"""Live smoke test — hits the real BLS API.

Opt-in only: deselected by default (see addopts in pyproject.toml). Run with:
    pytest -m live
Requires network and a BLS API key (BLS_API_KEY env var, or config.py).

Guards against silent series-ID drift: BLS occasionally retires codes (e.g. the
2010->2018 SOC change), which unit tests alone can't catch.
"""
import os

import pytest

from bls_client import BLSClient
from bls_client.queries import employment as E, prices as P, wages as W, productivity as PR


def _api_key():
    key = os.environ.get("BLS_API_KEY")
    if key:
        return key
    try:
        from config import BLS_API_KEY  # local, gitignored
        if BLS_API_KEY and BLS_API_KEY != "YOUR_KEY_HERE":
            return BLS_API_KEY
    except Exception:
        pass
    return None


pytestmark = pytest.mark.live


@pytest.fixture(scope="module")
def client():
    key = _api_key()
    if not key:
        pytest.skip("no BLS_API_KEY available")
    return BLSClient(key)


# One representative, previously-broken helper per repaired survey.
REPAIRED = {
    "JOLTS":        E.jolts_dashboard(),                       # dict of 5
    "OES wage":     W.occupation_annual_median_wage("151252"),
    "OES employ":   W.all_occupations_employment(),
    "ECI":          W.eci_total_compensation(),
    "Productivity": PR.business_output_per_hour(),
    "QCEW":         E.qcew_national_private(),
    "PPI final":    P.ppi_final_demand(),
    "ECEC health":  W.ecec_health_insurance(),
    "ECEC retire":  W.ecec_retirement(),
}


def _flatten(v):
    return list(v.values()) if isinstance(v, dict) else [v]


def test_repaired_surveys_return_data(client):
    """Every repaired survey must return at least one real observation."""
    all_ids = []
    for ids in REPAIRED.values():
        all_ids.extend(_flatten(ids))
    res = client.fetch(all_ids, 2024, 2025)
    missing = [sid for sid in all_ids if not res.get(sid, {}).get("data")]
    assert not missing, f"no data returned for: {missing}"


def test_headline_payrolls_plausible(client):
    res = client.fetch_latest(E.nonfarm_payrolls(), years=1)
    obs = client.latest_obs(next(iter(res.values())))
    assert obs is not None
    # US nonfarm payrolls are ~150,000 (thousands); sanity bound, not exact.
    assert 100_000 < float(obs["value"]) < 200_000