"""
Tools for visualizing portfolio data.
"""
import matplotlib.pyplot as plt
from io import BytesIO
from mcp.server.fastmcp import Image
from portfolio_server.data.storage import load_portfolio
def visualize_portfolio(user_id: str) -> Image:
"""
Create a visualization of the current portfolio allocation
Args:
user_id: Unique identifier for the user
"""
portfolio = load_portfolio(user_id)
# Prepare data for visualization
labels = []
sizes = []
colors = []
# Add stocks (in blue shades)
for i, (symbol, allocation) in enumerate(portfolio["stocks"].items()):
labels.append(f"{symbol} ({allocation}%)")
sizes.append(allocation)
# Generate different blue shades
blue_val = min(0.8, 0.3 + (i * 0.1))
colors.append((0, 0, blue_val))
# Add bonds (in green shades)
for i, (bond_id, allocation) in enumerate(portfolio["bonds"].items()):
labels.append(f"{bond_id} ({allocation}%)")
sizes.append(allocation)
# Generate different green shades
green_val = min(0.8, 0.3 + (i * 0.1))
colors.append((0, green_val, 0))
# Create pie chart
plt.figure(figsize=(10, 7))
plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', startangle=140)
plt.axis('equal') # Equal aspect ratio ensures the pie chart is circular
plt.title(f"Portfolio Allocation for User {user_id}")
# Save to bytes object
buf = BytesIO()
plt.savefig(buf, format='png')
buf.seek(0)
plt.close()
# Return as MCP Image
return Image(data=buf.getvalue(), format="png")
