58f9380ec4
- alphaear-deepear-lite: DeepEar Lite API integration - alphaear-logic-visualizer: Draw.io XML finance diagrams - alphaear-news: Real-time finance news (10+ sources) - alphaear-predictor: Kronos time-series forecasting - alphaear-reporter: Professional financial reports - alphaear-search: Web search + local RAG - alphaear-sentiment: FinBERT/LLM sentiment analysis - alphaear-signal-tracker: Signal evolution tracking - alphaear-stock: A-Share/HK/US stock data Updates: - All scripts updated to use universal .env path - Added JINA_API_KEY, LLM_*, DEEPSEEK_API_KEY to .env.example - Updated load_dotenv() to use ~/.config/opencode/.env
120 lines
4.1 KiB
Python
120 lines
4.1 KiB
Python
import sqlite3
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from pathlib import Path
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from typing import List, Dict, Optional
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import pandas as pd
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from loguru import logger
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class DatabaseManager:
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"""
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AlphaEar Stock Database Manager
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Reduced version for alphaear-stock skill
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"""
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def __init__(self, db_path: str = "data/signal_flux.db"):
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self.db_path = Path(db_path)
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self.db_path.parent.mkdir(parents=True, exist_ok=True)
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self.conn = sqlite3.connect(str(self.db_path), check_same_thread=False)
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self.conn.row_factory = sqlite3.Row
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self._init_db()
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logger.debug(f"💾 Stock Database initialized at {self.db_path}")
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def _init_db(self):
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"""Initialize stock-related tables"""
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cursor = self.conn.cursor()
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# Stock Prices Table
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS stock_prices (
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ticker TEXT,
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date TEXT,
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open REAL,
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close REAL,
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high REAL,
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low REAL,
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volume REAL,
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change_pct REAL,
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PRIMARY KEY (ticker, date)
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)
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""")
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# Stock List Table
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS stock_list (
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code TEXT PRIMARY KEY,
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name TEXT
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)
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""")
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cursor.execute("CREATE INDEX IF NOT EXISTS idx_stock_prices_ticker_date ON stock_prices(ticker, date)")
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self.conn.commit()
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# --- Stock Operations ---
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def save_stock_list(self, df: pd.DataFrame):
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cursor = self.conn.cursor()
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try:
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cursor.execute("DELETE FROM stock_list")
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data = df[['code', 'name']].to_dict('records')
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cursor.executemany(
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"INSERT INTO stock_list (code, name) VALUES (:code, :name)",
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data
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)
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self.conn.commit()
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except Exception as e:
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logger.error(f"Error saving stock list: {e}")
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def search_stock(self, query: str, limit: int = 5) -> List[Dict]:
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cursor = self.conn.cursor()
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wild = f"%{query}%"
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cursor.execute("""
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SELECT code, name FROM stock_list
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WHERE code LIKE ? OR name LIKE ?
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LIMIT ?
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""", (wild, wild, limit))
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return [dict(row) for row in cursor.fetchall()]
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def get_stock_by_code(self, code: str) -> Optional[Dict[str, str]]:
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if not code: return None
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clean = "".join([c for c in str(code).strip() if c.isdigit()])
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if not clean: return None
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cursor = self.conn.cursor()
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cursor.execute("SELECT code, name FROM stock_list WHERE code = ? LIMIT 1", (clean,))
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row = cursor.fetchone()
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return dict(row) if row else None
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def save_stock_prices(self, ticker: str, df: pd.DataFrame):
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if df.empty: return
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cursor = self.conn.cursor()
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try:
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for _, row in df.iterrows():
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cursor.execute("""
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INSERT OR REPLACE INTO stock_prices
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(ticker, date, open, close, high, low, volume, change_pct)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?)
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""", (
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ticker, row['date'], row['open'], row['close'],
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row['high'], row['low'], row['volume'], row['change_pct']
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))
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self.conn.commit()
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except Exception as e:
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logger.error(f"Error saving prices for {ticker}: {e}")
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def get_stock_prices(self, ticker: str, start_date: str, end_date: str) -> pd.DataFrame:
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cursor = self.conn.cursor()
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cursor.execute("""
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SELECT * FROM stock_prices
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WHERE ticker = ? AND date >= ? AND date <= ?
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ORDER BY date
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""", (ticker, start_date, end_date))
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rows = cursor.fetchall()
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if not rows: return pd.DataFrame()
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columns = ['ticker', 'date', 'open', 'close', 'high', 'low', 'volume', 'change_pct']
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return pd.DataFrame([dict(row) for row in rows], columns=columns)
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def close(self):
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if self.conn:
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self.conn.close()
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