TIANHE
314 lines
12 KiB
Python
314 lines
12 KiB
Python
"""
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外汇数据源
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使用 Tiingo 获取外汇数据
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"""
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from typing import Dict, List, Any, Optional
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from datetime import datetime, timedelta
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import time
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import requests
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from app.data_sources.base import BaseDataSource, TIMEFRAME_SECONDS
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from app.utils.logger import get_logger
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from app.config import TiingoConfig, APIKeys
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logger = get_logger(__name__)
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class ForexDataSource(BaseDataSource):
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"""外汇数据源 (Tiingo)"""
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name = "Forex/Tiingo"
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# Tiingo resampleFreq 映射
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# Tiingo 免费账户支持: 5min, 15min, 30min, 1hour, 4hour, 1day
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# 注意: 1min 需要付费订阅, 1week/1month 不被 Tiingo FX API 支持
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TIMEFRAME_MAP = {
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'1m': '1min', # 需要付费订阅
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'5m': '5min',
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'15m': '15min',
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'30m': '30min',
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'1H': '1hour',
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'4H': '4hour',
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'1D': '1day',
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'1W': None, # Tiingo 不支持，需要聚合
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'1M': None # Tiingo 不支持，需要聚合
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}
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# 外汇对映射 (Tiingo 使用标准 ticker，如 eurusd, audusd)
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# 大写也可以，Tiingo 通常不区分大小写，但建议统一
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SYMBOL_MAP = {
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# 贵金属 (Tiingo 不一定支持所有 OANDA 格式的贵金属，通常是 XAUUSD)
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'XAUUSD': 'xauusd',
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'XAGUSD': 'xagusd',
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# 主要货币对
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'EURUSD': 'eurusd',
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'GBPUSD': 'gbpusd',
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'USDJPY': 'usdjpy',
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'AUDUSD': 'audusd',
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'USDCAD': 'usdcad',
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'USDCHF': 'usdchf',
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'NZDUSD': 'nzdusd',
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}
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def __init__(self):
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self.base_url = TiingoConfig.BASE_URL
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if not APIKeys.TIINGO_API_KEY:
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logger.warning("Tiingo API key is not configured; FX data will be unavailable")
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def _get_timeframe_seconds(self, timeframe: str) -> int:
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"""获取时间周期对应的秒数"""
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return TIMEFRAME_SECONDS.get(timeframe, 86400)
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def get_kline(
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self,
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symbol: str,
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timeframe: str,
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limit: int,
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before_time: Optional[int] = None
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) -> List[Dict[str, Any]]:
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"""
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获取外汇K线数据
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Args:
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symbol: 外汇对代码（如 XAUUSD, EURUSD）
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timeframe: 时间周期
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limit: 数据条数
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before_time: 结束时间戳
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"""
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# 动态获取 API Key
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api_key = APIKeys.TIINGO_API_KEY
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if not api_key:
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logger.error("Tiingo API key is not configured")
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return []
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try:
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# 1. 解析 Symbol
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tiingo_symbol = self.SYMBOL_MAP.get(symbol)
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if not tiingo_symbol:
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# 尝试智能转换: EURUSD -> eurusd
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tiingo_symbol = symbol.lower()
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# 2. 解析 Resolution (resampleFreq)
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resample_freq = self.TIMEFRAME_MAP.get(timeframe)
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# 特殊处理：1W/1M 需要用日线聚合
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aggregate_to_weekly = (timeframe == '1W')
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aggregate_to_monthly = (timeframe == '1M')
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original_limit = limit # 保存原始请求数量
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if aggregate_to_weekly or aggregate_to_monthly:
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# 用日线数据聚合
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resample_freq = '1day'
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# 限制周线/月线的最大请求数量（Tiingo 免费 API 有数据量限制）
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# 周线最多请求 100 周 = 700 天 ≈ 2年
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# 月线最多请求 36 月 = 1080 天 ≈ 3年
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max_limit = 100 if aggregate_to_weekly else 36
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original_limit = min(original_limit, max_limit)
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# 需要更多日线数据来聚合（周线需要7天，月线需要30天）
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limit = original_limit * (7 if aggregate_to_weekly else 30)
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if not resample_freq:
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logger.warning(f"Tiingo does not support timeframe: {timeframe}")
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return []
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# 1分钟数据需要付费订阅提示
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if timeframe == '1m':
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logger.info(f"Note: Tiingo 1-minute forex data requires a paid subscription")
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# 3. 计算时间范围
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if before_time:
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end_dt = datetime.fromtimestamp(before_time)
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else:
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end_dt = datetime.now()
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# 根据周期和数量计算开始时间
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# 注意：聚合模式下使用日线秒数计算
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if aggregate_to_weekly or aggregate_to_monthly:
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tf_seconds = 86400 # 日线秒数
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else:
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tf_seconds = self._get_timeframe_seconds(timeframe)
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# 多取一些缓冲时间（1.5倍，外汇周末不交易）
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start_dt = end_dt - timedelta(seconds=limit * tf_seconds * 1.5)
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# Tiingo 免费 API 最多支持约 5 年数据，限制最大时间范围
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max_days = 365 * 3 # 最多 3 年
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if (end_dt - start_dt).days > max_days:
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start_dt = end_dt - timedelta(days=max_days)
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logger.info(f"Tiingo: Limited date range to {max_days} days")
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# 格式化日期为 YYYY-MM-DD (Tiingo 支持该格式)
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start_date_str = start_dt.strftime('%Y-%m-%d')
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end_date_str = end_dt.strftime('%Y-%m-%d')
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# 4. API 请求
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# URL: https://api.tiingo.com/tiingo/fx/{ticker}/prices
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url = f"{self.base_url}/fx/{tiingo_symbol}/prices"
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params = {
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'startDate': start_date_str,
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'endDate': end_date_str,
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'resampleFreq': resample_freq,
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'token': api_key,
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'format': 'json'
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}
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# logger.info(f"Tiingo Request: {url} params={params}")
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response = requests.get(url, params=params, timeout=TiingoConfig.TIMEOUT)
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if response.status_code == 403: # 具体的权限错误
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logger.error("Tiingo API permission error (403): check whether your API key is valid and has access to this dataset.")
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return []
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response.raise_for_status()
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data = response.json()
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# 5. 处理响应
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# Tiingo returns a list of dicts:
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# [
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# {
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# "date": "2023-01-01T00:00:00.000Z",
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# "ticker": "eurusd",
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# "open": 1.07,
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# "high": 1.08,
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# "low": 1.06,
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# "close": 1.07
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# "mid": ... (optional, depends on settings, usually OHLC are bid or mid)
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# }, ...
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# ]
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# Note: Tiingo FX prices objects keys: date, open, high, low, close.
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if not isinstance(data, list):
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logger.warning(f"Tiingo response is not a list: {data}")
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return []
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klines = []
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for item in data:
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# 解析时间: "2023-01-01T00:00:00.000Z"
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dt_str = item.get('date')
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# 简化处理，Tiingo 返回的是 UTC 时间 ISO 格式
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# datetime.fromisoformat 在 Py3.7+ 支持，但要注意 Z 的处理
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# 这里简单处理一下 Z
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if dt_str.endswith('Z'):
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dt_str = dt_str[:-1]
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dt = datetime.fromisoformat(dt_str)
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ts = int(dt.timestamp())
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klines.append({
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'time': ts,
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'open': float(item.get('open')),
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'high': float(item.get('high')),
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'low': float(item.get('low')),
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'close': float(item.get('close')),
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'volume': 0.0 # Tiingo FX 通常没有 volume
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})
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# 按时间排序
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klines.sort(key=lambda x: x['time'])
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# 如果需要聚合到周线或月线
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if aggregate_to_weekly:
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klines = self._aggregate_to_weekly(klines)
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logger.debug(f"Aggregated {len(klines)} weekly candles from daily data")
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elif aggregate_to_monthly:
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klines = self._aggregate_to_monthly(klines)
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logger.debug(f"Aggregated {len(klines)} monthly candles from daily data")
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# 过滤到原始请求数量
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if len(klines) > original_limit:
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klines = klines[-original_limit:]
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# logger.info(f"获取到 {len(klines)} 条 Tiingo 外汇数据")
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return klines
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except requests.exceptions.RequestException as e:
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logger.error(f"Tiingo API request failed: {e}")
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return []
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except Exception as e:
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logger.error(f"Failed to process Tiingo data: {e}")
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return []
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def _aggregate_to_weekly(self, daily_klines: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""将日线数据聚合为周线"""
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if not daily_klines:
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return []
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weekly_klines = []
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current_week = None
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week_data = None
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for kline in daily_klines:
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dt = datetime.fromtimestamp(kline['time'])
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# 获取该日期所在周的周一
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week_start = dt - timedelta(days=dt.weekday())
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week_key = week_start.strftime('%Y-%W')
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if week_key != current_week:
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# 保存上一周的数据
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if week_data:
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weekly_klines.append(week_data)
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# 开始新的一周
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current_week = week_key
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week_data = {
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'time': int(week_start.timestamp()),
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'open': kline['open'],
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'high': kline['high'],
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'low': kline['low'],
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'close': kline['close'],
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'volume': kline['volume']
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}
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else:
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# 更新本周数据
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week_data['high'] = max(week_data['high'], kline['high'])
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week_data['low'] = min(week_data['low'], kline['low'])
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week_data['close'] = kline['close']
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week_data['volume'] += kline['volume']
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# 添加最后一周
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if week_data:
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weekly_klines.append(week_data)
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return weekly_klines
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def _aggregate_to_monthly(self, daily_klines: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""将日线数据聚合为月线"""
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if not daily_klines:
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return []
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monthly_klines = []
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current_month = None
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month_data = None
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for kline in daily_klines:
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dt = datetime.fromtimestamp(kline['time'])
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month_key = dt.strftime('%Y-%m')
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if month_key != current_month:
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# 保存上个月的数据
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if month_data:
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monthly_klines.append(month_data)
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# 开始新的一月
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current_month = month_key
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month_start = dt.replace(day=1, hour=0, minute=0, second=0)
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month_data = {
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'time': int(month_start.timestamp()),
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'open': kline['open'],
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'high': kline['high'],
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'low': kline['low'],
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'close': kline['close'],
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'volume': kline['volume']
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}
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else:
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# 更新本月数据
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month_data['high'] = max(month_data['high'], kline['high'])
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month_data['low'] = min(month_data['low'], kline['low'])
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month_data['close'] = kline['close']
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month_data['volume'] += kline['volume']
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# 添加最后一月
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if month_data:
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monthly_klines.append(month_data)
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return monthly_klines
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