refactor: Optimize sunny scanner with direct database query and simplified processing
This commit is contained in:
parent
e7a32dd9ab
commit
7faf56a712
@ -277,81 +277,91 @@ def run_sunny_scanner(min_price: float, max_price: float, min_volume: int, portf
|
||||
interval = get_interval_choice()
|
||||
end_date = datetime.now()
|
||||
start_date = end_date - timedelta(days=1)
|
||||
lookback_start = end_date - timedelta(days=60)
|
||||
|
||||
tickers = get_valid_tickers(min_price, max_price, min_volume, interval)
|
||||
if not tickers:
|
||||
print("No stocks found matching criteria.")
|
||||
return
|
||||
# First get the data from database
|
||||
client = create_client()
|
||||
|
||||
print(f"\nScanning {len(tickers)} qualified stocks...")
|
||||
# Query to get stocks meeting criteria
|
||||
query = f"""
|
||||
SELECT DISTINCT ticker, close
|
||||
FROM stock_db.stock_prices_daily
|
||||
WHERE date = (SELECT max(date) FROM stock_db.stock_prices_daily)
|
||||
AND close BETWEEN {min_price} AND {max_price}
|
||||
AND volume >= {min_volume}
|
||||
ORDER BY ticker
|
||||
"""
|
||||
|
||||
sunny = SunnyBands()
|
||||
calculator = None
|
||||
if portfolio_size and portfolio_size > 0:
|
||||
calculator = PositionCalculator(account_size=portfolio_size)
|
||||
|
||||
bullish_signals = []
|
||||
bearish_signals = []
|
||||
|
||||
for ticker in tickers:
|
||||
try:
|
||||
df = get_stock_data(ticker, start_date, end_date, interval)
|
||||
if df.empty or len(df) < 50:
|
||||
continue
|
||||
|
||||
results = sunny.calculate(df)
|
||||
last_day = df.iloc[-1]
|
||||
try:
|
||||
result = client.query(query)
|
||||
qualified_stocks = [(row[0], row[1]) for row in result.result_rows]
|
||||
|
||||
if not qualified_stocks:
|
||||
print("No stocks found matching criteria.")
|
||||
return
|
||||
|
||||
if results['bullish_signal'].iloc[-1]:
|
||||
entry_price = last_day['close']
|
||||
dma = results['dma'].iloc[-1]
|
||||
upper_band = results['upper_band'].iloc[-1]
|
||||
band_range = upper_band - dma
|
||||
target_price = upper_band + band_range
|
||||
print(f"\nFound {len(qualified_stocks)} stocks matching criteria")
|
||||
|
||||
# Initialize indicators
|
||||
sunny = SunnyBands()
|
||||
calculator = None
|
||||
if portfolio_size and portfolio_size > 0:
|
||||
calculator = PositionCalculator(account_size=portfolio_size)
|
||||
|
||||
bullish_signals = []
|
||||
bearish_signals = []
|
||||
|
||||
# Process each qualified stock
|
||||
for ticker, current_price in qualified_stocks:
|
||||
try:
|
||||
df = get_stock_data(ticker, start_date, end_date, interval)
|
||||
if df.empty or len(df) < 50:
|
||||
continue
|
||||
|
||||
results = sunny.calculate(df)
|
||||
|
||||
signal_data = {
|
||||
'ticker': ticker,
|
||||
'entry': entry_price,
|
||||
'target': target_price
|
||||
}
|
||||
if results['bullish_signal'].iloc[-1]:
|
||||
target_price = results['upper_band'].iloc[-1]
|
||||
|
||||
if calculator:
|
||||
position = calculator.calculate_position_size(current_price, target_price)
|
||||
if position['shares'] > 0:
|
||||
signal_data = {
|
||||
'ticker': ticker,
|
||||
'entry': current_price,
|
||||
'target': target_price,
|
||||
'shares': position['shares'],
|
||||
'position_size': position['position_value'],
|
||||
'stop_loss': position['stop_loss'],
|
||||
'risk': position['potential_loss'],
|
||||
'reward': position['potential_profit'],
|
||||
'r_r': position['risk_reward_ratio']
|
||||
}
|
||||
bullish_signals.append(signal_data)
|
||||
print(f"\n🟢 {ticker} Entry: ${current_price:.2f} Target: ${target_price:.2f}")
|
||||
print(f" Shares: {signal_data['shares']} | Risk: ${abs(signal_data['risk']):.2f} | "
|
||||
f"Reward: ${signal_data['reward']:.2f} | R/R: {signal_data['r_r']:.2f}")
|
||||
|
||||
if calculator:
|
||||
position = calculator.calculate_position_size(entry_price, target_price)
|
||||
signal_data.update({
|
||||
'shares': position['shares'],
|
||||
'position_size': position['position_value'],
|
||||
'stop_loss': position['stop_loss'],
|
||||
'risk': position['potential_loss'],
|
||||
'reward': position['potential_profit'],
|
||||
'r_r': position['risk_reward_ratio']
|
||||
elif results['bearish_signal'].iloc[-1]:
|
||||
bearish_signals.append({
|
||||
'ticker': ticker,
|
||||
'price': current_price
|
||||
})
|
||||
|
||||
bullish_signals.append(signal_data)
|
||||
print(f"\n🟢 {ticker} Entry: ${entry_price:.2f} Target: ${target_price:.2f}")
|
||||
if calculator:
|
||||
print(f" Shares: {signal_data['shares']} | Risk: ${abs(signal_data['risk']):.2f} | "
|
||||
f"Reward: ${signal_data['reward']:.2f} | R/R: {signal_data['r_r']:.2f}")
|
||||
|
||||
elif results['bearish_signal'].iloc[-1]:
|
||||
bearish_signals.append({
|
||||
'ticker': ticker,
|
||||
'price': last_day['close']
|
||||
})
|
||||
print(f"\n🔴 {ticker} at ${last_day['close']:.2f}")
|
||||
|
||||
except Exception as e:
|
||||
continue
|
||||
|
||||
# Save results more concisely
|
||||
output_date = datetime.now().strftime("%Y%m%d")
|
||||
if bullish_signals:
|
||||
df_bullish = pd.DataFrame(bullish_signals)
|
||||
df_bullish.to_csv(f'reports/sunny_bullish_{output_date}.csv', index=False)
|
||||
|
||||
if bearish_signals:
|
||||
df_bearish = pd.DataFrame(bearish_signals)
|
||||
df_bearish.to_csv(f'reports/sunny_bearish_{output_date}.csv', index=False)
|
||||
|
||||
print(f"\nFound {len(bullish_signals)} bullish and {len(bearish_signals)} bearish signals")
|
||||
print("Results saved to reports directory")
|
||||
print(f"\n🔴 {ticker} at ${current_price:.2f}")
|
||||
|
||||
except Exception as e:
|
||||
continue
|
||||
|
||||
# Save results
|
||||
output_date = datetime.now().strftime("%Y%m%d")
|
||||
if bullish_signals:
|
||||
df_bullish = pd.DataFrame(bullish_signals)
|
||||
df_bullish.to_csv(f'reports/sunny_bullish_{output_date}.csv', index=False)
|
||||
|
||||
if bearish_signals:
|
||||
df_bearish = pd.DataFrame(bearish_signals)
|
||||
df_bearish.to_csv(f'reports/sunny_bearish_{output_date}.csv', index=False)
|
||||
|
||||
print(f"\nFound {len(bullish_signals)} bullish and {len(bearish_signals)} bearish signals")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error during scan: {str(e)}")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user