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
122 lines
3.7 KiB
Python
122 lines
3.7 KiB
Python
# -*- coding:utf-8 -*-
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# !/usr/bin/env python
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"""
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Date: 2024/5/16 20:00
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Desc: 99 期货-数据-期现-现货走势
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https://www.99qh.com/data/spotTrend
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"""
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import json
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import pandas as pd
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import requests
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from bs4 import BeautifulSoup
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def __get_item_of_spot_price_qh() -> pd.DataFrame:
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"""
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99 期货-数据-期现-品种和 ID 对应表
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https://www.99qh.com/data/spotTrend
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:return: 品种和 ID 对应表
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:rtype: str
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"""
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url = "https://www.99qh.com/data/spotTrend"
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r = requests.get(url)
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soup = BeautifulSoup(r.text, features="lxml")
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data_text = soup.find(name="script", attrs={"id": "__NEXT_DATA__"}).text
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data_json = json.loads(data_text)
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big_list = []
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for item in data_json["props"]["pageProps"]["data"]["varietyListData"]:
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big_list.extend(item["productList"])
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temp_df = pd.DataFrame(big_list)
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temp_df = temp_df[["qhExchangeName", "name", "productId"]]
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return temp_df
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def __get_token_of_spot_price_qh() -> str:
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"""
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99 期货-数据-期现-token
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https://www.99qh.com/data/spotTrend
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:return: token
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:rtype: str
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"""
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url = "https://centerapi.fx168api.com/app/common/v.js"
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headers = {
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"Origin": "https://www.99qh.com",
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"Referer": "https://www.99qh.com",
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/124.0.0.0 Safari/537.36",
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}
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r = requests.get(url, headers=headers)
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token = r.headers["_pcc"]
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return token
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def spot_price_table_qh() -> pd.DataFrame:
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"""
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99 期货-数据-期现-交易所与品种对照表
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https://www.99qh.com/data/spotTrend
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:return: 交易所与品种对照表
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:rtype: pandas.DataFrame
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"""
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temp_df = __get_item_of_spot_price_qh()
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temp_df.rename(
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columns={
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"qhExchangeName": "交易所名称",
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"name": "品种名称",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"交易所名称",
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"品种名称",
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]
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]
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return temp_df
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def spot_price_qh(symbol: str = "螺纹钢") -> pd.DataFrame:
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"""
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99 期货-数据-期现-现货走势
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https://www.99qh.com/data/spotTrend
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:param symbol: 品种名称
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:type symbol: str
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:return: 现货走势
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:rtype: pandas.DataFrame
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"""
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inner_df = __get_item_of_spot_price_qh()
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symbol_map = dict(zip(inner_df["name"], inner_df["productId"]))
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url = "https://centerapi.fx168api.com/app/qh/api/spot/trend"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/124.0.0.0 Safari/537.36",
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"_pcc": __get_token_of_spot_price_qh(),
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"Origin": "https://www.99qh.com",
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"Referer": "https://www.99qh.com",
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}
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params = {
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"productId": symbol_map[symbol],
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"pageNo": "1",
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"pageSize": "50000",
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"startDate": "",
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"endDate": "2050-01-01",
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"appCategory": "web",
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}
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r = requests.get(url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"]["list"])
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temp_df.rename(
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columns={"date": "日期", "fp": "期货收盘价", "sp": "现货价格"}, inplace=True
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)
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temp_df.sort_values(by=["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["期货收盘价"] = pd.to_numeric(temp_df["期货收盘价"], errors="coerce")
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temp_df["现货价格"] = pd.to_numeric(temp_df["现货价格"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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spot_price_qh_df = spot_price_qh(symbol="螺纹钢")
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print(spot_price_qh_df)
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