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
253 lines
8.0 KiB
Python
253 lines
8.0 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/3/9 22:00
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Desc: 东方财富网-行情中心-期货市场-国际期货
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https://quote.eastmoney.com/center/gridlist.html#futures_global
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"""
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import math
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from typing import Optional
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import pandas as pd
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import requests
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from akshare.utils.tqdm import get_tqdm
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def __futures_global_hist_market_code(symbol: str = "HG00Y") -> Optional[int]:
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"""
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东方财富网-行情中心-期货市场-国际期货-品种市场对照表
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https://quote.eastmoney.com/center/gridlist.html#futures_global
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:param symbol: HG00Y, 品种代码；可以通过 ak.futures_global_spot_em() 来获取所有可获取历史行情数据的品种代码
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:type symbol: str
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:return: 品种所属于的市场
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:rtype: str
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"""
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# 提取品种代码（去掉年份和月份部分）
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base_symbol = ""
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i = 0
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while i < len(symbol) and not symbol[i].isdigit():
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base_symbol += symbol[i]
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i += 1
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# 如果代码中没有数字（异常情况），则返回整个代码作为基础品种代码
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if not base_symbol and i == len(symbol):
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base_symbol = symbol
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# 金属和贵金属品种 - 101
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if base_symbol in ["HG", "GC", "SI", "QI", "QO", "MGC", "LTH"]:
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return 101
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# 能源品种 - 102
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if base_symbol in ["CL", "NG", "RB", "HO", "PA", "PL", "QM"]:
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return 102
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# 农产品和金融品种 - 103
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if base_symbol in [
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"ZW",
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"ZM",
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"ZS",
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"ZC",
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"XC",
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"XK",
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"XW",
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"YM",
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"TY",
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"US",
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"EH",
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"ZL",
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"ZR",
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"ZO",
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"FV",
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"TU",
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"UL",
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"NQ",
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"ES",
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]:
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return 103
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# 中国市场特有品种 - 104
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if base_symbol in ["TF", "RT", "CN"]:
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return 104
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# 软商品期货 - 108
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if base_symbol in ["SB", "CT", "SF"]:
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return 108
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# 特殊L开头品种 - 109
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if base_symbol in ["LCPT", "LZNT", "LALT", "LTNT", "LLDT", "LNKT"]:
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return 109
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# MPM开头品种 - 110
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if base_symbol == "MPM":
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return 110
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# 日本市场品种 - 111
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if base_symbol.startswith("J"):
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return 111
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# 单字母代码品种 - 112
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if base_symbol in ["M", "B", "G"]:
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return 112
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# 如果没有匹配到任何规则，返回一个默认值或者错误
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return None
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def futures_global_spot_em() -> pd.DataFrame:
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"""
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东方财富网-行情中心-期货市场-国际期货
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https://quote.eastmoney.com/center/gridlist.html#futures_global
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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://futsseapi.eastmoney.com/list/COMEX,NYMEX,COBOT,SGX,NYBOT,LME,MDEX,TOCOM,IPE"
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params = {
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"orderBy": "dm",
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"sort": "desc",
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"pageSize": "20",
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"pageIndex": "0",
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"token": "58b2fa8f54638b60b87d69b31969089c",
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"field": "dm,sc,name,p,zsjd,zde,zdf,f152,o,h,l,zjsj,vol,wp,np,ccl",
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"blockName": "callback",
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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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total_num = data_json["total"]
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total_page = math.ceil(total_num / 20) - 1
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tqdm = get_tqdm()
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big_df = pd.DataFrame()
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for page in tqdm(range(total_page), leave=False):
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params.update({"pageIndex": page})
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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["list"])
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big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
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big_df.reset_index(inplace=True)
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big_df["index"] = big_df["index"] + 1
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big_df.rename(
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columns={
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"index": "序号",
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"np": "卖盘",
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"h": "最高",
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"dm": "代码",
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"zsjd": "-",
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"l": "最低",
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"ccl": "持仓量",
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"o": "今开",
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"p": "最新价",
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"sc": "-",
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"vol": "成交量",
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"name": "名称",
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"wp": "买盘",
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"zde": "涨跌额",
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"zdf": "涨跌幅",
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"zjsj": "昨结",
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},
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inplace=True,
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)
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big_df = big_df[
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[
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"序号",
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"代码",
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"名称",
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"最新价",
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"涨跌额",
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"涨跌幅",
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"今开",
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"最高",
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"最低",
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"昨结",
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"成交量",
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"买盘",
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"卖盘",
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"持仓量",
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]
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]
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big_df["最新价"] = pd.to_numeric(big_df["最新价"], errors="coerce")
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big_df["涨跌额"] = pd.to_numeric(big_df["涨跌额"], errors="coerce")
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big_df["涨跌幅"] = pd.to_numeric(big_df["涨跌幅"], errors="coerce")
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big_df["今开"] = pd.to_numeric(big_df["今开"], errors="coerce")
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big_df["最高"] = pd.to_numeric(big_df["最高"], errors="coerce")
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big_df["最低"] = pd.to_numeric(big_df["最低"], errors="coerce")
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big_df["昨结"] = pd.to_numeric(big_df["昨结"], errors="coerce")
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big_df["成交量"] = pd.to_numeric(big_df["成交量"], errors="coerce")
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big_df["买盘"] = pd.to_numeric(big_df["买盘"], errors="coerce")
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big_df["卖盘"] = pd.to_numeric(big_df["卖盘"], errors="coerce")
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big_df["持仓量"] = pd.to_numeric(big_df["持仓量"], errors="coerce")
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return big_df
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def futures_global_hist_em(symbol: str = "HG00Y") -> pd.DataFrame:
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"""
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东方财富网-行情中心-期货市场-国际期货-历史行情数据
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https://quote.eastmoney.com/globalfuture/HG25J.html
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:param symbol: 品种代码；可以通过 ak.futures_global_spot_em() 来获取所有可获取历史行情数据的品种代码
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:type symbol: str
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:return: 历史行情数据
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:rtype: pandas.DataFrame
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"""
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url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
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market_code = __futures_global_hist_market_code(symbol)
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params = {
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"secid": f"{market_code}.{symbol}",
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"klt": "101",
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"fqt": "1",
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"lmt": "6600",
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"end": "20500000",
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"iscca": "1",
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"fields1": "f1,f2,f3,f4,f5,f6,f7,f8",
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"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64",
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"ut": "f057cbcbce2a86e2866ab8877db1d059",
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"forcect": "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([item.split(",") for item in data_json["data"]["klines"]])
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temp_df["code"] = data_json["data"]["code"]
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temp_df["name"] = data_json["data"]["name"]
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temp_df.columns = [
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"日期",
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"开盘",
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"最新价",
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"最高",
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"最低",
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"总量",
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"-",
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"-",
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"涨幅",
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"-",
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"-",
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"-",
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"持仓",
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"日增",
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"代码",
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"名称",
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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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"代码",
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"名称",
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"开盘",
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"最新价",
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"最高",
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"最低",
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"总量",
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"涨幅",
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"持仓",
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"日增",
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]
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]
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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"] = pd.to_numeric(temp_df["开盘"], errors="coerce")
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temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
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temp_df["最高"] = pd.to_numeric(temp_df["最高"], errors="coerce")
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temp_df["最低"] = pd.to_numeric(temp_df["最低"], errors="coerce")
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temp_df["总量"] = pd.to_numeric(temp_df["总量"], errors="coerce")
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temp_df["涨幅"] = pd.to_numeric(temp_df["涨幅"], errors="coerce")
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temp_df["日增"] = pd.to_numeric(temp_df["日增"], errors="coerce")
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# 日增修复为有符号32位整数值
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unsigned_max, signed_max = (2**32) - 1, (2**31) - 1
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mask = temp_df["日增"] > signed_max
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temp_df.loc[mask, "日增"] = temp_df.loc[mask, "日增"] - (unsigned_max + 1)
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return temp_df
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if __name__ == "__main__":
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futures_global_spot_em_df = futures_global_spot_em()
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print(futures_global_spot_em_df)
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futures_global_hist_em_df = futures_global_hist_em(symbol="HG00Y")
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print(futures_global_hist_em_df)
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