Added my stock-price-tracker #50

HARI21HP · 2025-12-07T20:31:34Z

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github-actions · 2025-12-07T20:31:43Z

👋 @HARI21HP
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Pull request overview

This PR adds a comprehensive Stock Price Tracker application that fetches stock data from Yahoo Finance, creates visualizations, and sends Telegram alerts for price movements. The implementation is well-structured with separate utility modules for data fetching, plotting, and notifications.

Key Changes:

New Stock Price Tracker application with CLI interface
Yahoo Finance integration for real-time and historical stock data
Matplotlib and Plotly-based visualization system with multiple chart types
Telegram bot integration for automated price alerts and notifications

Reviewed changes

Copilot reviewed 8 out of 8 changed files in this pull request and generated 28 comments.

Show a summary per file

File	Description
`Stock-Price-Tracker/stock_tracker.py`	Main CLI application orchestrating stock tracking, visualization, and alerts
`Stock-Price-Tracker/utils/yahoo_finance.py`	Yahoo Finance API wrapper providing stock data fetching and price calculations
`Stock-Price-Tracker/utils/telegram_alert.py`	Telegram bot integration for sending formatted stock price alerts
`Stock-Price-Tracker/utils/plotter.py`	Visualization module creating price trends, candlestick charts, and summary reports
`Stock-Price-Tracker/utils/__init__.py`	Package initialization exposing main utility classes
`Stock-Price-Tracker/requirements.txt`	Python dependencies including yfinance, pandas, matplotlib, plotly, and telegram bot
`Stock-Price-Tracker/config/.env.example`	Environment variable template for Telegram bot configuration
`Stock-Price-Tracker/README.md`	Comprehensive documentation with features, installation, usage examples, and project structure

Comments suppressed due to low confidence (1)

Stock-Price-Tracker/utils/yahoo_finance.py:204

Except block directly handles BaseException.

        except:

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Copilot · 2025-12-07T20:39:40Z

Stock-Price-Tracker/utils/yahoo_finance.py

+                '52_week_low': info.get('fiftyTwoWeekLow', 'N/A'),
+            }
+        except Exception as e:
+            print(f"Error fetching stock info: {e}")


The error message only prints the exception object but doesn't provide context about which ticker failed or guidance for users. Consider enhancing it to: print(f"Error fetching stock info for {self.ticker}: {e}") to make debugging easier.

Suggested change

print(f"Error fetching stock info: {e}")

print(f"Error fetching stock info for {self.ticker}: {e}")

Copilot · 2025-12-07T20:39:40Z

Stock-Price-Tracker/utils/yahoo_finance.py

+                'lowest': round(lowest_price, 2)
+            }
+        except Exception as e:
+            print(f"Error calculating price change: {e}")


Error message should include the ticker symbol for context: print(f"Error calculating price change for {self.ticker}: {e}")

Suggested change

print(f"Error calculating price change: {e}")

print(f"Error calculating price change for {self.ticker}: {e}")

Copilot · 2025-12-07T20:39:40Z

Stock-Price-Tracker/utils/plotter.py

+        Change:         ${stats.get('change', 'N/A')} ({stats.get('change_percent', 'N/A')}%)
+        Highest:        ${stats.get('highest', 'N/A')}
+        Lowest:         ${stats.get('lowest', 'N/A')}
+        Range:          ${stats.get('highest', 0) - stats.get('lowest', 0):.2f}


This calculation ${stats.get('highest', 0) - stats.get('lowest', 0):.2f} can produce incorrect results if either 'highest' or 'lowest' is missing (defaulting to 0). The range calculation should handle missing values more gracefully, perhaps by checking if both values exist first or using a more appropriate default like 'N/A'.

Copilot · 2025-12-07T20:39:41Z

Stock-Price-Tracker/utils/yahoo_finance.py

+            info = self.stock.info
+            return 'symbol' in info or 'longName' in info


Similar to get_current_price(), this method fetches all stock info via an API call just to validate the ticker. This is inefficient if called multiple times. Consider caching the validation result or implementing a lighter validation method.

Copilot · 2025-12-07T20:39:41Z

Stock-Price-Tracker/utils/plotter.py

+
+        # Plot closing price
+        plt.plot(data.index, data['Close'], label='Close Price', 
+                color='#2E86C1', linewidth=2)
+
+        # Add moving averages
+        if len(data) >= 7:
+            ma7 = data['Close'].rolling(window=7).mean()
+            plt.plot(data.index, ma7, label='7-Day MA', 
+                    color='#E67E22', linestyle='--', linewidth=1.5)
+
+        if len(data) >= 30:
+            ma30 = data['Close'].rolling(window=30).mean()
+            plt.plot(data.index, ma30, label='30-Day MA', 
+                    color='#27AE60', linestyle='--', linewidth=1.5)
+
+        # Formatting
+        if title is None:
+            title = f'{self.ticker} Stock Price Trend'
+        plt.title(title, fontsize=16, fontweight='bold', pad=20)
+        plt.xlabel('Date', fontsize=12, fontweight='bold')
+        plt.ylabel('Price ($)', fontsize=12, fontweight='bold')
+        plt.legend(loc='best', fontsize=10)
+        plt.grid(True, alpha=0.3, linestyle='--')
+
+        # Format x-axis
+        plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+        plt.gcf().autofmt_xdate()
+
+        plt.tight_layout()
+
+        if save_path:
+            plt.savefig(save_path, dpi=300, bbox_inches='tight')
+            print(f"Plot saved to {save_path}")
+
+        if show_plot:
+            plt.show()
+        else:
+            plt.close()


Creating a new figure without explicitly closing it when show_plot=False can lead to memory leaks in long-running applications. While plt.close() is called on line 81, if any exception occurs between lines 42-80, the figure remains in memory. Consider using a context manager or adding a try-finally block to ensure cleanup.

Suggested change

# Plot closing price

plt.plot(data.index, data['Close'], label='Close Price',

color='#2E86C1', linewidth=2)

# Add moving averages

if len(data) >= 7:

ma7 = data['Close'].rolling(window=7).mean()

plt.plot(data.index, ma7, label='7-Day MA',

color='#E67E22', linestyle='--', linewidth=1.5)

if len(data) >= 30:

ma30 = data['Close'].rolling(window=30).mean()

plt.plot(data.index, ma30, label='30-Day MA',

color='#27AE60', linestyle='--', linewidth=1.5)

# Formatting

if title is None:

title = f'{self.ticker} Stock Price Trend'

plt.title(title, fontsize=16, fontweight='bold', pad=20)

plt.xlabel('Date', fontsize=12, fontweight='bold')

plt.ylabel('Price ($)', fontsize=12, fontweight='bold')

plt.legend(loc='best', fontsize=10)

plt.grid(True, alpha=0.3, linestyle='--')

# Format x-axis

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

plt.gcf().autofmt_xdate()

plt.tight_layout()

if save_path:

plt.savefig(save_path, dpi=300, bbox_inches='tight')

print(f"Plot saved to {save_path}")

if show_plot:

plt.show()

else:

plt.close()

try:

# Plot closing price

plt.plot(data.index, data['Close'], label='Close Price',

color='#2E86C1', linewidth=2)

# Add moving averages

if len(data) >= 7:

ma7 = data['Close'].rolling(window=7).mean()

plt.plot(data.index, ma7, label='7-Day MA',

color='#E67E22', linestyle='--', linewidth=1.5)

if len(data) >= 30:

ma30 = data['Close'].rolling(window=30).mean()

plt.plot(data.index, ma30, label='30-Day MA',

color='#27AE60', linestyle='--', linewidth=1.5)

# Formatting

if title is None:

title = f'{self.ticker} Stock Price Trend'

plt.title(title, fontsize=16, fontweight='bold', pad=20)

plt.xlabel('Date', fontsize=12, fontweight='bold')

plt.ylabel('Price ($)', fontsize=12, fontweight='bold')

plt.legend(loc='best', fontsize=10)

plt.grid(True, alpha=0.3, linestyle='--')

# Format x-axis

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

plt.gcf().autofmt_xdate()

plt.tight_layout()

if save_path:

plt.savefig(save_path, dpi=300, bbox_inches='tight')

print(f"Plot saved to {save_path}")

if show_plot:

plt.show()

finally:

if not show_plot:

plt.close()

Copilot · 2025-12-07T20:39:45Z

Stock-Price-Tracker/utils/yahoo_finance.py

+        Returns:
+            float: Current price or None if unavailable
+        """
+        try:


This method calls self.stock.info which makes an API request to fetch all stock information just to get the current price. Consider caching the info data or using a more specific API call if available. If this method is called frequently, it could lead to rate limiting or unnecessary network overhead.

Suggested change

try:

try:

# Try fast_info for quick price access

price = None

if hasattr(self.stock, "fast_info"):

price = getattr(self.stock.fast_info, "last_price", None)

if price is not None:

return price

# Fallback: use history for the latest close price

hist = self.stock.history(period="1d", interval="1m")

if not hist.empty:

# Use the last available price (close or regularMarketPrice)

price = hist["Close"].iloc[-1]

if pd.notnull(price):

return float(price)

# Last resort: use info (slow)

Copilot · 2025-12-07T20:39:45Z

Stock-Price-Tracker/utils/plotter.py

+        gs = fig.add_gridspec(3, 2, hspace=0.3, wspace=0.3)
+
+        # Title
+        fig.suptitle(f'{self.ticker} Stock Analysis Report', 
+                    fontsize=18, fontweight='bold', y=0.98)
+
+        # Main price chart
+        ax1 = fig.add_subplot(gs[0:2, :])
+        ax1.plot(data.index, data['Close'], label='Close Price', 
+                color='#2E86C1', linewidth=2.5)
+        ax1.fill_between(data.index, data['Low'], data['High'], 
+                        alpha=0.2, color='#85C1E9', label='Daily Range')
+        ax1.set_title('Price Trend with Daily Range', fontweight='bold', fontsize=14)
+        ax1.set_ylabel('Price ($)', fontsize=12)
+        ax1.legend(loc='best')
+        ax1.grid(True, alpha=0.3)
+
+        # Statistics text box
+        ax2 = fig.add_subplot(gs[2, 0])
+        ax2.axis('off')
+        stats_text = f"""
+        STATISTICS SUMMARY
+        ━━━━━━━━━━━━━━━━━━━━━━━━━
+        Start Price:    ${stats.get('start_price', 'N/A')}
+        End Price:      ${stats.get('end_price', 'N/A')}
+        Change:         ${stats.get('change', 'N/A')} ({stats.get('change_percent', 'N/A')}%)
+        Highest:        ${stats.get('highest', 'N/A')}
+        Lowest:         ${stats.get('lowest', 'N/A')}
+        Range:          ${stats.get('highest', 0) - stats.get('lowest', 0):.2f}
+        """
+        ax2.text(0.1, 0.5, stats_text, fontsize=11, family='monospace',
+                verticalalignment='center', bbox=dict(boxstyle='round', 
+                facecolor='wheat', alpha=0.5))
+
+        # Volume chart
+        ax3 = fig.add_subplot(gs[2, 1])
+        ax3.bar(data.index, data['Volume'], color='#3498DB', alpha=0.6)
+        ax3.set_title('Trading Volume', fontweight='bold', fontsize=12)
+        ax3.set_ylabel('Volume', fontsize=10)
+        ax3.grid(True, alpha=0.3, axis='y')
+        ax3.tick_params(axis='x', rotation=45)
+
+        if save_path:
+            plt.savefig(save_path, dpi=300, bbox_inches='tight')
+            print(f"Summary report saved to {save_path}")
+
+        if show_plot:
+            plt.show()
+        else:
+            plt.close()


Same figure cleanup issue: figure created without guaranteed cleanup if an exception occurs before line 339. Consider using try-finally or a context manager.

Suggested change

gs = fig.add_gridspec(3, 2, hspace=0.3, wspace=0.3)

# Title

fig.suptitle(f'{self.ticker} Stock Analysis Report',

fontsize=18, fontweight='bold', y=0.98)

# Main price chart

ax1 = fig.add_subplot(gs[0:2, :])

ax1.plot(data.index, data['Close'], label='Close Price',

color='#2E86C1', linewidth=2.5)

ax1.fill_between(data.index, data['Low'], data['High'],

alpha=0.2, color='#85C1E9', label='Daily Range')

ax1.set_title('Price Trend with Daily Range', fontweight='bold', fontsize=14)

ax1.set_ylabel('Price ($)', fontsize=12)

ax1.legend(loc='best')

ax1.grid(True, alpha=0.3)

# Statistics text box

ax2 = fig.add_subplot(gs[2, 0])

ax2.axis('off')

stats_text = f"""

STATISTICS SUMMARY

━━━━━━━━━━━━━━━━━━━━━━━━━

Start Price: ${stats.get('start_price', 'N/A')}

End Price: ${stats.get('end_price', 'N/A')}

Change: ${stats.get('change', 'N/A')} ({stats.get('change_percent', 'N/A')}%)

Highest: ${stats.get('highest', 'N/A')}

Lowest: ${stats.get('lowest', 'N/A')}

Range: ${stats.get('highest', 0) - stats.get('lowest', 0):.2f}

"""

ax2.text(0.1, 0.5, stats_text, fontsize=11, family='monospace',

verticalalignment='center', bbox=dict(boxstyle='round',

facecolor='wheat', alpha=0.5))

# Volume chart

ax3 = fig.add_subplot(gs[2, 1])

ax3.bar(data.index, data['Volume'], color='#3498DB', alpha=0.6)

ax3.set_title('Trading Volume', fontweight='bold', fontsize=12)

ax3.set_ylabel('Volume', fontsize=10)

ax3.grid(True, alpha=0.3, axis='y')

ax3.tick_params(axis='x', rotation=45)

if save_path:

plt.savefig(save_path, dpi=300, bbox_inches='tight')

print(f"Summary report saved to {save_path}")

if show_plot:

plt.show()

else:

plt.close()

try:

gs = fig.add_gridspec(3, 2, hspace=0.3, wspace=0.3)

# Title

fig.suptitle(f'{self.ticker} Stock Analysis Report',

fontsize=18, fontweight='bold', y=0.98)

# Main price chart

ax1 = fig.add_subplot(gs[0:2, :])

ax1.plot(data.index, data['Close'], label='Close Price',

color='#2E86C1', linewidth=2.5)

ax1.fill_between(data.index, data['Low'], data['High'],

alpha=0.2, color='#85C1E9', label='Daily Range')

ax1.set_title('Price Trend with Daily Range', fontweight='bold', fontsize=14)

ax1.set_ylabel('Price ($)', fontsize=12)

ax1.legend(loc='best')

ax1.grid(True, alpha=0.3)

# Statistics text box

ax2 = fig.add_subplot(gs[2, 0])

ax2.axis('off')

stats_text = f"""

STATISTICS SUMMARY

━━━━━━━━━━━━━━━━━━━━━━━━━

Start Price: ${stats.get('start_price', 'N/A')}

End Price: ${stats.get('end_price', 'N/A')}

Change: ${stats.get('change', 'N/A')} ({stats.get('change_percent', 'N/A')}%)

Highest: ${stats.get('highest', 'N/A')}

Lowest: ${stats.get('lowest', 'N/A')}

Range: ${stats.get('highest', 0) - stats.get('lowest', 0):.2f}

"""

ax2.text(0.1, 0.5, stats_text, fontsize=11, family='monospace',

verticalalignment='center', bbox=dict(boxstyle='round',

facecolor='wheat', alpha=0.5))

# Volume chart

ax3 = fig.add_subplot(gs[2, 1])

ax3.bar(data.index, data['Volume'], color='#3498DB', alpha=0.6)

ax3.set_title('Trading Volume', fontweight='bold', fontsize=12)

ax3.set_ylabel('Volume', fontsize=10)

ax3.grid(True, alpha=0.3, axis='y')

ax3.tick_params(axis='x', rotation=45)

if save_path:

plt.savefig(save_path, dpi=300, bbox_inches='tight')

print(f"Summary report saved to {save_path}")

if show_plot:

plt.show()

finally:

plt.close(fig)

Copilot · 2025-12-07T20:39:46Z

Stock-Price-Tracker/utils/plotter.py

+import matplotlib.dates as mdates
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+from datetime import datetime


Import of 'datetime' is not used.

Suggested change

from datetime import datetime

Copilot · 2025-12-07T20:39:46Z

Stock-Price-Tracker/stock_tracker.py

+Author: Python-Projects Contributors
+"""
+
+import os


Import of 'os' is not used.

Suggested change

import os

Copilot · 2025-12-07T20:39:46Z

Stock-Price-Tracker/utils/yahoo_finance.py

+
+import yfinance as yf
+import pandas as pd
+from datetime import datetime, timedelta


Import of 'datetime' is not used.
Import of 'timedelta' is not used.

Suggested change

from datetime import datetime, timedelta

Added my stock-price-tracker

28e3d92

Copilot AI review requested due to automatic review settings December 7, 2025 20:31

github-actions bot requested a review from iamwatchdogs December 7, 2025 20:31

github-actions bot assigned HARI21HP Dec 7, 2025

Copilot started reviewing on behalf of HARI21HP December 7, 2025 20:31 View session

Copilot AI reviewed Dec 7, 2025

View reviewed changes

	print(f"Error fetching stock info: {e}")
	print(f"Error fetching stock info for {self.ticker}: {e}")

	print(f"Error calculating price change: {e}")
	print(f"Error calculating price change for {self.ticker}: {e}")

		info = self.stock.info
		return 'symbol' in info or 'longName' in info

-        try:
+        try:
+            # Try fast_info for quick price access
+            price = None
+            if hasattr(self.stock, "fast_info"):
+                price = getattr(self.stock.fast_info, "last_price", None)
+                if price is not None:
+                    return price
+            # Fallback: use history for the latest close price
+            hist = self.stock.history(period="1d", interval="1m")
+            if not hist.empty:
+                # Use the last available price (close or regularMarketPrice)
+                price = hist["Close"].iloc[-1]
+                if pd.notnull(price):
+                    return float(price)
+            # Last resort: use info (slow)

Added my stock-price-tracker #50

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