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
244 lines
8.5 KiB
Python
244 lines
8.5 KiB
Python
# -*- coding:utf-8 -*-
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# !/usr/bin/env python
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"""
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Date: 2025/4/11 22:00
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Desc: 上海黄金交易所-数据资讯-行情走势
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https://www.sge.com.cn/sjzx/mrhq
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上海黄金交易所-数据资讯-上海金基准价-历史数据
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上海黄金交易所-数据资讯-上海银基准价-历史数据
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"""
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import pandas as pd
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import requests
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from akshare.utils.cons import headers
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def spot_symbol_table_sge() -> pd.DataFrame:
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"""
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上海黄金交易所-数据资讯-行情走势-品种表
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https://www.sge.com.cn/sjzx/mrhq
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:return: 品种表
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:rtype: pandas.DataFrame
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"""
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temp_list = [
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"Au99.99",
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"Au99.95",
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"Au100g",
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"Pt99.95",
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"Ag(T+D)",
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"Au(T+D)",
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"mAu(T+D)",
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"Au(T+N1)",
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"Au(T+N2)",
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"Ag99.99",
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"iAu99.99",
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"Au99.5",
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"iAu100g",
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"iAu99.5",
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"PGC30g",
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"NYAuTN06",
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"NYAuTN12",
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]
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temp_df = pd.DataFrame(temp_list)
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temp_df.reset_index(inplace=True)
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temp_df.columns = ["序号", "品种"]
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temp_df["序号"] = temp_df["序号"] + 1
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return temp_df
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def spot_quotations_sge(symbol: str = "Au99.99") -> pd.DataFrame:
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"""
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上海黄金交易所-实时行情数据
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https://www.sge.com.cn/
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https://www.sge.com.cn/graph/quotations
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:param symbol: choice of {'Au99.99', 'Au99.95', 'Au100g', 'Pt99.95', 'Ag(T+D)', 'Au(T+D)',
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'mAu(T+D)', 'Au(T+N1)', 'Au(T+N2)', 'Ag99.99', 'iAu99.99', 'Au99.5', 'iAu100g',
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'iAu99.5', 'PGC30g', 'NYAuTN06', 'NYAuTN12'}; 可以通过 ak.spot_symbol_table_sge() 获取品种表
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:type symbol: str
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:return: 行情数据
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:rtype: pandas.DataFrame
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"""
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url = "https://www.sge.com.cn/graph/quotations"
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payload = {"instid": symbol}
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headers = {
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"Accept": "application/json, text/javascript, */*; q=0.01",
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"Accept-Encoding": "gzip, deflate, br, zstd",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Content-Length": "15",
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"Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
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"Host": "www.sge.com.cn",
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"Origin": "https://www.sge.com.cn",
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"Pragma": "no-cache",
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"Referer": "https://www.sge.com.cn/",
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"sec-ch-ua": '"Google Chrome";v="107", "Chromium";v="107", "Not=A?Brand";v="24"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Windows"',
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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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/107.0.0.0 Safari/537.36",
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"X-Requested-With": "XMLHttpRequest",
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}
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r = requests.get(url, data=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(
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{
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"品种": data_json["heyue"],
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"时间": data_json["times"],
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"现价": data_json["data"],
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"更新时间": data_json["delaystr"],
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}
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)
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temp_df["现价"] = pd.to_numeric(temp_df["现价"], errors="coerce")
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# 将更新时间中的时间部分提取出来
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update_time = temp_df["更新时间"].iloc[0].split()[1]
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# 将时间列转换为时间格式以便排序
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temp_df["时间"] = pd.to_datetime(temp_df["时间"], format="%H:%M").dt.time
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# 过滤掉大于等于更新时间的数据
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temp_df = temp_df[temp_df["时间"].astype(str) < update_time]
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# 按时间排序
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temp_df = temp_df.sort_values(by=["时间"])
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temp_df.reset_index(inplace=True, drop=True)
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return temp_df
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def spot_hist_sge(symbol: str = "Au99.99") -> pd.DataFrame:
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"""
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上海黄金交易所-数据资讯-行情走势-历史数据
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https://www.sge.com.cn/sjzx/mrhq
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:param symbol: choice of {'Au99.99', 'Au99.95', 'Au100g', 'Pt99.95', 'Ag(T+D)', 'Au(T+D)',
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'mAu(T+D)', 'Au(T+N1)', 'Au(T+N2)', 'Ag99.99', 'iAu99.99', 'Au99.5', 'iAu100g', 'iAu99.5',
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'PGC30g', 'NYAuTN06', 'NYAuTN12'}; 可以通过 ak.spot_symbol_table_sge() 获取品种表
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:type symbol: str
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:return: 历史数据
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:rtype: pandas.DataFrame
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"""
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url = "https://www.sge.com.cn/graph/Dailyhq"
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payload = {"instid": symbol}
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headers = {
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"Accept": "text/html, */*; q=0.01",
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"Accept-Encoding": "gzip, deflate, br",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Content-Length": "15",
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"Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
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"Host": "www.sge.com.cn",
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"Origin": "https://www.sge.com.cn",
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"Pragma": "no-cache",
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"Referer": "https://www.sge.com.cn/sjzx/mrhq",
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"sec-ch-ua": '"Google Chrome";v="107", "Chromium";v="107", "Not=A?Brand";v="24"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Windows"',
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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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/107.0.0.0 Safari/537.36",
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"X-Requested-With": "XMLHttpRequest",
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}
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r = requests.post(url, data=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["time"])
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temp_df.columns = [
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"date",
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"open",
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"close",
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"low",
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"high",
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]
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temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
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temp_df["open"] = pd.to_numeric(temp_df["open"], errors="coerce")
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temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce")
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temp_df["high"] = pd.to_numeric(temp_df["high"], errors="coerce")
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temp_df["low"] = pd.to_numeric(temp_df["low"], errors="coerce")
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return temp_df
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def spot_golden_benchmark_sge() -> pd.DataFrame:
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"""
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上海黄金交易所-数据资讯-上海金基准价-历史数据
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https://www.sge.com.cn/sjzx/jzj
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:return: 历史数据
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:rtype: pandas.DataFrame
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"""
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url = "https://www.sge.com.cn/graph/DayilyJzj"
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payload = {}
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r = requests.post(url, data=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["wp"])
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temp_df.columns = [
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"交易时间",
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"晚盘价",
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]
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temp_df["交易时间"] = pd.to_datetime(temp_df["交易时间"], unit="ms").dt.date
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temp_zp_df = pd.DataFrame(data_json["zp"])
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temp_zp_df.columns = [
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"交易时间",
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"早盘价",
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]
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temp_zp_df["交易时间"] = pd.to_datetime(
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temp_zp_df["交易时间"], unit="ms", errors="coerce"
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).dt.date
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temp_df["早盘价"] = temp_zp_df["早盘价"]
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temp_df["晚盘价"] = pd.to_numeric(temp_df["晚盘价"], errors="coerce")
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temp_df["早盘价"] = pd.to_numeric(temp_df["早盘价"], errors="coerce")
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return temp_df
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def spot_silver_benchmark_sge() -> pd.DataFrame:
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"""
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上海黄金交易所-数据资讯-上海银基准价-历史数据
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https://www.sge.com.cn/sjzx/mrhq
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:return: 历史数据
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:rtype: pandas.DataFrame
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"""
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url = "https://www.sge.com.cn/graph/DayilyShsilverJzj"
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payload = {}
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r = requests.post(url, data=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["wp"])
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temp_df.columns = [
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"交易时间",
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"晚盘价",
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]
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temp_df["交易时间"] = pd.to_datetime(temp_df["交易时间"], unit="ms").dt.date
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temp_zp_df = pd.DataFrame(data_json["zp"])
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temp_zp_df.columns = [
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"交易时间",
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"早盘价",
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]
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temp_zp_df["交易时间"] = pd.to_datetime(
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temp_zp_df["交易时间"], unit="ms", errors="coerce"
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).dt.date
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temp_df["早盘价"] = temp_zp_df["早盘价"]
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temp_df["晚盘价"] = pd.to_numeric(temp_df["晚盘价"], errors="coerce")
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temp_df["早盘价"] = pd.to_numeric(temp_df["早盘价"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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spot_symbol_table_sge_df = spot_symbol_table_sge()
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print(spot_symbol_table_sge_df)
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spot_hist_sge_df = spot_hist_sge(symbol="Au99.99")
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print(spot_hist_sge_df)
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spot_golden_benchmark_sge_df = spot_golden_benchmark_sge()
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print(spot_golden_benchmark_sge_df)
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spot_silver_benchmark_sge_df = spot_silver_benchmark_sge()
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print(spot_silver_benchmark_sge_df)
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for spot in spot_symbol_table_sge_df["品种"].tolist():
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spot_hist_sge_df = spot_hist_sge(symbol=spot)
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print(spot_hist_sge_df)
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spot_quotations_sge_df = spot_quotations_sge(symbol="Au99.99")
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print(spot_quotations_sge_df)
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