127 lines
4.4 KiB
Python
127 lines
4.4 KiB
Python
import akshare as ak
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import pandas as pd
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import datetime
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import time
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import logging
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# 配置日志
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logging.basicConfig(
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filename='stock_signals.log',
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s] %(message)s',
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)
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# 板块关键词
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TARGET_SECTORS = ['互联网服务', '芯片', '消费', '房地产']
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def fetch_sector_stocks(sector_name):
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"""
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获取某个行业板块的股票列表
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"""
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try:
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df_plates = ak.stock_board_industry_name_em()
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if not df_plates['板块名称'].isin([sector_name]).any():
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logging.warning(f"{sector_name} not exists!")
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return pd.DataFrame()
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df = ak.stock_board_industry_cons_em(symbol=sector_name)
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return df[['代码', '名称']]
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except Exception as e:
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logging.error(f"获取板块 {sector_name} 股票失败: {e}")
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return pd.DataFrame()
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def compute_signals(df):
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"""
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根据行情数据计算交易信号
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"""
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signals = []
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for _, row in df.iterrows():
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try:
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code = row['代码']
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name = row['名称']
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pct_today = row['当日涨跌幅']
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pct_year = row['年内涨跌幅']
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pe = row['市盈率']
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pb = row['市净率']
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signal = ''
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if pct_today < -5:
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signal += '今日大跌; '
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if pct_year < -20:
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signal += '年内大跌; '
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if pe < 50:
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signal += '低市盈率; '
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if signal:
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signals.append({
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'代码': code,
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'名称': name,
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'当日涨跌幅': pct_today,
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'年内涨跌幅': pct_year,
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'市盈率': pe,
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'市净率': pb,
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'信号': signal.strip()
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})
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except Exception as e:
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logging.warning(f"处理股票 {row} 时出错: {e}")
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return pd.DataFrame(signals)
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def fetch_and_analyze():
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"""
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获取行情并计算信号
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"""
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logging.info("开始获取并分析行情数据")
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all_stocks = pd.DataFrame()
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for sector in TARGET_SECTORS:
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df = fetch_sector_stocks(sector)
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if df.empty:
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continue
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logging.info(f"获取到板块 [{sector}] {len(df)} 只股票")
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for code in df['代码']:
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try:
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# 获取日K线
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kline = ak.stock_zh_a_hist(symbol=code, period='daily', adjust='qfq')
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kline['日期'] = pd.to_datetime(kline['日期'])
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kline.set_index('日期', inplace=True)
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today = kline.iloc[-1]
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close_today = today['收盘']
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close_5d = kline.iloc[-5]['收盘'] if len(kline) >= 5 else today['收盘']
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close_month = kline.iloc[-21]['收盘'] if len(kline) >= 21 else today['收盘']
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close_year = kline.iloc[0]['收盘']
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pct_today = (close_today / today['开盘'] - 1) * 100
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pct_5d = (close_today / close_5d -1) * 100
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pct_month = (close_today / close_month -1) * 100
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pct_year = (close_today / close_year -1) *100
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# 获取市盈率、市净率
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fundamentals = ak.stock_a_lg_indicator(symbol=code)
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pe = fundamentals.iloc[-1]['市盈率(TTM)']
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pb = fundamentals.iloc[-1]['市净率']
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all_stocks = pd.concat([all_stocks, pd.DataFrame([{
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'代码': code,
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'名称': df.loc[df['代码']==code, '名称'].values[0],
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'当日涨跌幅': pct_today,
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'5日涨跌幅': pct_5d,
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'本月涨跌幅': pct_month,
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'年内涨跌幅': pct_year,
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'市盈率': pe,
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'市净率': pb
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}])])
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except Exception as e:
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logging.error(f"获取股票 {code} 数据失败: {e}")
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continue
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signals = compute_signals(all_stocks)
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if not signals.empty:
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signals.to_csv(f'stock_signals_{datetime.date.today()}.csv', index=False, encoding='utf-8-sig')
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logging.info(f"生成信号 {len(signals)} 条，已写入 CSV。")
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else:
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logging.info("未发现符合条件的交易信号")
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if __name__ == "__main__":
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fetch_and_analyze() |