Python Academy · Lesson

Parametrize and Test Coverage

Run tests with multiple inputs using @pytest.mark.parametrize.

Parametrize and Test Coverage is a free Python Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Python Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

@pytest.mark.parametrize

Run the same test with multiple inputs using @pytest.mark.parametrize. Each tuple is a separate test case.

import pytest

@pytest.mark.parametrize("a,b,expected", [
    (1, 2, 3),
    (0, 0, 0),
    (-1, 1, 0),
    (10, -5, 5),
])
def test_add(a, b, expected):
    assert a + b == expected

Single Parameter

For a single argument, pass a list of values directly.

import pytest

@pytest.mark.parametrize("n", [1, 2, 3, 4, 5])
def test_positive(n):
    assert n > 0

Named Test IDs

Provide an ids list to label each parameter set for clearer output.

import pytest

@pytest.mark.parametrize("value,result", [
    (2, True),
    (3, False),
], ids=["even", "odd"])
def test_is_even(value, result):
    assert (value % 2 == 0) == result

Stacking parametrize Decorators

Stack two parametrize decorators to get the Cartesian product of inputs.

import pytest

@pytest.mark.parametrize("x", [1, 2])
@pytest.mark.parametrize("y", [10, 20])
def test_product(x, y):
    assert x * y > 0   # 4 test cases: (1,10),(1,20),(2,10),(2,20)

pytest-cov: Install

Install pytest-cov to measure which lines of your code are exercised by tests.

# pip install pytest-cov

# Basic usage:
# pytest --cov=mypackage

# HTML report:
# pytest --cov=mypackage --cov-report=html

Reading Coverage Output

Coverage shows which lines, branches, or statements were not reached during testing.

# Name          Stmts   Miss  Cover
# -------       -----   ----  -----
# mypackage/utils.py  20       3    85%
#
# Missing: lines 45, 67, 88

Branch Coverage

Use --cov-branch to track whether both branches of conditionals are tested.

# pytest --cov=mypackage --cov-branch

def is_positive(n):
    if n > 0:        # branch 1: True
        return True
    return False     # branch 2: False

Failing on Low Coverage

Use --cov-fail-under=N to fail the build if coverage drops below N percent.

# pytest --cov=mypackage --cov-fail-under=80
# FAIL Required test coverage of 80% not reached. Total: 72%

.coveragerc Configuration

Configure coverage exclusions in .coveragerc to skip boilerplate code.

# .coveragerc
[run]
omit =
    */migrations/*
    */tests/*
    setup.py

[report]
exclude_lines =
    pragma: no cover
    if TYPE_CHECKING:

What Good Coverage Means

High coverage does not guarantee correct tests. Aim for meaningful assertions, not just line hits. 80-90% is a practical target for most projects.

# A covered but useless test:
def test_nothing():
    is_positive(5)   # no assert — 100% coverage, zero confidence

# A meaningful test:
def test_positive():
    assert is_positive(5) is True
    assert is_positive(-1) is False

Combining parametrize and Coverage

Parametrized tests improve coverage naturally by exercising multiple code paths with one test definition.

import pytest

@pytest.mark.parametrize("n,expected", [
    (5, True), (-1, False), (0, False)
])
def test_is_positive(n, expected):
    assert is_positive(n) == expected

Quick Check

What does --cov-fail-under=90 do in a pytest run?

Recap

Use @pytest.mark.parametrize to test multiple inputs cleanly. Measure code coverage with pytest-cov, track branches with --cov-branch, and enforce minimums with --cov-fail-under.

Frequently asked questions

Is the “Parametrize and Test Coverage” lesson free?

Yes — the full text of “Parametrize and Test Coverage” is free to read here on the web, and the Python Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Python Academy course, upgrade to CoddyKit PRO.

What will I learn in “Parametrize and Test Coverage”?

Run tests with multiple inputs using @pytest.mark.parametrize. You practise Python Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Python Academy?

No prior experience is required. Python Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Parametrize and Test Coverage” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Python Academy lesson?

Yes. Every Python Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

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