Answer
Multithreading runs multiple threads within one process and shared memory space. • Threads are useful for many I/O-bound tasks. • Shared mutable data needs synchronization. • In GIL-enabled CPython, threads do not normally execute Python bytecode in parallel for CPU-bound work.
💡 Simple Example
from threading import Thread
def work():
print('worker')
thread = Thread(target=work)
thread.start()
thread.join()
Output
worker
⚡ Quick Revision
Threads share process memory and are often useful for I/O concurrency.