"""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()