Measuring total execution time of concurrent asynchronous tasks in Python

Last update on December 21 2024 07:18:39 (UTC/GMT +8 hours)

Write a Python program that runs multiple asynchronous tasks concurrently using asyncio.gather() and measures the time taken.

Sample Solution:

Code:

import asyncio
import time
async def task1():
    print("Task-1 started")
    await asyncio.sleep(4)
    print("Task-1 completed")
async def task2():
    print("Task-2 started")
    await asyncio.sleep(1)
    print("Task-2 completed")
async def task3():
    print("Task-3 started\n")
    await asyncio.sleep(2)
    print("Task-3 completed")

async def main():
    start_time = time.time()    
    await asyncio.gather(task1(), task2(), task3())    
    end_time = time.time()
    elapsed_time = end_time - start_time
    print("\nAll tasks completed in {:.2f} seconds".format(elapsed_time))
# Run the event loop
asyncio.run(main())

Output:

Task-1 started
Task-2 started
Task-3 started

Task-2 completed
Task-3 completed
Task-1 completed

All tasks completed in 4.00 seconds

Explanation:

In the above exercise-

• Three asynchronous tasks (task1, task2, and task3) are defined. Each task simulates a different duration of work using await asyncio.sleep().
• The main coroutine starts by recording the start time using time.time().
• The asyncio.gather() function runs all tasks concurrently. It takes the tasks as arguments and runs them concurrently, waiting for all of them to complete.
• After the asyncio.gather() call, the end time is recorded using time.time(), and the elapsed time is calculated.
• The program prints a message indicating that all tasks have been completed and displays the elapsed time.

Flowchart:

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