HelloFresh test exercise

mainClass.py

class Link(object):
    def __init__(self, parent_name, child_name):
        self.parent_name = parent_name
        self.child_name = child_name


def find_venture(list_of_links, account):
    for comp in list_of_links:
        # if child_name is the same as we are looking for, then proceed for checking its parent
        if comp.child_name == account:
            if comp.parent_name != "Root":
                venture = find_venture(list_of_links, comp.parent_name)
                
                return(venture)
            else:
                return(comp.child_name)


def main():
    list_of_links = []
    list_of_links.append(Link("Root", "HelloFresh UK"))
    list_of_links.append(Link("Root", "HelloFresh US"))
    list_of_links.append(Link("HelloFresh UK", "account1"))
    list_of_links.append(Link("HelloFresh UK", "account2"))
    list_of_links.append(Link("HelloFresh US", "account3"))
    list_of_links.append(Link("account3", "account4"))
    list_of_links.append(Link("account3", "account5"))
    list_of_links.append(Link("account4", "account6"))
    
# Printing the venture of "account5":
    print(find_venture(list_of_links, "account5"))

if __name__ == '__main__':
        main()

task2.py

# Ivan Sokolenko

# Imports
from random import seed
import math
import numpy as np
from scipy.stats import binom
import matplotlib.pyplot as plt

#setting variales: (set your variables here)

N = 100
a = 0.5
b = 0.5
    
# setting a seed value of 42:
seed(42)

# defining a range of x:
k = np.arange(0,N+1)


# defining intra cluster correlation p:
p = 1/(a+b+1)


# calculating the expected value of X, i.e. E[x]:
mean = N*p

# calculating variance of X, i.e. Var(x):
variance = N*p*(1-p)


# standard deviation of X:
std = math.sqrt(variance)

# 95% confidence intervals:
lower_bound = p - 1.96*std
upper_bound = p + 1.96*std
confidence_interval = [lower_bound, upper_bound]
print("The expected value of x is %d when N = %d, a = %d and b = %d. For the 95%% confidence interval the lower bound is %d and upper bound is %d." % ( mean, N, a, b ,lower_bound, upper_bound) )


# Plots:
binomial = binom.pmf(k, N, p)
binomial
plt.plot(k, binomial, "o-", label = "pmf")
plt.title("Binomial: N=%i, p=%.2f" % (N,p), fontsize=15)
plt.xlabel("Number of successes")
plt.ylabel("Probability of successes", fontsize=15)
plt.axvline(mean,color="red", label = "Mean")
plt.legend()
plt.show()



    

tests.py

import unittest
# importing class to test
from mainClass import Link
from mainClass import find_venture


class LinkTest(unittest.TestCase):
    """
    Our basic test class
    """
    def setUp(self):
        """
        Setting up values
        """
        self.list_of_links = []
        self.list_of_links.append(Link("Root", "HelloFresh UK"))
        self.list_of_links.append(Link("Root", "HelloFresh US"))
        self.list_of_links.append(Link("HelloFresh UK", "account1"))
        self.list_of_links.append(Link("HelloFresh UK", "account2"))
        self.list_of_links.append(Link("HelloFresh US", "account3"))
        self.list_of_links.append(Link("account3", "account4"))
        self.list_of_links.append(Link("account3", "account5"))
        self.list_of_links.append(Link("account4", "account6"))

    def test_UK(self):
        """
        The actual test.
        Any method which starts with ``test_`` will considered as a test case.
        Testing for vendor - HelloFresh UK
        """
        res = find_venture(self.list_of_links, "account2")
        self.assertEqual(res, "HelloFresh UK")

    def test_US(self):
        """
        Testing for vendor - HelloFresh US
        """
        res = find_venture(self.list_of_links, "account5")
        self.assertEqual(res, "HelloFresh US")

if __name__ == '__main__':
    unittest.main(argv=['first-arg-is-ignored'], exit=False)