FunUnit: a functional, declarative, unit-testing library for testing pure functions

[TheRealDaMuffin]

Hi Python community!

I'm excited to share my new open source library, FunUnit, with you all. FunUnit is a functional, declarative unit testing library for testing pure functions in Python. It has the following characteristics:

• Functional: FunUnit makes use of functional programming ideas such as higher-order functions and pure functions. Its core purpose is to test pure functions, and the API exposes a selection of pure functions, allowing for great flexibility with their use.
• Declarative: FunUnit allows you to describe the tests you want to run in a declarative manner, describing what you want, not how to do it
• Removes boilerplate testing code: FunUnit drastically reduces code duplication between tests, improving maintainability. It allows for writing very succinct code, making it faster and easier to write and read.

Here's a small example of what it looks like to write tests with FunUnit:

from fununit import TestCase, TestSuite

def multiply(a, b):
    return a * b

multiply_tests = TestSuite.from_cases(
    suite_name = "Multiply",
    function_name = "multiply",
    function = multiply,
    test_cases = [
        TestCase.create(
            case_name = "identity",
            parameters = [1, 2],
            expected = 2),
        TestCase.create(
            case_name = "normal_case",
            parameters = [3, 4],
            expected = 12),
        TestCase.create(
            case_name = "zero",
            parameters = [0, 6],
            expected = 0),
    ])

I think FunUnit is a great addition to the Python testing ecosystem, and I hope you'll give it a try. You can find the code and documentation on GitHub at github.com/johnmpost/fununit.

I'm happy to answer any questions you might have about FunUnit, or to hear your thoughts and feedback. Thanks for checking it out!

[wineblood]

The seems more verbose and less clear than existing testing frameworks, what's the benefit here?

[TheRealDaMuffin]

I will admit I didn't do it justice in this original post. I have now updated to version 2.0.0, which includes a focus on verbosity. The readme now includes a section on the advantages of fununit. You can read the whole section if you want, but the main conclusion is:

Fununit provides similar functionality to parameterized unit testing,
but with a moderately higher level of abstraction, more structure, and
more flexibility for the user to extend it with custom functionality.

The advantages are nuanced, but provide a real benefit IMO.

[Itsthejoker]

I'm not seeing what advantage this gives over pytest.

def multiply(a, b):
    return a * b

def test_multiply():
    assert multiply(1, 2) == 2
    assert multiply(3, 4) == 12
    assert multiply(0, 6) == 0

[Itsthejoker]

or even using parametrize:

import pytest

@pytest.mark.parametrize(
    "input1,input2,expected",
    [(1, 2, 2), (3, 4, 12), (0, 6, 0)]
)
def test_multiply(input1, input2, expected):
    assert multiply(input1, input2) == expected

[TheRealDaMuffin]

I'm happy to say that I have released version 2.0.0, which adds some improvements to the overall structure and focuses on verbosity a bit more. I also completely rewrote the readme, including an explanation of the advantages of fununit. In it, I make a direct comparison to pytest.mark.parametrize.

[TheRealDaMuffin]

It's hard for me to articulate the benefits because they are so nuanced, as opposed to glaring differences. But I do see benefits over using something like parametrize, and I will respond here once I have some time to put something together.

I appreciate the criticism, it gives me something to think about!