diff --git a/README.md b/README.md
index 6c15ca7..eb6f162 100644
--- a/README.md
+++ b/README.md
@@ -12,28 +12,28 @@
 │       └── scripts
 ├── ipynb
 │   ├── ddb.ipynb
+│   ├── ddb_pe.ipynb
 │   ├── ddb_pit.ipynb
 │   ├── dos.ipynb
 │   └── mssql.ipynb
-├── Readme.txt
+├── README.md
 └── src
     ├── DDBBase.py
-    ├── DDBExpression.py
-    ├── DDBFactor.py
-    ├── DDBLoader.py
-    ├── make_hft.py
-    ├── ProtoBuffEntitys
-    │   ├── HFDataTableMessage_pb2.py
-    │   ├── IndexFutureKLineMessage_pb2.py
-    │   ├── IndexFutureL1TickMessage_pb2.py
-    │   ├── IndexKLineMessage_pb2.py
-    │   ├── IndexTickMessage_pb2.py
-    │   ├── KLineMessage_pb2.py
-    │   ├── OrderMessage_pb2.py
-    │   ├── TickMessage_pb2.py
-    │   ├── TickQueueMessage_pb2.py
-    │   └── TranseMessage_pb2.py
+    ├── expr
+    │   └── DDBExpression.py
+    ├── factor
+    │   └── DDBFactor.py
+    ├── __init__.py
+    ├── loader
+    │   ├── DDBBasicInfoLoader.py
+    │   ├── DDBDailyLoader.py
+    │   ├── DDBHFTLoader.py
+    │   ├── DDBLoader.py
+    │   ├── DDBPITLoader.py
+    │   ├── make_hft.py
+    │   └── ProtoBuffEntitys
     ├── ReadTickFromDB.py
+    ├── run.py
     └── script.py
 ```
 
@@ -51,21 +51,28 @@
 - `src`
     - Python源代码目录，是工作的主要目录
     - 大部分源码文件以`DDB`开头，表示与DolphinDB相关，继承和代码复用关系可以进一步优化
-    - `DDBBase`是`DDB*`的基类，包含了一些常用常量
-    - `DDBLoader`专门用于向DolphinDB写入数据（似乎称为Dumper更合适），目前包括：
-        - `DDBHFTLoader`，用以导入高频数据（海通高频数据）
-        - `DDBDailyLoader`，用以导入日频数据（市场日K线数据）
-        - `DDBPITLoader`，用以导入低频PIT数据，主要是财报数据
-    - `DDBFactor`用于生成因子，目前只有生成日频因子
-    - `DDBExpression`提供了基本的操作表达式，目前包括：
+    - `DDBBase.py`：
+		- `DDB*`的基类，包含了一些常用常量
+	- `run.py`：
+		- 用于执行具体操作任务的入口脚本
+		- TODO：需要支持命令行参数来选择执行功能和配套参数
+    - `loader`目录：代码专门用于向DolphinDB写入数据（似乎称为Dumper更合适），目前包括：
+		- `DDBLoader.py`：其他Loader类的基础类
+        - `DDBHFTLoader.py`：用以导入高频数据（海通高频数据）
+        - `DDBDailyLoader.py`：用以导入日频数据（市场日K线数据）
+        - `DDBPITLoader.py`：用以导入低频PIT数据，主要是财报数据
+		- `loader/ProtoBuffEntitys`目录：
+			- 用以解析海通高频数据中，protobuf字节流的Python辅助代码
+    - `factor`目录：用于生成因子
+		- `DDBFactor.py`：目前只有生成日频因子
+	- `expr`目录：用于支持基于DDB的各种表达式操作
+		- `DDBExpression.py`：提供了基本的操作表达式，目前包括：
         - 通过Function View，读取DolphinDB的分布式存储表：
             - 在任意时间点上，获取所有公司某张财报、指定财报期的最新可见快照
             - 在任意时间点上，获取所有公司某张财报中某科目、指定财报期的最新可见快照
         - 通过一般Function，对内存表进行操作：
             - 流量表累计数值转单季值
             - 跨年同比指标计算（分母为去年基数取绝对值，函数会同时返回当年值和去年基数，以便进一步调整）
-- `src/ProtoBuffEntitys`
-    - 用以解析海通高频数据中，protobuf字节流的Python辅助代码
 
 
 ## 海通高频数据录入说明
diff --git a/ipynb/ddb.ipynb b/ipynb/ddb.ipynb
index e7669e7..4c0de16 100644
--- a/ipynb/ddb.ipynb
+++ b/ipynb/ddb.ipynb
@@ -35,15 +35,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 60,
    "id": "ed17fd0b-9b36-47e4-9ab6-11459a3621fb",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "115548"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
+    "sess = ddb.session('192.168.1.7', 8848)\n",
+    "sess.login('admin', '123456')\n",
+    "\n",
     "# backup(backup_path, sql_obj, force, parallel)\n",
     "code = \"\"\"\n",
-    "    backup('/data/dolphindb/backup/', <select * from loadTable(\"dfs://hft_stock_ts\", \"OrderPartitioned\")>, true, true)\n",
-    "\"\"\""
+    "    backup('/data/dolphindb/backup/', <select * from loadTable(\"dfs://hft_stock_ts\", \"TickPartitioned\")>, true, true)\n",
+    "\"\"\"\n",
+    "\n",
+    "sess.run(code)"
    ]
   },
   {
@@ -1389,7 +1405,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 100,
    "id": "4ba45027-bbb5-4b27-99da-3452cc8d2f1c",
    "metadata": {},
    "outputs": [
@@ -1420,7 +1436,7 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>2298</td>\n",
+       "      <td>2227</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1428,10 +1444,10 @@
       ],
       "text/plain": [
        "   count\n",
-       "0   2298"
+       "0   2227"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 100,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1439,14 +1455,14 @@
    "source": [
     "sess.run(\"\"\"\n",
     "    select count(*) from (\n",
-    "    select code, m_nDate, count(*) as cnt from tbl where code='002182.SZ' group by code, m_nDate map\n",
+    "    select code, m_nDate, count(*) as cnt from tbl where code='002459.SZ' group by code, m_nDate map\n",
     "    );\n",
     "\"\"\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 103,
    "id": "29ab8af5-e571-4064-b691-a186d9fb4d08",
    "metadata": {},
    "outputs": [
@@ -1471,66 +1487,32 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>count</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>m_nDate</th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2013-01-04</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2013-01-07</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2013-01-08</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2013-01-09</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2013-01-10</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2022-07-04</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2022-07-05</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2022-07-06</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2022-07-07</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2022-07-08</th>\n",
-       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>2298 rows × 0 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "Empty DataFrame\n",
-       "Columns: []\n",
-       "Index: [2013-01-04 00:00:00, 2013-01-07 00:00:00, 2013-01-08 00:00:00, 2013-01-09 00:00:00, 2013-01-10 00:00:00, 2013-01-11 00:00:00, 2013-01-14 00:00:00, 2013-01-15 00:00:00, 2013-01-16 00:00:00, 2013-01-17 00:00:00, 2013-01-18 00:00:00, 2013-01-21 00:00:00, 2013-01-22 00:00:00, 2013-01-23 00:00:00, 2013-01-24 00:00:00, 2013-01-25 00:00:00, 2013-01-28 00:00:00, 2013-01-29 00:00:00, 2013-01-30 00:00:00, 2013-01-31 00:00:00, 2013-02-01 00:00:00, 2013-02-04 00:00:00, 2013-02-05 00:00:00, 2013-02-06 00:00:00, 2013-02-07 00:00:00, 2013-02-08 00:00:00, 2013-02-18 00:00:00, 2013-02-19 00:00:00, 2013-02-20 00:00:00, 2013-02-21 00:00:00, 2013-02-22 00:00:00, 2013-02-25 00:00:00, 2013-02-26 00:00:00, 2013-02-27 00:00:00, 2013-02-28 00:00:00, 2013-03-01 00:00:00, 2013-03-04 00:00:00, 2013-03-05 00:00:00, 2013-03-06 00:00:00, 2013-03-07 00:00:00, 2013-03-08 00:00:00, 2013-03-11 00:00:00, 2013-03-12 00:00:00, 2013-03-13 00:00:00, 2013-03-14 00:00:00, 2013-03-15 00:00:00, 2013-03-18 00:00:00, 2013-03-19 00:00:00, 2013-03-20 00:00:00, 2013-03-21 00:00:00, 2013-03-22 00:00:00, 2013-03-25 00:00:00, 2013-03-26 00:00:00, 2013-03-27 00:00:00, 2013-03-28 00:00:00, 2013-03-29 00:00:00, 2013-04-01 00:00:00, 2013-04-02 00:00:00, 2013-04-03 00:00:00, 2013-04-08 00:00:00, 2013-04-09 00:00:00, 2013-04-10 00:00:00, 2013-04-11 00:00:00, 2013-04-12 00:00:00, 2013-04-15 00:00:00, 2013-04-16 00:00:00, 2013-04-17 00:00:00, 2013-04-18 00:00:00, 2013-04-19 00:00:00, 2013-04-22 00:00:00, 2013-04-23 00:00:00, 2013-04-24 00:00:00, 2013-04-25 00:00:00, 2013-04-26 00:00:00, 2013-05-02 00:00:00, 2013-05-03 00:00:00, 2013-05-06 00:00:00, 2013-05-07 00:00:00, 2013-05-08 00:00:00, 2013-05-09 00:00:00, 2013-05-10 00:00:00, 2013-05-13 00:00:00, 2013-05-14 00:00:00, 2013-05-15 00:00:00, 2013-05-16 00:00:00, 2013-05-17 00:00:00, 2013-05-20 00:00:00, 2013-05-21 00:00:00, 2013-05-22 00:00:00, 2013-05-23 00:00:00, 2013-05-24 00:00:00, 2013-05-27 00:00:00, 2013-05-28 00:00:00, 2013-05-29 00:00:00, 2013-05-30 00:00:00, 2013-05-31 00:00:00, 2013-06-03 00:00:00, 2013-06-04 00:00:00, 2013-06-05 00:00:00, 2013-06-06 00:00:00, ...]\n",
-       "\n",
-       "[2298 rows x 0 columns]"
+       "Columns: [count]\n",
+       "Index: []"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 103,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "df = sess.run(\"\"\"\n",
-    "    select m_nDate from tbl where code='002182.SZ' group by m_nDate map;\n",
+    "    select m_nDate, count(*) from tbl where code='002458.SZ' group by m_nDate having count(*) > 5000 map;\n",
     "\"\"\").set_index('m_nDate')\n",
     "df"
    ]