv[c_col] = df_rv[c_col].fillna('Main').astype(str).str.strip().str.upper()
+                    df_rv = df_rv[(df_rv[c_col] == type_b.strip().upper()) & (df_rv[b_col] == type_c.strip().upper())]
+
+            # 3. 필요한 컬럼만 추출해서 병합
+            b_sec = cols_fw_lower.get('base_section', 'Base_section')
+            c_sec = cols_fw_lower.get('comp_section', 'Comp_section')
+            
+            df_fw = df_fw[[b_sec, c_sec]].rename(columns={b_sec: 'Base_section', c_sec: 'Comp_section'})
+            if not df_rv.empty:
+                df_rv = df_rv[[b_sec, c_sec]].rename(columns={b_sec: 'Comp_section', c_sec: 'Base_section'})
             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()])
-                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(Base_std)=? AND TRIM(Base_ver)=?"
-                df_rv = pd.read_sql(q_rv, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
-            conn_map.close()
+                df_rv = pd.DataFrame(columns=['Base_section', 'Comp_section'])
 
             df_mapping = pd.concat([df_fw, df_rv], ignore_index=True)
+
             if not df_mapping.empty:
                 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(',')
@@ -463,7 +482,8 @@ def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, com
             else:
                 df_mapping = pd.DataFrame(columns=['Base_section', 'Comp_section'])
 
-            if base_std.strip().upper() == comp_std.strip().upper() and type_b == type_c:
+            # 4. 다른 법규/다른 테이블일 때는 강제 자동 매핑 금지 (이 원칙은 유지)
+            if base_std.strip().upper() == comp_std.strip().upper() and type_b.strip().upper() == type_c.strip().upper():
                 implicit = pd.DataFrame({'Base_section': list(set(df_base['merge_key']) & set(df_comp['merge_key'])), 
                                          'Comp_section': list(set(df_base['merge_key']) & set(df_comp['merge_key']))})
                 bridge = pd.concat([df_mapping, implicit], ignore_index=True).drop_duplicates()