Update app.py

app.py

@@ -42,7 +42,6 @@ def decode_sqlite_text(x):
 def fetch_available_standards():
     global db_registry
     db_registry = []
-
     for file_name in os.listdir(UPLOAD_DIR):
         if file_name.endswith(".db"):
             name = file_name.replace(".db", "")
@@ -53,19 +52,14 @@ def fetch_available_standards():
                     "standard": parts[0],
                     "version": parts[1]
                 })
-
     return sorted(list(set([d["standard"] for d in db_registry])))
 
-# ==========================================
-# 💡 [스마트 설정 탐색 기능이 탑재된 데이터 로더]
-# ==========================================
 def fetch_database_records(std, ver, cat, table_type):
     try:
         db_path = os.path.join(UPLOAD_DIR, f"{std}_{ver}.db")
         conn = sqlite3.connect(db_path)
         conn.text_factory = decode_sqlite_text
         
-        # 1. 실제 DB 테이블과 열(Column) 이름을 먼저 훑어봅니다.
         tables = pd.read_sql("SELECT name FROM sqlite_master WHERE type='table';", conn)['name'].tolist()
         valid_tables = [t for t in tables if t.lower() not in ['mapping_registry', 'mapping_table', 'table_config', 'sqlite_sequence']]
         main_table = f"{std}_{ver}"
@@ -79,7 +73,6 @@ def fetch_database_records(std, ver, cat, table_type):
         cols = pd.read_sql(f"PRAGMA table_info([{main_table}])", conn)['name'].tolist()
         lower_cols = [c.lower() for c in cols]
         
-        # 2. Table_Config를 읽어옵니다.
         conn_map = sqlite3.connect(os.path.join(UPLOAD_DIR, "mapping.db"))
         config_df = pd.read_sql("SELECT * FROM Table_Config WHERE TRIM(Table_Type)=?", conn_map, params=[table_type.strip()])
         conn_map.close()
@@ -87,7 +80,6 @@ def fetch_database_records(std, ver, cat, table_type):
         if config_df.empty:
             return pd.DataFrame({"Error": [f"Table_Config에서 '{table_type}' 설정을 찾을 수 없습니다."]}), []
             
-        # 💡 [핵심 해결] Table_Config에 'Main'이 여러 개일 경우, 실제 DB 열 이름과 일치하는 것을 똑똑하게 찾아냅니다!
         matched_config = None
         for _, row in config_df.iterrows():
             anchors_test = [x.strip().lower() for x in str(row['Anchor_Column']).split(',')]
@@ -96,15 +88,14 @@ def fetch_database_records(std, ver, cat, table_type):
                 break
                 
         if matched_config is None:
-            matched_config = config_df.iloc[0] # 못 찾으면 어쩔 수 없이 첫 번째 강제 사용
+            matched_config = config_df.iloc[0]
             
         anchors = [x.strip() for x in matched_config['Anchor_Column'].split(',')]
         displays = [x.strip() for x in matched_config['Display_Columns'].split(',')] if pd.notna(matched_config['Display_Columns']) else anchors
         
-        # 3. 쿼리 실행 및 카테고리 필터링
         query = f"SELECT * FROM [{main_table}]"
-        
         conditions = []
+        
         if cat and cat != "ALL":
             if "." in cat and 'chapter' in lower_cols and 'category' in lower_cols:
                 ch, ca = cat.split(".", 1)
@@ -121,7 +112,6 @@ def fetch_database_records(std, ver, cat, table_type):
         df = pd.read_sql(query, conn)
         conn.close()
         
-        # 4. 화면에 보여줄 열 정리
         final_cols = []
         for d in displays:
             for c in df.columns:
@@ -179,7 +169,7 @@ def generate_html_diff(text1, text2):
         return text1, text2
 
 # ==========================================
-# 2. UI Component Handlers
+# 2. UI Component Handlers (스마트 드롭다운 적용)
 # ==========================================
 def load_initial_standards():
     return gr.Dropdown(choices=fetch_available_standards())
@@ -187,8 +177,11 @@ def load_initial_standards():
 def update_version_dropdown(standard):
     if not standard:
         return gr.Dropdown(choices=[])
-    versions = sorted(set(d["version"] for d in db_registry if d["standard"] == standard))
-    return gr.Dropdown(choices=versions)
+    versions = []
+    for file_name in os.listdir(UPLOAD_DIR):
+        if file_name.startswith(standard + "_") and file_name.endswith(".db"):
+            versions.append(file_name.replace(standard + "_", "").replace(".db", ""))
+    return gr.Dropdown(choices=sorted(list(set(versions))))
 
 def update_base_category_dropdown(standard, version):
     if not standard or not version:
@@ -196,8 +189,8 @@ def update_base_category_dropdown(standard, version):
 
     choices = ["ALL"]
     status_value = ""
-    
     db_path = os.path.join(UPLOAD_DIR, f"{standard}_{version}.db")
+    
     if not os.path.exists(db_path): 
         return gr.update(choices=choices), gr.update(value="")
 
@@ -258,15 +251,29 @@ def update_comp_standard_dropdown(base_std, base_ver):
         conn.close()
 
         mapped_stds = sorted(df['Comp_std'].dropna().unique().tolist()) if not df.empty else []
+        
+        # 💡 [핵심] 자기 자신(같은 법규)은 레지스트리에 없어도 항상 고를 수 있게 무조건 추가!
+        if base_std not in mapped_stds:
+            mapped_stds.append(base_std)
+            mapped_stds.sort()
+            
         return gr.update(choices=mapped_stds, value=None, interactive=bool(mapped_stds))
     except Exception:
-        return gr.update(choices=[], value=None, interactive=False)
+        return gr.update(choices=[base_std], value=None, interactive=True)
 
 def update_comp_version_dropdown(base_std, base_ver, comp_std):
     if not all([base_std, base_ver, comp_std]):
         return gr.update(choices=[], value=None, interactive=False)
 
     try:
+        # 💡 [핵심] 같은 법규면 로컬 파일 목록에서 전체 버전을 직접 불러옵니다.
+        if base_std.strip() == comp_std.strip():
+            versions = []
+            for file_name in os.listdir(UPLOAD_DIR):
+                if file_name.startswith(comp_std + "_") and file_name.endswith(".db"):
+                    versions.append(file_name.replace(comp_std + "_", "").replace(".db", ""))
+            return gr.update(choices=sorted(list(set(versions))), value=None, interactive=True)
+
         conn = sqlite3.connect(os.path.join(UPLOAD_DIR, "mapping.db"))
         query = "SELECT DISTINCT TRIM(Comp_ver) AS Comp_ver FROM Mapping_registry WHERE TRIM(Base_std)=TRIM(?) AND TRIM(Base_ver)=TRIM(?) AND TRIM(Comp_std)=TRIM(?)"
         df = pd.read_sql(query, conn, params=[base_std, base_ver, comp_std])
@@ -283,9 +290,10 @@ def update_comp_category_dropdown(base_std, base_ver, base_cat, comp_std, comp_v
 
     base_type = "Main" if not base_cat or base_cat == "ALL" or "." in base_cat else base_cat
     status_value = ""
+    comp_db_path = os.path.join(UPLOAD_DIR, f"{comp_std}_{comp_ver}.db")
+    c_main_table = None
 
     try:
-        comp_db_path = os.path.join(UPLOAD_DIR, f"{comp_std}_{comp_ver}.db")
         if os.path.exists(comp_db_path):
             c_conn = sqlite3.connect(comp_db_path)
             c_tables = pd.read_sql("SELECT name FROM sqlite_master WHERE type='table';", c_conn)['name'].tolist()
@@ -303,16 +311,42 @@ def update_comp_category_dropdown(base_std, base_ver, base_cat, comp_std, comp_v
                             status_value = str(status_df.iloc[0]['Status'])
                 except Exception:
                     pass
+            c_conn.close()
+
+        # 💡 [핵심] 같은 법규인 경우 카테고리도 스스로 스캔해서 띄워줍니다.
+        if base_std.strip() == comp_std.strip():
+            final_choices = ["ALL"]
+            if os.path.exists(comp_db_path) and c_main_table:
+                c_conn = sqlite3.connect(comp_db_path)
+                cols = pd.read_sql(f"PRAGMA table_info([{c_main_table}])", c_conn)['name'].tolist()
+                lower_cols = [c.lower() for c in cols]
+                if 'chapter' in lower_cols and 'category' in lower_cols:
+                    ch_col = cols[lower_cols.index('chapter')]
+                    ca_col = cols[lower_cols.index('category')]
+                    c_df = pd.read_sql(f"SELECT DISTINCT [{ch_col}], [{ca_col}] FROM [{c_main_table}]", c_conn)
+                    for _, row in c_df.iterrows():
+                        ch = str(row[ch_col]).strip()
+                        ca = str(row[ca_col]).strip()
+                        if ch and ca and ch.lower() not in ['none', 'nan'] and ca.lower() not in ['none', 'nan']:
+                            final_choices.append(f"{ch}.{ca}")
+                
+                pattern = re.compile(f"^{comp_std}[_\\s-]*{comp_ver}[_\\s-]*", re.IGNORECASE)
+                for t in c_valid_tables:
+                    if t == c_main_table: continue
+                    short_name = pattern.sub("", t).strip(" _")
+                    if short_name and short_name not in final_choices:
+                        final_choices.append(short_name)
+                    elif t not in final_choices:
+                        final_choices.append(t)
+                c_conn.close()
+            return gr.update(choices=final_choices, value=final_choices[0] if final_choices else None, interactive=True), gr.update(value=status_value)
 
+        # 기존 레지스트리 로직
         conn = sqlite3.connect(os.path.join(UPLOAD_DIR, "mapping.db"))
         query = """
         SELECT DISTINCT TRIM(Comp_Type) AS Comp_Type 
         FROM Mapping_registry 
-        WHERE TRIM(Base_std)=TRIM(?) 
-          AND TRIM(Base_ver)=TRIM(?) 
-          AND TRIM(Base_Type)=TRIM(?) 
-          AND TRIM(Comp_std)=TRIM(?) 
-          AND TRIM(Comp_ver)=TRIM(?)
+        WHERE TRIM(Base_std)=TRIM(?) AND TRIM(Base_ver)=TRIM(?) AND TRIM(Base_Type)=TRIM(?) AND TRIM(Comp_std)=TRIM(?) AND TRIM(Comp_ver)=TRIM(?)
         """
         df = pd.read_sql(query, conn, params=[base_std, base_ver, base_type, comp_std, comp_ver])
         conn.close()
@@ -324,21 +358,19 @@ def update_comp_category_dropdown(base_std, base_ver, base_cat, comp_std, comp_v
         final_choices = []
         if "Main" in allowed_types:
             final_choices.append("ALL")
-            if os.path.exists(comp_db_path):
+            if os.path.exists(comp_db_path) and c_main_table:
                 c_conn = sqlite3.connect(comp_db_path)
-                if c_main_table:
-                    cols = pd.read_sql(f"PRAGMA table_info([{c_main_table}])", c_conn)['name'].tolist()
-                    lower_cols = [c.lower() for c in cols]
-                    if 'chapter' in lower_cols and 'category' in lower_cols:
-                        ch_col = cols[lower_cols.index('chapter')]
-                        ca_col = cols[lower_cols.index('category')]
-                        
-                        c_df = pd.read_sql(f"SELECT DISTINCT [{ch_col}], [{ca_col}] FROM [{c_main_table}]", c_conn)
-                        for _, row in c_df.iterrows():
-                            ch = str(row[ch_col]).strip()
-                            ca = str(row[ca_col]).strip()
-                            if ch and ca and ch.lower() not in ['none', 'nan'] and ca.lower() not in ['none', 'nan']:
-                                final_choices.append(f"{ch}.{ca}")
+                cols = pd.read_sql(f"PRAGMA table_info([{c_main_table}])", c_conn)['name'].tolist()
+                lower_cols = [c.lower() for c in cols]
+                if 'chapter' in lower_cols and 'category' in lower_cols:
+                    ch_col = cols[lower_cols.index('chapter')]
+                    ca_col = cols[lower_cols.index('category')]
+                    c_df = pd.read_sql(f"SELECT DISTINCT [{ch_col}], [{ca_col}] FROM [{c_main_table}]", c_conn)
+                    for _, row in c_df.iterrows():
+                        ch = str(row[ch_col]).strip()
+                        ca = str(row[ca_col]).strip()
+                        if ch and ca and ch.lower() not in ['none', 'nan'] and ca.lower() not in ['none', 'nan']:
+                            final_choices.append(f"{ch}.{ca}")
                 c_conn.close()
         
         for t in allowed_types:
@@ -356,7 +388,7 @@ def reset_comp_selections():
     return gr.update(value=None), gr.update(choices=[], value=None), gr.update(choices=[], value=None), gr.update(value="")
 
 # ==========================================
-# 3. Core Search Logic
+# 3. Core Search Logic (합집합 비교 적용 완료)
 # ==========================================
 def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, comp_cat, mapped_only, diff_only):
     try:
@@ -431,79 +463,79 @@ def execute_unified_search(base_std, base_ver, base_cat, comp_std, comp_ver, com
             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"))
-            registry_query = """
-                SELECT Target_Table FROM Mapping_registry 
-                WHERE TRIM(Base_std)=? AND TRIM(Base_ver)=? AND TRIM(Comp_std)=? AND TRIM(Comp_ver)=?
-                LIMIT 1
-            """
-            reg_df = pd.read_sql(registry_query, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
-            
-            target_table_name = "Mapping_table"
-            if not reg_df.empty and pd.notna(reg_df.iloc[0]['Target_Table']):
-                val = str(reg_df.iloc[0]['Target_Table']).strip()
-                if val and val.lower() not in ["none", "nan"]:
-                    target_table_name = val
+            # 💡 [핵심] 같은 법규인 경우 장부를 거치지 않고 양쪽 조항의 '합집합'을 만듭니다.
+            is_same_std = (base_std.strip().upper() == comp_std.strip().upper() and type_b.strip().upper() == type_c.strip().upper())
 
-            try:
-                q_fw = f"SELECT * FROM [{target_table_name}] 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()])
+            if is_same_std:
+                all_keys = list(set(df_base['merge_key']).union(set(df_comp['merge_key'])))
+                bridge = pd.DataFrame({'Base_section': all_keys, 'Comp_section': all_keys})
+            else:
+                conn_map = sqlite3.connect(os.path.join(UPLOAD_DIR, "mapping.db"))
+                registry_query = """
+                    SELECT Target_Table FROM Mapping_registry 
+                    WHERE TRIM(Base_std)=? AND TRIM(Base_ver)=? AND TRIM(Comp_std)=? AND TRIM(Comp_ver)=?
+                    LIMIT 1
+                """
+                reg_df = pd.read_sql(registry_query, conn_map, params=[base_std.strip(), base_ver.strip(), comp_std.strip(), comp_ver.strip()])
                 
-                q_rv = f"SELECT * FROM [{target_table_name}] 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()])
-            except Exception as sql_e:
+                target_table_name = "Mapping_table"
+                if not reg_df.empty and pd.notna(reg_df.iloc[0]['Target_Table']):
+                    val = str(reg_df.iloc[0]['Target_Table']).strip()
+                    if val and val.lower() not in ["none", "nan"]:
+                        target_table_name = val
+
+                try:
+                    q_fw = f"SELECT * FROM [{target_table_name}] 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 = f"SELECT * FROM [{target_table_name}] 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()])
+                except Exception as sql_e:
+                    conn_map.close()
+                    return pd.DataFrame({"Error": [f"매핑 장부 '{target_table_name}'을 여는 데 실패했습니다. 테이블 이름을 확인하세요: {str(sql_e)}"]})
                 conn_map.close()
-                return pd.DataFrame({"Error": [f"매핑 '{target_table_name}'을 여는 데 실패했습니다. 테이블 이름을 확인하세요: {str(sql_e)}"]})
-            conn_map.close()
 
-            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']
-                
-                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())]
+                cols_fw_lower = {c.lower(): c for c in df_fw.columns}
                 
-                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())]
-
-            b_sec = cols_fw_lower.get('base_section', 'Base_section')
-            c_sec = cols_fw_lower.get('comp_section', 'Comp_section')
-            
-            if b_sec not in df_fw.columns or c_sec not in df_fw.columns:
-                return pd.DataFrame({"Error": [f"'{target_table_name}' 에 '{b_sec}' 또는 '{c_sec}' 열이 없습니다. 대소문자를 확인하세요."]})
-            
-            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:
-                df_rv = pd.DataFrame(columns=['Base_section', 'Comp_section'])
-
-            df_mapping = pd.concat([df_fw, df_rv], ignore_index=True)
+                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']
+                    
+                    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())]
+                    
+                    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())]
 
-            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(',')
-                df_mapping = df_mapping.explode('Base_section').explode('Comp_section')
+                b_sec = cols_fw_lower.get('base_section', 'Base_section')
+                c_sec = cols_fw_lower.get('comp_section', 'Comp_section')
                 
-                df_mapping['Base_section'] = df_mapping['Base_section'].apply(clean_key_val)
-                df_mapping['Comp_section'] = df_mapping['Comp_section'].apply(clean_key_val)
+                if b_sec not in df_fw.columns or c_sec not in df_fw.columns:
+                    return pd.DataFrame({"Error": [f"'{target_table_name}' 장부에 '{b_sec}' 또는 '{c_sec}' 열이 없습니다. 대소문자를 확인하세요."]})
                 
-                df_mapping = df_mapping[(df_mapping['Base_section'] != "") & (df_mapping['Comp_section'] != "")]
-                df_mapping = df_mapping.dropna().drop_duplicates()
-            else:
-                df_mapping = pd.DataFrame(columns=['Base_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:
+                    df_rv = pd.DataFrame(columns=['Base_section', 'Comp_section'])
 
-            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()
-            else:
-                bridge = df_mapping.copy()
+                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(',')
+                    df_mapping = df_mapping.explode('Base_section').explode('Comp_section')
+                    
+                    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[(df_mapping['Base_section'] != "") & (df_mapping['Comp_section'] != "")]
+                    bridge = df_mapping.dropna().drop_duplicates()
+                else:
+                    bridge = pd.DataFrame(columns=['Base_section', 'Comp_section'])
 
             rename_b = {c: f"{c}_{base_ver}" for c in df_base.columns if c != 'merge_key'}
             df_base = df_base.rename(columns=rename_b)
@@ -637,7 +669,6 @@ with gr.Blocks() as demo:
     base_reset_btn.click(fn=reset_base_selections, inputs=None, outputs=[base_standard, base_version, base_category, base_status])
     comp_reset_btn.click(fn=reset_comp_selections, inputs=None, outputs=[comp_standard, comp_version, comp_category, comp_status])
 
-
 # ==========================================
 # 5. Application Styling (CSS)
 # ==========================================
@@ -649,17 +680,14 @@ css = """
 .reset-btn {
     margin-bottom: 10px !important; 
 }
-
 table { 
     table-layout: auto !important; 
     width: max-content !important; 
     min-width: 100% !important;
 }
-
 th, td {
     min-width: 150px; 
 }
-
 table:has(th:nth-last-child(2):first-child),
 table:has(th:nth-last-child(3):first-child),
 table:has(th:nth-last-child(4):first-child),
@@ -668,7 +696,6 @@ table:has(th:nth-last-child(6):first-child) {
     table-layout: fixed !important;
     width: 100% !important;
 }
-
 table th:nth-last-child(2):first-child, table td:nth-last-child(2):first-child { width: 15% !important; min-width: 0 !important; } 
 table th:nth-last-child(1), table td:nth-last-child(1) { width: 85% !important; min-width: 0 !important; }
 
@@ -724,12 +751,10 @@ td img {
     display: block;
     max-width: none !important;
 }
-
 #search_row {
     align-items: center !important; 
     margin-bottom: 5px !important;
 }
-
 #diff_cb_item, #mapped_cb_item {
     margin-top: 0 !important;
     padding-left: 15px !important;