thermograph/tests/api/test_payloads.py

"""The payload layer: pure builders, span clamping, and the layering guarantee
that offline callers (migrate) can use it without dragging in the web stack."""
import datetime
import os
import subprocess
import sys

import polars as pl
import pytest

from data import climate
from api import payloads

CELL = {"id": "1642_-4223", "center_lat": 47.6087, "center_lon": -122.29377}


def test_payloads_and_migrate_import_without_the_web_stack():
    """migrate.py must stay runnable offline: importing the payload layer may
    not construct the FastAPI app or start the places-index download."""
    code = ("import sys; from api import payloads; import migrate; "
            "assert 'fastapi' not in sys.modules, 'payloads/migrate pulled in FastAPI'; "
            "assert 'web.app' not in sys.modules, 'payloads/migrate imported the web app'; "
            "from data import places; assert places._load_started is False")
    backend = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
    subprocess.run([sys.executable, "-c", code], cwd=backend, check=True)


# ---- cache identity --------------------------------------------------------------
# These formats are shared by the endpoints, the /cell bundle and migrate; pin
# them so a change is always deliberate (an accidental drift silently strands
# every existing derived row — change them only alongside a PAYLOAD_VER bump).

def test_cache_identity_formats_are_pinned(history):
    t = datetime.date(2026, 6, 15)
    assert payloads.grade_key(t, 14, 7) == "2026-06-15:14:7"
    assert payloads.calendar_key(t, datetime.date(2026, 6, 20), 24) == "2026-06-15:2026-06-20:24"
    assert payloads.day_key(t) == "2026-06-15"
    assert payloads.forecast_key(t, 7) == "2026-06-15:7"
    assert payloads.history_token(history) == f"{payloads.PAYLOAD_VER}:{payloads.hist_end(history)}"


def test_recent_token_composes_history_and_stamp(history, monkeypatch):
    monkeypatch.setattr(climate, "recent_stamp", lambda cid: "stamp")
    assert payloads.recent_token(history, "1_2") == f"{payloads.history_token(history)}:stamp"


def test_day_token_expires_hourly_only_beyond_the_archive(history):
    last = history["date"].max()
    assert payloads.day_token(history, last) == payloads.history_token(history)
    future = payloads.day_token(history, last + datetime.timedelta(days=1))
    assert future.startswith(payloads.history_token(history) + ":h")


# ---- cal_span clamping ---------------------------------------------------------

def _hist(start, end):
    # cal_span only reads the record's min/max date, so two rows pin the span.
    return pl.DataFrame({"date": [datetime.date.fromisoformat(start),
                                  datetime.date.fromisoformat(end)]})


def test_cal_span_defaults_to_months_back_same_day_of_month():
    start_ts, end_ts = payloads.cal_span(_hist("2020-01-01", "2026-06-29"), None, None, 24)
    assert end_ts == datetime.date(2026, 6, 29)
    assert start_ts == datetime.date(2024, 6, 29)


def test_cal_span_clamps_to_the_record():
    h = _hist("2025-03-01", "2026-06-29")           # record shorter than the 2-year cap
    start_ts, end_ts = payloads.cal_span(h, "2020-01-01", None, 24)
    assert start_ts == datetime.date(2025, 3, 1)    # can't start before the record
    _, end_ts = payloads.cal_span(h, None, "2030-01-01", 24)
    assert end_ts == datetime.date(2026, 6, 29)     # nor end past it


def test_cal_span_caps_at_two_years():
    start_ts, end_ts = payloads.cal_span(_hist("2018-01-01", "2026-06-29"),
                                      "2018-01-01", "2026-06-29", 24)
    assert (end_ts - start_ts).days == payloads.CAL_MAX_SPAN_DAYS - 1


def test_cal_span_never_inverts():
    start_ts, end_ts = payloads.cal_span(_hist("2020-01-01", "2026-06-29"),
                                      "2026-06-01", "2021-01-01", 24)
    assert start_ts == end_ts


def test_months_before_clamps_month_end_and_leap():
    """Calendar-aware month subtraction (replaces pandas DateOffset): land on the
    same day-of-month, clamped to the target month's last valid day."""
    assert payloads._months_before(datetime.date(2026, 3, 31), 1) == datetime.date(2026, 2, 28)
    assert payloads._months_before(datetime.date(2024, 3, 31), 1) == datetime.date(2024, 2, 29)
    assert payloads._months_before(datetime.date(2026, 1, 15), 14) == datetime.date(2024, 11, 15)


def test_attach_dry_streaks_prefers_the_fresher_source_on_shared_dates():
    """De-dup keeps the recent/forecast row over the archive one for a shared date
    (concat archive-first, keep='last') — the fresher precip drives the streak."""
    d = datetime.date(2026, 1, 1)
    hist = pl.DataFrame({"date": [d], "precip": [1.0]})   # archive: it rained (streak resets)
    rec = pl.DataFrame({"date": [d], "precip": [0.0]})    # fresher: dry (streak counts)
    graded = [{"date": d.isoformat()}]
    payloads._attach_dry_streaks(graded, hist, rec)          # archive first, recent last
    assert graded[0]["dsr"] == 1                          # recent (dry) won


# ---- builders -------------------------------------------------------------------

def test_build_grade_window_and_shape(history, recent):
    target = datetime.date.today()
    payload = payloads.build_grade(CELL, target, 14, history, recent,
                                {"cached": True}, "Testville")
    assert payload["target_date"] == target.isoformat()
    days = [d["date"] for d in payload["recent"]]
    assert days == sorted(days, reverse=True)          # newest first
    assert payload["climatology"]["tmax"] is not None
    assert all(d["dsr"] is not None for d in payload["recent"])


def test_build_day_pulls_future_obs_from_recent(history, recent):
    today = datetime.date.today()
    payload = payloads.build_day(CELL, history, today, "Testville", recent=recent)
    assert payload["detail"]["date"] == today.isoformat()
    assert payload["detail"]["metrics"]["tmax"]["obs"] is not None


def test_build_day_survives_recent_fetch_failure(history, monkeypatch):
    def boom(cell):
        raise RuntimeError("upstream down")
    monkeypatch.setattr(climate, "get_recent_forecast", boom)
    today = datetime.date.today()
    payload = payloads.build_day(CELL, history, today, "Testville")
    assert payload["detail"]["metrics"]["tmax"]["obs"] is None      # climatology only
    assert payload["detail"]["metrics"]["tmax"]["ladder"] is not None


def test_build_forecast_only_future_days(history, recent):
    today = datetime.date.today()
    payload = payloads.build_forecast(CELL, 7, history, recent, today, None)
    days = [d["date"] for d in payload["recent"]]
    assert days == sorted(days, reverse=True)          # furthest-out first
    assert min(days) > today.isoformat()
    assert payload["forecast"] is True


# ---- build_score ---------------------------------------------------------------

def _full_history(years=45, seed=5):
    """A 45-year all-metric record — enough span for the climate score (the shared
    20-year `history` fixture is intentionally below MIN_BASELINE_YEARS)."""
    import numpy as np
    end = datetime.date(2026, 7, 11)
    start = datetime.date(end.year - years, end.month, end.day)
    dates = [start + datetime.timedelta(days=i) for i in range((end - start).days + 1)]
    n = len(dates)
    rng = np.random.default_rng(seed)
    doy = np.array([d.timetuple().tm_yday for d in dates])
    tmax = 55 + 30 * np.sin((doy - 100) / 366.0 * 2 * np.pi) + rng.normal(0, 8, n)
    return pl.DataFrame({
        "date": dates, "tmax": np.round(tmax, 1), "tmin": np.round(tmax - 15, 1),
        "feels": np.round(tmax + 1, 1), "humid": np.round(np.clip(12 + rng.normal(0, 3, n), 1, None), 1),
        "wetbulb": np.round(tmax - 12, 1), "wind": np.round(np.clip(8 + rng.normal(0, 3, n), 0, None), 1),
        "gust": np.round(np.clip(16 + rng.normal(0, 5, n), 0, None), 1),
        "precip": np.where(rng.random(n) < 0.3, 0.2, 0.0),
    }).with_columns(pl.col("date").dt.ordinal_day().cast(pl.Int16).alias("doy"))


def test_build_score_shape():
    hist = _full_history()
    payload = payloads.build_score(CELL, hist, "Testville")
    assert payload["api_version"] == "v2"
    assert payload["cell"] == CELL and payload["place"] == "Testville"
    assert payload["latest"] == payloads.hist_end(hist)
    s = payload["scores"]
    assert set(s["slices"]) == {"annual", "djf", "mam", "jja", "son"}
    ann = s["slices"]["annual"]
    assert ann["overall"]["score"] is not None
    assert ann["metrics"]["tmax"]["score"] is not None
    assert ann["metrics"]["wetbulb"]["score"] is not None   # derived metric flows through


def test_score_key_is_the_version():
    assert payloads.score_key() == payloads.SCORE_VER
    # Score payloads are history-only, so they ride the plain history token.
    hist = _full_history()
    assert payloads.history_token(hist) == f"{payloads.PAYLOAD_VER}:{payloads.hist_end(hist)}"