一、期货数据接口概述
StockTV提供全球主要期货市场的实时行情与历史数据接口，覆盖以下品种：
- 商品期货：原油、黄金、白银、铜、天然气、农产品等
- 金融期货：股指期货、国债期货
- 特色品种：马棕油、铁矿石等区域特色期货
二、环境准备与配置
1. API密钥获取
API_KEY = "your_futures_api_key" # 通过官网申请
BASE_URL = "https://api.stocktv.top"
2. 安装必要库
pip install requests pandas matplotlib websocket-client
三、期货行情数据对接
1. 获取期货合约列表
def get_futures_list():"""获取可交易期货合约列表"""url = f"{BASE_URL}/futures/list"params = {"key": API_KEY}response = requests.get(url, params=params)return response.json()# 示例调用
futures_list = get_futures_list()
print("可用期货合约:", [f"{x['symbol']} ({x['name']})" for x in futures_list['data'][:5]])
2. 查询特定合约行情
def get_futures_quote(symbol):"""获取期货合约实时行情"""url = f"{BASE_URL}/futures/quote"params = {"symbol": symbol,"key": API_KEY}response = requests.get(url, params=params)return response.json()# 获取原油期货行情
crude_oil = get_futures_quote("CL1!")
print(f"WTI原油最新价: {crude_oil['data']['last']} 涨跌: {crude_oil['data']['change']}")
四、期货K线数据获取
1. 历史K线数据接口
def get_futures_kline(symbol, interval="1d", limit=100):"""获取期货K线数据:param symbol: 合约代码:param interval: 时间间隔(1m/5m/15m/1h/1d):param limit: 数据条数"""url = f"{BASE_URL}/futures/kline"params = {"symbol": symbol,"interval": interval,"limit": limit,"key": API_KEY}response = requests.get(url, params=params)data = response.json()# 转换为DataFramedf = pd.DataFrame(data['data'])df['time'] = pd.to_datetime(df['time'], unit='ms')return df# 获取黄金期货15分钟K线
gold_kline = get_futures_kline("GC1!", "15m")
2. K线数据可视化
import matplotlib.pyplot as pltdef plot_futures_kline(df, title):plt.figure(figsize=(12,6))plt.title(title)# 绘制蜡烛图for i, row in df.iterrows():color = 'red' if row['close'] > row['open'] else 'green'plt.plot([i, i], [row['low'], row['high']], color=color)plt.plot([i-0.2, i+0.2], [row['open'], row['open']], color=color)plt.plot([i-0.2, i+0.2], [row['close'], row['close']], color=color)plt.xlabel('时间')plt.ylabel('价格')plt.grid()plt.show()plot_futures_kline(gold_kline, "COMEX黄金期货15分钟K线")
五、期货交易数据存储方案
1. 数据库设计（SQL示例）
import sqlite3def init_db():conn = sqlite3.connect('futures_data.db')c = conn.cursor()c.execute('''CREATE TABLE IF NOT EXISTS futures_quotes(symbol text, last real, volume integer, time timestamp, PRIMARY KEY (symbol, time))''')c.execute('''CREATE TABLE IF NOT EXISTS futures_kline(symbol text, open real, high real, low real, close real, volume integer, time timestamp,PRIMARY KEY (symbol, time))''')conn.commit()conn.close()init_db()
2. 数据存储实现
def save_futures_quote(data):conn = sqlite3.connect('futures_data.db')c = conn.cursor()c.execute('''INSERT INTO futures_quotes VALUES (?, ?, ?, ?)''',(data['symbol'], data['last'], data['volume'], data['time']))conn.commit()conn.close()def save_futures_kline(symbol, kline_data):conn = sqlite3.connect('futures_data.db')c = conn.cursor()for row in kline_data:c.execute('''INSERT INTO futures_kline VALUES (?, ?, ?, ?, ?, ?, ?)''',(symbol, row['open'], row['high'], row['low'],row['close'], row['volume'], row['time']))conn.commit()conn.close()
六、生产环境注意事项
- 错误处理与重试机制
from tenacity import retry, stop_after_attempt, wait_exponential@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=2, max=10))
def safe_futures_api_call(url, params):try:response = requests.get(url, params=params, timeout=5)response.raise_for_status()return response.json()except Exception as e:print(f"API调用失败: {e}")raise
- 性能优化建议
- 使用Redis缓存高频访问的合约信息
- 批量获取多个合约数据减少API调用次数
- 对历史K线数据实现本地存储
七、完整示例：期货监控系统
import schedule
import timeclass FuturesMonitor:def __init__(self):self.tracked_symbols = ["CL1!", "GC1!"]def update_data(self):for symbol in self.tracked_symbols:# 获取实时行情quote = get_futures_quote(symbol)print(f"{symbol} 最新价: {quote['data']['last']}")# 获取K线数据kline = get_futures_kline(symbol, "15m")print(f"最近3根K线: {kline.tail(3)}")# 存储数据save_futures_quote(quote['data'])def run(self):# 每15秒更新一次数据schedule.every(15).seconds.do(self.update_data)while True:schedule.run_pending()time.sleep(1)# 启动监控
monitor = FuturesMonitor()
monitor.run()
八、总结与资源
核心功能总结
- 实时行情：获取期货合约的最新价格、成交量等数据
- 历史数据：获取不同时间周期的K线数据
- 实时推送：通过WebSocket接收实时行情更新
扩展资源
- StockTV期货API文档
- 示例代码仓库
- 全球主要期货交易所列表
注意事项：
- 期货合约存在到期日，注意合约切换
- 不同品种的交易时间不同
- 实时行情需处理网络中断等异常情况