from IPython.parallel import Client
rc = Client()
rc.ids

dview = rc[:]

with open('../builtin-cpuheavy/prime_list.txt') as f:
    PRIMES = [int(l) for l in f]

def is_prime(n):
    import math  # import until the function is called
                 # make sure all engines import math
    if n % 2 == 0:
        return False

    sqrt_n = int(math.floor(math.sqrt(n)))
    for i in range(3, sqrt_n + 1, 2):
        if n % i == 0:
            return False
    return True

ar = dview.map_async(is_prime, PRIMES[:8])

ar.wait_interactive() # wait blocks, and wait_interactive provide working status

ar.get()

speedup = ar.serial_time / ar.wall_time
speedup

ar.metadata[:1]

with dview.sync_imports():
    import math
    import numpy as np

def find_np():
    np.random.randint(10)

rc[:2].apply_sync(find_np)

%%px
import numpy as np
np.random.randint(6)

%%px
# try to run it multiple times, engines use same processes (like a remote Python intepreter)
import os
os.getpid()

# push
dview['prog'] = 'val_prime'

# pull
dview['prog']

# all engines get x but with differnt value
ar = dview.scatter('x', list(range(13)))
ar.wait()

dview['x']

# get x from all engines and combined
dview.gather('x', block=True)

%%px 
import numpy as np
rand_n = np.random.randint(0, 10, 6)

dview['rand_n']

dview.gather('rand_n', block=True)

# sum at each engine
def rand_sum():
    return np.sum(rand_n)

ar = dview.apply_sync(rand_sum)

ar.get()

# parallel sum shoud equal to serial sum
sum(ar.get()) == sum(dview.gather('rand_n', block=True))