Concurrent Futures

Introduction

Concurrent.futures provides high-level interface for asynchronous task execution.

ThreadPoolExecutor

from concurrent.futures import ThreadPoolExecutor, as_completed
import time

def task(n):
    time.sleep(1)
    return n ** 2

with ThreadPoolExecutor(max_workers=4) as executor:
    futures = [executor.submit(task, i) for i in range(10)]
    
    for future in as_completed(futures):
        print(f"Result: {future.result()}")

ProcessPoolExecutor

from concurrent.futures import ProcessPoolExecutor

def cpu_intensive(n):
    return sum(i ** 2 for i in range(1000000))

with ProcessPoolExecutor(max_workers=4) as executor:
    results = list(executor.map(cpu_intensive, range(10)))

Submit and Future

from concurrent.futures import ThreadPoolExecutor

executor = ThreadPoolExecutor(max_workers=4)

future = executor.submit(pow, 2, 3)
print(future.result())  # 8

executor.shutdown(wait=True)

Practice Problems

1. Parallelize web scraping
2. Process images concurrently
3. Download multiple files
4. Use ProcessPoolExecutor for CPU tasks
5. Handle exceptions in futures