Add matplotlib-based chart generation with Yahoo Finance data

- Add chart_generator.py with price and candlestick chart support
- Implement Yahoo Finance candle data fetching for free historical data
- Update bot to generate and attach charts to stock embeds
- Add matplotlib dependency to requirements.txt
- Configure dual API approach: Finnhub for quotes, Yahoo for charts

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

bot.py

@@ -10,6 +10,7 @@ from config import Config
 from stock_api import YahooFinanceAPI, FinnhubAPI
 from market_hours import MarketHours
 from crypto_api import CoinGeckoAPI
+from chart_generator import ChartGenerator
 
 
 # Configure logging
@@ -36,6 +37,10 @@ class StockBot(commands.Bot):
             self.stock_api = YahooFinanceAPI()
             logger.info("Using Yahoo Finance API for stock data")
 
+        # Always initialize Yahoo Finance for chart data (free historical data)
+        self.yahoo_api = YahooFinanceAPI()
+        logger.info("Using Yahoo Finance API for chart data")
+
         self.scheduler = AsyncIOScheduler(timezone=pytz.timezone('America/New_York'))
         self.target_channel_ids = [int(id) for id in Config.CHANNEL_IDS]
         self.primary_ticker = Config.PRIMARY_TICKER
@@ -254,7 +259,25 @@ class StockBot(commands.Bot):
             return
 
         embed = self.create_stock_embed(stock_data)
+
+        # Generate chart using Yahoo Finance historical data
+        chart_file = None
+        candle_data = self.yahoo_api.get_candles(ticker, days=30)
+        if candle_data:
+            chart_buffer = ChartGenerator.create_price_chart(
+                ticker,
+                candle_data,
+                stock_data.get('company_name')
+            )
+            if chart_buffer:
+                chart_file = discord.File(chart_buffer, filename="chart.png")
+
+        # Send with chart attachment if available
+        if chart_file:
+            await channel.send(embed=embed, file=chart_file)
+        else:
             await channel.send(embed=embed)
+
         logger.info(f"Sent stock update for {ticker} to channel {channel_id}")
 
     def create_stock_embed(self, stock_data: dict) -> discord.Embed:
@@ -310,9 +333,8 @@ class StockBot(commands.Bot):
         embed.add_field(name="Change", value=change_str, inline=True)
         embed.add_field(name="Previous Close", value=f"${stock_data['previous_close']}", inline=True)
 
-        # Add FinViz daily chart
+        # Reference attached chart image
-        chart_url = f"https://finviz.com/chart.ashx?t={ticker}&ty=c&ta=1&p=d&s=l"
+        embed.set_image(url="attachment://chart.png")
-        embed.set_image(url=chart_url)
 
         market_status = "🟢 Market Open" if stock_data['market_open'] else "🔴 Market Closed"
         embed.set_footer(text=f"{market_status}")
@@ -526,6 +548,23 @@ async def get_stock_price(ctx, ticker: str = None):
         return
 
     embed = bot.create_stock_embed(stock_data)
+
+    # Generate chart using Yahoo Finance historical data
+    chart_file = None
+    candle_data = bot.yahoo_api.get_candles(ticker, days=30)
+    if candle_data:
+        chart_buffer = ChartGenerator.create_price_chart(
+            ticker,
+            candle_data,
+            stock_data.get('company_name')
+        )
+        if chart_buffer:
+            chart_file = discord.File(chart_buffer, filename="chart.png")
+
+    # Send with chart attachment if available
+    if chart_file:
+        await ctx.send(embed=embed, file=chart_file)
+    else:
         await ctx.send(embed=embed)
 
 

chart_generator.py

@@ -0,0 +1,162 @@
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+from datetime import datetime
+from typing import Dict, List, Optional
+import logging
+import io
+
+logger = logging.getLogger(__name__)
+
+
+class ChartGenerator:
+    """Generates stock price charts using matplotlib."""
+
+    @staticmethod
+    def create_price_chart(
+        ticker: str,
+        candle_data: Dict[str, List],
+        company_name: Optional[str] = None
+    ) -> Optional[io.BytesIO]:
+        """
+        Create a price chart from candle data.
+
+        Args:
+            ticker: Stock ticker symbol
+            candle_data: Dictionary with timestamps, open, high, low, close, volume
+            company_name: Optional company name for title
+
+        Returns:
+            BytesIO buffer containing the chart image, or None if error
+        """
+        try:
+            # Convert timestamps to datetime objects
+            dates = [datetime.fromtimestamp(ts) for ts in candle_data['timestamps']]
+            closes = candle_data['close']
+
+            # Create figure and axis
+            fig, ax = plt.subplots(figsize=(12, 6), facecolor='#1e1e1e')
+            ax.set_facecolor('#2d2d2d')
+
+            # Plot closing prices
+            ax.plot(dates, closes, color='#00d4ff', linewidth=2)
+
+            # Fill area under the line
+            ax.fill_between(dates, closes, alpha=0.3, color='#00d4ff')
+
+            # Format x-axis
+            ax.xaxis.set_major_formatter(mdates.DateFormatter('%m/%d'))
+            ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+            plt.xticks(rotation=45, ha='right')
+
+            # Grid styling
+            ax.grid(True, alpha=0.2, color='#ffffff', linestyle='-', linewidth=0.5)
+
+            # Labels and title
+            title = f"{company_name} ({ticker})" if company_name else ticker
+            ax.set_title(title, color='#ffffff', fontsize=14, fontweight='bold', pad=20)
+            ax.set_xlabel('Date', color='#ffffff', fontsize=10)
+            ax.set_ylabel('Price ($)', color='#ffffff', fontsize=10)
+
+            # Tick colors
+            ax.tick_params(colors='#ffffff', which='both')
+
+            # Spine colors
+            for spine in ax.spines.values():
+                spine.set_color('#444444')
+
+            # Tight layout
+            plt.tight_layout()
+
+            # Save to buffer
+            buffer = io.BytesIO()
+            plt.savefig(buffer, format='png', facecolor='#1e1e1e', dpi=100)
+            buffer.seek(0)
+            plt.close(fig)
+
+            return buffer
+
+        except Exception as e:
+            logger.error(f"Error generating chart for {ticker}: {e}")
+            return None
+
+    @staticmethod
+    def create_candlestick_chart(
+        ticker: str,
+        candle_data: Dict[str, List],
+        company_name: Optional[str] = None
+    ) -> Optional[io.BytesIO]:
+        """
+        Create a candlestick chart from candle data.
+
+        Args:
+            ticker: Stock ticker symbol
+            candle_data: Dictionary with timestamps, open, high, low, close, volume
+            company_name: Optional company name for title
+
+        Returns:
+            BytesIO buffer containing the chart image, or None if error
+        """
+        try:
+            # Convert timestamps to datetime objects
+            dates = [datetime.fromtimestamp(ts) for ts in candle_data['timestamps']]
+            opens = candle_data['open']
+            highs = candle_data['high']
+            lows = candle_data['low']
+            closes = candle_data['close']
+
+            # Create figure and axis
+            fig, ax = plt.subplots(figsize=(12, 6), facecolor='#1e1e1e')
+            ax.set_facecolor('#2d2d2d')
+
+            # Calculate bar width
+            width = 0.6
+
+            # Plot candlesticks
+            for i in range(len(dates)):
+                color = '#00ff88' if closes[i] >= opens[i] else '#ff4444'
+
+                # High-low line
+                ax.plot([dates[i], dates[i]], [lows[i], highs[i]], color=color, linewidth=1)
+
+                # Open-close rectangle
+                height = abs(closes[i] - opens[i])
+                bottom = min(opens[i], closes[i])
+                ax.bar(dates[i], height, width, bottom=bottom, color=color, alpha=0.8)
+
+            # Format x-axis
+            ax.xaxis.set_major_formatter(mdates.DateFormatter('%m/%d'))
+            ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+            plt.xticks(rotation=45, ha='right')
+
+            # Grid styling
+            ax.grid(True, alpha=0.2, color='#ffffff', linestyle='-', linewidth=0.5)
+
+            # Labels and title
+            title = f"{company_name} ({ticker})" if company_name else ticker
+            ax.set_title(title, color='#ffffff', fontsize=14, fontweight='bold', pad=20)
+            ax.set_xlabel('Date', color='#ffffff', fontsize=10)
+            ax.set_ylabel('Price ($)', color='#ffffff', fontsize=10)
+
+            # Tick colors
+            ax.tick_params(colors='#ffffff', which='both')
+
+            # Spine colors
+            for spine in ax.spines.values():
+                spine.set_color('#444444')
+
+            # Tight layout
+            plt.tight_layout()
+
+            # Save to buffer
+            buffer = io.BytesIO()
+            plt.savefig(buffer, format='png', facecolor='#1e1e1e', dpi=100)
+            buffer.seek(0)
+            plt.close(fig)
+
+            return buffer
+
+        except Exception as e:
+            logger.error(f"Error generating candlestick chart for {ticker}: {e}")
+            return None

requirements.txt

@@ -5,3 +5,4 @@ APScheduler==3.10.4
 python-dotenv==1.0.0
 pytz==2023.3
 requests==2.31.0
+matplotlib==3.8.2

stock_api/finnhub_api.py

@@ -1,8 +1,8 @@
 import finnhub
 import logging
-from typing import Optional, Dict, Any
+from typing import Optional, Dict, Any, List
 from .base import StockAPIBase
-from datetime import datetime
+from datetime import datetime, timedelta
 import pytz
 
 
@@ -170,3 +170,40 @@ class FinnhubAPI(StockAPIBase):
         except Exception as e:
             logger.error(f"Error fetching earnings calendar: {e}")
             return None
+
+    def get_candles(self, ticker: str, days: int = 30, resolution: str = 'D') -> Optional[Dict[str, List]]:
+        """
+        Retrieve historical candlestick data from Finnhub.
+
+        Args:
+            ticker: Stock ticker symbol
+            days: Number of days of historical data to fetch
+            resolution: Candle resolution (1, 5, 15, 30, 60, D, W, M)
+
+        Returns:
+            Dictionary with OHLCV data or None if unavailable
+        """
+        try:
+            # Calculate timestamps
+            end_time = int(datetime.now().timestamp())
+            start_time = int((datetime.now() - timedelta(days=days)).timestamp())
+
+            # Fetch candle data
+            candles = self.client.stock_candles(ticker, resolution, start_time, end_time)
+
+            if not candles or candles.get('s') != 'ok':
+                logger.warning(f"No candle data available for ticker: {ticker}")
+                return None
+
+            return {
+                'timestamps': candles['t'],
+                'open': candles['o'],
+                'high': candles['h'],
+                'low': candles['l'],
+                'close': candles['c'],
+                'volume': candles['v']
+            }
+
+        except Exception as e:
+            logger.error(f"Error fetching candle data for {ticker}: {e}")
+            return None

stock_api/yahoo.py

@@ -1,6 +1,6 @@
 import yfinance as yf
 import logging
-from typing import Optional, Dict, Any
+from typing import Optional, Dict, Any, List
 from .base import StockAPIBase
 
 
@@ -83,3 +83,46 @@ class YahooFinanceAPI(StockAPIBase):
         except Exception as e:
             logger.error(f"Yahoo Finance API unavailable: {e}")
             return False
+
+    def get_candles(self, ticker: str, days: int = 30, resolution: str = 'D') -> Optional[Dict[str, List]]:
+        """
+        Retrieve historical candlestick data from Yahoo Finance.
+
+        Args:
+            ticker: Stock ticker symbol
+            days: Number of days of historical data to fetch
+            resolution: Candle resolution (ignored, always daily for Yahoo Finance)
+
+        Returns:
+            Dictionary with OHLCV data or None if unavailable
+        """
+        try:
+            stock = yf.Ticker(ticker)
+
+            # Fetch historical data
+            hist = stock.history(period=f"{days}d")
+
+            if hist.empty:
+                logger.warning(f"No candle data available for ticker: {ticker}")
+                return None
+
+            # Convert to the format expected by chart generator
+            timestamps = [int(date.timestamp()) for date in hist.index]
+            opens = hist['Open'].tolist()
+            highs = hist['High'].tolist()
+            lows = hist['Low'].tolist()
+            closes = hist['Close'].tolist()
+            volumes = hist['Volume'].tolist()
+
+            return {
+                'timestamps': timestamps,
+                'open': opens,
+                'high': highs,
+                'low': lows,
+                'close': closes,
+                'volume': volumes
+            }
+
+        except Exception as e:
+            logger.error(f"Error fetching candle data for {ticker}: {e}")
+            return None