Task07_Unit_Testing_Python.md

Task 07 – Unit Testing (Python, unittest)

We are going to show how to write and run unit tests for a simple DAXPY operation (y := a*x + y) using Python's built‑in unittest.

What is Unit Testing?

Unit tests are small, focused tests that verify one function or behavior at a time. They help catch bugs early and document expected behavior.

Code Under Test: daxpy.py

import numpy as np

def daxpy(a, x, y):
    x = np.asarray(x, dtype=float)
    y = np.asarray(y, dtype=float)
    if x.shape != y.shape:
        raise ValueError("x and y must have the same shape")
    return a * x + y

Unit Tests: test_daxpy.py

import unittest
import numpy as np
from daxpy import daxpy

class TestDaxpy(unittest.TestCase):

    def test_basic(self):
        a = 2.0
        x = np.array([1., 2., 3.])
        y = np.array([4., 5., 6.])
        result = daxpy(a, x, y)
        np.testing.assert_array_equal(result, np.array([6., 9., 12.]))

    def test_zero_scalar(self):
        result = daxpy(0.0, [1,2,3], [7,8,9])
        np.testing.assert_array_equal(result, np.array([7., 8., 9.]))

    def test_zero_vector(self):
        result = daxpy(3.5, [0,0,0], [1,2,3])
        np.testing.assert_array_equal(result, np.array([1., 2., 3.]))

    def test_shape_mismatch_raises(self):
        with self.assertRaises(ValueError):
            daxpy(2.0, [1,2,3], [4,5])

    def test_large_values(self):
        a = 1e6
        x = np.array([1., 2., 3.])
        y = np.array([1., 1., 1.])
        expected = np.array([1e6+1, 2e6+1, 3e6+1])
        np.testing.assert_array_almost_equal(daxpy(a, x, y), expected)

if __name__ == "__main__":
    unittest.main()

Tests included:

• test_basic — normal case → exact result [6, 9, 12].
• test_zero_scalar — a=0 → returns y.
• test_zero_vector — x all zeros → returns y.
• test_shape_mismatch_raises — different lengths for x,y → raises ValueError.
• test_large_values — big numbers → almost-equal check for FP rounding.

How to Run

From the project folder:

python -m unittest -v

or directly:

python test_daxpy.py

Output

The following output was produced by running the command above in this environment showing all tests are ok

test_basic (test_daxpy.TestDaxpy.test_basic) ... ok
test_large_values (test_daxpy.TestDaxpy.test_large_values) ... ok
test_shape_mismatch_raises (test_daxpy.TestDaxpy.test_shape_mismatch_raises) ... ok
test_zero_scalar (test_daxpy.TestDaxpy.test_zero_scalar) ... ok
test_zero_vector (test_daxpy.TestDaxpy.test_zero_vector) ... ok

----------------------------------------------------------------------
Ran 5 tests in 0.008s

OK