from collections import defaultdict

user = defaultdict(lambda: 'Kevin')

user

defaultdict(<function __main__.<lambda>>, {})

type(user)

collections.defaultdict

user['abc']

'Kevin'

user['country']

'Kevin'

user['name'] = 'Peter'
user['age'] = 21 …

import socket

addr1 = socket.gethostbyname('google.com')
addr2 = socket.gethostbyname('yahoo.com')

print(addr1)

172.217.0.238

print(addr2)

98.137.246.8

def get_domain(url):
    spltAr = url.split("://")
    i = (0,1)[len(spltAr)>1]
    dm = spltAr[i].split("?")[0].split('/')[0].split(':')[0].lower()
    #print(dm)
    return dm

def get_domain_without_prefix(url):
    spltAr = url.split("://")
    i = (0,1)[len …

animals = ['cat', 'dog', 'monkey']

for idx, animal in enumerate(animals):
    print ('#%d: %s' % (idx , animal))

#0: cat
#1: dog
#2: monkey

data = ['Toronto', 'Montreal', 'Waterloo', 'Chennai', 'Bangalore', 123, ['One', 'Two', 'Three']]

for x in enumerate(data):
    print(x)

(0, 'Toronto')
(1, 'Montreal')
(2, 'Waterloo')
(3, 'Chennai')
(4, 'Bangalore')
(5, 123)
(6, ['One', 'Two', 'Three'])

for i, x in …

import matplotlib
import numpy
import perfplot
from scipy.spatial import distance

def linalg_norm(data):
    a, b = data
    return numpy.linalg.norm(a-b, axis=1)

def sqrt_sum(data):
    a, b = data
    return numpy.sqrt(numpy.sum((a-b …

def euclidean_distance(p, q):

    #make sure both array are in the same dimension
    assert len(p) == len(q)  

    return max([abs(x-y) for x,y in zip(p,q)])

acb = euclidean_distance([1,2,3],[1 …

import numpy

def dist(x,y):   
    return numpy.sqrt(numpy.sum((x-y)**2))

a = numpy.array((1,2,3))
b = numpy.array((4,5,6))
dist_a_b = dist(a,b)

print(dist_a_b)

5.196152422706632

import math
import numpy
from random import uniform

def fastest_calc_dist(p1,p2):
    return math.sqrt((p2[0] - p1[0]) ** 2 +
                     (p2[1] - p1[1]) ** 2 +
                     (p2[2] - p1[2]) ** 2)    

def math_calc_dist(p1,p2):
    return math.sqrt(math …

import random
import time

# PythonDecorators/entry_exit_class.py
class execution_time_calculator(object):

    def __init__(self, f):
        self.f = f

    def __call__(self):
        start = int(round(time.time() * 1000))
        print("Entering", self.f.__name__)
        self.f()
        end = int …