Concurrency & Multithreading Flashcards

Which class in the `concurrent.futures` module is best suited for thread-based parallelism?

Answer: ThreadPoolExecutor

ThreadPoolExecutor manages a pool of worker threads and provides a high-level interface for submitting tasks and retrieving results via Future objects.

What is the primary purpose of a threading.Lock object in Python?

Answer: To synchronize access to shared resources, preventing simultaneous modification by multiple threads

A Lock ensures mutual exclusion — only one thread can acquire the lock at a time, preventing race conditions on shared data.

In Python's asyncio framework, which keyword suspends a coroutine until an awaitable completes?

Answer: await

The `await` keyword suspends the current coroutine and yields control back to the event loop, which resumes it when the awaitable is done.

What is a deadlock in a multithreaded Python program?

Answer: A situation where two or more threads wait indefinitely for locks held by each other

Deadlock occurs when Thread A holds Lock 1 and waits for Lock 2, while Thread B holds Lock 2 and waits for Lock 1 — both block forever.

Which method of threading.Thread should you override in a subclass to define the thread's work?

Answer: run()

Overriding run() defines the code executed in the new thread; start() internally calls run() in a new thread context.

What is the primary advantage of asyncio over threading for I/O-bound tasks in Python?

Answer: asyncio uses cooperative multitasking, eliminating thread-switching overhead and scaling to thousands of concurrent tasks

asyncio's event loop runs in a single thread using cooperative multitasking — coroutines yield control voluntarily, avoiding the overhead of OS thread switching.

Which module and class should be used to safely pass data between threads using a FIFO queue?

Answer: queue.Queue

queue.Queue is thread-safe by design, using internal locks to prevent race conditions when multiple threads produce and consume items.