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"""
Stock Plot Generation Script
This script generates stock gain plots using yfinance and matplotlib.
It includes robust error handling and debugging information.
"""
import os
import sys
import traceback
import platform
from datetime import datetime
# Configure matplotlib before importing pyplot
import matplotlib
matplotlib.use('Agg') # Non-interactive backend
import matplotlib.pyplot as plt
import pandas as pd
import yfinance as yf
def setup_environment():
"""Print environment information and verify dependencies."""
print("\n" + "=" * 80)
print("ENVIRONMENT INFORMATION")
print("=" * 80)
print(f"Python: {sys.version}")
print(f"Platform: {platform.platform()}")
print(f"Current directory: {os.getcwd()}")
print(f"Python executable: {sys.executable}")
print(f"Current time: {datetime.now().isoformat()}")
# Verify required packages
print("\nChecking dependencies:")
for pkg in [('pandas', pd), ('matplotlib', matplotlib), ('yfinance', yf)]:
try:
print(f" ✓ {pkg[0]}: {pkg[1].__version__}")
except Exception as e:
print(f" ✗ {pkg[0]}: Not available ({e})")
def plot_stock_gain(symbols, timeframe="3mo"):
"""
Generate and save stock gain plots.
Args:
symbols: List of stock symbols or a single symbol string
timeframe: Time period to fetch data for (e.g., '1mo', '3mo', '1y')
Returns:
str: Path to the saved plot file, or None if failed
"""
# Convert single symbol to list
if isinstance(symbols, str):
symbols = [symbols]
print(f"\nProcessing symbols: {', '.join(symbols)} for timeframe: {timeframe}")
# Create output directory if it doesn't exist
output_dir = 'generated_plots'
os.makedirs(output_dir, exist_ok=True)
plot_paths = []
for symbol in symbols:
try:
print(f"\n{'='*40}")
print(f"Processing: {symbol}")
print(f"{'='*40}")
# Download stock data
print(f"Downloading {timeframe} data for {symbol}...")
ticker = yf.Ticker(symbol)
stock_data = ticker.history(period=timeframe)
if stock_data.empty:
print(f"⚠ No data found for {symbol}")
continue
print(f"Retrieved {len(stock_data)} data points from {stock_data.index[0].date()} to {stock_data.index[-1].date()}")
# Calculate percentage gain
stock_data['Gain'] = stock_data['Close'].pct_change().fillna(0).cumsum()
# Create plot
plt.figure(figsize=(12, 6))
plt.plot(stock_data.index, stock_data['Gain'],
linewidth=2,
label=f'{symbol} Gain')
# Format plot
plt.title(f'{symbol} Cumulative Gain - {timeframe.upper()}', fontsize=14)
plt.xlabel('Date', fontsize=12)
plt.ylabel('Cumulative Gain', fontsize=12)
plt.legend()
plt.grid(True, linestyle='--', alpha=0.7)
plt.tight_layout()
# Save plot
timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
plot_filename = f"{symbol}_{timeframe}_{timestamp}.png"
plot_path = os.path.join(output_dir, plot_filename)
plt.savefig(plot_path, dpi=120, bbox_inches='tight')
plt.close() # Close the figure to free memory
# Verify the file was created
if os.path.exists(plot_path):
file_size = os.path.getsize(plot_path)
print(f"✓ Plot saved: {plot_path} ({file_size} bytes)")
plot_paths.append(plot_path)
# Also save as plot.png in root for compatibility
if symbol == symbols[-1]: # Only for the last symbol
main_plot_path = 'plot.png'
plt.figure(plt.get_fignums()[-1]) # Get the last figure
plt.savefig(main_plot_path, dpi=120, bbox_inches='tight')
print(f"✓ Main plot saved as: {os.path.abspath(main_plot_path)}")
else:
print("❌ Failed to save plot")
except Exception as e:
print(f"❌ Error processing {symbol}: {str(e)}")
print("Traceback:")
traceback.print_exc()
return plot_paths[0] if plot_paths else None
def main():
"""Main execution function."""
try:
setup_environment()
# Default symbols and timeframe
symbols = ["META"]
timeframe = "ytd"
# Generate plots
plot_path = plot_stock_gain(symbols, timeframe)
if plot_path:
print(f"\n✅ Successfully generated plot: {os.path.abspath(plot_path)}")
return 0
else:
print("\n❌ Failed to generate any plots")
return 1
except Exception as e:
print(f"\n❌ Fatal error: {str(e)}")
print("Traceback:")
traceback.print_exc()
return 1
if __name__ == "__main__":
sys.exit(main())
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