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Parameterized Testing - Running Tests with Multiple Data Sets

Why parameterize?

Instead of repeating similar tests, parameterize inputs.

Example

test_parametrize.py

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):
    assert add(a, b) == expected

test_parametrize.py

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):
    assert add(a, b) == expected

Parametrize with ids

test_parametrize_ids.py

import pytest
 
 
@pytest.mark.parametrize(
    "s,expected",
    [("10", 10), ("0", 0)],
    ids=["ten", "zero"],
)
def test_int_parse(s, expected):
    assert int(s) == expected

test_parametrize_ids.py

import pytest
 
 
@pytest.mark.parametrize(
    "s,expected",
    [("10", 10), ("0", 0)],
    ids=["ten", "zero"],
)
def test_int_parse(s, expected):
    assert int(s) == expected

🧪 Try It Yourself

Exercise 1 – Write a unittest TestCase

Exercise 2 – assertRaises

Exercise 3 – setUp and tearDown

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