"""Phase 1 — the floor-free + coverage-aware invariants (the v1-collapse guardrails).

This is the test that would have caught the old engine: every factor is float-or-`None`
(no constant floors), and a sparse profile must NOT collapse all jobs to one neutral score.
"""
from app.engine import rank as R

_JOBS = [
    {"title": "Product Manager", "seniority_level": "senior", "location_city": "New Delhi",
     "location_country": "India", "salary_lpa": 30,
     "details": {"skills": ["Product Management", "SQL"], "industry": "Fintech",
                 "description": "product manager roadmap stakeholders"}},
    {"title": "Sales Lead", "seniority_level": "lead", "location_city": "Mumbai",
     "location_country": "India", "salary_lpa": None,
     "details": {"skills": ["Sales", "CRM"], "industry": "SaaS", "description": "sales quota targets"}},
    {"title": "Product Manager", "seniority_level": "mid", "location_mode": "remote",
     "location_city": "Remote", "details": {"skills": ["Product Management"], "description": "product manager"}},
    {"title": "Designer", "seniority_level": None, "location_city": None, "salary_lpa": None, "details": {}},
]


def test_every_factor_returns_float_or_none():
    p_full = R.profile_from({"title": "Product Manager", "location": ["New Delhi · India"],
                             "industry": ["Fintech"], "experience": ["Senior"], "years": 9,
                             "role": ["Product"], "targetComp": "₹25–30L"})
    p_sparse = R.profile_from({"title": "Product Manager"})
    for p in (p_full, p_sparse):
        for job in _JOBS:
            for name, fn in R.FACTORS.items():
                v = fn(p, job)
                assert v is None or (isinstance(v, float) and 0.0 <= v <= 1.0), f"{name} → {v!r}"


def test_sparse_profile_does_not_collapse():
    # The v1 bug: sparse profile → everyone ~60. Assert real score variance across varied jobs.
    p = R.profile_from({"title": "Product Manager", "location": ["New Delhi · India"]})
    us = [u for u in (R.utility(p, j)[0] for j in _JOBS) if u is not None]
    assert len(us) >= 2 and (max(us) - min(us)) > 0.1, f"collapsed to a flat band: {us}"


def test_absent_factor_redistributes_weight_not_floors():
    # A job missing salary/industry/skills must still score on what IS present (no 60 injected).
    p = R.profile_from({"title": "Product Manager", "location": ["New Delhi · India"]})
    bare = {"title": "Product Manager", "location_city": "New Delhi", "location_country": "India",
            "details": {"description": "product manager"}}
    U, factors = R.utility(p, bare)
    assert U is not None
    assert factors["salary"] is None and factors["skill"] is None     # absent
    assert factors["location"] == 1.0                                 # present, real