pytest-mock's MockerFixture is a powerful tool for mocking and patching during testing. But handling multiple exceptions gracefully can sometimes feel tricky. This guide demystifies the process, showing you how to effectively manage different exception scenarios within your tests using pytest and its mocker. We'll cover common approaches and best practices, ensuring your tests are robust and easy to understand.
What is pytest-mock and Why Use It?
pytest-mock is a pytest plugin that provides a MockerFixture which simplifies mocking and patching. This fixture gives you access to mocker.patch(), mocker.spy(), and other methods to control the behavior of external dependencies during your tests, isolating your code under test and improving test reliability. This is crucial for testing functions that rely on external services, databases, or other unpredictable elements.
Mocking and Patching with MockerFixture
Before diving into exception handling, let's briefly review how to use mocker for patching. Consider a function that might raise exceptions:
import requests
def fetch_data(url):
response = requests.get(url)
response.raise_for_status() # Raises HTTPError for bad responses
return response.json()
A simple test using mocker might look like this:
import pytest
import requests
from unittest.mock import MagicMock
def test_fetch_data_success(mocker):
mock_response = MagicMock()
mock_response.status_code = 200
mock_response.json.return_value = {"data": "success"}
mocker.patch('requests.get', return_value=mock_response)
data = fetch_data("http://example.com")
assert data == {"data": "success"}
Handling Multiple Exceptions: The side_effect Parameter
The most straightforward way to handle multiple exceptions with mocker.patch() is to use the side_effect parameter. This allows you to specify a sequence of return values or exceptions. Let's expand our example to handle potential requests.exceptions.HTTPError and requests.exceptions.RequestException:
import pytest
import requests
from requests.exceptions import HTTPError, RequestException
from unittest.mock import MagicMock
def test_fetch_data_multiple_exceptions(mocker):
mock_get = mocker.patch('requests.get')
# Simulate HTTPError
mock_response_error = MagicMock()
mock_response_error.raise_for_status.side_effect = HTTPError("Bad Request")
mock_get.side_effect = [mock_response_error, requests.get] # Second call succeeds
with pytest.raises(HTTPError):
fetch_data("http://example.com")
mock_response_success = MagicMock()
mock_response_success.status_code = 200
mock_response_success.json.return_value = {"data": "success"}
mock_get.side_effect = [mock_response_success] # Subsequent calls now succeed
data = fetch_data("http://example.com")
assert data == {"data": "success"}
#Simulate RequestException
mock_get.side_effect = RequestException("Network Error")
with pytest.raises(RequestException):
fetch_data("http://example.com")
This test showcases how to simulate both HTTPError and RequestException sequentially using side_effect. The pytest.raises context manager asserts that the specific exceptions are raised under the expected conditions.
Using a Custom Exception Handler Function
For more complex scenarios, consider using a custom function as the side_effect. This function can perform logic based on the input or the invocation count:
import pytest
import requests
from requests.exceptions import HTTPError, RequestException
from unittest.mock import MagicMock
def custom_exception_handler(url):
if "error1" in url:
raise HTTPError("Error from URL 1")
elif "error2" in url:
raise RequestException("Network error from URL 2")
else:
mock_response = MagicMock()
mock_response.status_code = 200
mock_response.json.return_value = {"data": "success"}
return mock_response
def test_fetch_data_custom_handler(mocker):
mocker.patch('requests.get', side_effect=custom_exception_handler)
with pytest.raises(HTTPError):
fetch_data("http://example.com/error1")
with pytest.raises(RequestException):
fetch_data("http://example.com/error2")
data = fetch_data("http://example.com")
assert data == {"data": "success"}
This approach enhances flexibility and readability for situations with intricate exception-handling logic.
Conclusion
Mastering exception handling with pytest-mock's MockerFixture is essential for creating comprehensive and reliable tests. Whether you utilize the side_effect parameter directly or leverage custom handler functions, these techniques ensure your tests accurately reflect the behavior of your code under various error conditions, resulting in more robust and maintainable codebases. Remember to choose the approach that best suits your specific needs and maintains code clarity.
