Add real-time console-based stock price plotter using dummy data

stock_price.py

@@ -1,64 +1,53 @@
-# Remember the pre-requisites
-# pip install requests matplotlib
-import requests
-import matplotlib.pyplot as plt
-from collections import deque
-import time
-
-# Use a public API for real data, e.g., Finnhub.io or Alpha Vantage.
-# This example uses a placeholder URL and dummy data.
-def get_stock_price(ticker):
-    """Fetches real-time stock price from a mock API."""
-    # Replace this with a real API call.
-    # Example using dummy data:
-    if ticker == 'AAPL':
-        # Simulate a slight price fluctuation
-        return 150.0 + (time.time() % 10) * 0.5 - 2.5
-    else:
-        return None
+# Real-Time Stock Price Plotter (Console Version)
+# Hacktoberfest 2025 Contribution
+# Author: Sonika KC
+# Works without installing any external libraries
 
+import random
+import time
+import datetime
+import os
+
+# Function: Generate dummy stock price
+def get_stock_price(dummy_price):
+    """Simulates stock price fluctuations."""
+    fluctuation = random.uniform(-1.0, 1.0)  # +/- $1
+    return round(dummy_price + fluctuation, 2)
+
+# Function: Draw simple text-based graph
+def draw_graph(prices):
+    os.system('cls' if os.name == 'nt' else 'clear')  # Clear terminal
+    max_price = max(prices)
+    min_price = min(prices)
+    scale = 50 / (max_price - min_price + 0.01)  # Scale to 50 characters
+
+    print("Real-Time Stock Price (AAPL)\n")
+    for price in prices:
+        num_chars = int((price - min_price) * scale)
+        print(f"${price:6} | " + "*" * num_chars)
+    print("\nPress Ctrl+C to stop.\n")
+
+# Main function
 def main():
-    """Fetches and plots stock prices in real time."""
     stock_ticker = 'AAPL'
-    time_series_data = deque(maxlen=50) # Use a deque for efficient sliding window
-    time_points = deque(maxlen=50)
-
-    plt.ion() # Turn on interactive mode
-    fig, ax = plt.subplots()
-    line, = ax.plot([], [], 'o-')
-    ax.set_title(f"Real-Time Stock Price for {stock_ticker}")
-    ax.set_xlabel("Time (s)")
-    ax.set_ylabel("Price ($)")
-
-    start_time = time.time()
+    max_points = 20  # number of points to display
+    current_price = 150.0
+    prices = []
 
     try:
         while True:
-          #code by Madhav :)
-            current_price = get_stock_price(stock_ticker)
-            if current_price is not None:
-                current_time = time.time() - start_time
-                time_series_data.append(current_price)
-                time_points.append(current_time)
-
-                # Update plot data
-                line.set_xdata(time_points)
-                line.set_ydata(time_series_data)
-
-                # Adjust plot limits dynamically
-                ax.relim()
-                ax.autoscale_view()
-
-                # Redraw the plot
-                fig.canvas.draw()
-                fig.canvas.flush_events()
+            current_price = get_stock_price(current_price)
+            prices.append(current_price)
+            if len(prices) > max_points:
+                prices.pop(0)
 
-            time.sleep(1) # Update every second
+            draw_graph(prices)
+            print(f"Time: {datetime.datetime.now().strftime('%H:%M:%S')}")
+            time.sleep(1)
 
     except KeyboardInterrupt:
-        print("\nStopping real-time plot.")
-        plt.ioff()
-        plt.show()
+        print("\nStopped real-time plotting.")
 
+# Run the program
 if __name__ == "__main__":
     main()