In article <qota9nhu6ag....@ruuvi.it.helsinki.fi>,
Jussi Piitulainen <jpiit...@ling.helsinki.fi> wrote:
> A light-weighter way is to have each task end by assigning the next
> task and returning, instead of calling the next task directly. When a
> task returns, a driver loop will call the assigned task, which again
> does a bounded amount of work, assigns the next task, and returns.
> Tasks can even pass parameters in the same way.
Yup. I've used this pattern for building state machines. Each state is
a function which returns the next state (or, sometimes, a (next_state,
output) tuple). The top level loop ends up looking very much like yours:
state = start
while state != end:
state, output = state(get_next_input())
print output
>
> Like so, Dr. Fred keeps adding to a pile as long as there is a pile,
> and Mr. Jim keeps taking from it as long as it's there to take from:
>
> from random import choice
>
> def fred():
> global fun, arg
> print('Fred adds 1')
> fun, arg = choice((fred, jim)), arg + 1
>
> def jim():
> global fun, arg
> print('Jim takes 1')
> fun, arg = choice((fred, jim)), arg - 1
>
> if __name__ == '__main__':
> fun, arg = choice((fred, jim)), 3
> while arg:
> print('Pile is', arg, end = '\t')
> fun()
> else:
> print('Pile is gone')
--
http://mail.python.org/mailman/listinfo/python-list
