Dev (#4387)

* add interfaces for individual fund by using data from xueqiu/danjuanfunds (#4386) Co-authored-by: none2003 <[email protected]> * add version 1.12.9 * add fund_individual_basic_info_xq * fix get_receipt * fix reits_realtime_em * update date * add fund_individual_basic_info_xq --------- Co-authored-by: none2003 <[email protected]> Co-authored-by: none2003 <[email protected]>
akfamily · Jan 3, 2024 · 17e1bec · 17e1bec
1 parent 063988c
commit 17e1bec
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diff --git a/akshare/__init__.py b/akshare/__init__.py
@@ -2621,9 +2621,10 @@
 1.12.6 fix: fix fund_open_fund_info_em interface
 1.12.7 fix: fix option_gfex_daily interface
 1.12.8 fix: fix fund_open_fund_info_em interface
+1.12.9 add: add fund_individual_basic_info_xq interface
 """
 
-__version__ = "1.12.8"
+__version__ = "1.12.9"
 __author__ = "AKFamily"
 
 import sys
@@ -5039,3 +5040,14 @@
     get_ine_daily,
     get_gfex_daily,
 )
+
+"""
+雪球基金数据
+"""
+from akshare.fund.fund_xq import (
+    fund_individual_basic_info_xq,
+    fund_individual_achievement_xq,
+    fund_individual_analysis_xq,
+    fund_individual_profit_probability_xq,
+    fund_individual_detail_info_xq,
+)
diff --git a/akshare/fund/fund_xq.py b/akshare/fund/fund_xq.py
@@ -0,0 +1,303 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+Date: 2024/01/03 15:40
+Desc: 雪球基金-基金详情
+https://danjuanfunds.com/funding/003545
+"""
+import pandas as pd
+import requests
+
+
+def fund_individual_basic_info_xq(
+        symbol: str = "000001", timeout: float = None
+) -> pd.DataFrame:
+    """
+    雪球基金-基金详情
+    https://danjuanfunds.com/djapi/fund/675091
+    :param symbol: 基金代码
+    :type symbol: str
+    :param timeout: choice of None or a positive float number
+    :type timeout: float
+    :return: 基金信息
+    :rtype: pandas.DataFrame
+    """
+    url = f"https://danjuanfunds.com/djapi/fund/{symbol}"
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36"
+    }
+    r = requests.get(url, headers=headers, timeout=timeout)
+    json_data = r.json()["data"]
+    temp_df = pd.json_normalize(json_data)
+    temp_df = temp_df[
+        [
+            "fd_code",
+            "fd_name",
+            "fd_full_name",
+            "found_date",
+            "totshare",
+            "keeper_name",
+            "manager_name",
+            "trup_name",
+            "type_desc",
+            "rating_source",
+            "rating_desc",
+            "invest_orientation",
+            "invest_target",
+            "performance_bench_mark",
+        ]
+    ]
+    temp_df.columns = [
+        "基金代码",
+        "基金名称",
+        "基金全称",
+        "成立时间",
+        "最新规模",
+        "基金公司",
+        "基金经理",
+        "托管银行",
+        "基金类型",
+        "评级机构",
+        "基金评级",
+        "投资策略",
+        "投资目标",
+        "业绩比较基准",
+    ]
+
+    temp_df = temp_df.T.reset_index()
+    temp_df.columns = ["item", "value"]
+    return temp_df
+
+
+def fund_individual_achievement_xq(
+        symbol: str = "000001", timeout: float = None
+) -> pd.DataFrame:
+    """
+    雪球基金-基金业绩
+    https://danjuanfunds.com/djapi/fundx/base/fund/achievement/675091
+    :param symbol: 基金代码
+    :type symbol: str
+    :param timeout: choice of None or a positive float number
+    :type timeout: float
+    :return: 基金业绩
+    :rtype: pandas.DataFrame
+    """
+    url = (
+        f"https://danjuanfunds.com/djapi/fundx/base/fund/achievement/{symbol}"
+    )
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36"
+    }
+    r = requests.get(url, headers=headers, timeout=timeout)
+    json_data = r.json()["data"]
+    combined_df = None
+    type_dict = {
+        "annual_performance_list": "年度业绩",
+        "stage_performance_list": "阶段业绩",
+    }
+    for k, v in type_dict.items():
+        temp_df = pd.DataFrame.from_dict(json_data[k], orient="columns")
+        temp_df["type"] = v
+        temp_df = temp_df[
+            [
+                "type",
+                "period_time",
+                "self_nav",
+                "self_max_draw_down",
+                "self_nav_rank",
+            ]
+        ]
+        temp_df.columns = [
+            "业绩类型",
+            "周期",
+            "本产品区间收益",
+            "本产品最大回撒",
+            "周期收益同类排名",
+        ]
+        combined_df = pd.concat([combined_df, temp_df], ignore_index=True)
+    combined_df = combined_df.map(
+        lambda x: x if "%" not in str(x) else x.replace("%", "")
+    )
+    combined_df[["本产品区间收益", "本产品最大回撒"]] = combined_df[
+        ["本产品区间收益", "本产品最大回撒"]
+    ].astype(float)
+    return combined_df
+
+
+def fund_individual_analysis_xq(
+        symbol: str = "000001", timeout: float = None
+) -> pd.DataFrame:
+    """
+    雪球基金-基金数据分析
+    https://danjuanfunds.com/djapi/fund/base/quote/data/index/analysis/675091
+    :param symbol: 基金代码
+    :type symbol: str
+    :param timeout: choice of None or a positive float number
+    :type timeout: float
+    :return: 基金数据分析
+    :rtype: pandas.DataFrame
+    """
+    url = f"https://danjuanfunds.com/djapi/fund/base/quote/data/index/analysis/{symbol}"
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36"
+    }
+    r = requests.get(url, headers=headers, timeout=timeout)
+    json_data = r.json()["data"]["index_data_list"]
+    temp_df = pd.json_normalize(json_data)
+    temp_df = temp_df[
+        [
+            "index_time_period",
+            "investment_cost_performance",
+            "risk_control",
+            "self_index.volatility_rank",
+            "self_index.sharpe_rank",
+            "self_index.max_draw_down",
+        ]
+    ]
+    temp_df.columns = [
+        "周期",
+        "较同类风险收益比",
+        "较同类抗风险波动",
+        "年化波动率",
+        "年化夏普比率",
+        "最大回撤",
+    ]
+    temp_df = temp_df.map(
+        lambda x: x if "%" not in str(x) else x.replace("%", "")
+    )
+    temp_df[["年化波动率", "最大回撤"]] *= 100
+    temp_df['较同类风险收益比'] = pd.to_numeric(temp_df['较同类风险收益比'], errors="coerce")
+    temp_df['较同类抗风险波动'] = pd.to_numeric(temp_df['较同类抗风险波动'], errors="coerce")
+    temp_df['年化波动率'] = pd.to_numeric(temp_df['年化波动率'], errors="coerce")
+    temp_df['年化夏普比率'] = pd.to_numeric(temp_df['年化夏普比率'], errors="coerce")
+    temp_df['最大回撤'] = pd.to_numeric(temp_df['最大回撤'], errors="coerce")
+    return temp_df
+
+
+def fund_individual_profit_probability_xq(
+        symbol: str = "000001", timeout: float = None
+) -> pd.DataFrame:
+    """
+    雪球基金-盈利概率-历史任意时点买入，持有满 X 年，盈利概率 Y%
+    https://danjuanfunds.com/djapi/fundx/base/fund/profit/ratio/675091
+    :param symbol: 基金代码
+    :type symbol: str
+    :param timeout: choice of None or a positive float number
+    :type timeout: float
+    :return: 盈利概率
+    :rtype: pandas.DataFrame
+    """
+    url = (
+        f"https://danjuanfunds.com/djapi/fundx/base/fund/profit/ratio/{symbol}"
+    )
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36"
+    }
+    r = requests.get(url, headers=headers, timeout=timeout)
+    json_data = r.json()["data"]["data_list"]
+    temp_df = pd.DataFrame.from_dict(json_data, orient="columns")
+    temp_df = temp_df[
+        [
+            "holding_time",
+            "profit_ratio",
+            "average_income",
+        ]
+    ]
+    temp_df.columns = [
+        "持有时长",
+        "盈利概率",
+        "平均收益",
+    ]
+    temp_df = temp_df.map(
+        lambda x: x if "%" not in str(x) else x.replace("%", "")
+    )
+    temp_df['盈利概率'] = pd.to_numeric(temp_df['盈利概率'], errors="coerce")
+    temp_df['平均收益'] = pd.to_numeric(temp_df['平均收益'], errors="coerce")
+    return temp_df
+
+
+def fund_individual_detail_info_xq(
+        symbol: str = "000001", indicator: str = "交易规则", timeout: float = None
+) -> pd.DataFrame:
+    """
+    雪球基金-详细信息
+    https://danjuanfunds.com/djapi/fund/detail/675091
+    :param symbol: 基金代码
+    :type symbol: str
+    :param indicator: 信息类型; choice of {"交易规则", "持仓资产比例"}
+    :type symbol: str
+    :param timeout: choice of None or a positive float number
+    :type timeout: float
+    :return: 盈利概率
+    :rtype: pandas.DataFrame
+    """
+    url = f"https://danjuanfunds.com/djapi/fund/detail/{symbol}"
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.149 Safari/537.36"
+    }
+    r = requests.get(url, headers=headers, timeout=timeout)
+    json_data = r.json()["data"]
+
+    if indicator == "持仓资产比例":
+        temp_df = pd.DataFrame.from_dict(
+            json_data["fund_position"]["chart_list"], orient="columns"
+        )
+        temp_df = temp_df[
+            [
+                "type_desc",
+                "percent",
+            ]
+        ]
+        temp_df.columns = [
+            "资产类型",
+            "仓位占比",
+        ]
+        temp_df['仓位占比'] = pd.to_numeric(temp_df['仓位占比'], errors="coerce")
+        return temp_df
+    elif indicator == "交易规则":
+        combined_df = None
+        rate_type_dict = {
+            "declare_rate_table": "买入规则",
+            "withdraw_rate_table": "卖出规则",
+            "other_rate_table": "其他费用",
+        }
+        for k, v in rate_type_dict.items():
+            temp_df = pd.DataFrame.from_dict(
+                json_data["fund_rates"][k], orient="columns"
+            )
+            temp_df["rate_type"] = v
+            temp_df = temp_df[
+                [
+                    "rate_type",
+                    "name",
+                    "value",
+                ]
+            ]
+            temp_df.columns = [
+                "费用类型",
+                "条件或名称",
+                "费用",
+            ]
+            combined_df = pd.concat([combined_df, temp_df], ignore_index=True)
+            combined_df['费用'] = pd.to_numeric(combined_df['费用'], errors="coerce")
+        return combined_df
+
+
+if __name__ == "__main__":
+    fund_individual_basic_info_xq_df = fund_individual_basic_info_xq()
+    print(fund_individual_basic_info_xq_df)
+
+    fund_individual_achievement_xq_df = fund_individual_achievement_xq()
+    print(fund_individual_achievement_xq_df)
+
+    fund_individual_analysis_xq_df = fund_individual_analysis_xq()
+    print(fund_individual_analysis_xq_df)
+
+    fund_individual_profit_probability_xq_df = fund_individual_profit_probability_xq()
+    print(fund_individual_profit_probability_xq_df)
+
+    fund_individual_detail_info_xq_df = fund_individual_detail_info_xq(indicator="交易规则")
+    print(fund_individual_detail_info_xq_df)
+
+    fund_individual_detail_info_xq_df = fund_individual_detail_info_xq(indicator="持仓资产比例")
+    print(fund_individual_detail_info_xq_df)
diff --git a/akshare/futures/receipt.py b/akshare/futures/receipt.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding:utf-8 -*-
 """
-Date: 2023/6/21 18:00
+Date: 2024/1/3 17:00
 Desc: 每日注册仓单数据
 大连商品交易所, 上海期货交易所, 郑州商品交易所, 广州期货交易所
 """
@@ -77,7 +77,7 @@ def get_shfe_receipt_1(date: str = None, vars_list: List = cons.contract_symbols
     :rtype: pandas.DataFrame
     """
     if not isinstance(vars_list, list):
-        return warnings.warn(f"symbol_list: 必须是列表")
+        raise warnings.warn(f"symbol_list: 必须是列表")
     date = cons.convert_date(date).strftime('%Y%m%d') if date is not None else datetime.date.today()
     if date not in calendar:
         warnings.warn(f"{date.strftime('%Y%m%d')}非交易日")
@@ -128,10 +128,10 @@ def get_shfe_receipt_2(date: str = None, vars_list: List = cons.contract_symbols
     :rtype: pandas.DataFrame
     """
     if not isinstance(vars_list, list):
-        return warnings.warn(f"symbol_list: 必须是列表")
+        raise warnings.warn(f"symbol_list: 必须是列表")
     date = cons.convert_date(date).strftime('%Y%m%d') if date is not None else datetime.date.today()
     if date not in calendar:
-        warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
+        warnings.warn('%s 非交易日' % date.strftime('%Y%m%d'))
         return None
     url = cons.SHFE_RECEIPT_URL_2 % date
     r = requests_link(url, encoding='utf-8', headers=cons.shfe_headers)
@@ -389,15 +389,18 @@ def get_gfex_receipt(date: str = None, vars_list: List = cons.contract_symbols)
     result_df = result_df[[
         'var', 'receipt', 'receipt_chg', 'date'
     ]]
+    result_df.set_index(['var'], inplace=True)
+    result_df = result_df.loc[vars_list, :]
+    result_df.reset_index(inplace=True)
     return result_df
 
 
 def get_receipt(start_day: str = None, end_day: str = None, vars_list: List = cons.contract_symbols):
     """
     大宗商品-注册仓单数据
-    :param start_day: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
+    :param start_day: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date 对象 为空时为当天
     :type start_day: str
-    :param end_day: 结束数据 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
+    :param end_day: 结束数据 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date 对象 为空时为当天
     :type end_day: str
     :param vars_list: 合约品种如 RB、AL 等列表为空时为所有商品
     :type vars_list: str
@@ -412,7 +415,7 @@ def get_receipt(start_day: str = None, end_day: str = None, vars_list: List = co
     records = pd.DataFrame()
     while start_day <= end_day:
         if start_day.strftime('%Y%m%d') not in calendar:
-            warnings.warn(f"{start_day.strftime('%Y%m%d')}非交易日")
+            warnings.warn(f"{start_day.strftime('%Y%m%d')} 非交易日")
         else:
             print(start_day)
             for market, market_vars in cons.market_exchange_symbols.items():
@@ -458,5 +461,5 @@ def get_receipt(start_day: str = None, end_day: str = None, vars_list: List = co
 
 
 if __name__ == '__main__':
-    get_receipt_df = get_receipt(start_day='20231205', end_day='20231210')
+    get_receipt_df = get_receipt(start_day='20240103', end_day='20240103', vars_list=['SI'])
     print(get_receipt_df)