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