14_multithreading.py

"""
14_multithreading.py
--------------------
Concept: Multithreading (Threading for I/O bound tasks)
Context: Running a Heartbeat Monitor while listening to a Simulated WebSocket.

Python Global Interpreter Lock (GIL) limits threads to one CPU content, 
but they are great for I/O tasks like waiting for network data or user input.
"""

import threading
import time
import random

# Shared state
market_data = {"BTC": 60000}
is_running = True

# 1. Thread 1: The Worker (Simulated WebSocket Listener)
def data_stream_listener():
    print("[Stream] Connected to Exchange Stream...")
    while is_running:
        time.sleep(1) # Simulate network latency
        # Update shared memory
        new_price = 60000 + random.randint(-500, 500)
        market_data["BTC"] = new_price
        print(f"[Stream] Updated BTC Price: ${new_price}")
    print("[Stream] Connection Closed.")

# 2. Thread 2: The Monitor (Heartbeat / UI updater)
def heartbeat_monitor():
    print("[Monitor] Service Started...")
    while is_running:
        time.sleep(2.5) # Checks every 2.5 seconds
        current_price = market_data["BTC"]
        print(f"    >>> [Monitor] Heartbeat Check. Current BTC: ${current_price}")
    print("[Monitor] Service Stopped.")

# Main Execution
if __name__ == "__main__":
    # Create threads
    t1 = threading.Thread(target=data_stream_listener)
    t2 = threading.Thread(target=heartbeat_monitor)

    # Start threads
    t1.start()
    t2.start()

    # Let them run for 8 seconds
    try:
        time.sleep(8)
    except KeyboardInterrupt:
        pass
    
    # Stop everything
    print("\n[Main] Stopping threads...")
    is_running = False
    
    # Wait for threads to finish
    t1.join()
    t2.join()
    print("[Main] All threads stopped. Exiting.")