"""Dashboard stats — pure-helper and RQ Score client contract tests."""
import asyncio

import httpx

from app.engine import stats as S
from app.engine.stats import clients
from app.engine.normalize import _posted_date
from app.db.repo import _activity_score


def test_posted_date_per_board():
    assert _posted_date({"createdDate": "2026-06-18T10:37:17Z"}) == "2026-06-18T10:37:17Z"   # Naukri
    assert _posted_date({"postedDate": "2026-06-18T12:46:39Z"}) == "2026-06-18T12:46:39Z"     # LinkedIn
    assert _posted_date({"date_posted": "2026-06-17T17:38:14Z"}) == "2026-06-17T17:38:14Z"    # Foundit
    assert _posted_date({"jobDetails": {"createdDate": "2026-06-18T00:00:00Z"}}) is not None   # nested
    assert _posted_date({"nope": "x"}) is None


def test_match_scores_and_histogram():
    opps = [{"match": {"score": 84}}, {"matchScore": 72}, {"match": {"score": 0}}, {}]
    scores = S._match_scores(opps)
    assert sorted(scores) == [72, 84]                 # 0 and missing dropped
    h = S._histogram(scores)
    assert sum(h) == 2 and len(h) == 11


def test_scout_stats_accepts_numeric_applicant_strings(monkeypatch):
    feed = {"opportunities": [{"applicants": "10"}, {"applicants": 30}, {"applicants": "unknown"}]}
    activity = {
        "matches": 3, "viewed": 0, "saved": 0, "applied": 0, "tailored": 0,
        "searches": 1, "percentile": None, "cohort_size": 1,
    }
    monkeypatch.setattr(S._repo, "get_feed", lambda _user_id: asyncio.sleep(0, result=feed))
    monkeypatch.setattr(S._repo, "get_activity_stats", lambda _user_id: asyncio.sleep(0, result=activity))
    monkeypatch.setattr(S._repo, "get_active_window", lambda _user_id: asyncio.sleep(0, result={}))
    monkeypatch.setattr(S._repo, "get_salary_band", lambda _user_id: asyncio.sleep(0, result=None))
    monkeypatch.setattr(S._clients, "fetch_qx", lambda _user_uuid: asyncio.sleep(0, result=None))
    monkeypatch.setattr(S._clients, "fetch_qx_trend", lambda _user_uuid: asyncio.sleep(0, result=None))
    monkeypatch.setattr(S._clients, "fetch_streak", lambda _user_id: asyncio.sleep(0, result=None))

    result = asyncio.run(S.build_scout_stats("user-1"))

    assert result["avgApplicants"] == 20


def test_apply_window_freshness():
    # all None when no posting dates (honest — never fabricated)
    assert S._apply_window([{}, {"posted_date": None}])["urgency"] is None
    w = S._apply_window([{"posted_date": "2026-06-19T00:00:00Z"}, {"posted_date": "2026-06-15T00:00:00Z"}])
    assert w["dated"] == 2 and w["median_age_days"] is not None and w["urgency"] in ("high", "medium", "low")


def test_activity_score_weighting():
    # applies weighted highest, then saves, views, searches
    assert _activity_score(0, 0, 1, 0) > _activity_score(0, 1, 0, 0) > _activity_score(1, 0, 0, 0)
    assert _activity_score(0, 0, 0, 0) == 0


class _Response:
    status_code = 200

    def __init__(self, payload):
        self._payload = payload

    def raise_for_status(self):
        return None

    def json(self):
        return self._payload


def test_fetch_qx_reads_strict_rq_score_contract(monkeypatch):
    async def _get(_self, _url, **_kwargs):
        return _Response({"rq_score": 68.25, "quotients": {"technical": 71}})

    monkeypatch.setattr(httpx.AsyncClient, "get", _get)

    assert asyncio.run(clients.fetch_qx("user-uuid")) == {
        "qx": 68.2,
        "quotients": {"technical": 71},
    }


def test_fetch_qx_does_not_alias_legacy_q_score(monkeypatch):
    async def _get(_self, _url, **_kwargs):
        return _Response({"q_score": 99, "quotients": {"technical": 99}})

    monkeypatch.setattr(httpx.AsyncClient, "get", _get)

    assert asyncio.run(clients.fetch_qx("user-uuid")) is None


def test_fetch_qx_treats_malformed_payload_as_absent(monkeypatch):
    async def _get(_self, _url, **_kwargs):
        return _Response([{"rq_score": 88}])

    monkeypatch.setattr(httpx.AsyncClient, "get", _get)

    assert asyncio.run(clients.fetch_qx("user-uuid")) is None


def test_fetch_qx_trend_ignores_malformed_and_absent_points(monkeypatch):
    async def _get(_self, _url, **_kwargs):
        return _Response({"points": [None, {"rq_score": "bad"}, {"rq_score": 35}, {"rq_score": 40}]})

    monkeypatch.setattr(httpx.AsyncClient, "get", _get)

    assert asyncio.run(clients.fetch_qx_trend("user-uuid")) == [35.0, 40.0]


def test_fetch_qx_trend_reads_strict_rq_score_points(monkeypatch):
    async def _get(_self, _url, **_kwargs):
        return _Response({
            "points": [
                {"rq_score": 35, "q_score": 91},
                {"rq_score": 44.16, "q_score": 92},
                {"q_score": 93},
            ]
        })

    monkeypatch.setattr(httpx.AsyncClient, "get", _get)

    assert asyncio.run(clients.fetch_qx_trend("user-uuid")) == [35.0, 44.2]