"""The honest rubric — the displayed score is COMPUTED from dimension ratings, never model-emitted."""
import pytest

from app.engine import rubric as R


def test_weights_sum_to_one():
    assert abs(sum(R.WEIGHTS.values()) - 1.0) < 1e-9


def test_perfect_match_scores_high_90s():
    # all dimensions genuinely aligned → the overall lands in the high 90s (earned, not prompted)
    perfect = {k: 100 for k in R.KEYS}
    assert R.aggregate(perfect) == 100
    strong = {"role": 100, "skills": 92, "seniority": 95, "location": 100, "industry": 95, "experience": 90}
    assert R.aggregate(strong) >= 94      # a real strong match reaches the 90s


def test_partial_match_scores_mid():
    partial = {"role": 75, "skills": 50, "seniority": 70, "location": 60, "industry": 65, "experience": 60}
    s = R.aggregate(partial)
    assert 55 <= s <= 72                   # honestly a partial, not inflated


def test_weak_role_drags_score_down():
    # role is 25% — a wrong-function job can't score high no matter how good the rest is
    weak = {"role": 15, "skills": 90, "seniority": 90, "location": 100, "industry": 90, "experience": 90}
    assert R.aggregate(weak) < 80


def test_absent_dimension_redistributes_not_zeroes():
    # industry absent (no preference) must NOT act as a 0 that tanks the score — weight redistributes
    no_ind = {"role": 100, "skills": 100, "seniority": 100, "location": 100, "experience": 100}
    assert R.aggregate(no_ind) == 100      # not dragged down by the missing 10% industry weight


def test_empty_is_zero_not_crash():
    assert R.aggregate({}) == 0


def test_scores_are_clamped():
    assert R.aggregate({k: 150 for k in R.KEYS}) == 100
    assert R.aggregate({k: -20 for k in R.KEYS}) == 0


def test_level_bands():
    assert R.level_for(90) == "Strong" and R.level_for(60) == "Solid" and R.level_for(40) == "Light"


def test_prompt_block_lists_every_dimension():
    block = R.prompt_block()
    for k in R.KEYS:
        assert f'"{k}"' in block           # every rubric key is shown to the curator


def test_calibration_is_monotonic_floor_anchored_and_lifts_top():
    # the transparent "little bias": strictly increasing, floor fixed, top expanded into the 90s
    assert R.calibrate(50) == 50                     # floor unchanged — weak stays weak
    assert R.calibrate(49) == 49 and R.calibrate(20) == 20   # below floor untouched
    assert R.calibrate(100) == 100                   # ceiling fixed
    assert R.calibrate(90) >= 93                     # genuinely-strong → presents in the 90s
    assert R.calibrate(60) <= 65                     # a weak match is NOT lifted into the strong zone
    # strictly monotonic across the range (ordering never lies)
    vals = [R.calibrate(x) for x in range(50, 101, 5)]
    assert all(b > a for a, b in zip(vals, vals[1:]))