Future of Pypy?

[Paul Rubin]

Chris Angelico <rosuav at 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.