Here's an example of using multithreading in Python:

```python
import threading

def worker(num):
    """Thread worker function"""
    print(f"Thread {num} starting")

threads = []
for i in range(5):
    t = threading.Thread(target=worker, args=(i,))
    threads.append(t)
    t.start()

for t in threads:
    t.join()

print("All threads finished")```

And here's an example of using multiprocessing in Python:

```python
import multiprocessing

def worker(num):
    """Process worker function"""
    print(f"Process {num} starting")

processes = []
for i in range(5):
    p = multiprocessing.Process(target=worker, args=(i,))
    processes.append(p)
    p.start()

for p in processes:
    p.join()

print("All processes finished")```

In general, you should use multithreading when you have a task that is CPU-bound and can run in parallel, and you should use multiprocessing when you have a task that is I/O-bound or requires a large amount of memory.
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