What is the GIL and how does it affect concurrency?

Question

Accepted Answer

**GIL (Global Interpreter Lock)** allows only **one thread to execute Python bytecode** at a time.

**Impact:**
- **CPU-bound**: no true parallelism with threads.
- **I/O-bound**: GIL released during I/O, threads work fine.

```python
import threading
import time

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

# Threading (GIL limits CPU-bound)
start = time.time()
threads = [
    threading.Thread(target=cpu_bound, args=(10**7,))
    for _ in range(4)
]
for t in threads:
    t.start()
for t in threads:
    t.join()
print(f"Threading: {time.time() - start:.2f}s")

# Multiprocessing (bypasses GIL)
from multiprocessing import Pool
start = time.time()
with Pool(4) as pool:
    pool.map(cpu_bound, [10**7] * 4)
print(f"Multiprocessing: {time.time() - start:.2f}s")
```

**Solutions:**
- **multiprocessing**: separate processes.
- **asyncio**: single-thread concurrency.
- **C extensions**: release GIL (NumPy).
- **Alternative implementations**: PyPy, Jython.

Python: What is the GIL and how does it affect concurrency?