What is the difference between multiprocessing and multithreading in Python?

Due to Python's GIL (Global Interpreter Lock), threads can't run Python code in parallel — only one thread executes at a time.

**Multithreading (threading module):**
- Multiple threads, ONE Python process
- GIL prevents true parallel execution of Python code
- BUT: releases GIL for I/O operations (network, file, database)
- Best for: I/O-bound tasks (web scraping, API calls, file reading)

```python
import threading
t = threading.Thread(target=my_function)
t.start()
```

**Multiprocessing (multiprocessing module):**
- Multiple processes, each with its own GIL and memory
- True parallel execution on multiple CPU cores
- Higher memory usage (separate process)
- Best for: CPU-bound tasks (data processing, ML training, image processing)

```python
from multiprocessing import Pool
with Pool(4) as p:
results = p.map(process_data, data_chunks)
```

**Rule:** I/O bound → threading. CPU bound → multiprocessing.