💻 Exercise: Exercise: Cosine similarity from scratch

📝 Instructions

Write cosine_similarity(a, b) returning the cosine of the angle between two vectors as a float: dot(a, b) / (norm(a) * norm(b)). If either vector has zero magnitude, return 0.0 to avoid dividing by zero. Implement it from scratch using only the standard library (the math module) -- no numpy. Standard library only.

🧪 Initial Code / Tests 1 Files

📄 evaluate.py

from unittest import TestCase
from exercise import cosine_similarity


class Evaluate(TestCase):
    def test_identical_vectors_are_one(self):
        self.assertAlmostEqual(cosine_similarity([1, 2, 3], [1, 2, 3]), 1.0)

    def test_orthogonal_vectors_are_zero(self):
        self.assertAlmostEqual(cosine_similarity([1, 0], [0, 1]), 0.0)

    def test_opposite_vectors_are_minus_one(self):
        self.assertAlmostEqual(cosine_similarity([1, 0], [-1, 0]), -1.0)

    def test_zero_vector_guard(self):
        self.assertEqual(cosine_similarity([0, 0], [1, 1]), 0.0)

✅ Solutions 1 Files

📄 exercise.py

import math


def cosine_similarity(a, b):
    dot = sum(x * y for x, y in zip(a, b))
    na = math.sqrt(sum(x * x for x in a))
    nb = math.sqrt(sum(y * y for y in b))
    denom = na * nb
    if denom == 0:
        return 0.0
    return dot / denom