Summary - Pytest

Combine fixture, parametrize and monkeypatch to write a calculator test.

Summary - Pytest

This group covered the core tools of pytest. assert checks conditions; fixture injects setup code into tests; parametrize runs the same test with many inputs; monkeypatch changes values temporarily.

The final task combines parametrize with a helper function: you'll test a filter function with several inputs.

Exercise filter test with parametrize

The function keep_positive(nums) returns [n for n in nums if n > 0]. Decorate test_keep_positive with @pytest.mark.parametrize; first string "nums,expected", second argument [([1, -2, 3], [1, 3]), ([-1, -2], [])]. The test body contains assert keep_positive(nums) == expected. End with test_keep_positive([1, -2, 3], [1, 3]) and print("ok").

Show example solution

import pytest

def keep_positive(nums):
    return [n for n in nums if n > 0]

@pytest.mark.parametrize("nums,expected", [([1, -2, 3], [1, 3]), ([-1, -2], [])])
def test_keep_positive(nums, expected):
    assert keep_positive(nums) == expected

test_keep_positive([1, -2, 3], [1, 3])
print("ok")

Test yourself

What is the best way to test a function with many inputs?
- Copy and paste the same test manually
- Use @pytest.mark.parametrize
- Generate random data inside the test
- Run with only one fixed input
Show answer

Use @pytest.mark.parametrize — parametrize avoids repetition and provides data-driven testing.

Complete the summary parametrize

import pytest

@____("nums,expected", [([1, 2, 3], 6), ([10, 20], 30)])
def test_sum(nums, expected):
    assert sum(nums) == expected

Show answer

import pytest

@pytest.mark.parametrize("nums,expected", [([1, 2, 3], 6), ([10, 20], 30)])
def test_sum(nums, expected):
    assert sum(nums) == expected

Match the group tools

assert

Checks a condition
fixture

Injects setup
parametrize

Data-driven repeat
monkeypatch

Temporary change

Next lesson: unittest.mock

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