fix: fix stock_lhb_yytj_sina

akfamily · May 9, 2024 · 149909a · 149909a
1 parent 0a12cb6
commit 149909a
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diff --git a/akshare/stock_feature/stock_lhb_sina.py b/akshare/stock_feature/stock_lhb_sina.py
@@ -1,10 +1,11 @@
 #!/usr/bin/env python
 # -*- coding:utf-8 -*-
 """
-Date: 2024/2/26 15:00
+Date: 2024/5/10 00:00
 Desc: 新浪财经-龙虎榜
 https://vip.stock.finance.sina.com.cn/q/go.php/vInvestConsult/kind/lhb/index.phtml
 """
+
 from io import StringIO
 
 import pandas as pd
@@ -39,16 +40,27 @@ def stock_lhb_detail_daily_sina(date: str = "20240222") -> pd.DataFrame:
         big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
     big_df["股票代码"] = big_df["股票代码"].astype(str).str.zfill(6)
     del big_df["查看详情"]
-    big_df.columns = ["序号", "股票代码", "股票名称", "收盘价", "对应值", "成交量", "成交额", "指标"]
-    big_df['收盘价'] = pd.to_numeric(big_df['收盘价'], errors="coerce")
-    big_df['对应值'] = pd.to_numeric(big_df['对应值'], errors="coerce")
-    big_df['成交量'] = pd.to_numeric(big_df['成交量'], errors="coerce")
-    big_df['成交额'] = pd.to_numeric(big_df['成交额'], errors="coerce")
+    big_df.columns = [
+        "序号",
+        "股票代码",
+        "股票名称",
+        "收盘价",
+        "对应值",
+        "成交量",
+        "成交额",
+        "指标",
+    ]
+    big_df["收盘价"] = pd.to_numeric(big_df["收盘价"], errors="coerce")
+    big_df["对应值"] = pd.to_numeric(big_df["对应值"], errors="coerce")
+    big_df["成交量"] = pd.to_numeric(big_df["成交量"], errors="coerce")
+    big_df["成交额"] = pd.to_numeric(big_df["成交额"], errors="coerce")
     return big_df
 
 
-def _find_last_page(url: str = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/ggtj/index.phtml",
-                    recent_day: str = "60"):
+def _find_last_page(
+    url: str = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/ggtj/index.phtml",
+    recent_day: str = "60",
+):
     params = {
         "last": recent_day,
         "p": "1",
@@ -57,7 +69,7 @@ def _find_last_page(url: str = "https://vip.stock.finance.sina.com.cn/q/go.php/v
     soup = BeautifulSoup(r.text, "lxml")
     try:
         previous_page = int(soup.find_all(attrs={"class": "page"})[-2].text)
-    except Exception as e:
+    except:  # noqa: E722
         previous_page = 1
     if previous_page != 1:
         while True:
@@ -66,7 +78,7 @@ def _find_last_page(url: str = "https://vip.stock.finance.sina.com.cn/q/go.php/v
                 "p": previous_page,
             }
             r = requests.get(url, params=params)
-            soup = BeautifulSoup(r.text, "lxml")
+            soup = BeautifulSoup(r.text, features="lxml")
             last_page = int(soup.find_all(attrs={"class": "page"})[-2].text)
             if last_page != previous_page:
                 previous_page = last_page
@@ -76,44 +88,56 @@ def _find_last_page(url: str = "https://vip.stock.finance.sina.com.cn/q/go.php/v
     return previous_page
 
 
-def stock_lhb_ggtj_sina(recent_day: str = "30") -> pd.DataFrame:
+def stock_lhb_ggtj_sina(symbol: str = "5") -> pd.DataFrame:
     """
     龙虎榜-个股上榜统计
     https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/ggtj/index.phtml
-    :param recent_day: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
-    :type recent_day: str
-    :return: 龙虎榜-每日详情
+    :param symbol: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
+    :type symbol: str
+    :return: 龙虎榜-个股上榜统计
     :rtype: pandas.DataFrame
     """
-    url = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/ggtj/index.phtml"
-    last_page_num = _find_last_page(url, recent_day)
+    url = (
+        "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/ggtj/index.phtml"
+    )
+    last_page_num = _find_last_page(url, symbol)
     big_df = pd.DataFrame()
     tqdm = get_tqdm()
     for page in tqdm(range(1, last_page_num + 1), leave=False):
         params = {
-            "last": recent_day,
+            "last": symbol,
             "p": page,
         }
         r = requests.get(url, params=params)
         temp_df = pd.read_html(StringIO(r.text))[0].iloc[0:, :]
-        big_df = pd.concat([big_df, temp_df], ignore_index=True)
+        big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
     big_df["股票代码"] = big_df["股票代码"].astype(str).str.zfill(6)
-    big_df.columns = ["股票代码", "股票名称", "上榜次数", "累积购买额", "累积卖出额", "净额", "买入席位数",
-                      "卖出席位数"]
+    big_df.columns = [
+        "股票代码",
+        "股票名称",
+        "上榜次数",
+        "累积购买额",
+        "累积卖出额",
+        "净额",
+        "买入席位数",
+        "卖出席位数",
+    ]
     return big_df
 
 
-def stock_lhb_yytj_sina(recent_day: str = "5") -> pd.DataFrame:
+def stock_lhb_yytj_sina(symbol: str = "5") -> pd.DataFrame:
     """
     龙虎榜-营业部上榜统计
     https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/yytj/index.phtml
-    :param recent_day: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
-    :type recent_day: str
+    :param symbol: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
+    :type symbol: str
     :return: 龙虎榜-营业部上榜统计
     :rtype: pandas.DataFrame
     """
-    url = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/yytj/index.phtml"
-    last_page_num = _find_last_page(url, recent_day)
+    url = (
+        "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/yytj/index.phtml"
+    )
+    last_page_num = _find_last_page(url, symbol)
     big_df = pd.DataFrame()
     tqdm = get_tqdm()
     for page in tqdm(range(1, last_page_num + 1), leave=False):
@@ -124,29 +148,39 @@ def stock_lhb_yytj_sina(recent_day: str = "5") -> pd.DataFrame:
         r = requests.get(url, params=params)
         temp_df = pd.read_html(StringIO(r.text))[0].iloc[0:, :]
         big_df = pd.concat([big_df, temp_df], ignore_index=True)
-    big_df.columns = ["营业部名称", "上榜次数", "累积购买额", "买入席位数", "累积卖出额", "卖出席位数", "买入前三股票"]
+    big_df.columns = [
+        "营业部名称",
+        "上榜次数",
+        "累积购买额",
+        "买入席位数",
+        "累积卖出额",
+        "卖出席位数",
+        "买入前三股票",
+    ]
     big_df["上榜次数"] = pd.to_numeric(big_df["上榜次数"], errors="coerce")
     big_df["买入席位数"] = pd.to_numeric(big_df["买入席位数"], errors="coerce")
     big_df["卖出席位数"] = pd.to_numeric(big_df["卖出席位数"], errors="coerce")
     return big_df
 
 
-def stock_lhb_jgzz_sina(recent_day: str = "5") -> pd.DataFrame:
+def stock_lhb_jgzz_sina(symbol: str = "5") -> pd.DataFrame:
     """
     龙虎榜-机构席位追踪
     https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/jgzz/index.phtml
-    :param recent_day: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
-    :type recent_day: str
+    :param symbol: choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;}
+    :type symbol: str
     :return: 龙虎榜-机构席位追踪
     :rtype: pandas.DataFrame
     """
-    url = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/jgzz/index.phtml"
-    last_page_num = _find_last_page(url, recent_day)
+    url = (
+        "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/jgzz/index.phtml"
+    )
+    last_page_num = _find_last_page(url, symbol)
     big_df = pd.DataFrame()
     tqdm = get_tqdm()
     for page in tqdm(range(1, last_page_num + 1), leave=False):
         params = {
-            "last": recent_day,
+            "last": symbol,
             "p": page,
         }
         r = requests.get(url, params=params)
@@ -157,7 +191,15 @@ def stock_lhb_jgzz_sina(recent_day: str = "5") -> pd.DataFrame:
     big_df["股票代码"] = big_df["股票代码"].astype(str).str.zfill(6)
     del big_df["当前价"]
     del big_df["涨跌幅"]
-    big_df.columns = ["股票代码", "股票名称", "累积买入额", "买入次数", "累积卖出额", "卖出次数", "净额"]
+    big_df.columns = [
+        "股票代码",
+        "股票名称",
+        "累积买入额",
+        "买入次数",
+        "累积卖出额",
+        "卖出次数",
+        "净额",
+    ]
     big_df["买入次数"] = pd.to_numeric(big_df["买入次数"], errors="coerce")
     big_df["卖出次数"] = pd.to_numeric(big_df["卖出次数"], errors="coerce")
     return big_df
@@ -170,15 +212,17 @@ def stock_lhb_jgmx_sina() -> pd.DataFrame:
     :return: 龙虎榜-机构席位成交明细
     :rtype: pandas.DataFrame
     """
-    url = "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/jgmx/index.phtml"
+    url = (
+        "https://vip.stock.finance.sina.com.cn/q/go.php/vLHBData/kind/jgmx/index.phtml"
+    )
     params = {
         "p": "1",
     }
     r = requests.get(url, params=params)
     soup = BeautifulSoup(r.text, features="lxml")
     try:
         last_page_num = int(soup.find_all(attrs={"class": "page"})[-2].text)
-    except:
+    except:  # noqa: E722
         last_page_num = 1
     big_df = pd.DataFrame()
     tqdm = get_tqdm()
@@ -190,27 +234,30 @@ def stock_lhb_jgmx_sina() -> pd.DataFrame:
         temp_df = pd.read_html(StringIO(r.text))[0].iloc[0:, :]
         big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
     big_df["股票代码"] = big_df["股票代码"].astype(str).str.zfill(6)
-    big_df['交易日期'] = pd.to_datetime(big_df['交易日期'], errors="coerce").dt.date
-    big_df.rename(columns={"机构席位买入额(万)": "机构席位买入额", "机构席位卖出额(万)": "机构席位卖出额"},
-                  inplace=True)
-    big_df['机构席位买入额'] = pd.to_numeric(big_df['机构席位买入额'], errors="coerce")
-    big_df['机构席位卖出额'] = pd.to_numeric(big_df['机构席位卖出额'], errors="coerce")
+    big_df["交易日期"] = pd.to_datetime(big_df["交易日期"], errors="coerce").dt.date
+    big_df.rename(
+        columns={
+            "机构席位买入额(万)": "机构席位买入额",
+            "机构席位卖出额(万)": "机构席位卖出额",
+        },
+        inplace=True,
+    )
+    big_df["机构席位买入额"] = pd.to_numeric(big_df["机构席位买入额"], errors="coerce")
+    big_df["机构席位卖出额"] = pd.to_numeric(big_df["机构席位卖出额"], errors="coerce")
     return big_df
 
 
 if __name__ == "__main__":
-    stock_lhb_detail_daily_sina_df = stock_lhb_detail_daily_sina(
-        date="20240222"
-    )
+    stock_lhb_detail_daily_sina_df = stock_lhb_detail_daily_sina(date="20240222")
     print(stock_lhb_detail_daily_sina_df)
 
-    stock_lhb_ggtj_sina_df = stock_lhb_ggtj_sina(recent_day="5")
+    stock_lhb_ggtj_sina_df = stock_lhb_ggtj_sina(symbol="5")
     print(stock_lhb_ggtj_sina_df)
 
-    stock_lhb_yytj_sina_df = stock_lhb_yytj_sina(recent_day="5")
+    stock_lhb_yytj_sina_df = stock_lhb_yytj_sina(symbol="5")
     print(stock_lhb_yytj_sina_df)
 
-    stock_lhb_jgzz_sina_df = stock_lhb_jgzz_sina(recent_day="5")
+    stock_lhb_jgzz_sina_df = stock_lhb_jgzz_sina(symbol="5")
     print(stock_lhb_jgzz_sina_df)
 
     stock_lhb_jgmx_sina_df = stock_lhb_jgmx_sina()

diff --git a/docs/data/stock/stock.md b/docs/data/stock/stock.md
@@ -17057,13 +17057,13 @@ print(stock_lhb_detail_daily_sina_df)
 
 描述: 新浪财经-龙虎榜-个股上榜统计
 
-限量: 单次返回指定 recent_day 的所有历史数据
+限量: 单次返回指定 symbol 的所有历史数据
 
 输入参数
 
-| 名称         | 类型  | 描述                                                                                    |
-|------------|-----|---------------------------------------------------------------------------------------|
-| recent_day | str | recent_day="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
+| 名称     | 类型  | 描述                                                                                |
+|--------|-----|-----------------------------------------------------------------------------------|
+| symbol | str | symbol="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
 
 输出参数
 
@@ -17083,7 +17083,7 @@ print(stock_lhb_detail_daily_sina_df)
 ```python
 import akshare as ak
 
-stock_lhb_ggtj_sina_df = ak.stock_lhb_ggtj_sina(recent_day="5")
+stock_lhb_ggtj_sina_df = ak.stock_lhb_ggtj_sina(symbol="5")
 print(stock_lhb_ggtj_sina_df)
 ```
 
@@ -17113,13 +17113,13 @@ print(stock_lhb_ggtj_sina_df)
 
 描述: 新浪财经-龙虎榜-营业上榜统计
 
-限量: 单次返回指定 recent_day 的所有历史数据
+限量: 单次返回指定 symbol 的所有历史数据
 
 输入参数
 
-| 名称         | 类型  | 描述                                                                                    |
-|------------|-----|---------------------------------------------------------------------------------------|
-| recent_day | str | recent_day="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
+| 名称     | 类型  | 描述                                                                                |
+|--------|-----|-----------------------------------------------------------------------------------|
+| symbol | str | symbol="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
 
 输出参数
 
@@ -17138,7 +17138,7 @@ print(stock_lhb_ggtj_sina_df)
 ```python
 import akshare as ak
 
-stock_lhb_yytj_sina_df = ak.stock_lhb_yytj_sina(recent_day="5")
+stock_lhb_yytj_sina_df = ak.stock_lhb_yytj_sina(symbol="5")
 print(stock_lhb_yytj_sina_df)
 ```
 
@@ -17168,13 +17168,13 @@ print(stock_lhb_yytj_sina_df)
 
 描述: 新浪财经-龙虎榜-机构席位追踪
 
-限量: 单次返回指定 recent_day 的所有历史数据
+限量: 单次返回指定 symbol 的所有历史数据
 
 输入参数
 
-| 名称         | 类型  | 描述                                                                                    |
-|------------|-----|---------------------------------------------------------------------------------------|
-| recent_day | str | recent_day="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
+| 名称     | 类型  | 描述                                                                                |
+|--------|-----|-----------------------------------------------------------------------------------|
+| symbol | str | symbol="5"; choice of {"5": 最近 5 天; "10": 最近 10 天; "30": 最近 30 天; "60": 最近 60 天;} |
 
 输出参数
 
@@ -17193,7 +17193,7 @@ print(stock_lhb_yytj_sina_df)
 ```python
 import akshare as ak
 
-stock_lhb_jgzz_sina_df = ak.stock_lhb_jgzz_sina(recent_day="5")
+stock_lhb_jgzz_sina_df = ak.stock_lhb_jgzz_sina(symbol="5")
 print(stock_lhb_jgzz_sina_df)
 ```