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test_exercise1.py
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test_exercise1.py
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#!/usr/bin/env python
""" Assignment 3, Exercise 1, INF1340, Fall, 2015. DBMS
Test module for exercise3.py
"""
__author__ = 'Susan Sim'
__email__ = "ses@drsusansim.org"
__copyright__ = "2015 Susan Sim"
__license__ = "MIT License"
from exercise1 import selection, projection, cross_product
###########
# TABLES ##
###########
EMPLOYEES = [["Surname", "FirstName", "Age", "Salary"],
["Smith", "Mary", 25, 2000],
["Black", "Lucy", 40, 3000],
["Verdi", "Nico", 36, 4500],
["Smith", "Mark", 40, 3900]]
R1 = [["Employee", "Department"],
["Smith", "sales"],
["Black", "production"],
["White", "production"]]
R2 = [["Department", "Head"],
["production", "Mori"],
["sales", "Brown"]]
RNM = [["Sayings", "People"],
["squanch", "Squanchy"],
["wubalubadubdub", "Rick"],
["ohjeez", "Morty"]]
GAMES = [["Title", "Genre", "Time"],
["Catan", "resource", "90"],
["XCOM", "space", "150"]]
#####################
# HELPER FUNCTIONS ##
#####################
def is_equal(t1, t2):
t1.sort()
t2.sort()
return t1 == t2
#####################
# FILTER FUNCTIONS ##
#####################
def filter_employees(row):
"""
Check if employee represented by row
is AT LEAST 30 years old and makes
MORE THAN 3500.
:param row: A List in the format:
[{Surname}, {FirstName}, {Age}, {Salary}]
:return: True if the row satisfies the condition.
"""
return row[-2] >= 30 and row[-1] > 3500
###################
# TEST FUNCTIONS ##
###################
def test_selection():
"""
Test select operation.
"""
result = [["Surname", "FirstName", "Age", "Salary"],
["Verdi", "Nico", 36, 4500],
["Smith", "Mark", 40, 3900]]
assert is_equal(result, selection(EMPLOYEES, filter_employees))
def test_projection():
"""
Test projection operation.
"""
result = [["Surname", "FirstName"],
["Smith", "Mary"],
["Black", "Lucy"],
["Verdi", "Nico"],
["Smith", "Mark"]]
assert is_equal(result, projection(EMPLOYEES, ["Surname", "FirstName"]))
result2 = [["Surname", "Age", "Salary"],
["Smith", 25, 2000],
["Black", 40, 3000],
["Verdi", 36, 4500],
["Smith", 40, 3900]]
assert is_equal(result2, projection(EMPLOYEES, ["Surname", "Age", "Salary"]))
result3 = [["Head"],
["Mori"],
["Brown"]]
assert is_equal(result3, projection(R2, ["Head"]))
def test_cross_product():
"""
Test cross product operation.
"""
result = [["Employee", "Department", "Department", "Head"],
["Smith", "sales", "production", "Mori"],
["Smith", "sales", "sales", "Brown"],
["Black", "production", "production", "Mori"],
["Black", "production", "sales", "Brown"],
["White", "production", "production", "Mori"],
["White", "production", "sales", "Brown"]]
assert is_equal(result, cross_product(R1, R2))
result = [["Sayings", "People", "Title", "Genre", "Time"],
["squanch", "Squanchy", "Catan", "resource", "90"],
["squanch", "Squanchy", "XCOM", "space", "150"],
["wubalubadubdub", "Rick", "Catan", "resource", "90"],
["wubalubadubdub", "Rick", "XCOM", "space", "150"],
["ohjeez", "Morty", "Catan", "resource", "90"],
["ohjeez", "Morty", "XCOM", "space", "150"]]
assert is_equal(result, cross_product(RNM, GAMES))