In an asyncio producer/consumer crawler, each consumer loops forever on await queue.get(). How does the program know all work is done, and how do you then stop the idle consumers?

You submit two tasks; the first is slow, the second fast. You print f1.result() then f2.result(). Which result appears first?

You have a CPU-bound function (heavy number crunching). You run 4 copies across 4 threading.Threads on a 4-core machine. Does it finish ~4x faster?

If the GIL makes threads useless for speeding up CPU work, what ARE threads actually good for in CPython?

You need to share a large mutable dict between parallel workers and have them all update it live. Threads or processes?

What does this print? ``` import threading class C(threading.Thread): counter = 0 def run(self): for _ in range(2000000): C.counter += 1 a, b = C(), C() a.start(); b.start() a.join(); b.join() print(C.counter) ```

How do you fix the lost-update race on a shared counter incremented by multiple threads?