151 lines
5.6 KiB
Python
151 lines
5.6 KiB
Python
import asyncio
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import pandas as pd
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from typing import List, Dict, Any, Optional
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from logger import get_logger
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# 获取日志器
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logger = get_logger()
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class USStockServiceAsync:
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"""
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异步美股服务
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提供美股数据的异步搜索和获取功能
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"""
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def __init__(self):
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"""初始化异步美股服务"""
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logger.debug("初始化USStockServiceAsync")
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# 可选：添加缓存以减少频繁请求
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self._cache = None
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self._cache_timestamp = None
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async def search_us_stocks(self, keyword: str) -> List[Dict[str, Any]]:
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"""
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异步搜索美股代码
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Args:
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keyword: 搜索关键词
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Returns:
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匹配的股票列表
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"""
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try:
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logger.info(f"异步搜索美股: {keyword}")
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# 使用线程池执行同步的akshare调用
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df = await asyncio.to_thread(self._get_us_stocks_data)
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# 模糊匹配搜索
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mask = df['name'].str.contains(keyword, case=False, na=False)
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results = df[mask]
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# 格式化返回结果并处理 NaN 值
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formatted_results = []
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for _, row in results.iterrows():
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formatted_results.append({
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'name': row['name'] if pd.notna(row['name']) else '',
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'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '',
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'price': float(row['price']) if pd.notna(row['price']) else 0.0,
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'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0
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})
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logger.info(f"美股搜索完成，找到 {len(formatted_results)} 个匹配项")
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return formatted_results
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except Exception as e:
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error_msg = f"搜索美股代码失败: {str(e)}"
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logger.error(error_msg)
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logger.exception(e)
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raise Exception(error_msg)
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def _get_us_stocks_data(self) -> pd.DataFrame:
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"""
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获取美股数据（同步方法，将被异步方法调用）
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Returns:
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包含美股数据的DataFrame
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"""
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import akshare as ak
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try:
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# 获取美股数据
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df = ak.stock_us_spot_em()
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# 转换列名
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df = df.rename(columns={
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"序号": "index",
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"名称": "name",
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"最新价": "price",
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"涨跌额": "price_change",
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"涨跌幅": "price_change_percent",
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"开盘价": "open",
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"最高价": "high",
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"最低价": "low",
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"昨收价": "pre_close",
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"总市值": "market_value",
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"市盈率": "pe_ratio",
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"成交量": "volume",
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"成交额": "turnover",
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"振幅": "amplitude",
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"换手率": "turnover_rate",
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"代码": "symbol"
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})
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return df
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except Exception as e:
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logger.error(f"获取美股数据失败: {str(e)}")
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logger.exception(e)
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raise Exception(f"获取美股数据失败: {str(e)}")
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async def get_us_stock_detail(self, symbol: str) -> Dict[str, Any]:
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"""
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异步获取单个美股详细信息
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Args:
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symbol: 股票代码
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Returns:
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股票详细信息
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"""
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try:
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logger.info(f"获取美股详情: {symbol}")
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# 使用线程池执行同步的akshare调用
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df = await asyncio.to_thread(self._get_us_stocks_data)
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# 精确匹配股票代码
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result = df[df['symbol'] == symbol]
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if len(result) == 0:
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raise Exception(f"未找到股票代码: {symbol}")
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# 获取第一行数据
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row = result.iloc[0]
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# 格式化为字典
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stock_detail = {
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'name': row['name'] if pd.notna(row['name']) else '',
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'symbol': str(row['symbol']) if pd.notna(row['symbol']) else '',
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'price': float(row['price']) if pd.notna(row['price']) else 0.0,
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'price_change': float(row['price_change']) if pd.notna(row['price_change']) else 0.0,
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'price_change_percent': float(row['price_change_percent'].strip('%'))/100 if pd.notna(row['price_change_percent']) else 0.0,
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'open': float(row['open']) if pd.notna(row['open']) else 0.0,
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'high': float(row['high']) if pd.notna(row['high']) else 0.0,
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'low': float(row['low']) if pd.notna(row['low']) else 0.0,
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'pre_close': float(row['pre_close']) if pd.notna(row['pre_close']) else 0.0,
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'market_value': float(row['market_value']) if pd.notna(row['market_value']) else 0.0,
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'pe_ratio': float(row['pe_ratio']) if pd.notna(row['pe_ratio']) else 0.0,
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'volume': float(row['volume']) if pd.notna(row['volume']) else 0.0,
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'turnover': float(row['turnover']) if pd.notna(row['turnover']) else 0.0
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}
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logger.info(f"获取美股详情成功: {symbol}")
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return stock_detail
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except Exception as e:
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error_msg = f"获取美股详情失败: {str(e)}"
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logger.error(error_msg)
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logger.exception(e)
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raise Exception(error_msg) |