加入了一个基础的时到财报爬虫待补全更新逻辑，加入了万策财报后端的接口待补全模糊查询逻辑，加入了沪深300，中证500，国证2000，沪深京A，财报表的model对象

.env

@@ -1,6 +1,6 @@
-;使用本地docker数据库就将这段代码解开，如何将IP换成本机IP或者localhost
-; DATABASE_URL="mysql://root:123456@10.1.5.219:3306/ftrade"
-; DATABASE_CREATE_URL ="mysql://root:123456@10.1.5.219:3306/ftrade"
+# 使用本地docker数据库就将这段代码解开，如何将IP换成本机IP或者localhost
+# DATABASE_URL="mysql://root:123456@10.1.5.219:3306/ftrade"
+# DATABASE_CREATE_URL ="mysql://root:123456@10.1.5.219:3306/ftrade"
 
 DATABASE_URL="mysql://wangche:fN7sXX8saiQKXWbG@cqxqg.tech:3308/wangche"
 DATABASE_CREATE_URL ="mysql://wangche:fN7sXX8saiQKXWbG@cqxqg.tech:3308/wangche"

.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="ftrade_back" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (wance_data)" project-jdk-type="Python SDK" />
 </project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

.idea/wance_data.iml

@@ -1,8 +1,10 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="ftrade_back" jdkType="Python SDK" />
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
   <component name="PackageRequirementsSettings">

.vscode/launch.json

@@ -0,0 +1,17 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python 调试程序: FastAPI",
+            "type": "debugpy",
+            "request": "launch",
+            "module": "uvicorn",
+            "args": [
+                "src.main:app",
+                "--reload",
+                "--port", "8012"
+            ],
+            "jinja": true
+        }
+    ]
+}

src/financial_reports/mappings.py

@@ -0,0 +1,36 @@
+"""
+    映射表， 为空则返回none表示不筛选此字段
+"""
+
+# 时间选择映射表
+year_mapping = {
+    """
+    为空则返回none
+    """
+    "2024": 2024,
+}
+
+# 股票池映射表
+stock_pool_mapping = {
+    "000300.SH": "000300.SH",
+    "000905.SH": "000905.SH",
+    "399303.SZ": "399303.SZ",
+    "large_mv": "large_mv",
+    "medium_mv": "medium_mv",
+    "small_mv": "small_mv",
+}
+
+# 财报周期映射
+period_mapping = {
+    1: "一季度报告",         # 一季度报告
+    2: "半年度报告",         # 半年度报告
+    3: "三季度报告",         # 三季度报告
+    4: "正式年报",           # 正式年报
+    9: "一季度业绩预告",     # 一季度业绩预告
+    10: "半年度业绩预告",    # 半年度业绩预告
+    11: "三季度业绩预告",    # 三季度业绩预告
+    12: "年度业绩预告",      # 年度业绩预告
+    5: "一季度业绩快报",     # 一季度业绩快报
+    6: "半年度业绩快报",     # 半年度业绩快报
+    7: "三季度业绩快报"      # 三季度业绩快报
+}

src/financial_reports/router.py

@@ -0,0 +1,13 @@
+from fastapi import APIRouter
+from fastapi.responses import JSONResponse
+
+from src.financial_reports.schemas import *
+from src.financial_reports.service import *
+
+financial_reports_router = APIRouter()
+
+@financial_reports_router.post("/query")
+async def financial_repoets_query(request: FinancialReportQuery )-> JSONResponse:
+    result = await financial_reports_query_service(request)
+
+    return result

src/financial_reports/schemas.py

@@ -0,0 +1,16 @@
+from typing import List, Optional, Any, Dict
+
+from pydantic import BaseModel, Field
+
+class FinancialReportQuery(BaseModel):
+    pageNo: int = Field(..., ge=1, le=1000, description="页码，必须大于等于1且小于等于1000")
+    pageSize: int = Field(..., ge=1, le=50, description="每页条数，必须大于等于1且小于等于50")
+
+    # 可选参数
+    year: Optional[int] = Field(None, ge=1, le=2100, description="时间选择，必须为正整数或特定年份且小于等于2100，或留空")
+    stockPoolCode: Optional[str] = Field(None, max_length=20, min_length=1, description="股票池，限制最大长度为20，限制最小长度为1，或留空")
+    period: Optional[int] = Field(None, ge=1, le=50, description="财报周期，必须大于等于1且小于等于50，或留空")
+    revenueYoyType: Optional[int] = Field(None, ge=1, le=10, description="营业收入同比，必须大于等于1且小于等于10，或留空")
+    nIncomeYoyType: Optional[int] = Field(None, ge=1, le=10, description="净利润同比，必须大于等于1且小于等于10，或留空")
+    revenueYoyTop10: Optional[int] = Field(None, ge=1, le=10, description="营业收入行业前10%，必须大于等于1且小于等于10，或留空")
+    

src/financial_reports/service.py

@@ -0,0 +1,134 @@
+import json
+import adata
+
+from math import ceil
+from typing import Any, Dict
+from fastapi import Request, HTTPException, BackgroundTasks
+from tortoise.expressions import Subquery,Q
+from tortoise.contrib.pydantic import pydantic_model_creator
+
+from src.models.financial_reports import *
+from src.models.stock_hu_shen300 import *
+from src.models.stock_zhong_zheng_500 import *
+from src.models.stock_guo_zheng_2000 import *
+from src.models.stock_hu_shen_jing_a import *
+from src.financial_reports.schemas import *
+from src.utils.paginations import *
+from src.financial_reports.mappings import *
+
+
+# 创建一个不包含 "created_at" 字段的 Pydantic 模型用于响应
+FinancialReport_Pydantic = pydantic_model_creator(FinancialReport, exclude=("created_at",))
+
+async def financial_reports_query_service(
+    request: FinancialReportQuery
+) -> PaginationPydantic:
+    """
+    根据选择器和关键词查询财报，并进行分页
+    """
+    # 构建查询集，这里假设财报数据模型为 FinancialReport
+    query_set: QuerySet = FinancialReport.all()
+
+    try:
+       # 年度映射
+        if request.year:
+            mapped_year = year_mapping.get(request.year)
+            if mapped_year is not None:
+                query_set =  query_set.filter(year=mapped_year)
+            else:
+                raise ValueError("无效的年份参数")
+
+        # 股票池映射
+        if request.stockPoolCode is None:
+            # 未提供股票池代码，返回所有记录
+            pass
+        else:
+            # 获取映射值，如果不存在则返回 None
+            mapped_stock_pool = stock_pool_mapping.get(request.stockPoolCode)
+            
+            # 检查 mapped_stock_pool 是否为 None（即不在映射表中）
+            if mapped_stock_pool is None:
+                # 如果 stockPoolCode 不在映射表中，抛出无效股票池参数错误
+                raise ValueError("无效的股票池参数")
+            
+            # 如果存在有效的映射值，执行相应的过滤
+            elif mapped_stock_pool == "000300.SH":
+                subquery = await StockHuShen300.filter().values_list('code', flat=True)
+                query_set = query_set.filter(stock_code__in=subquery)
+            elif mapped_stock_pool == "000905.SH":
+                subquery = await StockZhongZheng500.filter().values_list('code', flat=True)
+                query_set = query_set.filter(stock_code__in=subquery)
+            elif mapped_stock_pool == "399303.SZ":
+                subquery = await StockGuoZheng2000.filter().values_list('code', flat=True)
+                query_set = query_set.filter(stock_code__in=subquery)
+            elif mapped_stock_pool in ["large_mv", "medium_mv", "small_mv"]:
+                # 先获取所有有总市值的关联的股票代码
+                subquery = await StockHuShenJingA.filter(total_market_value__isnull=False).values_list('code', 'total_market_value')
+
+                # 转换为 DataFrame 或者直接进行排序
+                stock_list = sorted(subquery, key=lambda x: x[1], reverse=True)  # 按 total_market_value 降序排序
+
+                total_count = len(stock_list)
+
+                if mapped_stock_pool == "large_mv":
+                    # 获取前 30% 的数据
+                    limit_count = ceil(total_count * 0.3)
+                    selected_stocks = [stock[0] for stock in stock_list[:limit_count]]
+                elif mapped_stock_pool == "medium_mv":
+                    # 获取中间 40% 的数据
+                    start_offset = ceil(total_count * 0.3)
+                    limit_count = ceil(total_count * 0.4)
+                    selected_stocks = [stock[0] for stock in stock_list[start_offset:start_offset + limit_count]]
+                elif mapped_stock_pool == "small_mv":
+                    # 获取后 30% 的数据
+                    start_offset = ceil(total_count * 0.7)
+                    selected_stocks = [stock[0] for stock in stock_list[start_offset:]]
+
+                # 对 FinancialReport 表进行筛选
+                query_set = query_set.filter(stock_code__in=selected_stocks)
+
+        # 财报周期映射
+        if request.period is not None:
+            mapped_period = period_mapping.get(request.period)
+            if mapped_period is not None:
+                # 如果映射到有效的周期，则进行过滤
+                query_set = query_set.filter(period=mapped_period)
+            else:
+                # 如果找不到有效的映射，抛出错误
+                raise ValueError("无效的财报周期参数")
+
+        # 检查是否所有筛选条件都为空
+        if not request.revenueYoyType and not request.nIncomeYoyType and not request.revenueYoyTop10:
+            # 如果全部为空，则按 date 和 created_at 降序排序
+            query_set = query_set.order_by("-date", "-created_at")
+
+        # 筛选 revenueYoyType，如果是 1 则筛选 revenue_yoy 大于 10.0 的记录
+        if request.revenueYoyType == 1:
+            query_set = query_set.filter(revenue_yoy__gt=10.0).order_by("-revenue_yoy")
+
+        # 筛选 nIncomeYoyType，如果是 1 则筛选 nincome_yoy 大于 10.0 的记录
+        elif request.nIncomeYoyType == 1:
+            query_set = query_set.filter(nincome_yoy__gt=10.0).order_by("-nincome_yoy")
+        
+        # 如果 revenueYoyTop10 为 1，则筛选 revenue_yoy 前 10% 的记录
+        elif request.revenueYoyTop10 == 1:
+            # 计算前 10% 的数量
+            total_count = await FinancialReport.all().count()  # 获取总记录数
+            limit_count = ceil(total_count * 0.1)
+            
+            # 按 revenue_yoy 降序排列，获取前 10% 记录
+            query_set = query_set.order_by("-revenue_yoy").limit(limit_count).order_by("-revenue_yoy")
+        
+
+        # 调用分页函数进行分页处理
+        params = Params(page=request.pageNo, size=request.pageSize) #parms作用是传页码和页面大小
+        result = await pagination(pydantic_model=FinancialReport_Pydantic,
+                                query_set=query_set,
+                                params=params)
+
+        return result
+
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="内部服务器错误")

src/main.py

@@ -6,7 +6,12 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
 import sentry_sdk
 import uvicorn
+import pandas as pd
+import asyncio
 from fastapi import FastAPI
+from datetime import datetime
+
+
 from starlette.middleware.cors import CORSMiddleware
 
 from src.exceptions import register_exception_handler
@@ -14,11 +19,15 @@ from src.tortoises import register_tortoise_orm
 from src.xtdata.router import router as xtdata_router
 from src.backtest.router import router as backtest_router
 from src.combination.router import router as combine_router
+from src.models.financial_reports import FinancialReport 
+from src.utils.update_financial_reports_spider import combined_search_and_list
+from src.financial_reports.router import financial_reports_router
 
 from xtquant import xtdata
 from src.settings.config import app_configs, settings
 
-
+import adata
+import akshare as ak
 
 
 app = FastAPI(**app_configs)
@@ -30,7 +39,7 @@ register_exception_handler(app)
 app.include_router(xtdata_router, prefix="/getwancedata", tags=["数据接口"])
 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"])
 
 if settings.ENVIRONMENT.is_deployed:
     sentry_sdk.init(
@@ -48,12 +57,46 @@ app.add_middleware(
 )
 
 
-
-
 @app.get("/")
 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_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
+        latest_db_date = latest_db_date.replace(tzinfo=None)
+
+        # 当前时间
+        current_time = pd.Timestamp(datetime.now()).replace(tzinfo=None)
+
+       # 检查当前时间是否超过数据库最新记录时间 12 个小时
+        if (current_time - latest_db_date).total_seconds() > 43200: 
+            print("启动财报数据抓取...")
+            await combined_search_and_list()
+        else:
+            print("未满足条件，跳过抓取任务。")
+
+        # 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")
+   
+
+
+# 启动时立即运行检查任务
+@app.on_event("startup")
+async def lifespan():
+     # 启动时将任务放入后台，不阻塞启动流程
+    asyncio.create_task(test_liang_hua_ku())
+    asyncio.create_task(run_data_fetcher())
+    
 
 
 if __name__ == "__main__":

src/models/financial_reports.py

@@ -0,0 +1,32 @@
+from tortoise import fields, Model
+
+class FinancialReport (Model):
+    """
+    财报数据
+    """
+    id = fields.IntField(pk=True, description="自增主键")  # 自增主键
+    date = fields.DateField(description="日期")  # 日期
+    period = fields.CharField(max_length=50, description="报告期")  # 报告期
+    year = fields.IntField(description="年份")  # 年份
+    stock_code =   fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    stock_name = fields.CharField(max_length=50, description="股票名称")  # 股票名称
+    industry_code = fields.CharField(max_length=10, null=True, description="行业代码")  # 行业代码
+    industry_name = fields.CharField(max_length=50, null=True, description="行业名称")  # 行业名称
+    pdf_name = fields.CharField(max_length=100, null=True, description="PDF 报告名称")  # PDF 报告名称
+    pdf_url = fields.CharField(max_length=255, null=True, description="PDF 报告链接")  # PDF 报告链接
+    revenue = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="收入")  # 收入
+    revenue_yoy = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="收入同比增长")  # 收入同比增长
+    pr_of_today = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="今日涨跌幅")  # 今日涨跌幅
+    pr_of_after_1_day = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="次日涨跌幅")  # 次日涨跌幅
+    pr_of_after_1_week = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="一周后涨跌幅")  # 一周后涨跌幅
+    pr_of_after_1_month = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="一月后涨跌幅")  # 一月后涨跌幅
+    pr_of_after_6_month = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="六个月后涨跌幅")  # 六个月后涨跌幅
+    pr_of_that_year = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="年初至今涨跌幅")  # 年初至今涨跌幅
+    nincome_yoy_lower_limit = fields.CharField(max_length=10, null=True, description="净利润同比增长下限")  # 净利润同比增长下限
+    nincome_yoy_upper_limit = fields.CharField(max_length=10, null=True, description="净利润同比增长上限")  # 净利润同比增长上限
+    nincome = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="净利润")  # 净利润
+    nincome_yoy = fields.DecimalField(max_digits=15, decimal_places=2, null=True, description="净利润同比增长率")  # 净利润同比增长率
+    created_at = fields.DatetimeField(auto_now_add=True, description="创建时间")  # 创建时间，自动生成当前时间
+
+    class Meta:
+        table = "financial_reports"

src/models/stock_guo_zheng_2000.py

@@ -0,0 +1,12 @@
+from tortoise import fields, Model
+
+class StockGuoZheng2000(Model):
+    """
+    国证2000成分股数据
+    """
+    code = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    name = fields.CharField(max_length=50, description="股票名称")  # 股票名称
+    included_date = fields.CharField(max_length=20, description="纳入日期")  # 纳入日期
+
+    class Meta:
+        table = "stock_guo_zheng_2000"

src/models/stock_hu_shen300.py

@@ -0,0 +1,12 @@
+from tortoise import fields, Model
+
+class StockHuShen300(Model):
+    """
+    沪深300成分股数据
+    """
+    symbol = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    code = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    name = fields.CharField(max_length=50, description="股票名称")  # 股票名称
+
+    class Meta:
+        table = "stock_hu_shen_300"

src/models/stock_hu_shen_jing_a.py

@@ -0,0 +1,32 @@
+from tortoise import fields, Model
+
+class StockHuShenJingA(Model):
+    """
+    沪深京 A 股实时行情数据
+    """
+    seq = fields.IntField(description="序号")  # 序号
+    code = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    name = fields.CharField(max_length=50, description="股票名称")  # 股票名称
+    latest_price = fields.FloatField(null=True, description="最新价格")  # 最新价格
+    change_percent = fields.FloatField(null=True, description="涨跌幅")  # 涨跌幅
+    change_amount = fields.FloatField(null=True, description="涨跌额")  # 涨跌额
+    volume = fields.FloatField(null=True, description="成交量")  # 成交量
+    turnover = fields.FloatField(null=True, description="成交额")  # 成交额
+    amplitude = fields.FloatField(null=True, description="振幅")  # 振幅
+    high = fields.FloatField(null=True, description="最高价")  # 最高价
+    low = fields.FloatField(null=True, description="最低价")  # 最低价
+    open = fields.FloatField(null=True, description="今开价")  # 今开价
+    previous_close = fields.FloatField(null=True, description="昨收价")  # 昨收价
+    volume_ratio = fields.FloatField(null=True, description="量比")  # 量比
+    turnover_rate = fields.FloatField(null=True, description="换手率")  # 换手率
+    pe_dynamic = fields.FloatField(null=True, description="市盈率-动态")  # 市盈率-动态
+    pb = fields.FloatField(null=True, description="市净率")  # 市净率
+    total_market_value = fields.FloatField(null=True, description="总市值")  # 总市值
+    circulating_market_value = fields.FloatField(null=True, description="流通市值")  # 流通市值
+    rise_speed = fields.FloatField(null=True, description="涨速")  # 涨速
+    five_minute_change = fields.FloatField(null=True, description="5分钟涨跌幅")  # 5分钟涨跌幅
+    sixty_day_change = fields.FloatField(null=True, description="60日涨跌幅")  # 60日涨跌幅
+    year_to_date_change = fields.FloatField(null=True, description="年初至今涨跌幅")  # 年初至今涨跌幅
+
+    class Meta:
+        table = "stock_hu_shen_jing_a"

src/models/stock_zhong_zheng_500.py

@@ -0,0 +1,12 @@
+from tortoise import fields, Model
+
+class StockZhongZheng500(Model):
+    """
+    中证500成分股数据
+    """
+    symbol = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    code = fields.CharField(max_length=10, description="股票代码")  # 股票代码
+    name = fields.CharField(max_length=50, description="股票名称")  # 股票名称
+
+    class Meta:
+        table = "stock_zhong_zheng_500"

src/tortoises.py

@@ -67,7 +67,13 @@ models = [
     "src.models.stock_data_processing",
     "src.models.wance_data_stock",
     "src.models.wance_data_storage_backtest",
-    "src.models.user_combination_history"
+    "src.models.user_combination_history",
+    "src.models.financial_reports",
+    "src.models.stock_hu_shen300",
+    "src.models.stock_zhong_zheng_500",
+    "src.models.stock_guo_zheng_2000",
+    "src.models.stock_hu_shen_jing_a"
+
     
 ]
 

src/utils/paginations.py

@@ -1,12 +1,12 @@
-from typing import Generic, Optional, Sequence, TypeVar
-
+from typing import Type, TypeVar, Generic, Sequence, Optional, Callable, Awaitable
 import math
 from fastapi import Query
 from pydantic import BaseModel
 from tortoise.queryset import QuerySet
+from tortoise.models import Model
 
-T = TypeVar("T")
-
+T = TypeVar('T', bound=BaseModel)
+M = TypeVar('M', bound=Model)
 
 class PaginationPydantic(BaseModel, Generic[T]):
     """分页模型"""
@@ -18,57 +18,49 @@ class PaginationPydantic(BaseModel, Generic[T]):
     total_pages: int
     data: Sequence[T]
 
-
 class Params(BaseModel):
     """传参"""
-    # 设置默认值为1，不能够小于1
     page: int = Query(1, ge=1, description="Page number")
-
-    # 设置默认值为10，最大为100
     size: int = Query(10, gt=0, le=200, description="Page size")
-
-    # 默认值None表示选传
     order_by: Optional[str] = Query(None, max_length=32, description="Sort key")
 
-
-async def pagination(pydantic_model, query_set: QuerySet, params: Params, callback=None):
+async def pagination(
+    pydantic_model: Type[T],
+    query_set: QuerySet[M],
+    params: Params,
+    callback: Optional[Callable[[QuerySet[M]], Awaitable[QuerySet[M]]]] = None
+) -> PaginationPydantic[T]:
     """分页响应"""
-    """
-    pydantic_model: Pydantic model
-    query_set: QuerySet
-    params: Params
-    callback: if you want to do something for query_set,it will be useful.
-    """
     page: int = params.page
     size: int = params.size
-    order_by: str = params.order_by
+    order_by: Optional[str] = params.order_by
     total = await query_set.count()
 
-    # 通过总数和每页数量计算出总页数
-    total_pages = math.ceil(total / size)
+    # 计算总页数
+    total_pages = math.ceil(total / size) if total > 0 else 1
 
-    if page > total_pages and total:  # 排除查询集为空时报错，即total=0时
+    if page > total_pages and total > 0:
         raise ValueError("页数输入有误")
 
-    # 排序后分页
+    # 排序
     if order_by:
-        order_by = order_by.split(',')
-        query_set = query_set.order_by(*order_by)
+        order_by_fields = order_by.split(',')
+        query_set = query_set.order_by(*order_by_fields)
 
     # 分页
-    query_set = query_set.offset((page - 1) * size)  # 页数 * 页面大小=偏移量
-    query_set = query_set.limit(size)
+    query_set = query_set.offset((page - 1) * size).limit(size)
 
+    # 回调处理
     if callback:
-        """对查询集操作"""
         query_set = await callback(query_set)
 
-    # query_set = await query_set
+    # 获取数据
     data = await pydantic_model.from_queryset(query_set)
-    return PaginationPydantic(**{
-        "total": total,
-        "page": page,
-        "size": size,
-        "total_pages": total_pages,
-        "data": data,
-    })
+
+    return PaginationPydantic[T](
+        total=total,
+        page=page,
+        size=size,
+        total_pages=total_pages,
+        data=data
+    )

src/utils/update_financial_reports_spider.py

@@ -0,0 +1,202 @@
+"""
+TO DO待完善全体数据更新逻辑
+"""
+
+
+import time
+import requests
+import pandas as pd
+from fastapi import APIRouter
+from src.models.financial_reports import FinancialReport   # 确保路径正确
+
+async def combined_search_and_list():
+    # 分页参数
+    pageNo = 1
+    pageSize = 50
+    selector_url = "https://www.shidaotec.com/api/research/getFinaResearchPageList"
+
+    # 请求第一页获取总记录数
+    response = requests.get(selector_url, params={
+        "pageNo": pageNo,
+        "pageSize": pageSize,
+        "year": "2024",
+        "type": ""
+    })
+    response.raise_for_status()
+    selector_data = response.json()
+
+    # 获取总记录数和数据库已有记录数
+    total_records = selector_data.get("data", {}).get("total", 0)
+    db_record_count = await FinancialReport .all().count()
+    remaining_insert_count = total_records - db_record_count
+
+    print(f"总记录数: {total_records}，数据库已有记录数: {db_record_count}，需要插入: {remaining_insert_count}")
+
+    # 如果已有记录数与总记录数相同，则直接结束函数
+    if remaining_insert_count <= 0:
+        print("数据库已包含所有记录，无需插入新数据。")
+        return
+
+    # 获取数据库中最新的记录
+    latest_record = await FinancialReport .all().order_by("-date").first()
+    latest_db_date = latest_record.date if latest_record else None
+    latest_db_date = pd.Timestamp(latest_db_date)
+
+    # 缓存数据
+    all_data = []
+
+    # 开始分页请求，直到遇到比数据库最新日期更早的数据
+    while True:
+        try:
+            # 请求当前页数据
+            response = requests.get(selector_url, params={
+                "pageNo": pageNo,
+                "pageSize": pageSize,
+                "year": "2024",
+                "type": ""
+            })
+            response.raise_for_status()
+            selector_data = response.json()
+            fina_data_list = selector_data.get("data", {}).get("list", [])
+
+            # 如果页数据为空，停止循环
+            if not fina_data_list:
+                print("No more data available.")
+                break
+
+            # 缓存本页数据
+            for record in fina_data_list:
+                record.pop("seq", None)  # 移除不必要的字段
+                record = {k: (None if v == "-" else v) for k, v in record.items()}
+                all_data.append(record)
+
+            # 检查本页第一条数据日期，决定是否继续请求
+            first_record_date = pd.to_datetime(fina_data_list[0]["date"])
+            if latest_db_date and first_record_date < latest_db_date:
+                print(f"Data on page {pageNo} is older than the latest entry in the database. Stopping requests.")
+                break  # 停止请求
+
+            print(f"第 {pageNo} 页成功获取并缓存 {len(fina_data_list)} 条记录")
+            pageNo += 1
+            time.sleep(2)  # 请求间隔
+
+        except requests.RequestException as e:
+            print(f"Error fetching data for page {pageNo}: {e}")
+            break
+        except Exception as e:
+            print(f"Unexpected error on page {pageNo}: {e}")
+            break
+
+    # 批量查询数据库中已存在的记录
+    existing_records = await FinancialReport .filter(
+        date__in=[record["date"] for record in all_data],
+        period__in=[record["period"] for record in all_data],
+        stock_code__in=[record["stockCode"] for record in all_data]
+    ).all()
+
+    # 将已存在记录存入集合以便于后续检查
+    existing_data_set = {
+        (record.date, record.period, record.stock_code, record.stock_name,
+         record.industry_code, record.industry_name, record.pdf_name,
+         record.pdf_url, record.revenue, record.revenue_yoy,
+         record.pr_of_today, record.pr_of_after_1_day,
+         record.pr_of_after_1_week, record.pr_of_after_1_month,
+         record.pr_of_after_6_month, record.pr_of_that_year,
+         record.nincome_yoy_lower_limit, record.nincome_yoy_upper_limit,
+         record.nincome, record.nincome_yoy)
+        for record in existing_records
+    }
+
+    # 开始处理缓存的数据，插入数据库
+    success_count = 0
+    records_to_insert = []
+
+    for record in all_data[:]:  # 使用切片拷贝以避免在迭代时修改原始列表
+        record_date = pd.to_datetime(record["date"])
+
+        # 检查该记录是否已存在于数据库中
+        if (record["date"], record["period"], record["stockCode"], record["stockName"],
+            record["industryCode"], record["industryName"], record["pdfName"], record["pdfUrl"],
+            record["revenue"], record["revenueYoy"], record["prOfToday"], record["prOfAfter1Day"],
+            record["prOfAfter1Week"], record["prOfAfter1Month"], record["prOfAfter6Month"],
+            record["prOfThatYear"], record["nincomeYoyLowerLimit"], record["nincomeYoyUpperLimit"],
+            record["nincome"], record["nincomeYoy"]) in existing_data_set:
+            print(f"Skipping existing record: {record}")  # 打印已跳过的记录
+            continue  # 跳过已存在的记录
+
+        # 打印即将插入的数据
+        print(f"Inserting record: {record}")
+
+        if record_date >= latest_db_date:
+            # 创建待插入的 FinancialReport  对象并添加到列表
+            try:
+                records_to_insert.append(
+                    FinancialReport (
+                        date=record["date"],
+                        period=record["period"],
+                        year=int(record["year"]),
+                        stock_code=record["stockCode"],
+                        stock_name=record["stockName"],
+                        industry_code=record["industryCode"] if record["industryCode"] else None,
+                        industry_name=record["industryName"] if record["industryName"] else None,
+                        pdf_name=record["pdfName"] if record["pdfName"] else None,
+                        pdf_url=record["pdfUrl"] if record["pdfUrl"] else None,
+                        revenue=float(record["revenue"]) if record["revenue"] else None,
+                        revenue_yoy=float(record["revenueYoy"]) if record["revenueYoy"] else None,
+                        pr_of_today=float(record["prOfToday"]) if record["prOfToday"] else None,
+                        pr_of_after_1_day=float(record["prOfAfter1Day"]) if record["prOfAfter1Day"] else None,
+                        pr_of_after_1_week=float(record["prOfAfter1Week"]) if record["prOfAfter1Week"] else None,
+                        pr_of_after_1_month=float(record["prOfAfter1Month"]) if record["prOfAfter1Month"] else None,
+                        pr_of_after_6_month=float(record["prOfAfter6Month"]) if record["prOfAfter6Month"] else None,
+                        pr_of_that_year=float(record["prOfThatYear"]) if record["prOfThatYear"] else None,
+                        nincome_yoy_lower_limit=record["nincomeYoyLowerLimit"] if record["nincomeYoyLowerLimit"] else None,
+                        nincome_yoy_upper_limit=record["nincomeYoyUpperLimit"] if record["nincomeYoyUpperLimit"] else None,
+                        nincome=float(record["nincome"]) if record["nincome"] else None,
+                        nincome_yoy=float(record["nincomeYoy"]) if record["nincomeYoy"] else None
+                    )
+                )
+                success_count += 1
+
+            except Exception as e:
+                print(f"Error processing record {record}: {e}")  # 输出处理错误
+
+        # 成功插入所需条数后停止
+        if success_count >= remaining_insert_count:
+            print("this riqi:" + str(latest_db_date))
+            break
+
+    # 批量插入到数据库
+    if records_to_insert:
+        try:
+            await FinancialReport .bulk_create(records_to_insert)
+            print(f"成功插入 {len(records_to_insert)} 条记录")
+        except Exception as e:
+            print(f"Error during bulk insert: {e}")
+
+
+    # 去重步骤
+    try:
+        # 查找基于 date、period 和 stock_code 的重复记录
+        duplicates = await FinancialReport.raw("""
+            SELECT id FROM financial_reports WHERE id NOT IN (
+                SELECT id FROM (
+                    SELECT MAX(id) AS id
+                    FROM financial_reports
+                    GROUP BY date, period, stock_code
+                ) AS temp
+            )
+        """)
+        
+        duplicate_ids = [record.id for record in duplicates]
+        
+        if duplicate_ids:
+            # 删除较旧的重复记录
+            await FinancialReport.filter(id__in=duplicate_ids).delete()
+            print(f"删除了 {len(duplicate_ids)} 条重复记录")
+        else:
+            print("未发现重复记录")
+        
+    except Exception as e:
+        print(f"去重过程中出错: {e}")
+
+    return {"message": "数据获取、插入和去重已完成"}