Chris Angelico <ros...@gmail.com> writes: > So, you would have to pass code to the other process, probably. What > about this: > y = 4 > other_thread_queue.put(lambda x: x*y)
the y in the lambda is a free variable that's a reference to the surrounding mutable context, so that's at best dubious. You could use: other_thread_queue.put(lambda x, y=y: x*y) > Or this: > > y = [4] > def next_y(): > y[0] += 1 > return y[0] > other_thread_queue.put(next_y) There you have shared mutable data, which isn't allowed in this style. > It may not be obvious with your squaring example, but every Python > function has its context (module globals, etc). You can't pass a > function around without also passing, or sharing, its data. That is ok as long as the data can't change. > With threads in a single process, this isn't a problem. They all > access the same memory space, so they can all share state. As soon as > you go to separate processes, these considerations become serious. Right, that's a limitation of processes compared to threads. -- https://mail.python.org/mailman/listinfo/python-list
