51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
import akshare as ak
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import pandas as pd
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class FundService:
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def search_funds(self, keyword, market_type='ETF'):
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"""
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搜索基金代码
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:param keyword: 搜索关键词
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:return: 匹配的基金列表
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"""
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try:
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# 获取ETF和LOF数据
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if market_type == 'ETF':
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df = ak.fund_etf_spot_em()
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else:
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df = ak.fund_lof_spot_em()
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# 转换列名
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df = df.rename(columns={
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"代码": "symbol",
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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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"成交量": "volume",
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"流通市值": "market_value",
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"总市值": "total_value",
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"基金折价率": "discount_rate",
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})
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# 模糊匹配搜索（同时匹配代码和名称）
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mask = (df['name'].str.contains(keyword, case=False, na=False) |
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df['symbol'].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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'volume': float(row['volume']) if pd.notna(row['volume']) 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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'total_value': float(row['total_value']) if pd.notna(row['total_value']) else 0.0,
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})
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return formatted_results
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except Exception as e:
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raise Exception(f"搜索基金代码失败: {str(e)}") |