What is concurrent.futures and when to use it?

Question

Accepted Answer

**concurrent.futures** provides high-level interfaces for **threading and multiprocessing**.

```python
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor, as_completed
import time

def io_task(url):
    time.sleep(1)  # Simulate I/O
    return f"Result from {url}"

def cpu_task(n):
    return sum(i * i for i in range(n))

# ThreadPoolExecutor — for I/O-bound
with ThreadPoolExecutor(max_workers=5) as executor:
    futures = [executor.submit(io_task, f"url{i}") for i in range(10)]
    for future in as_completed(futures):
        print(future.result())

# ProcessPoolExecutor — for CPU-bound
with ProcessPoolExecutor(max_workers=4) as executor:
    results = list(executor.map(cpu_task, [10**6] * 4))
    print(results)

# Future object
future = executor.submit(cpu_task, 10**6)
print(future.done())     # False (or True)
print(future.result())   # Blocks until done
print(future.cancel())   # Cancel if not started
```

**Benefits:**
- Same API for threads and processes.
- Automatic resource management.
- `as_completed()` for streaming results.

Python: What is concurrent.futures and when to use it?