and if you need to have access to the actual exception info you may use: def test_recursion_depth(): with pytest.raises(RuntimeError) as excinfo: def f(): f() f() assert "maximum recursion" in str(excinfo.value)

July 24, 2023 - from contextlib import nullcontext as does_not_raise import pytest from operations import divide @pytest.mark.parametrize( "num_1, num_2, expected_result, exception, message", [ (30, 2.5, 12.0, does_not_raise(), None), (10.5, 0, None, pytest.raises(ZeroDivisionError), "float division by zero"), ("a", 10.5, None, pytest.raises(TypeError), "at least one of the inputs is not a number: a, 10.5") ], ids=["valid inputs", "divide by zero", "not a number input"] ) def test_division(num_1, num_2, expected_result, exception, message): with exception as e: result = divide(num_1, num_2) assert message is None or message in str(e) if expected_result is not None: assert result == expected_result

March 23, 2026 - But, with more exception handling comes challenges in testing. How do you handle unpredictability in code execution and flow? What about error propagation to the rest of the stack? Do you raise errors or handle them? And how do you ensure to display the correct and helpful type of error? This is very important, particularly when dealing with User facing tooling like APIs and response codes. Pytest assert exception handling can help with this.

Test that an exception is raised when callable is called with any positional or keyword arguments that are also passed to assertRaises(). The test passes if exception is raised, is an error if another exception is raised, or fails if no exception ...

In Python’s unittest framework, the assertRaises TestCase method is used to test that a specific exception is raised.

July 15, 2025 - Just pass the exception, the callable function and the parameters of the callable function as keyword arguments that will elicit the exception. ... assertRaises(exception) Make a function call that should raise the exception with a context.

In order to write assertions about raised exceptions, you can use pytest.raises() as a context manager like this:

November 14, 2020 - The try and except blocks are used to handle exceptions. The assert is used to ensure the conditions are compatible with the requirements of a function.

March 9, 2025 - There are two helpers in unittest.TestCase for asserting that exceptions are raised and properties of them: assertRaises checks that an exception is raised and asserts its type assertRaisesRegex checks that an exception is raised and matches its type and str I generally try to assert something about the message just to make sure the test doesn’t accidentally pass by raising the same exception in a different way, so I almost always use assertRaisesRegex.

Saying that, it’s easy to see why people get confused because assert itself raises an exception called AssertionError which does little to resolve the confusion between the two modes of control flow.

June 26, 2026 - Explanation: The failed assertion raises an exception, which is caught by except AssertionError as e, allowing the program to continue gracefully.

Assertions can be caught and handled like any other exception using a try-except block.

and if you need to have access to the actual exception info you may use: def test_recursion_depth(): with pytest.raises(RuntimeError) as excinfo: def f(): f() f() assert "maximum recursion" in str(excinfo.value)

The AssertionError exception occurs when an assert statement fails.

AssertionError is a built-in exception that occurs when an assert statement fails. The assert statement checks that a condition is truthy. If the condition is falsy, then Python raises an AssertionError.

To catch any of a group of exceptions, a tuple containing the exception classes may be passed as exception. In the example below, a test function is defined to check whether ZeroDivisionError is raised. import unittest def div(a,b): return a/b class raiseTest(unittest.TestCase): def testraise(self): self.assertRaises(ZeroDivisionError, div, 1,0) if __name__ == '__main__': unittest.main()

November 16, 2016 - import unittest def func(): raise Exception('lets see if this works') class ExampleTest(unittest.TestCase): def test_error(self): self.assertRaises(Exception, lambda:func()) if __name__=='__main__': unittest.main() But lambda is a whole new monster on its own. It doesn't seem to be the right tool to use just as a wrapper for the function. This is a much more appropriate and pythonic way of using assertRaises.

This repo contains the sample code for the article - How To Test Python Exception Handling Using Pytest Assert (A Simple Guide)

October 11, 2022 - In the same way we can use pytest in order to assert that a function raises an exception.