149 lines
4.9 KiB
Python
149 lines
4.9 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import os
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import json
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import requests
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import urllib.parse
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from typing import Dict, Any, Optional
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from datetime import datetime
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import pandas as pd
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class AllTickAPI:
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"""AllTick API客户端，用于获取黄金等商品的K线数据"""
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def __init__(self, api_key: str):
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"""
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初始化AllTick API客户端
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Args:
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api_key: AllTick API密钥
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"""
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self.api_key = api_key
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self.base_url = "https://quote.alltick.io/quote-b-api"
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self.stock_url = "https://quote.alltick.io/quote-stock-b-api"
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self.session = requests.Session()
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def get_stock_klines(self, symbol: str, interval: str,
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limit: int = 500) -> pd.DataFrame:
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"""
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获取股票历史K线数据
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"""
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return self._get_historical_klines(symbol, interval, limit, self.stock_url)
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def get_common_klines(self, symbol: str, interval: str,
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limit: int = 500) -> pd.DataFrame:
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"""
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获取历史K线数据
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"""
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return self._get_historical_klines(symbol, interval, limit, self.base_url)
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def _get_historical_klines(self, symbol: str, interval: str,
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limit: int = 500, base_url: str = None) -> pd.DataFrame:
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"""
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获取历史K线数据
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Args:
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symbol: 交易对符号，例如 "XAUUSD"
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interval: K线时间间隔，可选: 1m, 5m, 15m, 30m, 1h, 2h, 4h, 1d, 1w, 1M
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start_str: 开始时间，格式为 "YYYY-MM-DD"
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limit: 获取的K线数量，最大为1000
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Returns:
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K线数据的DataFrame
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"""
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# 转换时间间隔格式
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kline_type = self._convert_interval(interval)
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# 计算结束时间戳
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end_timestamp = 0 # 0表示从当前时间开始查询
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# 限制查询数量
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query_kline_num = min(limit, 1000) # AllTick API每次最多查询1000根K线
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# 构建查询参数
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query_data = {
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"trace": datetime.now().strftime("%Y%m%d%H%M%S"),
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"data": {
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"code": symbol,
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"kline_type": kline_type,
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"kline_timestamp_end": end_timestamp,
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"query_kline_num": query_kline_num,
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"adjust_type": 0 # 0: 除权
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}
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}
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# 对查询参数进行编码
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encoded_query = urllib.parse.quote(json.dumps(query_data))
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# 构建完整的URL
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url = f"{base_url}/kline?token={self.api_key}&query={encoded_query}"
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try:
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# 发送请求
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response = self.session.get(url)
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response.raise_for_status() # 如果响应状态码不是200，则抛出异常
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# 解析响应
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result = response.json()
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# 检查返回状态
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if result.get("ret") != 200:
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print(f"请求出错: {result.get('msg')}")
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return pd.DataFrame()
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# 获取K线数据
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kline_data = result.get("data", {}).get("kline_list", [])
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if not kline_data:
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print(f"未获取到{symbol}的K线数据")
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return pd.DataFrame()
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# 转换为DataFrame
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df = pd.DataFrame(kline_data)
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# 转换列类型
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df["timestamp"] = df["timestamp"].astype(int)
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df["open"] = df["open_price"].astype(float)
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df["high"] = df["high_price"].astype(float)
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df["low"] = df["low_price"].astype(float)
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df["close"] = df["close_price"].astype(float)
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df["volume"] = df["volume"].astype(float)
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# 设置索引
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# df.set_index("timestamp", inplace=True)
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# 选择需要的列
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df = df[["open", "high", "low", "close", "volume","timestamp"]]
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return df
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except Exception as e:
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print(f"获取K线数据时出错: {e}")
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return pd.DataFrame()
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def _convert_interval(self, interval: str) -> int:
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"""
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将Binance格式的时间间隔转换为AllTick格式
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Args:
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interval: Binance格式的时间间隔，例如 "1m", "1h", "1d"
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Returns:
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AllTick格式的K线类型
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"""
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interval_map = {
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"1m": 1, # 1分钟K
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"5m": 2, # 5分钟K
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"15m": 3, # 15分钟K
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"30m": 4, # 30分钟K
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"1h": 5, # 小时K
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"2h": 6, # 2小时K
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"4h": 7, # 4小时K
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"1d": 8, # 日K
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"1w": 9, # 周K
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"1M": 10 # 月K
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}
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return interval_map.get(interval, 8) # 默认返回日K |