import sympy as s
from sympy.abc import x,y
s.init_printing()

element = lambda n, m : m * x**n if (n+m) % 3 else y
L = s.Matrix([[element(n,m) for m in range(9)] for n in range(9)])
L

numer_L = s.lambdify((x,y), L, 'numpy')
numer_L(3,4)

# in series
import numpy
s_result = list(map(lambda y: numpy.linalg.det(numer_L(3,y)), range(30)))
s_result

# set up parallel environment. 2 engines started with `ipcluster start -n 2`
from IPython.parallel import Client
rc = Client()
dview = rc[:]

# in parallel
# do imports and push our lambda function over
dview.execute('import numpy')
dview.push(dict(numer_L=numer_L))
p_result = dview.map_sync(lambda y: numpy.linalg.det(numer_L(3,y)), range(30))
p_result

type(L)

from sympy.utilities.lambdify import lambdastr
lstr = lambdastr((x,y), L, dummify=True)
lstr

# in parallel
# do imports and push our lambda function over
dview.execute('import numpy')
dview.execute('from numpy import matrix as ImmutableMatrix')
dview.push(dict(numer_L=numer_L))
p_result = dview.map_sync(lambda y: numpy.linalg.det(numer_L(3,y)), range(30))
p_result

# in parallel
# do imports and push our lambda function over
dview.execute('import numpy')
dview.execute('from numpy import matrix as ImmutableMatrix')
dview.push(dict(lstr=lstr))
p_result = dview.map_sync(lambda y: numpy.linalg.det(eval(lstr)(3,y)), range(30))
p_result

p_result == s_result

import sys
sys.version

import IPython
IPython.version_info

s.__version__ # sympy

numpy.__version__