How to implement parallel execution?

To implement parallel execution in Python, you can use the multiprocessing module. Here’s a simple example that demonstrates how to run tasks in parallel:

import multiprocessing
import time

def worker(task_id):
    print(f"Task {task_id} is starting.")
    time.sleep(2)  # Simulate a time-consuming task
    print(f"Task {task_id} is completed.")

if __name__ == "__main__":
    tasks = [1, 2, 3, 4, 5]  # List of tasks
    processes = []

    # Create a process for each task
    for task_id in tasks:
        process = multiprocessing.Process(target=worker, args=(task_id,))
        processes.append(process)
        process.start()  # Start the process

    # Wait for all processes to complete
    for process in processes:
        process.join()

    print("All tasks are completed.")

Explanation:

• Importing the Module: The multiprocessing module is imported to handle parallel execution.
• Defining the Worker Function: The worker function simulates a task that takes time to complete.
• Creating Processes: For each task, a new process is created and started.
• Joining Processes: The main program waits for all processes to finish using join().

This example will run five tasks in parallel, each simulating a time-consuming operation. You can adjust the number of tasks and the workload as needed.