Dev

HISTORY.md

@@ -9,6 +9,12 @@ master
 
 专注股票量化数据，为Ai(爱)发电，向阳而生。
 
+2.3.0 (2024-07-06)
+------------------
+1. 新增：股票：百度的概念接口。
+2. 新增：股票：龙虎榜单列表接口。
+3. 修复：股票：资金流,成立日期格式等bug。
+
 2.2.0 (2024-07-01)
 ------------------
 1. 新增：股票：资金流接口。
@@ -24,11 +30,6 @@ master
 1. 新增：基金ETF行情接口。
 2. 新增：股票股东信息接口。
 
-1.2.4 (2024-02-02)
-------------------
-1. 修复：修复概念返回为空bug。
-2. flag：保卫3000点失败，继续保卫2500点。
-
 ......
 ------------------
 

README.md

@@ -213,6 +213,7 @@ print(res_df)
 | **热度榜单**             | sentiment.hot.pop_rank_100_east      | 东方财富人气100榜单                        | 来源：[东方财富](http://guba.eastmoney.com/rank/)            |
 |                          | sentiment.hot.hot_rank_100_ths()     | 同花顺热度100排行榜                        | 来源：[同花顺](https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/stock?stock_type=a&type=hour&list_type=normal) |
 |                          | sentiment.hot.hot_concept_20_ths()   | 同花顺热门概念板块20排行榜                 | 来源：[同花顺](https://dq.10jqka.com.cn/fuyao/hot_list_data/out/hot_list/v1/stock?stock_type=a&type=hour&list_type=normal) |
+|                          | sentiment.hot.list_a_list_daily()    | 龙虎榜单列表                               | 来源：[东方财富](https://data.eastmoney.com/stock/lhb/yyb/10033779.html) |
 | 其它数据排期中           | TODO                                 | 若您有相关资源可以一起参与贡献             |                                                              |
 
 ## 三、[数据源](https://adata.30006124.xyz/dataSource.html)

adata/__version__.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-VERSION = (2, 2, 0)
+VERSION = (2, 3, 0)
 PRERELEASE = None  # alpha, beta or rc
 REVISION = None
 

adata/common/utils/unit_conver.py

@@ -18,6 +18,7 @@ def convert_to_yuan(input_dict):
     unit_multipliers = {'亿': 100000000, '万': 10000}
 
     for key, value in input_dict.items():
+        input_dict[key] = value.replace('元', '')
         if isinstance(value, str) and any(unit in value for unit in unit_multipliers.keys()):
             number, unit = re.findall(r'([-+]?\d*\.\d+|\d+)([亿万]?)', value)[0]
             number = float(number)

adata/sentiment/alist.py

@@ -20,6 +20,10 @@
 class AList(BaseThs):
     """龙虎榜单"""
 
+    __A_LIST_DAILY_COLUMNS = ['trade_date', 'short_name', 'stock_code', 'close', 'change_cpt', 'turnover_ratio',
+                              'a_net_amount', 'a_buy_amount', 'a_sell_amount', 'a_amount', 'amount',
+                              'net_amount_rate', 'a_amount_rate', 'reason']
+
     # 东方财富人气榜
     def list_a_list_daily(self, report_date=None):
         """
@@ -35,16 +39,20 @@ def list_a_list_daily(self, report_date=None):
         # 2. 请求数据
         text = requests.request(method='post', url=url).text
         res = json.loads(text[text.index('{'):-2])
+        if res['result'] is None:
+            return pd.DataFrame()
         df = pd.DataFrame(res['result']["data"])
-
-        # 3. 解析封装数据 TODO
-        rename = {'f2': 'price', 'f3': 'change_pct', 'f12': 'stock_code', 'f14': 'short_name', }
-        rank_df = pd.rename(columns=rename)
-        rank_df["change_pct"] = pd.to_numeric(rank_df["change_pct"], errors="coerce")
-        rank_df["price"] = pd.to_numeric(rank_df["price"], errors="coerce")
-        rank_df["change"] = rank_df["price"] * rank_df["change_pct"] / 100
-        rank_df["rank"] = range(1, len(rank_df) + 1)
-        return rank_df[["rank", "stock_code", "short_name", "price", "change", "change_pct"]]
+        # 3. 解析封装数据
+        rename = {'SECURITY_CODE': 'stock_code', 'SECURITY_NAME_ABBR': 'short_name', 'TRADE_DATE': 'trade_date',
+                  'CLOSE_PRICE': 'close', 'CHANGE_RATE': 'change_cpt', 'TURNOVERRATE': 'turnover_ratio',
+                  'BILLBOARD_NET_AMT': 'a_net_amount', 'BILLBOARD_BUY_AMT': 'a_buy_amount',
+                  'BILLBOARD_SELL_AMT': 'a_sell_amount', 'BILLBOARD_DEAL_AMT': 'a_amount',
+                  'ACCUM_AMOUNT': 'amount', 'DEAL_NET_RATIO': 'net_amount_rate', 'DEAL_AMOUNT_RATIO': 'a_amount_rate',
+                  'EXPLANATION': 'reason', }
+        df = df.rename(columns=rename)
+        df['trade_date'] = pd.to_datetime(df['trade_date']).dt.strftime('%Y-%m-%d')
+        df['short_name'] = df['short_name'].str.replace(' ', '')
+        return df[self.__A_LIST_DAILY_COLUMNS]
 
     def get_a_list(self, stock_code, report_date=None):
         """
@@ -56,4 +64,5 @@ def get_a_list(self, stock_code, report_date=None):
 
 
 if __name__ == '__main__':
-    AList().list_a_list_daily()
+    print(AList().list_a_list_daily(report_date='2024-07-04'))
+    print(AList().list_a_list_daily())

adata/sentiment/hot.py

@@ -11,12 +11,12 @@
 """
 import pandas as pd
 
-from adata.common.base.base_ths import BaseThs
 from adata.common.headers import ths_headers
 from adata.common.utils import requests
+from adata.sentiment.alist import AList
 
 
-class Hot(BaseThs):
+class Hot(AList):
     """热门榜单"""
 
     # 东方财富人气榜

adata/stock/info/concept/stock_concept.py

@@ -10,11 +10,12 @@
 @author: 1nchaos
 @date: 2023/3/30 16:17
 """
+from adata.stock.info.concept.stock_concept_baidu import StockConceptBaidu
 from adata.stock.info.concept.stock_concept_east import StockConceptEast
 from adata.stock.info.concept.stock_concept_ths import StockConceptThs
 
 
-class StockConcept(StockConceptThs, StockConceptEast):
+class StockConcept(StockConceptThs, StockConceptEast, StockConceptBaidu):
 
     def __init__(self) -> None:
         super().__init__()

adata/stock/info/concept/stock_concept_baidu.py

@@ -0,0 +1,67 @@
+# -*- coding: utf-8 -*-
+"""
+@summary: 股票概念
+东方财富股票概念
+
+https://data.eastmoney.com/bkzj/gn.html
+
+单个股票的所有概念板块
+https://datacenter.eastmoney.com/securities/api/data/v1/get?reportName=RPT_F10_CORETHEME_BOARDTYPE&columns=SECUCODE%2CSECURITY_CODE%2CSECURITY_NAME_ABBR%2CNEW_BOARD_CODE%2CBOARD_NAME%2CSELECTED_BOARD_REASON%2CIS_PRECISE%2CBOARD_RANK%2CBOARD_YIELD%2CDERIVE_BOARD_CODE&quoteColumns=f3~05~NEW_BOARD_CODE~BOARD_YIELD&filter=(SECUCODE%3D%22600138.SH%22)(IS_PRECISE%3D%221%22)&pageNumber=1&pageSize=&sortTypes=1&sortColumns=BOARD_RANK&source=HSF10&client=PC&v=0029565688091059528
+@author: 1nchaos
+@date: 2023/3/30 16:17
+"""
+
+import json
+from urllib.parse import parse_qs
+
+import pandas as pd
+
+from adata.common import requests
+from adata.common.headers import baidu_headers
+from adata.stock.info.concept.stock_concept_template import StockConceptTemplate
+
+
+class StockConceptBaidu(StockConceptTemplate):
+    """
+    股票概念
+    """
+
+    def __init__(self) -> None:
+        super().__init__()
+
+    def get_concept_baidu(self, stock_code='000001'):
+        """
+        根据股票代码获取，股票所属的所有的概念信息
+        https://finance.pae.baidu.com/api/getrelatedblock?stock=[{"code":"300059","market":"ab","type":"stock"}]&finClientType=pc
+        :param stock_code: 股票代码
+        :return: 概念信息
+        """
+        # 1. 请求参数封装
+        code_list = []
+        if isinstance(stock_code, str):
+            stock_code = [stock_code]
+        for code in stock_code:
+            code_list.append({"code": code, "market": "ab", "type": "stock"})
+        url = f"""https://finance.pae.baidu.com/api/getrelatedblock?stock={json.dumps(code_list)}&finClientType=pc"""
+        res_json = requests.request('get', url, headers=baidu_headers.json_headers, proxies={}).json()
+
+        # 1. 返回结果判断
+        if not res_json['Result']:
+            return pd.DataFrame(data=[], columns=self._CONCEPT_INFO_COLUMNS)
+
+        # 2. 正常返回数据结果封装
+        res_json = res_json['Result']
+        data = []
+        for key, value in res_json.items():
+            for concept_type in value:
+                if concept_type['name'] == '概念':
+                    for _ in concept_type['list']:
+                        data.append({'stock_code': key, 'concept_code': parse_qs(_['xcx_query']).get('code', '')[0],
+                                     'name': _['name'],
+                                     'reason': '', 'source': '百度股市通'})
+        result_df = pd.DataFrame(data=data, columns=self._CONCEPT_INFO_COLUMNS)
+        return result_df
+
+
+if __name__ == '__main__':
+    print(StockConceptBaidu().get_concept_baidu(stock_code=["600020", '300059', '300033']).to_string())

adata/stock/info/stock_index.py

@@ -101,9 +101,9 @@ def index_constituent(self, index_code=None, wait_time=None):
         :param wait_time: 等待时间：毫秒；表示每个请求的间隔时间，主要用于防止请求太频繁的限制。
         :return: ['index_code', 'stock_code', 'short_name']
         """
-        # res = self.__index_constituent_sina(index_code=index_code)
-        # if not res.empty:
-        #     return res
+        res = self.__index_constituent_baidu(index_code=index_code)
+        if not res.empty:
+            return res
         return self.__index_constituent_ths(index_code=index_code, wait_time=wait_time)
 
     def __index_constituent_ths(self, index_code=None, wait_time=None):
@@ -245,5 +245,5 @@ def __index_constituent_sina(self, index_code=None, wait_time=None):
 
 if __name__ == '__main__':
     print(StockIndex().all_index_code())
-    print(StockIndex().index_constituent(index_code='000033'))
-    print(StockIndex().index_constituent(index_code='399387', wait_time=158))
+    # print(StockIndex().index_constituent(index_code='000033'))
+    # print(StockIndex().index_constituent(index_code='399387', wait_time=158))

adata/stock/info/stock_info.py

@@ -46,4 +46,4 @@ def get_stock_shares(self, stock_code: str = '000033', is_history=True):
 
 
 if __name__ == '__main__':
-    print(StockInfo().get_stock_shares(stock_code='600001', is_history=True))
+    print(StockInfo().get_stock_shares(stock_code='300033', is_history=True))

adata/stock/market/capital_flow/stock_capital_flow_baidu.py

@@ -74,7 +74,7 @@ def get_capital_flow(self, stock_code: str = '000001', start_date=None, end_date
             url = f"https://finance.pae.baidu.com/vapi/v1/fundsortlist?" \
                   f"code={stock_code}&market=ab&finance_type=stock&tab=day&" \
                   f"from=history&date={end_date}&pn=0&rn=20&finClientType=pc"
-            res = requests.request('get', url, headers= baidu_headers.json_headers, proxies={})
+            res = requests.request('get', url, headers=baidu_headers.json_headers, proxies={})
             data_list = res.json()["Result"]["content"]
             if len(data_list) == 0:
                 break
@@ -102,4 +102,4 @@ def get_capital_flow(self, stock_code: str = '000001', start_date=None, end_date
 
 if __name__ == '__main__':
     print(StockCapitalFlowBaidu().get_capital_flow_min(stock_code='300059'))
-    print(StockCapitalFlowBaidu().get_capital_flow(stock_code='300059'))
+    print(StockCapitalFlowBaidu().get_capital_flow(stock_code='300059', start_date='2024-01-01', end_date='2024-04-01'))

adata/stock/market/stock_market/stock_market_baidu.py

@@ -82,11 +82,12 @@ def get_market(self, stock_code: str = '000001', start_date='1990-01-01', k_type
         result_df['stock_code'] = stock_code
         result_df['trade_date'] = result_df['trade_time']
         result_df['trade_time'] = pd.to_datetime(result_df['trade_time']).dt.strftime('%Y-%m-%d %H:%M:%S')
-        # 5. 数据清洗，剔除成交量为0的异常数据
+        # 5. 数据清洗，剔除成交量且成交额为0的异常数据
         result_df.replace('--', None, inplace=True)
         result_df.replace('', None, inplace=True)
         result_df['amount'] = result_df['amount'].astype(float)
-        result_df = result_df[result_df['amount'] > 0]
+        result_df['volume'] = result_df['volume'].astype(float)
+        result_df = result_df[(result_df['amount'] > 0) | (result_df['volume'] > 0)]
         result_df['change'] = result_df['change'].str.replace('+', '').astype(float)
         result_df['change_pct'] = result_df['change_pct'].str.replace('+', '').astype(float)
         return result_df

tests/adata_test/sentiment/sentiment_hot_test.py

@@ -0,0 +1,48 @@
+import unittest
+
+import adata
+
+
+class SentimentHotTestCase(unittest.TestCase):
+
+    @classmethod
+    def setUpClass(cls) -> None:
+        print("----STAR执行舆情-热门-函数测试用例STAR----")
+
+    @classmethod
+    def tearDownClass(cls) -> None:
+        print("----END执行舆情-热门-函数测试用例END----")
+
+    def setUp(self):
+        pass
+
+    def tearDown(self):
+        pass
+
+    def test_pop_rank_100_east(self):
+        print("开始测试：pop_rank_100_east")
+        df = adata.sentiment.hot.pop_rank_100_east()
+        print(df)
+        self.assertEqual(True, len(df) == 100)
+
+    def test_hot_rank_100_ths(self):
+        print("开始测试：hot_rank_100_ths")
+        df = adata.sentiment.hot.hot_rank_100_ths()
+        print(df)
+        self.assertEqual(True, len(df) == 100)
+
+    def test_hot_concept_20_ths(self):
+        print("开始测试：hot_concept_20_ths")
+        df = adata.sentiment.hot.hot_concept_20_ths()
+        print(df)
+        self.assertEqual(True, len(df) == 20)
+
+    def test_list_a_list_daily(self):
+        print("开始测试：list_a_list_daily")
+        df = adata.sentiment.hot.list_a_list_daily(report_date='2024-07-04')
+        print(df)
+        self.assertEqual(True, len(df) >= 20)
+
+
+if __name__ == '__main__':
+    unittest.main()