Hi rpyc users and developpers!
(cf my code below as I can not attach files...)
I am building a big dummy dictionary, and call a dummy function on it that
loops through all keys and sets the values to 0.
This function takes 0.00099 seconds.
If run by a rpyc.service (that runs on the same host), it takes 9.346
seconds.
Also, it looks like the execution of the body of the function exposed by
the service will start even if the input object "sent" by the client has
not been "received" entirely on the server side. Cf in my code:
dummy.print1 will fail (trying to perform a for k,v in d.items).
Thus my questions:
- Is there a connection param I could use to speed up the transmission of a
big object between my client and my service? (typically a 150kB object when
pickled)
- How is it that the function run by the service starts its execution while
the function input is not available yet?
Thanks a lot for your comments/suggestions, and the great work on rpyc,
Boris
**************** mini_service.py ******************************************
******************************************************************************
import rpyc
from rpyc.utils.server import ThreadedServer
import dummy
class miniService(rpyc.Service):
def exposed_myfunc(self,d):
#dummy.print1(d) #success
#dummy.print2(d) #Netref.py / protocol.py / AttributeError: cannot access
'items'
dummy.dummy(d)
if __name__=='__main__':
t = ThreadedServer(miniService,protocol_config = {"allow_pickle" : True},
port = 19865)
t.start()
********************* mini_client.py **************************************
******************************************************************************
import rpyc
import sys
#import socket
import pickle
import dummy
def makedict(n):
d={x:x for x in range(n)}
return d
if __name__ == "__main__":
d=makedict(20000)
print(sys.getsizeof(d)) #result = 393356
# dummy.print2(d)
# output = open("C:\\rd\\non_mc_test_files\\mini.pkl",'wb') #117kB object
for n=20k
# pickle.dump(d,output)
# output.close()
#RUN1 : dummy.dummy(d) out of rpyc takes 0.00099 seconds
# dummy.dummy(d)
#RUN2 : dummy.dummy(d) via RPYC on localhost takes 9.346 seconds
# conn=rpyc.connect('localhost',19865,config={"allow_pickle":True})
# conn.root.myfunc(d)
print('Done.')
**************** dummy.py ***********************************************
******************************************************************************
import time
def print1(d):
for k,v in d.items():
print(k,v)
def print2(d):
for key in d:
print(key)
def dummy(d):
start_ = time.time()
for key in d:
d[key]=0
print('Time spent in dummy in seconds: ' + str(time.time()-start_))
