Merge pull request #7 from 1nchaos/dev

Dev

README.md

@@ -8,7 +8,7 @@
 >
 > 专注股票行情数据，为了保证数据的高可用性，采用多数据源融合切换。
 >
-> 目标：支持个人量化行情的需要；众人拾柴火焰高。
+> 目标：支持个人量化行情的需要；众人拾柴火焰高，欢迎加入。
 
 ## 一、快速开始
 
@@ -130,7 +130,7 @@ print(res_df)
 | 分红信息 | stock.market.get_dividend()                   | 获取单只股票的分红信息                |                                                              |
 | 股票行情 | stock.market.get_market()                     | 获取单只股票的行情信息-日、周、月 k线 |                                                              |
 |          | stock.market.get_market_min()                 | 获取单个股票的今日分时行情            | 只能获取当天                                                 |
-|          | stock.market.list_market_current()            | 获取多个股票最新行情信息              | 实时行情                                                     |
+|          | stock.market.list_market_current()            | 获取多个股票最新行情信息              | 实时行情<br />数据源：2个，源新浪和腾讯                      |
 | 概念行情 | stock.market.get_market_concept_ths()         | 获取单个概念的行情信息-日、周、月 k线 | 目前只有同花顺相关概念行情，<br />获取概念行情时，<br />请注意传入参数是指数代码还是概念代码，<br />指数代码8开头，index_code |
 |          | stock.market.get_market_concept_min_ths()     | 获取同花顺概念行情-当日分时           | 只能获取当天                                                 |
 |          | stock.market.get_market_concept_current_ths() | 获取同花顺当前的概念行情              | 实时行情                                                     |
@@ -168,15 +168,16 @@ print(res_df)
 | 百度股市通 | [股市通](https://gushitong.baidu.com/)                       | 科技让投资更简单 |
 | 东方财富   | [数据中心](https://data.eastmoney.com/center/)，[行情中心](http://quote.eastmoney.com/center/) | 财经门户         |
 | 腾讯理财   | [行情中心](https://stockapp.finance.qq.com/mstats/#)         |                  |
+| 新浪财经   | [新浪财经](https://finance.sina.com.cn/stock/)               | 门户网站         |
 
-***--------------------------------------------------------------感谢各位大厂提供的数据-------------------------------------------------***
+***--------------------------------------------感谢各位大厂提供的数据----------------------------------------------***
 
 ## 四、 其它参考
 
 主要记录查阅过的项目和相关平台，并对此项目产生了深远印象，特此鸣谢。
 
-| [akshare](https://gitee.com/mirrors/akshare) | [聚宽量化](https://www.joinquant.com/) | [baostock](http://baostock.com/baostock/index.php/Python%E5%BC%80%E5%8F%91%E8%B5%84%E6%BA%90) | [MyData](http://api.mairui.club/hsdata.html) |      |
-| -------------------------------------------- | -------------------------------------- | ------------------------------------------------------------ | -------------------------------------------- | ---- |
+| [akshare](https://gitee.com/mirrors/akshare) | [聚宽量化](https://www.joinquant.com/) | [baostock](http://baostock.com/baostock/index.php/Python%E5%BC%80%E5%8F%91%E8%B5%84%E6%BA%90) | [MyData](http://api.mairui.club/hsdata.html) |
+| -------------------------------------------- | -------------------------------------- | ------------------------------------------------------------ | -------------------------------------------- |
 
 ## 五、发布计划
 

adata/__version__.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-VERSION = (0, 0, 23)
+VERSION = (0, 0, 24)
 # PRERELEASE = None  # alpha, beta or rc
 PRERELEASE = 'beta'  # alpha, beta or rc
 REVISION = None
@@ -15,7 +15,7 @@ def generate_version(version, prerelease=None, revision=None):
     return "".join(version_parts)
 
 __title__ = "adata"
-__description__ = "A Data,A Stock,ETF,Bond,Quant"
+__description__ = "A Data,A Stock,ETF,Bond,Quant,Stock Market,K Line"
 __url__ = "https://github.com/1nchaos/adata"
 __version__ = generate_version(VERSION, prerelease=PRERELEASE, revision=REVISION)
 __author__ = "1nchaos"

adata/common/utils/cookie.py

@@ -10,10 +10,10 @@
 from py_mini_racer import py_mini_racer
 
 
-def ths_cookie():
+def ths_cookie(js_path="ths.js"):
     """获取同花顺cookie"""
     js_code = py_mini_racer.MiniRacer()
-    js_content = _get_file_content_ths(file_path="ths.js")
+    js_content = _get_file_content_ths(file_path=js_path)
     js_code.eval(js_content)
     return 'v=' + js_code.call("v")
 

adata/stock/market/stock_market/__init__.py

@@ -8,3 +8,4 @@
 from .stock_market import StockMarket
 from .stock_market_qq import StockMarketQQ
 from .stock_market_sina import StockMarketSina
+from .stock_market_baidu import StockMarketBaiDu

adata/stock/market/stock_market/stock_market.py

@@ -1,29 +1,21 @@
 # -*- coding: utf-8 -*-
 """
-@desc: readme
+@desc: 股票行情
 @author: 1nchaos
 @time: 2023/3/29
 @log: change log
+TODO 数据返回类型转换
 """
 
-import time
-
 import pandas as pd
 
-from adata.common.headers import baidu_headers
-from adata.common.utils import requests
 from adata.stock.market.stock_market import *
 
 
 class StockMarket(object):
     """
-    股票行情 TODO 数据返回类型转换
+    股票行情
     """
-    __MARKET_COLUMNS = ['trade_time', 'open', 'close', 'volume', 'high', 'low', 'amount', 'change', 'change_pct',
-                        'turnover_ratio', 'pre_close']
-    __MARKET_MIN_COLUMNS = ['stock_code', 'trade_time', 'price', 'change', 'change_pct', 'volume', 'avg_price',
-                            'amount']
-    __MARKET_CURRENT_COLUMNS = ['stock_code', 'short_name', 'price', 'change', 'change_pct', 'volume', 'amount']
 
     def __init__(self) -> None:
         super().__init__()
@@ -37,146 +29,40 @@ def get_market(self, stock_code: str = '000001', start_date='1990-01-01', k_type
         :param adjust_type: k线复权类型：0.不复权；1.前复权；2.后复权 默认：1 前复权 （目前：只有前复权,作为股票交易已经可用）
         :return: k线行情数据
         """
-        return self.__market_baidu(stock_code, start_date, k_type)
+        return StockMarketBaiDu().get_market(stock_code=stock_code, start_date=start_date, k_type=k_type)
 
     def get_market_min(self, stock_code: str = '000001'):
         """
         获取单个股票的今日分时行情
         :param stock_code: 股票代码
         :return: 当日分钟行情数据
         """
-        return self.__market_baidu_today_min(stock_code)
+        return StockMarketBaiDu().get_market_min(stock_code=stock_code)
 
     def list_market_current(self, code_list=None):
         """
         获取多个股票最新行情信息
         :param code_list: 股票代码
         :return: 当前最新的行情价格信息
+        stock_code: 股票代码
+        short_name: 股票简称
+        price: 当前价格（元）
+        change: 涨跌额（元）
+        change_pct: 涨跌幅（%）
+        volume: 成交量（股）
+        amount: 成交金额（元）
         """
         if code_list is None:
             return pd.DataFrame()
-        return StockMarketSina().list_market_current(code_list=code_list)
-
-    def __market_baidu(self, stock_code, start_date, k_type=1):
-        """
-        获取百度的股票行情数据
-        web： https://gushitong.baidu.com/stock/ab-002926
-        url：quotation_fiveday_ab 5日分时，quotation_kline_ab K线， quotation_minute_ab 当日分钟
-        k线
-        https://finance.pae.baidu.com/selfselect/getstockquotation?all=1&isIndex=false&isBk=false&isBlock=false&
-        isFutures=false&isStock=true&newFormat=1&group=quotation_kline_ab&finClientType=pc&
-        code=002926&start_time=2018-02-05 00:00:00&ktype=1
-        分钟
-        https://finance.pae.baidu.com/selfselect/getstockquotation?
-        all=1&code=601318&isIndex=false&isBk=false&isBlock=false&isFutures=false&isStock=true&newFormat=1&
-        group=quotation_minute_ab&finClientType=pc
-        "ma5均价","ma5成交量","ma10均价","ma10成交量","ma20均价","ma20成交量"
-        :param stock_code: 6位股票代码
-        :param start_date: 开始时间
-        :param k_type: k线类型：1.日；2.周；3.月
-        # :param adjust_type: k线复权类型：0.不复权；1.前复权；2.后复权 默认：1 前复权 TODO
-        :return: k线行情数据:"时间戳", "时间","开盘","收盘","成交量","最高","最低","成交额","涨跌额","涨跌幅","换手率","昨收"
-        """
-        # 1. 请求接口 url
-        api_url = f"https://finance.pae.baidu.com/selfselect/getstockquotation?all=1&isIndex=false&isBk=false&" \
-                  f"isBlock=false&isFutures=false&isStock=true&newFormat=1&group=quotation_kline_ab&finClientType=pc&" \
-                  f"code={stock_code}&start_time={start_date} 00:00:00&ktype={k_type}"
-
-        res_json = None
-        for i in range(3):
-            res = requests.request('get', api_url, headers=baidu_headers.json_headers, proxies={})
-            # 2. 校验请求结果数据
-            res_json = res.json()
-            if res_json['ResultCode'] == '0':
-                break
-            time.sleep(2)
-        # 3.解析数据
-        # 3.1 空数据时返回为空
-        result = res_json['Result']
-        if not result:
-            return pd.DataFrame(data=[], columns=self.__MARKET_COLUMNS)
-
-        # 3.2. 正常解析数据
-        keys = res_json['Result']['newMarketData']['keys']
-        market_data = res_json['Result']['newMarketData']['marketData']
-        market_data_list = str(market_data).split(';')
-        data = []
-        for one in market_data_list:
-            data.append(one.split(','))
-
-        # 4. 封装数据
-        rename_columns = {'turnoverratio': 'turnover_ratio', 'preClose': 'pre_close', 'range': 'change',
-                          'ratio': 'change_pct', 'time': 'trade_time'}
-        result_df = pd.DataFrame(data=data, columns=keys).rename(columns=rename_columns)[self.__MARKET_COLUMNS]
-        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')
-        result_df.replace('--', None, inplace=True)
-        result_df.replace('', None, inplace=True)
-        result_df['change'] = result_df['change'].str.replace('+', '', regex=True)
-        result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True)
-        # 5. 数据清洗，剔除成交量为0的异常数据
-        result_df['amount'] = result_df['amount'].astype(float)
-        result_df = result_df[result_df['amount'] > 0]
-        result_df.replace('--', None, inplace=True)
-        result_df.replace('', None, inplace=True)
-        result_df['change'] = result_df['change'].str.replace('+', '', regex=True).astype(float)
-        result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True).astype(float)
-        return result_df
-
-    def __market_baidu_today_min(self, stock_code):
-        """
-        获取百度的股票行情数据
-        web： https://gushitong.baidu.com/stock/ab-002926
-        url: https://finance.pae.baidu.com/selfselect/getstockquotation?
-        all=1&code=601318&isIndex=false&isBk=false&isBlock=false&isFutures=false&isStock=true&newFormat=1
-        &group=quotation_minute_ab&finClientType=pc
-        time, price, ratio, increase, volume, avgPrice, amount, timeKey, datetime, oriAmount
-        :param stock_code: 6位股票代码
-        :return: k线行情数据:"时间","价格","涨跌率","涨幅","均价","成交量", "成交额"
-        """
-        # 1. 请求接口 url
-        api_url = f"https://finance.pae.baidu.com/selfselect/getstockquotation?all=1&isIndex=false&isBk=false&" \
-                  f"isBlock=false&isFutures=false&isStock=true&newFormat=1&group=quotation_minute_ab&" \
-                  f"finClientType=pc&code={stock_code}"
-
-        res_json = None
-        for i in range(3):
-            res = requests.request('get', api_url, headers=baidu_headers.json_headers, proxies={})
-            # 2. 校验请求结果数据
-            res_json = res.json()
-            if res_json['ResultCode'] == '0':
-                break
-            time.sleep(2)
-        # 3.解析数据
-        # 3.1 空数据时返回为空
-        result = res_json['Result']
-        if not result:
-            return pd.DataFrame(data=[], columns=self.__MARKET_MIN_COLUMNS)
-
-        # 3.2. 正常解析数据
-        market_data_list = res_json['Result']['priceinfo']
-
-        # 4. 封装数据
-        field = ['time', 'price', 'ratio', 'increase', 'volume', 'avgPrice', 'amount', 'timeKey', 'datetime',
-                 'oriAmount']
-        rename_columns = {'avgPrice': 'avg_price', 'oriAmount': 'ori_amount', 'ratio': 'change_pct',
-                          'increase': 'change'}
-        result_df = pd.DataFrame(data=market_data_list, columns=field).rename(columns=rename_columns)
-        result_df['amount'] = result_df['ori_amount']
-        result_df['stock_code'] = stock_code
-        # 这里是分钟均价，数据存在四舍五入的情况
-        result_df['volume'] = result_df['volume'].astype(int) * 100
-        result_df['trade_time'] = pd.to_datetime(result_df['time'], unit='s', utc=True).dt.tz_convert(
-            'Asia/Shanghai')
-        result_df['trade_time'] = pd.to_datetime(result_df['trade_time']).dt.strftime("%Y-%m-%d %H:%M:%S")
-        result_df['trade_date'] = result_df['trade_time'].str[:10]
-        result_df['change'] = result_df['change'].str.replace('+', '', regex=True).astype(float)
-        result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True).astype(float)
-        return result_df[self.__MARKET_MIN_COLUMNS]
+        # 1. 先查询新浪
+        df = StockMarketSina().list_market_current(code_list=code_list)
+        # 2. 然后腾讯
+        if df.empty:
+            df = StockMarketQQ().list_market_current(code_list=code_list)
+        return df
 
 
 if __name__ == '__main__':
-    # print(StockMarket().get_market(stock_code='000001', start_date='2021-01-01', k_type=1))
-    # print(StockMarket().get_market_min(stock_code='000001'))
+    print(StockMarket().get_market(stock_code='000001', start_date='2021-01-01', k_type=1))
+    print(StockMarket().get_market_min(stock_code='000001'))
     print(StockMarket().list_market_current(code_list=['000001', '600001', '000795', '872925']))

adata/stock/market/stock_market/stock_market_baidu.py

@@ -14,7 +14,7 @@
 
 from adata.common.headers import baidu_headers
 from adata.common.utils import requests
-from stock_market_template import StockMarketTemplate
+from adata.stock.market.stock_market.stock_market_template import StockMarketTemplate
 
 
 class StockMarketBaiDu(StockMarketTemplate):
@@ -25,14 +25,6 @@ class StockMarketBaiDu(StockMarketTemplate):
     def __init__(self) -> None:
         super().__init__()
 
-    def get_market_min(self, stock_code: str = '000001'):
-        """
-        获取单个股票的今日分时行情
-        :param stock_code: 股票代码
-        :return: 当日分钟行情数据
-        """
-        return self.__market_baidu_today_min(stock_code)
-
     def get_market(self, stock_code: str = '000001', start_date='1990-01-01', k_type=1, adjust_type: int = 1):
         """
         获取百度的股票行情数据
@@ -100,7 +92,7 @@ def get_market(self, stock_code: str = '000001', start_date='1990-01-01', k_type
         result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True).astype(float)
         return result_df
 
-    def __market_baidu_today_min(self, stock_code):
+    def get_market_min(self, stock_code: str = '000001'):
         """
         获取百度的股票行情数据
         web： https://gushitong.baidu.com/stock/ab-002926
@@ -143,15 +135,15 @@ def __market_baidu_today_min(self, stock_code):
         result_df['stock_code'] = stock_code
         # 这里是分钟均价，数据存在四舍五入的情况
         result_df['volume'] = result_df['volume'].astype(int) * 100
-        result_df['trade_time'] = pd.to_datetime(result_df['time'], unit='s', utc=True).dt.tz_convert(
-            'Asia/Shanghai')
+        result_df['trade_time'] = pd.to_datetime(result_df['time'], unit='s', utc=True).dt.tz_convert('Asia/Shanghai')
         result_df['trade_time'] = pd.to_datetime(result_df['trade_time']).dt.strftime("%Y-%m-%d %H:%M:%S")
         result_df['trade_date'] = result_df['trade_time'].str[:10]
         result_df['change'] = result_df['change'].str.replace('+', '', regex=True).astype(float)
-        result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True).astype(float)
+        result_df['change_pct'] = result_df['change_pct'].str.replace('+', '', regex=True) \
+            .str.replace('%', '', regex=True).astype(float)
         return result_df[self._MARKET_MIN_COLUMNS]
 
 
 if __name__ == '__main__':
     print(StockMarketBaiDu().get_market(stock_code='000001', start_date='2021-01-01', k_type=1))
-    # print(StockMarketBaiDu().get_market_min(stock_code='000001'))
+    print(StockMarketBaiDu().get_market_min(stock_code='000001'))

adata/stock/market/stock_market/stock_market_qq.py

@@ -7,8 +7,10 @@
 @time: 2023/6/19
 @log: change log
 """
+import pandas as pd
 
-from .stock_market_template import StockMarketTemplate
+from adata.common import requests
+from adata.stock.market.stock_market.stock_market_template import StockMarketTemplate
 
 
 class StockMarketQQ(StockMarketTemplate):
@@ -26,6 +28,41 @@ def list_market_current(self, code_list=None):
         :param code_list: 股票代码
         :return: 当前最新的行情价格信息
         """
+        api_url = f"https://qt.gtimg.cn/r=0.5979076524724433&q="
+        for code in code_list:
+            if code.startswith('0') or code.startswith('3'):
+                api_url += 's_sz' + code + ','
+            elif code.startswith('6') or code.startswith('9'):
+                api_url += 's_sh' + code + ','
+            elif code.startswith('4') or code.startswith('8'):
+                api_url += 's_bj' + code + ','
+
+        # 1.请求接口
+        res = requests.request('get', api_url, headers={})
+
+        # 2. 判断结果是否正确
+        if len(res.text) < 1 or res.status_code != 200:
+            return pd.DataFrame(data=[], columns=self._MARKET_CURRENT_COLUMNS)
+        # 3.解析数据
+
+        # 正常解析数据 v_s_sz000936="51~华西股份~000936~12.60~1.15~10.04~69137~8711~~111.64~GP-A";
+        data_list = res.text.split(';')
+        data = []
+        for data_str in data_list:
+            if len(data_str) < 8:
+                continue
+            code = data_str.split('~')
+            if len(code) == 11:
+                data.append(code[1:8])
+
+        # 4. 封装数据
+        data_columns = ['short_name', 'stock_code', 'price', 'change', 'change_pct', 'volume', 'amount']
+        result_df = pd.DataFrame(data=data, columns=data_columns)
+        # 单位：手，万元
+        mask = result_df['stock_code'].str.startswith(('0', '3', '6', '9'))
+        result_df.loc[mask, 'volume'] = result_df['volume'].astype(int) * 100
+        result_df.loc[mask, 'amount'] = result_df['amount'].astype(float) * 10000
+        return result_df[self._MARKET_CURRENT_COLUMNS]
 
 
 if __name__ == '__main__':

adata/stock/market/stock_market/stock_market_sina.py

@@ -12,13 +12,14 @@
 
 from adata.common.headers import sina_headers
 from adata.common.utils import requests
-from .stock_market_template import StockMarketTemplate
+from adata.stock.market.stock_market.stock_market_template import StockMarketTemplate
 
 
 class StockMarketSina(StockMarketTemplate):
     """
     新浪股票行情
     """
+
     def __init__(self) -> None:
         super().__init__()