Files
cloudy-profile-matching/test_profile_matching.py
T
2026-07-19 20:25:08 +02:00

69 lines
2.2 KiB
Python

"""Tests for the public profile-matching code sample."""
from __future__ import annotations
import unittest
from profile_matching import (
INTEREST_WEIGHT,
LOCATION_WEIGHT,
PROJECT_TAG_WEIGHT,
SKILL_WEIGHT,
haversine_distance_km,
jaccard_similarity,
location_similarity,
recommendation_score,
weighted_jaccard_similarity,
)
class ProfileMatchingTests(unittest.TestCase):
def test_component_weights_add_up_to_one(self) -> None:
self.assertAlmostEqual(
SKILL_WEIGHT + INTEREST_WEIGHT + LOCATION_WEIGHT + PROJECT_TAG_WEIGHT,
1.0,
)
def test_similarity_normalises_case_whitespace_and_duplicates(self) -> None:
self.assertEqual(
jaccard_similarity([" Python ", "python", ""], ["PYTHON"]), 1.0
)
def test_empty_profiles_do_not_create_a_match(self) -> None:
self.assertEqual(jaccard_similarity([], []), 0.0)
self.assertEqual(location_similarity(None, (51.34, 12.37)), 0.0)
def test_unweighted_mode_is_backwards_compatible(self) -> None:
left, right = ["Python", "Rust"], ["Rust", "TypeScript"]
self.assertAlmostEqual(
weighted_jaccard_similarity(left, right),
jaccard_similarity(left, right),
)
def test_shared_high_affinity_interest_increases_match_score(self) -> None:
neutral = weighted_jaccard_similarity(
["Hiking", "Opera"], ["Opera", "Cooking"]
)
personalised = weighted_jaccard_similarity(
["Hiking", "Opera"], ["Opera", "Cooking"], {"opera": 3.0}
)
self.assertGreater(personalised, neutral)
def test_distance_is_symmetric_and_decays_to_zero(self) -> None:
leipzig = (51.3397, 12.3731)
berlin = (52.52, 13.405)
self.assertAlmostEqual(
haversine_distance_km(*leipzig, *berlin),
haversine_distance_km(*berlin, *leipzig),
)
self.assertEqual(location_similarity(leipzig, berlin), 0.0)
def test_final_score_is_explainable_weighted_sum(self) -> None:
self.assertAlmostEqual(
recommendation_score(0.5, 0.5, 1.0, 0.0),
0.475,
)
if __name__ == "__main__":
unittest.main()