dienakdz
128 lines
4.1 KiB
Python
128 lines
4.1 KiB
Python
"""
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data source factory
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Return the corresponding data source according to the market type
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"""
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from typing import Dict, List, Any, Optional
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from app.data_sources.base import BaseDataSource
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from app.utils.logger import get_logger
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logger = get_logger(__name__)
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class DataSourceFactory:
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"""data source factory"""
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_sources: Dict[str, BaseDataSource] = {}
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@classmethod
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def get_source(cls, market: str) -> BaseDataSource:
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"""
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Get the data source for the specified market
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Args:
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market: market type (Crypto, USStock, Forex, Futures)
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Returns:
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Data source instance
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"""
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if market not in cls._sources:
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cls._sources[market] = cls._create_source(market)
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return cls._sources[market]
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@classmethod
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def get_data_source(cls, name: str) -> BaseDataSource:
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"""
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Backward compatible alias used by older code paths.
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Some modules historically called `get_data_source("binance")` to fetch a crypto data source.
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In the localized Python backend we primarily use `get_source("Crypto")`.
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"""
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key = (name or "").strip().lower()
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if key in ("crypto", "binance", "okx", "bybit", "bitget", "kucoin", "gate", "mexc", "kraken", "coinbase"):
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return cls.get_source("Crypto")
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if key in ("futures",):
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return cls.get_source("Futures")
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# Default to Crypto for safety (most callers want a ticker for crypto pairs).
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return cls.get_source("Crypto")
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@classmethod
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def _create_source(cls, market: str) -> BaseDataSource:
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"""Create data source instance"""
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if market == 'Crypto':
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from app.data_sources.crypto import CryptoDataSource
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return CryptoDataSource()
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elif market == 'USStock':
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from app.data_sources.us_stock import USStockDataSource
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return USStockDataSource()
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elif market == 'Forex':
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from app.data_sources.forex import ForexDataSource
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return ForexDataSource()
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elif market == 'Futures':
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from app.data_sources.futures import FuturesDataSource
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return FuturesDataSource()
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else:
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raise ValueError(f"不支持的市场类型: {market}")
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@classmethod
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def get_kline(
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cls,
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market: str,
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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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A convenient way to obtain K-line data
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Args:
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market: market type
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symbol: trading pair/stock code
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timeframe: time period
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limit: number of data items
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before_time: Get data before this time
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Returns:
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K-line data list
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"""
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try:
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source = cls.get_source(market)
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klines = source.get_kline(symbol, timeframe, limit, before_time)
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# Make sure the data is sorted by time
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klines.sort(key=lambda x: x['time'])
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return klines
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except Exception as e:
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logger.error(f"Failed to fetch K-lines {market}:{symbol} - {str(e)}")
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return []
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@classmethod
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def get_ticker(cls, market: str, symbol: str) -> Dict[str, Any]:
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"""
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The convenient way to get realtime quotes
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Args:
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market: market type
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symbol: trading pair/stock code
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Returns:
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Real-time quotation data: {
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'last': latest price,
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'change': change amount,
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'changePercent': increase or decrease,
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...
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}
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"""
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try:
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source = cls.get_source(market)
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return source.get_ticker(symbol)
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except NotImplementedError:
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logger.warning(f"get_ticker not implemented for market: {market}")
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return {'last': 0, 'symbol': symbol}
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except Exception as e:
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logger.error(f"Failed to fetch ticker {market}:{symbol} - {str(e)}")
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return {'last': 0, 'symbol': symbol}
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