How does the GIL affect I/O-bound vs CPU-bound tasks?

Question

Accepted Answer

**GIL** only affects **CPU-bound** tasks. **I/O-bound** tasks are not impacted.

**CPU-bound (GIL limits parallelism):**
```python
import threading
import time

def cpu_heavy():
    total = 0
    for i in range(10_000_000):
        total += i
    return total

# Slower than single-threaded!
start = time.time()
t1 = threading.Thread(target=cpu_heavy)
t2 = threading.Thread(target=cpu_heavy)
t1.start(); t2.start()
t1.join(); t2.join()
print(time.time() - start)  # ~6s (not ~3s)
```

**I/O-bound (GIL released during I/O):**
```python
import threading
import urllib.request

def fetch(url):
    return urllib.request.urlopen(url).read()

# Much faster with threads
threads = [
    threading.Thread(target=fetch, args=(url,))
    for url in urls
]
```

**Rules of thumb:**
- **CPU-bound** → `multiprocessing`.
- **I/O-bound** → `asyncio` or `threading`.
- **Mixed** → combine approaches.

Python: How does the GIL affect I/O-bound vs CPU-bound tasks?