Why parametrize multiplies test coverage in PyTest - Automation Benefits in Action

Verify addition function with multiple input sets

Preconditions (2)

Step 1: Open the test file containing the addition function test

Step 2: Run the test with input values (1, 2) expecting 3

Step 3: Run the test with input values (0, 0) expecting 0

Step 4: Run the test with input values (-1, 1) expecting 0

✅ Expected Result: All tests pass for each input set, confirming the addition function works correctly for multiple cases

Automation Requirements - pytest

Assertions Needed:

Assert the addition function returns the correct sum for each input pair

Best Practices:

Use @pytest.mark.parametrize to run the same test with different inputs

Keep tests small and focused

Use descriptive test names

Automated Solution

PyTest

import pytest

def add(a, b):
    return a + b

@pytest.mark.parametrize("a,b,expected", [
    (1, 2, 3),
    (0, 0, 0),
    (-1, 1, 0)
])
def test_add(a, b, expected):
    result = add(a, b)
    assert result == expected, f"Expected {expected} but got {result}"

This test uses @pytest.mark.parametrize to run test_add three times with different inputs.

Each time, it checks if the add function returns the expected sum.

This multiplies test coverage by testing multiple cases with one test function, making tests concise and clear.

Common Mistakes - 3 Pitfalls

Writing separate test functions for each input set

Not asserting the expected result properly

Using complex logic inside the test instead of simple inputs

Bonus Challenge

Now add data-driven testing with 3 different input sets including floats and large numbers

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