All 15 Concurrency (asyncio/threading/multiprocessing) questions
More in Concurrency (asyncio/threading/multiprocessing)
What is the fundamental difference between concurrency and parallelism, and how does this map to Python's threading versus multiprocessing modules? What is the basic pattern for running an async function using asyncio.run()? How does the Global Interpreter Lock (GIL) affect CPU-bound versus I/O-bound multithreaded programs differently? How do you run multiple coroutines concurrently using asyncio.gather()? How do you protect shared mutable state from race conditions when using multiple threads, using threading.Lock? How does multiprocessing.Pool let you parallelize a CPU-bound function across multiple worker processes? What is a race condition, and how does it differ from a deadlock? How does asyncio's event loop schedule and switch between multiple coroutines, and what makes this cooperative rather than preemptive? How do you safely run a blocking, synchronous function from within an asyncio coroutine without freezing the event loop? How do you share data between processes using multiprocessing, given that separate processes don't share memory the way threads do?
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Python › Concurrency (asyncio/threading/multiprocessing)

How do you create and run a basic thread using the threading module?

Beginner

Answer

Create a threading.Thread object, passing the target function (and optional args), then call .start() to begin execution concurrently, and .join() to wait for it to finish before continuing.
import threading

def greet(name):
    print(f"Hello, {name}!")

thread = threading.Thread(target=greet, args=("Sam",))
thread.start()
thread.join()  # waits for the thread to finish
Real-world example Running a background task (like a periodic health check) concurrently with the main program's execution.

Common follow-ups: What happens to the main program if it exits before a non-daemon thread finishes?

Functions & Scope
All 15 Concurrency (asyncio/threading/multiprocessing) questions