Threads aren't the only way to handle I/O. We compare ThreadPoolExecutor to asyncio, clarifying when to use pre-emptive threading versus cooperative multitasking for modern apps.

ThreadPoolExecutor isn't for everything. We contrast it with ProcessPoolExecutor, showing why CPU-heavy tasks need processes to bypass the GIL, while threads remain the superior choice for network and file I/O.

Sometimes you need "global" variables that are unique to each thread. threading.local() creates thread-specific storage, allowing workers to maintain their own isolated state (like database connections) without interference.

To protect critical sections, we use threading.Lock and RLock. These tools enforce mutual exclusion, acting like a traffic light that ensures only one thread can enter a protected block of code at a time.

A critical section is a block of code that accesses a shared resource and must not be interrupted by other threads. We learn to identify these sensitive areas in your codebase where multiple threads overlapping would cause inconsistency.