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
245 lines
7.4 KiB
Python
245 lines
7.4 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2026/1/12 15:00
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Desc: 国证指数
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https://www.cnindex.com.cn/index.html
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"""
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import zipfile
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from io import BytesIO
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import pandas as pd
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import requests
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def index_all_cni() -> pd.DataFrame:
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"""
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国证指数-最近交易日的所有指数
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https://www.cnindex.com.cn/zh_indices/sese/index.html?act_menu=1&index_type=-1
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:return: 国证指数-所有指数
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:rtype: pandas.DataFrame
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"""
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url = "https://www.cnindex.com.cn/index/indexList"
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params = {
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"channelCode": "-1",
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"rows": "2000",
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"pageNum": "1",
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}
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r = requests.get(url, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"]["rows"])
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temp_df.columns = [
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"_",
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"_",
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"指数代码",
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"_",
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"_",
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"_",
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"_",
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"_",
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"指数简称",
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"_",
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"_",
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"_",
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"样本数",
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"收盘点位",
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"涨跌幅",
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"_",
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"PE滚动",
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"_",
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"成交量",
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"成交额",
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"总市值",
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"自由流通市值",
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"_",
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"_",
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"_",
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]
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temp_df = temp_df[
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[
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"指数代码",
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"指数简称",
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"样本数",
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"收盘点位",
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"涨跌幅",
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"PE滚动",
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"成交量",
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"成交额",
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"总市值",
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"自由流通市值",
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]
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]
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temp_df["成交量"] = temp_df["成交量"] / 100000
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temp_df["成交额"] = temp_df["成交额"] / 100000000
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temp_df["总市值"] = temp_df["总市值"] / 100000000
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temp_df["自由流通市值"] = temp_df["自由流通市值"] / 100000000
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return temp_df
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def index_hist_cni(
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symbol: str = "399001", start_date: str = "20230114", end_date: str = "20240114"
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) -> pd.DataFrame:
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"""
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指数历史行情数据
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http://www.cnindex.com.cn/module/index-detail.html?act_menu=1&indexCode=399001
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:param symbol: 指数代码
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:type symbol: str
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:param start_date: 开始时间
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:type start_date: str
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:param end_date: 结束时间
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:type end_date: str
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:return: 指数历史行情数据
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:rtype: pandas.DataFrame
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"""
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start_date = "-".join([start_date[:4], start_date[4:6], start_date[6:]])
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end_date = "-".join([end_date[:4], end_date[4:6], end_date[6:]])
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url = "http://hq.cnindex.com.cn/market/market/getIndexDailyDataWithDataFormat"
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params = {
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"indexCode": symbol,
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"startDate": start_date,
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"endDate": end_date,
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"frequency": "day",
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}
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r = requests.get(url, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"]["data"])
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temp_df.columns = [
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"日期",
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"_",
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"最高价",
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"开盘价",
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"最低价",
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"收盘价",
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"_",
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"涨跌幅",
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"成交额",
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"成交量",
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"_",
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]
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temp_df = temp_df[
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[
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"日期",
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"开盘价",
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"最高价",
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"最低价",
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"收盘价",
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"涨跌幅",
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"成交量",
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"成交额",
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]
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]
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temp_df["涨跌幅"] = temp_df["涨跌幅"].str.replace("%", "")
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temp_df["涨跌幅"] = temp_df["涨跌幅"].astype("float")
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temp_df["涨跌幅"] = temp_df["涨跌幅"] / 100
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temp_df.sort_values(["日期"], inplace=True, ignore_index=True)
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temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
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temp_df["开盘价"] = pd.to_numeric(temp_df["开盘价"], errors="coerce")
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temp_df["最高价"] = pd.to_numeric(temp_df["最高价"], errors="coerce")
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temp_df["最低价"] = pd.to_numeric(temp_df["最低价"], errors="coerce")
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temp_df["收盘价"] = pd.to_numeric(temp_df["收盘价"], errors="coerce")
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temp_df["涨跌幅"] = pd.to_numeric(temp_df["涨跌幅"], errors="coerce")
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temp_df["成交量"] = pd.to_numeric(temp_df["成交量"], errors="coerce")
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temp_df["成交额"] = pd.to_numeric(temp_df["成交额"], errors="coerce")
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return temp_df
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def index_detail_cni(symbol: str = "399001") -> pd.DataFrame:
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"""
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国证指数-样本详情-指定日期的样本成份
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https://www.cnindex.com.cn/module/index-detail.html?act_menu=1&indexCode=399001
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:param symbol: 指数代码
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:type symbol: str
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:return: 指定日期的样本成份
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:rtype: pandas.DataFrame
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"""
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import warnings
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warnings.simplefilter(action="ignore", category=UserWarning)
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url = "https://www.cnindex.com.cn/sample-detail/download-history"
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params = {"indexcode": symbol}
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r = requests.get(url, params=params)
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temp_df = pd.read_excel(BytesIO(r.content))
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temp_df["样本代码"] = temp_df["样本代码"].astype(str).str.zfill(6)
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temp_df.columns = [
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"日期",
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"样本代码",
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"样本简称",
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"所属行业",
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"总市值",
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"权重",
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]
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temp_df["总市值"] = pd.to_numeric(temp_df["总市值"], errors="coerce")
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temp_df["权重"] = pd.to_numeric(temp_df["权重"], errors="coerce")
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return temp_df
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def index_detail_hist_cni(symbol: str = "399001") -> pd.DataFrame:
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"""
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国证指数-样本详情-历史样本
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https://www.cnindex.com.cn/module/index-detail.html?act_menu=1&indexCode=399001
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:param symbol: 指数代码; "399001"
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:type symbol: str
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:return: 历史样本
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:rtype: pandas.DataFrame
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"""
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url = "https://www.cnindex.com.cn/sample-detail/download-history"
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params = {"indexcode": symbol}
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r = requests.get(url, params=params)
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temp_df = pd.read_excel(BytesIO(r.content))
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temp_df["样本代码"] = temp_df["样本代码"].astype(str).str.zfill(6)
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temp_df.columns = [
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"日期",
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"样本代码",
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"样本简称",
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"所属行业",
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"总市值",
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"权重",
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]
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temp_df["总市值"] = pd.to_numeric(temp_df["总市值"])
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temp_df["权重"] = pd.to_numeric(temp_df["权重"])
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return temp_df
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def index_detail_hist_adjust_cni(symbol: str = "399005") -> pd.DataFrame:
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"""
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国证指数-样本详情-历史调样
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http://www.cnindex.com.cn/module/index-detail.html?act_menu=1&indexCode=399005
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:param symbol: 指数代码
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:type symbol: str
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:return: 历史调样
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:rtype: pandas.DataFrame
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"""
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url = "http://www.cnindex.com.cn/sample-detail/download-adjustment"
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params = {"indexcode": symbol}
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r = requests.get(url, params=params)
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try:
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import warnings
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with warnings.catch_warnings():
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warnings.simplefilter(action="ignore", category=UserWarning)
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temp_df = pd.read_excel(BytesIO(r.content), engine="openpyxl")
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except zipfile.BadZipFile:
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return pd.DataFrame()
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temp_df["样本代码"] = temp_df["样本代码"].astype(str).str.zfill(6)
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return temp_df
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if __name__ == "__main__":
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index_all_cni_df = index_all_cni()
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print(index_all_cni_df)
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index_hist_cni_df = index_hist_cni(
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symbol="399005", start_date="20230114", end_date="20260328"
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)
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print(index_hist_cni_df)
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index_detail_cni_df = index_detail_cni(symbol="399001")
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print(index_detail_cni_df)
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index_detail_hist_cni_df = index_detail_hist_cni(symbol="399101", date="202404")
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print(index_detail_hist_cni_df)
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index_detail_hist_adjust_cni_df = index_detail_hist_adjust_cni(symbol="399005")
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print(index_detail_hist_adjust_cni_df)
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