import numpy as np

N, F = 1000, 20

A = np.random.randn(N, F)

def sig(x, mean, std):
    return (x-mean)/std

def sig_loop():
    svals = []
    for j in range(F):
        a = A[:, j]
        mean = np.mean(a)
        std = np.std(a)
        svals.append([sig(x, mean, std) for x in a])
    return svals

def sig_vec():
    svals = []
    for j in range(F):
        a = A[:, j]
        mean = np.mean(a)
        std = np.std(a)
        svals.append(sig(a, mean, std))
    return svals

def sig_mat():
    return sig(A, np.mean(A, 0), np.std(A, 0))

%timeit sig_loop()
%timeit sig_vec()
%timeit sig_mat()

from mongoengine import connect, Document, ListField

class Test(Document):
    g = ListField()
    
t = Test(g=['3']*20)

class Test2:
    g = ['3']*20
    
t2 = Test2()

%timeit t.g
%timeit t2.g

%timeit t._data['g']

import pymongo
from mongoengine import connect, Document, ListField
connect('test')
db = pymongo.MongoClient().test

class Test(Document):
    g = ListField()

docs1 = [Test(g=['3']*20) for _ in range(10000)]
docs2 = [{'g':['3']*20} for _ in range(10000)]


db.drop_collection('test')
%time Test.objects.insert(docs1)

db.drop_collection('test')
%time x=[doc.save() for doc in docs1]

db.drop_collection('test')
%time db.test.insert(docs2)

db.drop_collection('test')
%time x=[db.test.insert(doc) for doc in docs2]