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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"]]
STUDENTS = [["FirstName", "Surname", "Age"],
["Yueyue", "Yang", 25],
["Yuchen", "Jia", 23],
["Xike", "Wang", 25],
["Ming", "Fu", 31],
["Black", "Whiten", 66]]
TEACHER = [["FirstName", "Surname", "Age"],
["Susan", "Sim", 40],
["Eric", "Yu", 60]]
COURSES = [["Course"],
["Inf1340"],
["Inf1341"]]
#####################
# 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
def filter_students(row):
return row[-1] <= 35
###################
# 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"]))
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))
def test_selection_student():
# Test selection
result = [["FirstName", "Surname", "Age"],
["Yueyue", "Yang", 25],
["Yuchen", "Jia", 23],
["Xike", "Wang", 25],
["Ming", "Fu", 31]]
assert is_equal(result, selection(STUDENTS, filter_students))
def test_projection_student():
# Test projection
result = [["Surname", "Age"],
["Yang", 25],
["Jia", 23],
["Wang", 25],
["Fu", 31],
["Whiten", 66]]
assert is_equal(result, projection(STUDENTS, ["Surname", "Age"]))
def test_cross_product_student():
# Test cross product
result = [["FirstName", "Surname", "Age", "Course"],
["Susan", "Sim", 40, "Inf1340"],
["Susan", "Sim", 40, "Inf1341"],
["Eric", "Yu", 60, "Inf1340"],
["Eric", "Yu", 60, "Inf1341"]]
assert is_equal(result, cross_product(TEACHER, COURSES))
def test_selection_returns_nothing():
# Test if selection is none
t = [["Name", "Age"],
["Bob", 47],
["Mary", 65],
["Carla", 54]]
def f(r):
return r[-1] < 35
assert selection(t, f) is None
def test_projection_returns_error():
# Test if projection has error
try:
projection(STUDENTS, ["Age", "Surname"])
except AttributeError:
assert True
def test_cross_product_returns_nothing():
# Test if cross product is none
t1 = [["Teacher", "Age"],
["Susan", 47],
["Eric", 65]]
t2 = [["Teacher", "Age"]]
assert cross_product(t1, t2) is None