How to Mock Return Value in pytest: Simple Guide

In pytest, you can mock a function's return value using unittest.mock.patch or unittest.mock.Mock. Use patch as a decorator or context manager to replace the target function and set its return_value to the desired output.

Syntax

Use unittest.mock.patch to replace a function or method during a test. Set the return_value attribute to specify what the mocked function should return.

• @patch('module.function'): Decorator to mock function in module.
• mock_function.return_value = value: Sets the return value of the mocked function.
• with patch('module.function') as mock_function:: Context manager alternative to decorator.

python

from unittest.mock import patch

@patch('module.function')
def test_example(mock_function):
    mock_function.return_value = 'mocked value'
    result = module.function()
    assert result == 'mocked value'

Example

This example shows how to mock the return value of a function get_data in a module data_source. The test replaces get_data to return a fixed value, allowing you to test code that depends on it without calling the real function.

python

from unittest.mock import patch
import pytest

# Imagine this is in data_source.py

def get_data():
    return 'real data'

# Function under test

def process_data():
    data = get_data()
    return data.upper()

# Test with mocked return value

@patch('__main__.get_data')
def test_process_data(mock_get_data):
    mock_get_data.return_value = 'mocked data'
    result = process_data()
    assert result == 'MOCKED DATA'

if __name__ == '__main__':
    pytest.main([__file__])

Output

============================= test session starts ==============================
collecting ... collected 1 item

test_mock_return_value.py::test_process_data PASSED                      [100%]

============================== 1 passed in 0.01s ===============================

Common Pitfalls

Common mistakes when mocking return values in pytest include:

• Mocking the wrong import path. Always patch where the function is used, not where it is defined.
• Forgetting to set return_value, so the mock returns MagicMock instead of the expected value.
• Not using patch as a decorator or context manager, causing the mock to not apply during the test.

python

from unittest.mock import patch

# Wrong patch location (patching the function's original module)
@patch('data_source.get_data')  # This may fail if process_data imports differently

def test_wrong_patch(mock_get_data):
    mock_get_data.return_value = 'mocked'
    result = process_data()
    assert result == 'MOCKED'  # This might fail

# Correct patch location (patch where process_data uses get_data)
@patch('__main__.get_data')
def test_correct_patch(mock_get_data):
    mock_get_data.return_value = 'mocked'
    result = process_data()
    assert result == 'MOCKED'

Quick Reference

Remember these tips when mocking return values in pytest:

• Use patch('target_path') where target_path is where the function is used.
• Set mock.return_value to control what the mock returns.
• Use patch as a decorator or context manager to apply the mock only during the test.
• Check your import paths carefully to avoid patching the wrong place.

Key Takeaways

Use unittest.mock.patch to replace functions and set their return_value in pytest tests.

Always patch the function where it is used, not where it is defined, to ensure the mock works.

Set mock.return_value explicitly to avoid unexpected MagicMock objects.

Use patch as a decorator or context manager to limit the mock's scope to the test.

Verify your mock paths and test outputs to catch common mocking mistakes early.