知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
107 lines
3.6 KiB
Python
107 lines
3.6 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2023/11/11 16:30
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Desc: 东方财富-基金
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"""
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from io import StringIO
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import pandas as pd
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import requests
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def fund_aum_em() -> pd.DataFrame:
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"""
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东方财富-基金-基金公司排名列表
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https://fund.eastmoney.com/Company/lsgm.html
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:return: 基金公司排名列表
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:rtype: pandas.DataFrame
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"""
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url = "https://fund.eastmoney.com/Company/home/gspmlist"
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params = {"fundType": "0"}
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r = requests.get(url, params=params)
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temp_df = pd.read_html(StringIO(r.text))[0]
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del temp_df["相关链接"]
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del temp_df["天相评级"]
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temp_df.columns = [
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"序号",
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"基金公司",
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"成立时间",
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"全部管理规模",
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"全部基金数",
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"全部经理数",
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]
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expanded_df = temp_df["全部管理规模"].str.split(" ", expand=True)
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temp_df["全部管理规模"] = expanded_df.iloc[:, 0].str.replace(",", "")
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temp_df["更新日期"] = expanded_df.iloc[:, 1]
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temp_df["全部管理规模"] = pd.to_numeric(temp_df["全部管理规模"], errors="coerce")
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temp_df["全部基金数"] = pd.to_numeric(temp_df["全部基金数"], errors="coerce")
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temp_df["全部经理数"] = pd.to_numeric(temp_df["全部经理数"], errors="coerce")
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temp_df["成立时间"] = pd.to_datetime(temp_df["成立时间"], errors="coerce").dt.date
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return temp_df
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def fund_aum_trend_em() -> pd.DataFrame:
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"""
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东方财富-基金-基金市场管理规模走势图
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https://fund.eastmoney.com/Company/default.html
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:return: 基金市场管理规模走势图
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:rtype: pandas.DataFrame
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"""
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url = "https://fund.eastmoney.com/Company/home/GetFundTotalScaleForChart"
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payload = {"fundType": "0"}
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r = requests.get(url, data=payload)
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data_json = r.json()
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temp_df = pd.DataFrame()
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temp_df["date"] = data_json["x"]
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temp_df["value"] = data_json["y"]
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temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
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temp_df["value"] = pd.to_numeric(temp_df["value"], errors="coerce")
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return temp_df
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def fund_aum_hist_em(year: str = "2023") -> pd.DataFrame:
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"""
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东方财富-基金-基金公司历年管理规模排行列表
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https://fund.eastmoney.com/Company/lsgm.html
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:param year: query year
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:type year: str
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:return: 基金公司历年管理规模排行列表
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:rtype: pandas.DataFrame
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"""
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url = "https://fund.eastmoney.com/Company/home/HistoryScaleTable"
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params = {"year": year}
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r = requests.get(url, params=params)
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temp_df = pd.read_html(StringIO(r.text))[0]
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temp_df.columns = [
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"序号",
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"基金公司",
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"总规模",
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"股票型",
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"混合型",
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"债券型",
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"指数型",
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"QDII",
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"货币型",
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]
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temp_df["总规模"] = pd.to_numeric(temp_df["总规模"], errors="coerce")
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temp_df["股票型"] = pd.to_numeric(temp_df["股票型"], errors="coerce")
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temp_df["混合型"] = pd.to_numeric(temp_df["混合型"], errors="coerce")
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temp_df["债券型"] = pd.to_numeric(temp_df["债券型"], errors="coerce")
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temp_df["指数型"] = pd.to_numeric(temp_df["指数型"], errors="coerce")
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temp_df["QDII"] = pd.to_numeric(temp_df["QDII"], errors="coerce")
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temp_df["货币型"] = pd.to_numeric(temp_df["货币型"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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fund_aum_em_df = fund_aum_em()
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print(fund_aum_em_df)
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fund_aum_trend_em_df = fund_aum_trend_em()
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print(fund_aum_trend_em_df)
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fund_em_aum_hist_df = fund_aum_hist_em(year="2023")
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print(fund_em_aum_hist_df)
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