How to Write a pytest Test Function with assert Equal in Python

Define simple pytest test functions that use assert to verify result equality and run them with pytest.main.

Easy Python 3.9+ Aug 9, 2026 Testing & modern typing 11 views 0 copies

pytest unit testing assert equality

Requires third-party packages — install first

pip install pytest

Python code

19 lines

Python 3.9+

import pytest

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

def test_add_positive_numbers():
    result = add(2, 3)
    assert result == 5

def test_add_negative_numbers():
    result = add(-2, -3)
    assert result == -5

def test_add_mixed_numbers():
    result = add(2, -3)
    assert result == -1

if __name__ == "__main__":
    pytest.main([__file__, "-v"])

Output

stdout

============================= test session starts ==============================
platform darwin -- Python 3.11.0, pytest-7.4.0, pluggy-1.3.0
rootdir: /path/to/your/test
collected 3 items

test_file.py ...                                                          [100%]

============================== 3 passed in 0.01s ===============================

How it works

Each test function is named with a test_ prefix so pytest discovers it automatically. Inside the test, you call the function under test and use the assert statement to compare the actual result to the expected value. If the assertion fails, pytest reports a detailed diff showing both the expected and actual values. Running pytest.main([__file__, "-v"]) lets you execute the tests directly from the script with verbose output.

Common mistakes

Forgetting the test_ prefix on function names, causing pytest to skip them
Using `assert result == expected` without any message; adding a helpful message improves debugging
Naming the test file without a `test_` prefix, so pytest doesn't collect it by default

Variations

Use `pytest.approx` for floating-point comparisons to avoid precision issues
Parameterize the test with `@pytest.mark.parametrize` to test multiple input sets without duplicating code

Real-world use cases

Verifying that a data transformation function returns the correct result for known inputs.
Ensuring that an API client correctly parses a response payload into expected fields.
Checking that a validation helper returns the expected error dictionary for invalid data.

How to Write a pytest Test Function with assert Equal in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Testing & modern typing

Tutorials

Quizzes

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

More from Testing & modern typing

Keep learning

Tutorials

Quizzes