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test.py
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test.py
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import main
from settings import Node
import pytest
# For the test suite, I opt for the external library "pytest," the "industry standard" Python library for testing
# (the most widely used by the community). Then, I chose to define the test technique "Table test"
# For Table test, I define the test cases as a list of tuples (input_values, expected_result)
test_cases = [
# TEST CASE 1:
(
(
Node(
op="or_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="gt", val=50),
right=Node(var="flood_risk", op="lt", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
), # The rule
{
"credit_rating": 75,
"flood_risk": 5,
"revenue": 1000
}
), # Data input that satisfy the rule
True), # Output that I expect (True)
# TEST CASE 2:
(
(
Node(
op="or_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="gt", val=50),
right=Node(var="flood_risk", op="lt", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 50,
"flood_risk": 5,
"revenue": 1000
}
),
False),
# TEST CASE 3:
(
(Node(
op="or_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="gt", val=50),
right=Node(var="flood_risk", op="lt", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 45,
"flood_risk": 5,
"revenue": 123456789
}
),
True),
# TEST CASE 4:
(
(
Node(
op="or_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="ge", val=50),
right=Node(var="flood_risk", op="lt", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 50,
"flood_risk": 5,
"revenue": 123456789
},
),
True),
# TEST CASE 5:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="ge", val=50),
right=Node(var="flood_risk", op="lt", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 40,
"flood_risk": 5,
"revenue": 123456789
}
),
False),
# TEST CASE 6:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="ge", val=50),
right=Node(var="flood_risk", op="le", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 40,
"flood_risk": 5,
"revenue": 123456789
},
),
False),
# TEST CASE 7:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="ge", val=50),
right=Node(var="flood_risk", op="le", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"credit_rating": 50,
"flood_risk": 10,
"revenue": 123456789
},
),
True),
# TEST CASE 8:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="ge", val=50),
right=Node(var="flood_risk", op="le", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789
}
),
False),
# TEST CASE 9:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(var="flood_risk", op="le", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789
}
),
True),
# TEST CASE 10:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(var="flood_risk", op="le", val=10)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789,
"other": 999
}
),
True),
# TEST CASE 11:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(
op="or_",
left=Node(var="flood_risk", op="eq", val=9),
right=Node(var="other", op="ge", val=100)
)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789,
"other": 999
}
),
True),
# TEST CASE 12:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(
op="xor",
left=Node(var="flood_risk", op="eq", val=9),
right=Node(var="other", op="ge", val=100)
)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789,
"other": 999
}
),
True),
# TEST CASE 13:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(
op="or_",
left=Node(var="flood_risk", op="eq", val=9),
right=Node(var="other", op="ge", val=1000)
)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789,
"other": 999
}
),
False),
# TEST CASE 14:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(
op="and_",
left=Node(var="flood_risk", op="ne", val=9),
right=Node(var="other", op="ge", val=100)
)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 10,
"revenue": 123456789,
"other": 999
}
),
True),
# TEST CASE 15:
(
(
Node(
op="and_",
left=Node(
op="and_",
left=Node(var="credit_rating", op="le", val=9),
right=Node(
op="and_",
left=Node(var="flood_risk", op="ne", val=9),
right=Node(var="other", op="ge", val=100)
)
),
right=Node(var="revenue", op="gt", val=1000000)
),
{
"flood_risk": 9,
"revenue": 123456789,
"other": 999
}
),
False)
]
# I use the @pytest.mark.parametrize decorator to create the table-driven test
@pytest.mark.parametrize("input_values, expected_result", test_cases)
def test_evaluate(input_values, expected_result):
result = main.evaluate(*input_values)
assert result == expected_result