后端代码

.idea/dataSources.xml

@@ -8,5 +8,12 @@
       <jdbc-url>jdbc:mysql://lawyer5.cn:3308/wangche</jdbc-url>
       <working-dir>$ProjectFileDir$</working-dir>
     </data-source>
+    <data-source source="LOCAL" name="@localhost" uuid="7b52e754-e1c2-4a7c-ae09-3c939af31a22">
+      <driver-ref>mysql.8</driver-ref>
+      <synchronize>true</synchronize>
+      <jdbc-driver>com.mysql.cj.jdbc.Driver</jdbc-driver>
+      <jdbc-url>jdbc:mysql://localhost:3306</jdbc-url>
+      <working-dir>$ProjectFileDir$</working-dir>
+    </data-source>
   </component>
 </project>

.idea/misc.xml

@@ -3,5 +3,5 @@
   <component name="Black">
     <option name="sdkName" value="Python 3.7" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (wance_data)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (testenv) (2)" project-jdk-type="Python SDK" />
 </project>

.idea/wance_data.iml

@@ -4,7 +4,7 @@
     <content url="file://$MODULE_DIR$">
       <excludeFolder url="file://$MODULE_DIR$/venv" />
     </content>
-    <orderEntry type="inheritedJdk" />
+    <orderEntry type="jdk" jdkName="Python 3.11 (testenv) (2)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="PackageRequirementsSettings">

src/akshare_data/router.py

@@ -0,0 +1,915 @@
+from fastapi import APIRouter, Query, FastAPI, Body
+from starlette.middleware.cors import CORSMiddleware
+import akshare as ak
+import pymysql
+import json
+from pydantic import BaseModel
+from typing import List, Dict
+import math
+router = APIRouter()  # 创建一个 FastAPI 路由器实例
+
+
+# 数据库测试
+@router.get("/userstrategy")
+async def userstrategy():
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    # 使用 execute()方法执行 SQL 查询
+    # 通配符 *，意思是查询表里所有内容
+    cursor.execute("select * from user_strategy where user_id = 100096")
+
+    # 使用 fetchone() 方法获取一行数据.
+    # data = cursor.fetchone()
+    data = cursor.fetchall()
+    # print(data)
+
+    # 关闭数据库连接
+    cursor.close()
+    # 将strategy_request字段中的JSON字符串转换为Python字典
+    for i in range(0, len(data)):
+        strategy_request = data[i]['strategy_request']
+        # 将JSON字符串转换为Python字典
+        data_dict = json.loads(strategy_request)
+        data[i]['strategy_request'] = data_dict
+    return data
+
+
+# 定义Pydantic模型
+class InfoItem(BaseModel):
+    code: str
+    name: str
+    market: str
+    newprice: float
+    amplitudetype: bool
+    amplitude: float
+    type: str
+
+class MessageItem(BaseModel):
+    id: str
+    label: str
+    value: str
+    state: bool
+    info: List[InfoItem]
+    inputClass: str
+    fixchange: bool
+
+class StrategyRequest(BaseModel):
+    id: int
+    strategy_name: str
+    message: List[MessageItem] or None
+    info: List[InfoItem] or None
+
+class MyData(BaseModel):
+    mes: List[StrategyRequest]
+
+# 新加的new_user_strategy数据库表
+@router.post("/newuserstrategy")
+async def newuserstrategy(strategy: StrategyRequest = Body(...)):
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+    # cursor1 = conn.cursor()
+    # cursor2 = conn.cursor()
+    # --------------------new_user_strategy数据------------------
+    # SQL 查询语句
+    sql1 = "SELECT strategy_name FROM new_user_strategy WHERE id = %s"
+    # 执行查询
+    cursor.execute(sql1, ('100096',))
+    # 获取所有数据
+    result1 = cursor.fetchall()
+    # 提取 strategy_name 列并转换为列表
+    strategy_names1 = [row['strategy_name'] for row in result1]
+    # print(strategy_names1)
+
+    # --------------------user_strategy数据------------------
+    # SQL 查询语句
+    sql2 = "SELECT strategy_name FROM user_strategy WHERE user_id = %s"
+    # 执行查询
+    cursor.execute(sql2, ('100096',))
+    # 获取所有数据
+    result2 = cursor.fetchall()
+    # 提取 strategy_name 列并转换为列表
+    strategy_names2 = [row['strategy_name'] for row in result2]
+    # print(strategy_names2)
+
+
+    # --------------------获取整个请求数据--------------------
+    request_data = strategy.dict()
+    # print(request_data)
+
+    # 准备SQL插入语句（注意：没有包含id列，因为它可能是自动递增的）
+    sql = "INSERT INTO new_user_strategy (id, strategy_name, message, info) VALUES (%s, %s, %s, %s)"
+    # 要插入的数据（确保数据类型与数据库表列匹配）
+    # 将message和info转换为JSON字符串
+    import json
+    message_json = json.dumps(request_data['message'])
+    info_json = json.dumps(request_data['info'])
+    values = (request_data['id'], request_data['strategy_name'], message_json, info_json)
+
+    # 是否进行写入数据库表中
+    set_strategy_names1 = set(strategy_names1)
+    set_strategy_names2 = set(strategy_names2)
+
+    if request_data['strategy_name'] in strategy_names1:
+        # print("信息已存在")
+        conn.close()
+    else:
+        # 执行SQL语句
+        cursor.execute(sql, values)
+        # 提交事务到数据库执行
+        conn.commit()
+        print("数据插入成功")
+        # 关闭数据库连接
+        conn.close()
+        return {"message": "数据插入成功"}
+    # for i in range(0, len(result2)):
+    #     if result2[i] not in strategy_names1:
+    #         # 执行SQL语句
+    #         cursor.execute(sql, values)
+    #         # 提交事务到数据库执行
+    #         conn.commit()
+    #         print("数据插入成功")
+    #         # 关闭数据库连接
+    #         conn.close()
+    #         return {"message": "数据插入成功"}
+
+
+    # conn.close()
+
+@router.post("/newadd")
+async def newadd(strategy: StrategyRequest = Body(...)):
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    # SQL 查询语句
+    sql1 = "SELECT strategy_name FROM new_user_strategy WHERE id = %s"
+    # 执行查询
+    cursor.execute(sql1, ('100096',))
+    # 获取所有数据
+    result1 = cursor.fetchall()
+
+    # 获取整个请求数据
+    request_data = strategy.dict()
+    print(request_data)
+
+    import json
+    message_json = json.dumps(request_data['message'])
+    info_json = json.dumps(request_data['info'])
+
+    print(result1)
+    for item in result1:
+        if request_data['strategy_name'] == item['strategy_name']:
+            return {
+                "code": 204,
+                "message": "该分组已经存在"
+            }
+
+    sql = "INSERT INTO new_user_strategy (id, strategy_name, message, info) VALUES (%s, %s, %s, %s)"
+    # # 执行 SQL
+    cursor.execute(sql, (request_data["id"], request_data['strategy_name'], message_json, info_json))
+    #
+    # # 提交事务到数据库执行
+    conn.commit()
+    # print("更新数据成功")
+    # 关闭数据库连接
+    conn.close()
+    return {
+        "code": 200,
+        "message": "新建分组成功！"
+    }
+
+
+
+# 获取数据
+@router.get("/newget")
+async def newget():
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    # 使用 execute()方法执行 SQL 查询
+    # 通配符 *，意思是查询表里所有内容
+    cursor.execute("select * from new_user_strategy where id = 100096")
+
+    # 使用 fetchone() 方法获取一行数据.
+    # data = cursor.fetchone()
+    data = cursor.fetchall()
+    # print(data)
+
+    # 关闭数据库连接
+    cursor.close()
+    # 将strategy_request字段中的JSON字符串转换为Python字典
+    for i in range(0, len(data)):
+        strategy_request1 = data[i]['message']
+        strategy_request2 = data[i]['info']
+        # 将JSON字符串转换为Python字典
+        data_dict1 = json.loads(strategy_request1)
+        data_dict2 = json.loads(strategy_request2)
+        data[i]['message'] = data_dict1
+        data[i]['info'] = data_dict2
+    return {
+        "code": 200,
+        "data": data
+    }
+
+
+
+# 新增分组
+@router.post("/newupdata")
+async def newupdata(strategy: StrategyRequest = Body(...)):
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    # 获取整个请求数据
+    request_data = strategy.dict()
+    print(request_data)
+
+    import json
+    message_json = json.dumps(request_data['message'])
+    info_json = json.dumps(request_data['info'])
+
+
+    # SQL 语句
+    sql = """
+    UPDATE new_user_strategy
+    SET message = %s, info = %s
+    WHERE strategy_name = %s;
+    """
+
+    # 执行 SQL
+    cursor.execute(sql, (message_json, info_json, request_data['strategy_name']))
+
+
+    # 提交事务到数据库执行
+    conn.commit()
+    print("更新数据成功")
+    # 关闭数据库连接
+    conn.close()
+    return "更新成功"
+
+
+
+class delItem(BaseModel):
+    strategy_name: str
+# 删除分组
+@router.post("/newdel")
+async def newdel(delitem: delItem):
+    delitem = delitem.strategy_name
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    sql1 = "DELETE FROM new_user_strategy WHERE strategy_name = %s"
+
+    sql2 = "DELETE FROM user_strategy WHERE strategy_name = %s"
+
+    cursor.execute(sql1, (delitem,))
+    cursor.execute(sql2, (delitem,))
+    # 提交事务到数据库执行
+    conn.commit()
+    print("数据删除成功")
+    # 关闭数据库连接
+    conn.close()
+    return "删除成功"
+
+
+
+@router.get("/newmodify")
+async def newmodify(
+    strategy_name: str = Query(..., description="原始值"),
+    new_strategy_name: str = Query(..., description="更改值")
+):
+    print(strategy_name)
+    print(new_strategy_name)
+    # return "success"
+    # pass
+    # 创建数据库连接
+    conn = pymysql.connect(
+        host='cqxqg.tech',  # MySQL服务器地址
+        user='wangche',  # MySQL用户名
+        password='fN7sXX8saiQKXWbG',  # MySQL密码
+        database='wangche',  # 要连接的数据库名
+        port=3308,
+        charset='utf8mb4',  # 字符集，确保支持中文等
+        cursorclass=pymysql.cursors.DictCursor  # 使用字典形式返回结果
+    )
+
+    # 使用 cursor() 方法创建一个游标对象 cursor
+    cursor = conn.cursor()
+
+    # 更新 strategy_name
+    update_sql = "UPDATE new_user_strategy SET strategy_name = %s WHERE strategy_name = %s"
+    cursor.execute(update_sql, (new_strategy_name, strategy_name))
+    # 提交事务到数据库执行
+    conn.commit()
+    print("重命名成功")
+    # 关闭数据库连接
+    conn.close()
+    return "重命名成功"
+
+
+
+
+# 侧边栏webview数据
+@router.post("/asidestrinfo/")
+async def asidestrinfo():
+    pass
+
+
+
+# 股票数据
+stock_data = None
+@router.get("/stock")
+async def stock(
+        symbol: str = Query(..., description="股票代码"),
+        start_date: str = Query(..., description="起始日期"),
+        end_date: str = Query(..., description="结束日期"),
+):
+    # 获取股票日线行情数据
+    # print(symbol, start_date, end_date)
+    # print(symbol)
+    global stock_data
+    try:
+        stock_zh_a_daily_df = ak.stock_zh_a_daily(symbol=symbol, start_date=start_date, end_date=end_date, adjust="qfq")
+
+        # 获取所有的code
+        all_dates = stock_zh_a_daily_df['date']
+        # 如果你想要一个列表而不是Pandas Series
+        dates_list = all_dates.tolist()
+
+        all_opens = stock_zh_a_daily_df['open']
+        opens_list = all_opens.tolist()
+        cleaned_opens_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in opens_list
+        ]
+
+        all_closes = stock_zh_a_daily_df['close']
+        close_list = all_closes.tolist()
+        cleaned_close_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in close_list
+        ]
+
+        all_highs = stock_zh_a_daily_df['high']
+        high_list = all_highs.tolist()
+        cleaned_high_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in high_list
+        ]
+
+        all_lows = stock_zh_a_daily_df['low']
+        low_list = all_lows.tolist()
+        cleaned_low_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in low_list
+        ]
+
+        all_volumes = stock_zh_a_daily_df['volume']
+        volume_list = all_volumes.tolist()
+        cleaned_volume_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in volume_list
+        ]
+
+        all_amounts = stock_zh_a_daily_df['amount']
+        amount_lists = all_amounts.tolist()
+        cleaned_amount_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in amount_lists
+        ]
+        global stock_data
+        stock_data = {
+            "amount": cleaned_amount_list,
+            "close": cleaned_close_list,
+            "date": dates_list,
+            "high": cleaned_high_list,
+            "low": cleaned_low_list,
+            "open": cleaned_opens_list,
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": cleaned_volume_list
+        }
+    except Exception as e:
+        print(e)
+        print("无法使用该方式请求股票数据，当前股票可能不是A股")
+        stock_data = {
+            "amount": [],
+            "close": [],
+            "date": [],
+            "high": [],
+            "low": [],
+            "open": [],
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": []
+        }
+    finally:
+        return {"message": stock_data}
+
+# 前端获取数据接口
+@router.get("/kdata")
+async def kdata():
+    global stock_data
+    if stock_data is None:
+        stock_data = {
+            "amount": [],
+            "close": [],
+            "date": [],
+            "high": [],
+            "low": [],
+            "open": [],
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": []
+        }
+        return {"message": stock_data}
+    else:
+        return {"message": stock_data}
+
+# ---------------------------------------------------------------------
+# 港股代码数据
+@router.get("/ganggudata")
+async def ganggudata():
+    stock_hk_spot_em_df = ak.stock_hk_spot_em()
+    # print(stock_hk_spot_em_df)
+    # 获取所有的code
+    all_codes = stock_hk_spot_em_df['代码']
+    # 如果你想要一个列表而不是Pandas Series
+    codes_list = all_codes.tolist()
+
+    all_names = stock_hk_spot_em_df['名称']
+    names_list = all_names.tolist()
+
+    all_prices = stock_hk_spot_em_df['最新价']
+    price_list = all_prices.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_price_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in price_list
+    ]
+
+    all_amplitudes = stock_hk_spot_em_df['涨跌幅']
+    amplitudes_list = all_amplitudes.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_amplitudes_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in amplitudes_list
+    ]
+
+    # 返回的数据
+    ggstocking = []
+    for i in range(9):
+        if cleaned_price_list[i] >= 0:
+            flag = True
+        else:
+            flag = False
+        ggstocking.append({
+            'code': codes_list[i],
+            'name': names_list[i],
+            'market': '港股',
+            'newprice': cleaned_price_list[i],
+            'amplitudetype': flag,
+            'amplitude': cleaned_amplitudes_list[i],
+            'type': 'ganggu'
+        })
+
+    # 返回清理后的列表
+    return ggstocking
+
+# 港股K线图历史数据
+@router.get("/ganggudataK")
+async def ganggudataK(
+        symbol: str = Query(..., description="股票代码"),
+        start_date: str = Query(..., description="起始日期"),
+        end_date: str = Query(..., description="结束日期"),
+):
+    try:
+        stock_hk_hist_df = ak.stock_hk_hist(symbol=symbol, period="daily", start_date=start_date, end_date=end_date,
+                                            adjust="")
+
+        # 获取所有的code
+        all_dates = stock_hk_hist_df['日期']
+        # 如果你想要一个列表而不是Pandas Series
+        dates_list = all_dates.tolist()
+
+        all_opens = stock_hk_hist_df['开盘']
+        opens_list = all_opens.tolist()
+        cleaned_opens_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in opens_list
+        ]
+
+        all_closes = stock_hk_hist_df['收盘']
+        close_list = all_closes.tolist()
+        cleaned_close_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in close_list
+        ]
+
+        all_highs = stock_hk_hist_df['最高']
+        high_list = all_highs.tolist()
+        cleaned_high_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in high_list
+        ]
+
+        all_lows = stock_hk_hist_df['最低']
+        low_list = all_lows.tolist()
+        cleaned_low_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in low_list
+        ]
+
+        all_volumes = stock_hk_hist_df['成交量']
+        volume_list = all_volumes.tolist()
+        cleaned_volume_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in volume_list
+        ]
+
+        all_amounts = stock_hk_hist_df['成交额']
+        amount_list = all_amounts.tolist()
+        cleaned_amount_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in amount_list
+        ]
+        global stock_data
+        stock_data = {
+            "amount": cleaned_amount_list,
+            "close": cleaned_close_list,
+            "date": dates_list,
+            "high": cleaned_high_list,
+            "low": cleaned_low_list,
+            "open": cleaned_opens_list,
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": cleaned_volume_list
+        }
+    except Exception as e:
+        print(e)
+        stock_data = {
+            "amount": [],
+            "close": [],
+            "date": [],
+            "high": [],
+            "low": [],
+            "open": [],
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": []
+        }
+    finally:
+        return {"message": stock_data}
+
+
+
+# ---------------------------------------------------------------------
+# 美股代码数据
+@router.get("/meigudata")
+async def meigudata():
+    stock_us_spot_em_df = ak.stock_us_spot_em()
+    # print(stock_us_spot_em_df)
+    all_codes = stock_us_spot_em_df['代码']
+    # 如果你想要一个列表而不是Pandas Series
+    codes_list = all_codes.tolist()
+
+    all_names = stock_us_spot_em_df['名称']
+    names_list = all_names.tolist()
+
+    all_prices = stock_us_spot_em_df['最新价']
+    price_list = all_prices.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_price_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in price_list
+    ]
+
+    all_amplitudes = stock_us_spot_em_df['涨跌幅']
+    amplitudes_list = all_amplitudes.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_amplitudes_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in amplitudes_list
+    ]
+    # 返回的数据
+    mgstocking = []
+    for i in range(9):
+        if cleaned_price_list[i] >= 0:
+            flag = True
+        else:
+            flag = False
+        mgstocking.append({
+            'code': codes_list[i],
+            'name': names_list[i],
+            'market': '港股',
+            'newprice': cleaned_price_list[i],
+            'amplitudetype': flag,
+            'amplitude': cleaned_amplitudes_list[i],
+            'type': 'meigu'
+        })
+
+    # 返回清理后的列表
+    return mgstocking
+# 美股K线图历史数据
+@router.get("/meigudataK")
+async def meigudataK(
+        symbol: str = Query(..., description="股票代码"),
+        start_date: str = Query(..., description="起始日期"),
+        end_date: str = Query(..., description="结束日期"),
+):
+    try:
+        stock_us_hist_df = ak.stock_us_hist(symbol=symbol, period="daily", start_date=start_date, end_date=end_date,
+                                            adjust="qfq")
+
+        # 获取所有的code
+        all_dates = stock_us_hist_df['日期']
+        # 如果你想要一个列表而不是Pandas Series
+        dates_list = all_dates.tolist()
+
+        all_opens = stock_us_hist_df['开盘']
+        opens_list = all_opens.tolist()
+        cleaned_opens_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in opens_list
+        ]
+
+        all_closes = stock_us_hist_df['收盘']
+        close_list = all_closes.tolist()
+        cleaned_close_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in close_list
+        ]
+
+        all_highs = stock_us_hist_df['最高']
+        high_list = all_highs.tolist()
+        cleaned_high_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in high_list
+        ]
+
+        all_lows = stock_us_hist_df['最低']
+        low_list = all_lows.tolist()
+        cleaned_low_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in low_list
+        ]
+
+        all_volumes = stock_us_hist_df['成交量']
+        volume_list = all_volumes.tolist()
+        cleaned_volume_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in volume_list
+        ]
+
+        all_amounts = stock_us_hist_df['成交额']
+        amount_list = all_amounts.tolist()
+        cleaned_amount_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in amount_list
+        ]
+        global stock_data
+        stock_data = {
+            "amount": cleaned_amount_list,
+            "close": cleaned_close_list,
+            "date": dates_list,
+            "high": cleaned_high_list,
+            "low": cleaned_low_list,
+            "open": cleaned_opens_list,
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": cleaned_volume_list
+        }
+    except Exception as e:
+        print(e)
+        stock_data = {
+            "amount": [],
+            "close": [],
+            "date": [],
+            "high": [],
+            "low": [],
+            "open": [],
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": []
+        }
+    finally:
+        return {"message": stock_data}
+
+# ---------------------------------------------------------------------
+# 沪深代码数据
+@router.get("/hushendata")
+async def hushendata():
+    try:
+        stock_zh_a_spot_df = ak.stock_kc_a_spot_em()
+    except Exception as e:
+        print(e)
+    # print(stock_zh_a_spot_df)
+    all_codes = stock_zh_a_spot_df['代码']
+    # 如果你想要一个列表而不是Pandas Series
+    codes_list = all_codes.tolist()
+
+    all_names = stock_zh_a_spot_df['名称']
+    names_list = all_names.tolist()
+
+    all_prices = stock_zh_a_spot_df['最新价']
+    price_list = all_prices.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_price_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in price_list
+    ]
+
+    all_amplitudes = stock_zh_a_spot_df['涨跌幅']
+    amplitudes_list = all_amplitudes.tolist()
+    # 清理非法浮点数值（NaN, Infinity, -Infinity）
+    cleaned_amplitudes_list = [
+        value if not (math.isnan(value) or math.isinf(value)) else 0.00
+        for value in amplitudes_list
+    ]
+    # 返回的数据
+    hsstocking = []
+
+    # for i in range(len(codes_list)):
+    #     if cleaned_price_list[i] >= 0:
+    #         flag = True
+    #     else:
+    #         flag = False
+    #     hsstocking.append({
+    #         'code': codes_list[i],
+    #         'name': names_list[i],
+    #         'market': '港股',
+    #         'newprice': cleaned_price_list[i],
+    #         'amplitudetype': flag,
+    #         'amplitude': cleaned_amplitudes_list[i],
+    #     })
+
+
+    for i in range(9):
+        if cleaned_price_list[i] >= 0:
+            flag = True
+        else:
+            flag = False
+        hsstocking.append({
+            'code': codes_list[i],
+            'name': names_list[i],
+            'market': '港股',
+            'newprice': cleaned_price_list[i],
+            'amplitudetype': flag,
+            'amplitude': cleaned_amplitudes_list[i],
+            'type': 'hushen'
+        })
+
+    # 返回清理后的列表
+    return hsstocking
+@router.get("/hushendataK")
+async def hushendataK(
+        symbol: str = Query(..., description="股票代码"),
+        start_date: str = Query(..., description="起始日期"),
+        end_date: str = Query(..., description="结束日期"),
+):
+    try:
+        stock_zh_a_daily_qfq_df = ak.stock_zh_a_daily(symbol='sh' + symbol, start_date=start_date, end_date=end_date,
+                                                      adjust="qfq")
+
+        # 获取所有的code
+        all_dates = stock_zh_a_daily_qfq_df['date']
+        # 如果你想要一个列表而不是Pandas Series
+        dates_list = all_dates.tolist()
+
+        all_opens = stock_zh_a_daily_qfq_df['open']
+        opens_list = all_opens.tolist()
+        cleaned_opens_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in opens_list
+        ]
+
+        all_closes = stock_zh_a_daily_qfq_df['close']
+        close_list = all_closes.tolist()
+        cleaned_close_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in close_list
+        ]
+
+        all_highs = stock_zh_a_daily_qfq_df['high']
+        high_list = all_highs.tolist()
+        cleaned_high_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in high_list
+        ]
+
+        all_lows = stock_zh_a_daily_qfq_df['low']
+        low_list = all_lows.tolist()
+        cleaned_low_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in low_list
+        ]
+
+        all_volumes = stock_zh_a_daily_qfq_df['volume']
+        volume_list = all_volumes.tolist()
+        cleaned_volume_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in volume_list
+        ]
+
+        all_amounts = stock_zh_a_daily_qfq_df['amount']
+        amount_lists = all_amounts.tolist()
+        cleaned_amount_list = [
+            value if not (math.isnan(value) or math.isinf(value)) else 0.00
+            for value in amount_lists
+        ]
+        global stock_data
+        stock_data = {
+            "amount": cleaned_amount_list,
+            "close": cleaned_close_list,
+            "date": dates_list,
+            "high": cleaned_high_list,
+            "low": cleaned_low_list,
+            "open": cleaned_opens_list,
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": cleaned_volume_list
+        }
+    except Exception as e:
+        print(e)
+        stock_data = {
+            "amount": [],
+            "close": [],
+            "date": [],
+            "high": [],
+            "low": [],
+            "open": [],
+            "outstanding_share": [],
+            "turnover": [],
+            "volume": []
+        }
+    finally:
+        return {"message": stock_data}
+
+
+
+
+
+

src/akshare_data/service.py

@@ -0,0 +1,6 @@
+from fastapi import FastAPI,Query
+from starlette.middleware.cors import CORSMiddleware
+import akshare as ak
+
+async def get_day_k_data():
+    pass

src/exceptions.py

@@ -1,3 +1,4 @@
+3
 from typing import Any
 
 from fastapi import FastAPI, HTTPException, Request, status

src/financial_reports/router.py

@@ -8,7 +8,7 @@ from src.responses import response_list_response
 financial_reports_router = APIRouter()
 
 @financial_reports_router.post("/query")
-async def financial_repoets_query(request: FinancialReportQuery )-> JSONResponse:
+async def financial_repoets_query(request: FinancialReportQuery) -> JSONResponse:
     """
     搜索接口
     """

src/main.py

@@ -11,7 +11,6 @@ import asyncio
 from fastapi import FastAPI
 from datetime import datetime
 
-
 from starlette.middleware.cors import CORSMiddleware
 
 from src.exceptions import register_exception_handler
@@ -25,11 +24,13 @@ from src.financial_reports.router import financial_reports_router
 from src.utils.generate_pinyin_abbreviation import generate_pinyin_abbreviation
 from src.composite.router import composite_router
 
+from src.akshare_data.router import router as akshare_data_router
+
 from xtquant import xtdata
 from src.settings.config import app_configs, settings
 
-import adata
-import akshare as ak
+# import adata
+# import akshare as ak
 
 
 app = FastAPI(**app_configs)
@@ -43,6 +44,7 @@ app.include_router(backtest_router, prefix="/backtest", tags=["回测接口"])
 app.include_router(combine_router, prefix="/combine", tags=["组合接口"])
 app.include_router(financial_reports_router, prefix="/financial-reports", tags=["财报接口"])
 app.include_router(composite_router, prefix="/composite", tags=["vacode组合接口"])
+app.include_router(akshare_data_router, prefix="/akshare", tags=["数据接口"])
 
 if settings.ENVIRONMENT.is_deployed:
     sentry_sdk.init(
@@ -52,11 +54,14 @@ if settings.ENVIRONMENT.is_deployed:
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=settings.CORS_ORIGINS,
-    allow_origin_regex=settings.CORS_ORIGINS_REGEX,
+    # allow_origins=settings.CORS_ORIGINS,
+    # allow_origin_regex=settings.CORS_ORIGINS_REGEX,
+    allow_origins=["*"],
+    allow_origin_regex=None,
     allow_credentials=True,
     allow_methods=("GET", "POST", "PUT", "PATCH", "DELETE", "OPTIONS"),
-    allow_headers=settings.CORS_HEADERS,
+    # allow_headers=settings.CORS_HEADERS,
+    allow_headers=["*"],  # 允许所有请求头
 )
 
 
@@ -64,12 +69,13 @@ app.add_middleware(
 async def root():
     return {"message": "Hello, FastAPI!"}
 
+
 # 定时检查和数据抓取函数
 async def run_data_fetcher():
     print("财报抓取启动")
     while True:
         # 获取数据库中最新记录的时间
-        latest_record = await FinancialReport .all().order_by("-created_at").first()
+        latest_record = await FinancialReport.all().order_by("-created_at").first()
         latest_db_date = latest_record.created_at if latest_record else pd.Timestamp("1970-01-01")
 
         # 将最新数据库日期设为无时区，以便比较
@@ -88,6 +94,7 @@ async def run_data_fetcher():
         # 休眠 12 小时（43200 秒），然后再次检查
         await asyncio.sleep(43200)
 
+
 async def test_liang_hua_ku():
     print("量化库测试函数启动")
 
@@ -100,6 +107,5 @@ async def lifespan():
     asyncio.create_task(run_data_fetcher())
 
 
-
 if __name__ == "__main__":
-    uvicorn.run('src.main:app', host="0.0.0.0", port=8012, reload=True)
+    uvicorn.run('src.main:app', host="127.0.0.1", port=8012, reload=True)

src/settings/config.py

@@ -44,9 +44,3 @@ app_configs: dict[str, Any] = {
     "docs_url": "/api/docs",
 }
 
-# app_configs['debug'] = True
-# if settings.ENVIRONMENT.is_deployed:
-#     app_configs["root_path"] = f"/v{settings.APP_VERSION}"
-#
-# if not settings.ENVIRONMENT.is_debug:
-#     app_configs["openapi_url"] = None  # hide docs