更新环境

优化表结构，增加表数据
尝试加载数据
2026-02-02 09:08:37 +08:00 · 2026-01-30 17:57:12 +08:00 · 2026-01-29 18:10:40 +08:00 · 2026-01-29 10:41:53 +08:00
13 changed files with 2632 additions and 313 deletions
--- a/.idea/dataSources.xml
+++ b/.idea/dataSources.xml
@@ -8,5 +8,12 @@
      <jdbc-url>jdbc:postgresql://81.71.3.24:6785/leopard_dev</jdbc-url>
      <working-dir>$ProjectFileDir$</working-dir>
    </data-source>
+    <data-source source="LOCAL" name="leopard.sqlite" uuid="c9e16f8e-81be-45cf-847c-47a6750eeee2">
+      <driver-ref>sqlite.xerial</driver-ref>
+      <synchronize>true</synchronize>
+      <jdbc-driver>org.sqlite.JDBC</jdbc-driver>
+      <jdbc-url>jdbc:sqlite:$USER_HOME$/Documents/leopard_data/leopard.sqlite</jdbc-url>
+      <working-dir>$ProjectFileDir$</working-dir>
+    </data-source>
  </component>
 </project>
--- a/.idea/data_source_mapping.xml
+++ b/.idea/data_source_mapping.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="DataSourcePerFileMappings">
+    <file url="file://$APPLICATION_CONFIG_DIR$/consoles/db/bd7b5f2a-eb99-4aad-81ec-1fec76b3d7fc/console.sql" value="bd7b5f2a-eb99-4aad-81ec-1fec76b3d7fc" />
+    <file url="file://$APPLICATION_CONFIG_DIR$/consoles/db/c9e16f8e-81be-45cf-847c-47a6750eeee2/console.sql" value="c9e16f8e-81be-45cf-847c-47a6750eeee2" />
+  </component>
+</project>
--- a/.idea/db-forest-config.xml
+++ b/.idea/db-forest-config.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="db-tree-configuration">
+    <option name="data" value="" />
+  </component>
+</project>
--- a/.idea/sqldialects.xml
+++ b/.idea/sqldialects.xml
@@ -1,6 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
  <component name="SqlDialectMappings">
+    <file url="file://$PROJECT_DIR$/sql/initial.sql" dialect="SQLite" />
    <file url="PROJECT" dialect="PostgreSQL" />
  </component>
 </project>
--- a/.idea/vcs.xml
+++ b/.idea/vcs.xml
@@ -2,6 +2,5 @@
 <project version="4">
  <component name="VcsDirectoryMappings">
    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-    <mapping directory="$PROJECT_DIR$/backtestingpy" vcs="Git" />
  </component>
 </project>
--- a/data.py
+++ b/data.py
@@ -0,0 +1,136 @@
+from datetime import date, datetime, timedelta
+from time import sleep
+
+from sqlalchemy import Column, Double, Integer, String, create_engine
+from sqlalchemy.orm import DeclarativeBase, Session
+from tushare import pro_api
+
+TUSHARE_API_KEY = '64ebff4fa679167600b905ee45dd88e76f3963c0ff39157f3f085f0e'
+
+
+class Base(DeclarativeBase):
+    pass
+
+
+class Stock(Base):
+    __tablename__ = 'stock'
+
+    code = Column(String, primary_key=True, comment="代码")
+    name = Column(String, comment="名称")
+    fullname = Column(String, comment="全名")
+    market = Column(String, comment="市场")
+    exchange = Column(String, comment="交易所")
+    industry = Column(String, comment="行业")
+    list_date = Column(String, comment="上市日期")
+
+
+class Daily(Base):
+    __tablename__ = 'daily'
+
+    code = Column(String, primary_key=True)
+    trade_date = Column(String, primary_key=True)
+    open = Column(Double)
+    close = Column(Double)
+    high = Column(Double)
+    low = Column(Double)
+    previous_close = Column(Double)
+    turnover = Column(Double)
+    volume = Column(Integer)
+    price_change_amount = Column(Double)
+    factor = Column(Double)
+
+
+def main():
+    print("开始更新数据")
+
+    engine = create_engine(f"sqlite:////Users/lanyuanxiaoyao/Documents/leopard_data/leopard.sqlite")
+    try:
+        Stock.metadata.create_all(engine, checkfirst=True)
+        Daily.metadata.create_all(engine, checkfirst=True)
+        pro = pro_api(TUSHARE_API_KEY)
+        # with engine.connect() as connection:
+        #     stocks = pro.stock_basic(list_status="L", market="主板", fields="ts_code,name,fullname,market,exchange,industry,list_date")
+        #     for row in stocks.itertuples():
+        #         stmt = insert(Stock).values(
+        #             code=row.ts_code,
+        #             name=row.name,
+        #             fullname=row.fullname,
+        #             market=row.market,
+        #             exchange=row.exchange,
+        #             industry=row.industry,
+        #             list_date=row.list_date,
+        #         )
+        #         stmt = stmt.on_conflict_do_update(
+        #             index_elements=["code"],
+        #             set_={
+        #                 "name": stmt.excluded.name,
+        #                 "fullname": stmt.excluded.fullname,
+        #                 "market": stmt.excluded.market,
+        #                 "exchange": stmt.excluded.exchange,
+        #                 "industry": stmt.excluded.industry,
+        #                 "list_date": stmt.excluded.list_date,
+        #             },
+        #         )
+        #         print(stmt)
+        #         connection.execute(stmt)
+        #         connection.commit()
+        #
+        #     print("清理行情数据")
+        #     connection.execute(text("delete from daily where code not in (select distinct code from stock)"))
+        #     connection.commit()
+        #
+        #     print("清理财务数据")
+        #     connection.execute(text("delete from finance_indicator where code not in (select distinct code from stock)"))
+        #     connection.commit()
+
+        with Session(engine) as session:
+            stock_codes = [row[0] for row in session.query(Stock.code).all()]
+
+            latest_date = session.query(Daily.trade_date).order_by(Daily.trade_date.desc()).first()
+            if latest_date is None:
+                latest_date = '1990-12-19'
+            else:
+                latest_date = latest_date.trade_date
+            latest_date = datetime.strptime(latest_date, '%Y-%m-%d').date()
+            current_date = date.today() - timedelta(days=1)
+            delta = (current_date - latest_date).days
+            print(f"最新数据日期：{latest_date}，当前日期：{current_date}，待更新天数：{delta}")
+            if delta > 0:
+                update_dates = []
+                for i in range(delta):
+                    latest_date = latest_date + timedelta(days=1)
+                    update_dates.append(latest_date.strftime('%Y%m%d'))
+                for target_date in update_dates:
+                    print(f"正在采集：{target_date}")
+                    dailies = pro.daily(trade_date=target_date)
+                    dailies.set_index("ts_code", inplace=True)
+                    factors = pro.adj_factor(trade_date=target_date)
+                    factors.set_index("ts_code", inplace=True)
+                    results = dailies.join(factors, lsuffix="_daily", rsuffix="_factor", how="left")
+                    rows = []
+                    for row in results.itertuples():
+                        if row.Index in stock_codes:
+                            rows.append(
+                                Daily(
+                                    code=row.Index,
+                                    trade_date=datetime.strptime(target_date, '%Y%m%d').strftime("%Y-%m-%d"),
+                                    open=row.open,
+                                    close=row.close,
+                                    high=row.high,
+                                    low=row.low,
+                                    previous_close=row.pre_close,
+                                    turnover=row.amount,
+                                    volume=row.vol,
+                                    price_change_amount=row.pct_chg,
+                                    factor=row.adj_factor,
+                                )
+                            )
+                    session.add_all(rows)
+                    session.commit()
+                    sleep(1)
+    finally:
+        engine.dispose()
+
+
+if __name__ == '__main__':
+    main()
--- a/notebook/datasource/data.ipynb
+++ b/notebook/datasource/data.ipynb
--- a/notebook/datasource/data_old.ipynb
+++ b/notebook/datasource/data_old.ipynb
@@ -0,0 +1,455 @@
+{
+ "cells": [
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-01-30T05:41:51.291397Z",
+     "start_time": "2026-01-30T04:34:22.917761Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "import urllib.parse\n",
+    "\n",
+    "import pandas as pd\n",
+    "import sqlalchemy\n",
+    "from sqlalchemy import text\n",
+    "from sqlalchemy.orm import DeclarativeBase, Session\n",
+    "\n",
+    "postgresql_engin = sqlalchemy.create_engine(\n",
+    "    f\"postgresql://leopard:{urllib.parse.quote_plus(\"9NEzFzovnddf@PyEP?e*AYAWnCyd7UhYwQK$pJf>7?ccFiN^x4$eKEZ5~E<7<+~X\")}@81.71.3.24:6785/leopard\"\n",
+    ")\n",
+    "sqlite_engine = sqlalchemy.create_engine(f\"sqlite:////Users/lanyuanxiaoyao/Documents/leopard_data/leopard.sqlite\")\n",
+    "\n",
+    "\n",
+    "class Base(DeclarativeBase):\n",
+    "    pass\n",
+    "\n",
+    "\n",
+    "class Daily(Base):\n",
+    "    __tablename__ = 'daily'\n",
+    "\n",
+    "    code = sqlalchemy.Column(sqlalchemy.String, primary_key=True)\n",
+    "    trade_date = sqlalchemy.Column(sqlalchemy.Date, primary_key=True)\n",
+    "    open = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    close = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    high = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    low = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    previous_close = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    turnover = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    volume = sqlalchemy.Column(sqlalchemy.Integer)\n",
+    "    price_change_amount = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "    factor = sqlalchemy.Column(sqlalchemy.Double)\n",
+    "\n",
+    "\n",
+    "try:\n",
+    "    with Session(postgresql_engin) as pg_session:\n",
+    "        results = pg_session.execute(text(\"select distinct trade_date from leopard_daily\")).fetchall()\n",
+    "        results = list(map(lambda x: x[0].strftime(\"%Y-%m-%d\"), results))\n",
+    "        dates = [results[i: i + 30] for i in range(0, len(results), 30)]\n",
+    "\n",
+    "        for index, date in enumerate(dates):\n",
+    "            print(date)\n",
+    "            daily_df = pd.read_sql(\n",
+    "                f\"\"\"\n",
+    "                   select code,\n",
+    "                          trade_date,\n",
+    "                          open,\n",
+    "                          close,\n",
+    "                          high,\n",
+    "                          low,\n",
+    "                          previous_close,\n",
+    "                          turnover,\n",
+    "                          volume,\n",
+    "                          price_change_amount,\n",
+    "                          factor\n",
+    "                   from leopard_daily d\n",
+    "                            left join leopard_stock s on d.stock_id = s.id\n",
+    "                   where d.trade_date in ('{\"','\".join(date)}')\n",
+    "               \"\"\",\n",
+    "                postgresql_engin\n",
+    "            )\n",
+    "            with Session(sqlite_engine) as session:\n",
+    "                rows = []\n",
+    "                for _, row in daily_df.iterrows():\n",
+    "                    rows.append(\n",
+    "                        Daily(\n",
+    "                            code=row[\"code\"],\n",
+    "                            trade_date=row[\"trade_date\"],\n",
+    "                            open=row[\"open\"],\n",
+    "                            close=row[\"close\"],\n",
+    "                            high=row[\"high\"],\n",
+    "                            low=row[\"low\"],\n",
+    "                            previous_close=row[\"previous_close\"],\n",
+    "                            turnover=row[\"turnover\"],\n",
+    "                            volume=row[\"volume\"],\n",
+    "                            price_change_amount=row[\"price_change_amount\"],\n",
+    "                            factor=row[\"factor\"]\n",
+    "                        )\n",
+    "                    )\n",
+    "                session.add_all(rows)\n",
+    "                session.commit()\n",
+    "finally:\n",
+    "    postgresql_engin.dispose()\n",
+    "    sqlite_engine.dispose()"
+   ],
+   "id": "48821306efc640a1",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['2025-12-25', '2025-12-26', '2025-12-29', '2025-12-30', '2025-12-31', '2026-01-05', '2026-01-06', '2026-01-07', '2026-01-08', '2026-01-09']\n"
+     ]
+    }
+   ],
+   "execution_count": 22
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-01-30T09:24:09.859231Z",
+     "start_time": "2026-01-30T09:24:09.746912Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "import tushare as ts\n",
+    "\n",
+    "pro = ts.pro_api(\"64ebff4fa679167600b905ee45dd88e76f3963c0ff39157f3f085f0e\")\n",
+    "# stocks = pro.stock_basic(ts_code=\"600200.SH\", list_status=\"D\", fields=\"ts_code,name,fullname,market,exchange,industry,list_date,delist_date\")\n",
+    "# stocks"
+   ],
+   "id": "ed58a1faaf2cdb8e",
+   "outputs": [],
+   "execution_count": 34
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-01-30T07:14:29.897120Z",
+     "start_time": "2026-01-30T07:14:29.664124Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "# stocks.to_csv(\"dlist.csv\")",
+   "id": "3c8c0a38d6b2992e",
+   "outputs": [],
+   "execution_count": 24
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-01-30T09:46:34.808300Z",
+     "start_time": "2026-01-30T09:46:34.129412Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "daily_df = pro.daily(trade_date=\"20251231\")\n",
+    "daily_df.set_index(\"ts_code\", inplace=True)\n",
+    "factor_df = pro.adj_factor(trade_date=\"20251231\")\n",
+    "factor_df.set_index(\"ts_code\", inplace=True)"
+   ],
+   "id": "c052a945869aa329",
+   "outputs": [],
+   "execution_count": 50
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2026-01-30T09:46:36.697015Z",
+     "start_time": "2026-01-30T09:46:36.642975Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "result_df = daily_df.join(factor_df, lsuffix=\"_daily\", rsuffix=\"_factor\", how=\"left\")\n",
+    "result_df\n",
+    "# factor_df"
+   ],
+   "id": "d61ee80d2cd9f06b",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "          trade_date_daily    open    high     low   close  pre_close  change  \\\n",
+       "ts_code                                                                         \n",
+       "000001.SZ         20251231   11.48   11.49   11.40   11.41      11.48   -0.07   \n",
+       "000002.SZ         20251231    4.66    4.68    4.62    4.65       4.62    0.03   \n",
+       "000004.SZ         20251231   11.30   11.35   11.07   11.08      11.27   -0.19   \n",
+       "000006.SZ         20251231    9.95   10.03    9.69    9.95       9.86    0.09   \n",
+       "000007.SZ         20251231   11.72   11.75   11.28   11.44      11.62   -0.18   \n",
+       "...                    ...     ...     ...     ...     ...        ...     ...   \n",
+       "920978.BJ         20251231   37.64   38.39   36.88   36.90      37.78   -0.88   \n",
+       "920981.BJ         20251231   32.20   32.29   31.75   31.96      32.07   -0.11   \n",
+       "920982.BJ         20251231  233.00  238.49  232.10  233.70     234.80   -1.10   \n",
+       "920985.BJ         20251231    7.32    7.35    7.17    7.19       7.30   -0.11   \n",
+       "920992.BJ         20251231   17.33   17.60   17.29   17.39      17.38    0.01   \n",
+       "\n",
+       "           pct_chg         vol      amount trade_date_factor  adj_factor  \n",
+       "ts_code                                                                   \n",
+       "000001.SZ  -0.6098   590620.37  675457.357          20251231    134.5794  \n",
+       "000002.SZ   0.6494  1075561.25  499883.113          20251231    181.7040  \n",
+       "000004.SZ  -1.6859    18056.00   20248.567          20251231      4.0640  \n",
+       "000006.SZ   0.9128   270369.08  267758.676          20251231     39.7400  \n",
+       "000007.SZ  -1.5491    80556.00   92109.366          20251231      8.2840  \n",
+       "...            ...         ...         ...               ...         ...  \n",
+       "920978.BJ  -2.3293    33945.04  126954.937          20251231      1.2885  \n",
+       "920981.BJ  -0.3430     8237.16   26301.206          20251231      1.4343  \n",
+       "920982.BJ  -0.4685     5210.09  122452.646          20251231      4.2831  \n",
+       "920985.BJ  -1.5068    35174.30   25350.257          20251231      1.6280  \n",
+       "920992.BJ   0.0575     6991.87   12193.445          20251231      1.4932  \n",
+       "\n",
+       "[5458 rows x 12 columns]"
+      ],
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>trade_date_daily</th>\n",
+       "      <th>open</th>\n",
+       "      <th>high</th>\n",
+       "      <th>low</th>\n",
+       "      <th>close</th>\n",
+       "      <th>pre_close</th>\n",
+       "      <th>change</th>\n",
+       "      <th>pct_chg</th>\n",
+       "      <th>vol</th>\n",
+       "      <th>amount</th>\n",
+       "      <th>trade_date_factor</th>\n",
+       "      <th>adj_factor</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ts_code</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>000001.SZ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>11.48</td>\n",
+       "      <td>11.49</td>\n",
+       "      <td>11.40</td>\n",
+       "      <td>11.41</td>\n",
+       "      <td>11.48</td>\n",
+       "      <td>-0.07</td>\n",
+       "      <td>-0.6098</td>\n",
+       "      <td>590620.37</td>\n",
+       "      <td>675457.357</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>134.5794</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>000002.SZ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>4.66</td>\n",
+       "      <td>4.68</td>\n",
+       "      <td>4.62</td>\n",
+       "      <td>4.65</td>\n",
+       "      <td>4.62</td>\n",
+       "      <td>0.03</td>\n",
+       "      <td>0.6494</td>\n",
+       "      <td>1075561.25</td>\n",
+       "      <td>499883.113</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>181.7040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>000004.SZ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>11.30</td>\n",
+       "      <td>11.35</td>\n",
+       "      <td>11.07</td>\n",
+       "      <td>11.08</td>\n",
+       "      <td>11.27</td>\n",
+       "      <td>-0.19</td>\n",
+       "      <td>-1.6859</td>\n",
+       "      <td>18056.00</td>\n",
+       "      <td>20248.567</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>4.0640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>000006.SZ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>9.95</td>\n",
+       "      <td>10.03</td>\n",
+       "      <td>9.69</td>\n",
+       "      <td>9.95</td>\n",
+       "      <td>9.86</td>\n",
+       "      <td>0.09</td>\n",
+       "      <td>0.9128</td>\n",
+       "      <td>270369.08</td>\n",
+       "      <td>267758.676</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>39.7400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>000007.SZ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>11.72</td>\n",
+       "      <td>11.75</td>\n",
+       "      <td>11.28</td>\n",
+       "      <td>11.44</td>\n",
+       "      <td>11.62</td>\n",
+       "      <td>-0.18</td>\n",
+       "      <td>-1.5491</td>\n",
+       "      <td>80556.00</td>\n",
+       "      <td>92109.366</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>8.2840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>920978.BJ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>37.64</td>\n",
+       "      <td>38.39</td>\n",
+       "      <td>36.88</td>\n",
+       "      <td>36.90</td>\n",
+       "      <td>37.78</td>\n",
+       "      <td>-0.88</td>\n",
+       "      <td>-2.3293</td>\n",
+       "      <td>33945.04</td>\n",
+       "      <td>126954.937</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>1.2885</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>920981.BJ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>32.20</td>\n",
+       "      <td>32.29</td>\n",
+       "      <td>31.75</td>\n",
+       "      <td>31.96</td>\n",
+       "      <td>32.07</td>\n",
+       "      <td>-0.11</td>\n",
+       "      <td>-0.3430</td>\n",
+       "      <td>8237.16</td>\n",
+       "      <td>26301.206</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>1.4343</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>920982.BJ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>233.00</td>\n",
+       "      <td>238.49</td>\n",
+       "      <td>232.10</td>\n",
+       "      <td>233.70</td>\n",
+       "      <td>234.80</td>\n",
+       "      <td>-1.10</td>\n",
+       "      <td>-0.4685</td>\n",
+       "      <td>5210.09</td>\n",
+       "      <td>122452.646</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>4.2831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>920985.BJ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>7.32</td>\n",
+       "      <td>7.35</td>\n",
+       "      <td>7.17</td>\n",
+       "      <td>7.19</td>\n",
+       "      <td>7.30</td>\n",
+       "      <td>-0.11</td>\n",
+       "      <td>-1.5068</td>\n",
+       "      <td>35174.30</td>\n",
+       "      <td>25350.257</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>1.6280</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>920992.BJ</th>\n",
+       "      <td>20251231</td>\n",
+       "      <td>17.33</td>\n",
+       "      <td>17.60</td>\n",
+       "      <td>17.29</td>\n",
+       "      <td>17.39</td>\n",
+       "      <td>17.38</td>\n",
+       "      <td>0.01</td>\n",
+       "      <td>0.0575</td>\n",
+       "      <td>6991.87</td>\n",
+       "      <td>12193.445</td>\n",
+       "      <td>20251231</td>\n",
+       "      <td>1.4932</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5458 rows × 12 columns</p>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 51
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--- a/notebook/indicator.ipynb
+++ b/notebook/indicator.ipynb
--- a/notebook/sqlalchemy.ipynb
+++ b/notebook/sqlalchemy.ipynb
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,11 @@ version = "0.1.0"
 description = "Stock analysis"
 requires-python = ">=3.14"
 dependencies = [
+    "adata>=2.9.5",
+    "akshare>=1.18.20",
    "backtesting~=0.6.5",
+    "baostock>=0.8.9",
+    "duckdb>=1.4.4",
    "jupyter~=1.1.1",
    "jupyter-bokeh>=4.0.5",
    "matplotlib~=3.10.8",
@@ -17,4 +21,5 @@ dependencies = [
    "ta-lib>=0.6.8",
    "tabulate>=0.9.0",
    "tqdm>=4.67.1",
+    "tushare>=1.4.24",
 ]
--- a/sql/initial.sql
+++ b/sql/initial.sql
@@ -0,0 +1,94 @@
+CREATE TABLE stock
+(
+    code        varchar not null,
+    name        varchar not null,
+    fullname    varchar,
+    industry    varchar,
+    listed_date date,
+    market      varchar,
+    exchange    varchar,
+    primary key (code)
+);
+
+
+CREATE TABLE daily
+(
+    code                varchar not null,
+    trade_date          date    not null,
+    open                double,
+    close               double,
+    high                double,
+    low                 double,
+    previous_close      double,
+    turnover            double,
+    volume              integer,
+    price_change_amount double,
+    factor              double,
+    primary key (code, trade_date)
+);
+
+CREATE TABLE finance_indicator
+(
+    code                                             varchar not null,
+    year                                             integer not null,
+    accounts_payable                                 double,
+    accounts_payable_to_total_assets_ratio           double,
+    accounts_receivable                              double,
+    accounts_receivable_to_total_assets_ratio        double,
+    accounts_receivable_turnover                     double,
+    capital_surplus                                  double,
+    cash_and_cash_equivalents                        double,
+    cash_and_cash_equivalents_to_total_assets_ratio  double,
+    cash_flow_adequacy_ratio                         double,
+    cash_flow_from_financing_activities              double,
+    cash_flow_from_investing_activities              double,
+    cash_flow_from_operating_activities              double,
+    cash_flow_ratio                                  double,
+    cash_reinvestment_ratio                          double,
+    current_assets                                   double,
+    current_assets_to_total_assets_ratio             double,
+    current_liabilities                              double,
+    current_liabilities_to_total_assets_ratio        double,
+    current_liabilities_to_total_liabilities_ratio   double,
+    current_ratio                                    double,
+    days_accounts_receivable_turnover                double,
+    days_fixed_assets_turnover                       double,
+    days_inventory_turnover                          double,
+    days_total_assets_turnover                       double,
+    earnings_per_share                               double,
+    fixed_assets                                     double,
+    fixed_assets_to_total_assets_ratio               double,
+    fixed_assets_turnover                            double,
+    goodwill                                         double,
+    goodwill_to_total_assets_ratio                   double,
+    inventory                                        double,
+    inventory_to_total_assets_ratio                  double,
+    inventory_turnover                               double,
+    liabilities_to_total_assets_ratio                double,
+    long_term_funds_to_fixed_assets_ratio            double,
+    long_term_liabilities                            double,
+    long_term_liabilities_to_total_assets_ratio      double,
+    long_term_liabilities_to_total_liabilities_ratio double,
+    net_cash_flow_from_operating_activities          double,
+    net_profit                                       double,
+    net_profit_margin                                double,
+    operating_cost                                   double,
+    operating_expenses                               double,
+    operating_gross_profit_margin                    double,
+    operating_profit                                 double,
+    operating_profit_margin                          double,
+    operating_revenue                                double,
+    operating_safety_margin_ratio                    double,
+    quick_ratio                                      double,
+    return_on_assets                                 double,
+    return_on_equity                                 double,
+    shareholders_equity                              double,
+    shareholders_equity_to_total_assets_ratio        double,
+    surplus_reserve                                  double,
+    total_assets                                     double,
+    total_assets_turnover                            double,
+    total_liabilities                                double,
+    total_share_capital                              double,
+    undistributed_profit                             double,
+    primary key (code, year)
+)
--- a/uv.lock
+++ b/uv.lock
@@ -2,6 +2,57 @@ version = 1
 revision = 3
 requires-python = ">=3.14"

+[[package]]
+name = "adata"
+version = "2.9.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "beautifulsoup4" },
+    { name = "pandas" },
+    { name = "py-mini-racer" },
+    { name = "requests" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/0e/da/1eb2f05b14e4d41edcc017b9d6b428f30712d0d046f1b85cd54201b423a5/adata-2.9.5.tar.gz", hash = "sha256:b398fd885ee31baca41b8a141c586d3430ef0fec633f6088a830429437210cf6", size = 188823, upload-time = "2025-12-26T11:09:29.759Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/1d/9f/51a65fb438febc0ab38f493a837c5aeb9135dfee2e2c1224920038bbc686/adata-2.9.5-py3-none-any.whl", hash = "sha256:f9dc5d276f8771cf5a5f11fb81c6d97a00d188e20cfcef67022f210c8b23cbf1", size = 229158, upload-time = "2025-12-26T11:09:23.007Z" },
+]
+
+[[package]]
+name = "akracer"
+version = "0.0.14"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/1e/c6/f38feed5b961d73e1b4cb049fdb45338356e0f5b828b230c00d0e51f3137/akracer-0.0.14.tar.gz", hash = "sha256:e084c14bf6d9a02d5da375e3af1cba3d46f103aa1cf3a2010593b3e95bf1c29a", size = 10047643, upload-time = "2025-09-10T13:47:34.811Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/53/cb/1041355b14cd4b76ac082e8c676858f6eddb78f0ba37c59284adf36e5103/akracer-0.0.14-py3-none-any.whl", hash = "sha256:629eaccd0e1d18366804b797eb2692ed47bed0028f55b5a5af3cc277d521df04", size = 10076442, upload-time = "2025-09-10T13:47:29.061Z" },
+]
+
+[[package]]
+name = "akshare"
+version = "1.18.20"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "akracer", marker = "sys_platform == 'linux'" },
+    { name = "beautifulsoup4" },
+    { name = "curl-cffi" },
+    { name = "decorator" },
+    { name = "html5lib" },
+    { name = "jsonpath" },
+    { name = "lxml" },
+    { name = "mini-racer", marker = "sys_platform != 'linux'" },
+    { name = "openpyxl" },
+    { name = "pandas" },
+    { name = "py-mini-racer", marker = "sys_platform == 'linux'" },
+    { name = "requests" },
+    { name = "tabulate" },
+    { name = "tqdm" },
+    { name = "urllib3" },
+    { name = "xlrd" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/da/e0/48c0d7fc2527787b3179960454037dbe5b8d3409aa00eab23748a34317be/akshare-1.18.20.tar.gz", hash = "sha256:f3797d454fd2bc9e75f85e24abdd2af2c29989d4f89379b3385998bbf1464d16", size = 855384, upload-time = "2026-01-27T14:35:25.261Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e6/b4/2743787e5366eb281b966f8c3fcc85d6e3a8456cefbac27d30ca7baafedd/akshare-1.18.20-py3-none-any.whl", hash = "sha256:9ba6cb3a17ee4cf957cf81e01cec59d55962a3fd867ab669d151a213bb5a9fc3", size = 1074968, upload-time = "2026-01-27T14:35:23.937Z" },
+]
+
 [[package]]
 name = "anyio"
 version = "4.12.1"
@@ -129,6 +180,18 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/b3/b6/cf57538b968c5caa60ee626ec8be1c31e420067d2a4cf710d81605356f8c/backtesting-0.6.5-py3-none-any.whl", hash = "sha256:8ac2fa500c8fd83dc783b72957b600653a72687986fe3ca86d6ef6c8b8d74363", size = 192105, upload-time = "2025-07-30T05:57:03.322Z" },
 ]

+[[package]]
+name = "baostock"
+version = "0.8.9"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pandas" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ee/d5/0fb2c61f392f89b1655490acb17a02861f1f1c38e973c9fc6aa049e54401/baostock-0.8.9.tar.gz", hash = "sha256:8169cdbed14fa442ace63c59549bef3f92b0c3dd1df9e5d9069f7bd04a76b0da", size = 21876, upload-time = "2024-05-31T02:56:54.546Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b2/37/bbabac2d33723d71bd8dbd5e819d9cbe5dc1e031b7dd12ed7de8fa040816/baostock-0.8.9-py3-none-any.whl", hash = "sha256:7a51fb30cd6b4325f5517198e350dc2fffaaab2923cd132b9f747b8b73ae7303", size = 45923, upload-time = "2024-05-31T02:56:53.161Z" },
+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.14.3"
@@ -180,6 +243,18 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/f6/a8/877f306720bc114c612579c5af36bcb359026b83d051226945499b306b1a/bokeh-3.8.2-py3-none-any.whl", hash = "sha256:5e2c0d84f75acb25d60efb9e4d2f434a791c4639b47d685534194c4e07bd0111", size = 7207131, upload-time = "2026-01-06T00:20:04.917Z" },
 ]

+[[package]]
+name = "bs4"
+version = "0.0.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "beautifulsoup4" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c9/aa/4acaf814ff901145da37332e05bb510452ebed97bc9602695059dd46ef39/bs4-0.0.2.tar.gz", hash = "sha256:a48685c58f50fe127722417bae83fe6badf500d54b55f7e39ffe43b798653925", size = 698, upload-time = "2024-01-17T18:15:47.371Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/51/bb/bf7aab772a159614954d84aa832c129624ba6c32faa559dfb200a534e50b/bs4-0.0.2-py2.py3-none-any.whl", hash = "sha256:abf8742c0805ef7f662dce4b51cca104cffe52b835238afc169142ab9b3fbccc", size = 1189, upload-time = "2024-01-17T18:15:48.613Z" },
+]
+
 [[package]]
 name = "build"
 version = "1.4.0"
@@ -312,6 +387,29 @@ wheels = [
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 ]

+[[package]]
+name = "curl-cffi"
+version = "0.14.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "certifi" },
+    { name = "cffi" },
+]
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Author	SHA1	Message	Date
lanyuanxiaoyao	48c6154fab	更新环境	2026-02-02 09:08:37 +08:00
lanyuanxiaoyao	3174f306bb	优化表结构，增加表数据	2026-01-30 17:57:12 +08:00
lanyuanxiaoyao	b90d030899	尝试加载数据	2026-01-29 18:10:40 +08:00
lanyuanxiaoyao	9f06ebf87d	完成macd图的绘制	2026-01-29 10:41:53 +08:00