I must be doing something silly and wrong, hopefully I can get some help
from this list. I am writing a blocking call in the c api which is
serviced by a [pool] of other threads, of course when the call is made I
want to let stackless continue processing, so I did this, which works great:
PyObject* getData(PyObject *self, PyObject *args)
{
// blah blah construct request on the heap
request->task = PyStackless_GetCurrent();
queueRequest( request ); // this will get picked up by the thread pool
PyStackless_Schedule( request->task ); // away it goes back into
python-land
Py_DECREF( request->task ); // if we got here its because we were
woken up
// blah blah construct response and return
}
The thread pool does this:
worker()
{
// blah blah wait on queue and get a job and do some work
waiting for awhile (or returning immediately)
while( !PyTasklet_Paused(request->task) ) // prevent race
(deadlock if this runs before the _Schedule call)
{
Sleep(0); // yield
}
PyTasklet_Insert( request->task );
}
This works just fine. Until I stress it. this program from python
crashes instantly in unpredicatbale (corrupt memory) ways:
import stackless
import dbase
def test():
while 1:
dbase.request()
for i in range( 10 ):
task = stackless.tasklet( test )()
while 1:
stackless.schedule()
BUT if I change that range from 10 to 1? runs all day long without any
problems. Clearly I am doing something that isn't thread safe. but what?
I've tried placing mutexes around the PyTask_ calls but since schedule
doesn't normally return thats not possible everywhere, If I add Sleep's
it helps, in fact if I make them long enough it fixes the problem and
all 10 threads run concurrently.
I assume PyTasklet_Schedule()/_Insert() are meant to be used this way,
(ie- multiple threads) can anyone tell me which stupid way I have gone
wrong?
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