281 lines
12 KiB
Python
281 lines
12 KiB
Python
"""Route-level tests over the FastAPI app with the weather/geocode layer faked —
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they exercise the real routing, validation, derived-store and ETag plumbing, and
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would catch wiring regressions (e.g. a handler calling a deleted helper)."""
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import pytest
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from fastapi.testclient import TestClient
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from web import app as appmod
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from data import climate
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@pytest.fixture
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def client(monkeypatch, history, recent):
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monkeypatch.setattr(climate, "get_history",
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lambda cell: (history.clone(), {"cached": True, "cache_age_days": 3}))
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monkeypatch.setattr(climate, "get_recent_forecast", lambda cell: recent.clone())
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monkeypatch.setattr(climate, "load_cached_history", lambda cell: history.clone())
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monkeypatch.setattr(climate, "recent_stamp", lambda cell_id: "rs-test")
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monkeypatch.setattr(climate, "reverse_geocode", lambda lat, lon: "Testville, Washington")
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return TestClient(appmod.app)
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Q = {"lat": 47.6062, "lon": -122.3321}
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def test_place_serves_any_point_worldwide(client):
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for q in (Q, {"lat": 48.8566, "lon": 2.3522}, {"lat": -33.8688, "lon": 151.2093}):
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r = client.get("/thermograph/api/v2/place", params=q)
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assert r.status_code == 200
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assert r.json()["place"] == "Testville, Washington"
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assert set(r.json()["cell"]) == {"center_lat", "center_lon"}
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def test_grade_shape_and_conditional_revalidation(client, history):
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r = client.get("/thermograph/api/v2/grade", params=Q)
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assert r.status_code == 200
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body = r.json()
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assert body["place"] == "Testville, Washington"
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assert body["climatology"]["tmax"] is not None
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days = [d["date"] for d in body["recent"]]
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assert days == sorted(days, reverse=True) # newest first
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assert body["recent"][0]["tmax"]["grade"]
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etag = r.headers["etag"]
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r304 = client.get("/thermograph/api/v2/grade", params=Q,
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headers={"If-None-Match": etag})
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assert r304.status_code == 304 and r304.headers["etag"] == etag
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# Without the validator the derived store replays the exact same bytes.
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r2 = client.get("/thermograph/api/v2/grade", params=Q)
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assert r2.status_code == 200 and r2.content == r.content
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def test_grade_is_aliased_across_api_versions(client):
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for prefix in ("api", "api/v1", "api/v2"):
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assert client.get(f"/thermograph/{prefix}/grade", params=Q).status_code == 200
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def test_query_validation_rejects_out_of_range(client):
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assert client.get("/thermograph/api/v2/grade",
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params={"lat": 999, "lon": 0}).status_code == 422
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assert client.get("/thermograph/api/v2/grade",
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params={**Q, "days": 0}).status_code == 422
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def test_api_version_reports_backend_contract(client):
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r = client.get("/thermograph/api/version")
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assert r.status_code == 200
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body = r.json()
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assert {"backend_version", "min_frontend", "payload_ver"} <= body.keys()
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assert body["backend_version"] == "2"
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def test_day_detail_and_ladders(client, history):
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r = client.get("/thermograph/api/v2/day", params=Q)
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assert r.status_code == 200
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body = r.json()
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assert body["latest"] == history["date"].max().isoformat()
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tmax = body["detail"]["metrics"]["tmax"]
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assert tmax["ladder"]["tiers"][0]["c"] == "rec-hot"
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assert tmax["obs"]["grade"]
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@pytest.mark.parametrize("path", ["grade", "calendar", "day", "forecast", "cell"])
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def test_every_data_route_maps_rate_limit_to_503(client, monkeypatch, path):
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def rate_limited(cell):
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raise climate.WeatherUnavailable(climate.limit_message(False))
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monkeypatch.setattr(climate, "get_history", rate_limited)
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# A distinct spot per route: a store row cached by an earlier test would
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# otherwise be checked only after the (failing) history fetch anyway.
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r = client.get(f"/thermograph/api/v2/{path}", params={"lat": 51.5, "lon": -0.1})
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assert r.status_code == 503
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assert "rate-limited" in r.json()["detail"]
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def test_upstream_failure_classification(client, monkeypatch):
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q = {"lat": 52.52, "lon": 13.4}
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def daily_quota(cell):
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raise climate.WeatherUnavailable(climate.limit_message(True), daily=True)
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monkeypatch.setattr(climate, "get_history", daily_quota)
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r = client.get("/thermograph/api/v2/grade", params=q)
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assert r.status_code == 503 and "tomorrow" in r.json()["detail"]
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# A raw upstream 429 that no fetcher classified still maps to a clean 503.
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def raw_429(cell):
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e = RuntimeError("upstream said no")
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e.response = type("R", (), {"status_code": 429})()
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raise e
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monkeypatch.setattr(climate, "get_history", raw_429)
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r = client.get("/thermograph/api/v2/grade", params=q)
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assert r.status_code == 503 and "rate-limited" in r.json()["detail"]
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# Anything else is a genuine upstream fault: 502 with the raw error.
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def boom(cell):
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raise RuntimeError("parquet cache corrupted")
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monkeypatch.setattr(climate, "get_history", boom)
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r = client.get("/thermograph/api/v2/grade", params=q)
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assert r.status_code == 502 and "parquet cache corrupted" in r.json()["detail"]
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def test_cell_prefetch_never_fetches_upstream(client, monkeypatch):
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def boom(cell):
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raise AssertionError("prefetch=1 must never fetch weather upstream")
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monkeypatch.setattr(climate, "get_history", boom)
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monkeypatch.setattr(climate, "get_recent_forecast", boom)
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monkeypatch.setattr(climate, "load_cached_history", lambda cell: None)
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r = client.get("/thermograph/api/v2/cell", params={**Q, "prefetch": 1})
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assert r.status_code == 204 # cold cell: no body, no quota spent
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def test_cell_prefetch_builds_history_slices_only(client):
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r = client.get("/thermograph/api/v2/cell", params={"lat": 10.0, "lon": 10.0, "prefetch": 1})
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assert r.status_code == 200
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assert set(r.json()["slices"]) == {"calendar", "day"}
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def test_calendar_placeless_payload_is_not_persisted(client, monkeypatch):
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q = {"lat": -10.0, "lon": 20.0, "months": 2}
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monkeypatch.setattr(climate, "reverse_geocode", lambda lat, lon: None)
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r = client.get("/thermograph/api/v2/calendar", params=q)
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assert r.status_code == 200 and r.json()["place"] is None
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# The placeless payload wasn't cached, so the next request retries the
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# label instead of replaying bare coordinates for the life of the token.
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monkeypatch.setattr(climate, "reverse_geocode", lambda lat, lon: "Resolved, Now")
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assert client.get("/thermograph/api/v2/calendar", params=q).json()["place"] == "Resolved, Now"
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def test_calendar_compact_range(client, history):
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r = client.get("/thermograph/api/v2/calendar", params={**Q, "months": 2})
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assert r.status_code == 200
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body = r.json()
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assert body["range"]["end"] == history["date"].max().isoformat()
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day = body["days"][0]
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assert {"date", "dsr", "tmax", "tmin", "precip"} <= set(day)
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assert set(day["tmax"]) == {"v", "pct", "c", "g"}
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def test_forecast_grades_future_days(client):
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r = client.get("/thermograph/api/v2/forecast", params=Q)
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assert r.status_code == 200
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body = r.json()
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assert body["forecast"] is True
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days = [d["date"] for d in body["recent"]]
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assert days and days == sorted(days, reverse=True) # furthest-out first
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assert min(days) > body["target_date"] # strictly future
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def test_cell_bundle_matches_per_view_payloads(client):
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r = client.get("/thermograph/api/v2/cell", params=Q)
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assert r.status_code == 200
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slices = r.json()["slices"]
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assert set(slices) == {"calendar", "grade", "forecast", "day"}
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for s in slices.values():
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assert s["etag"] and s["data"]
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# The grade slice must be byte-for-byte what /grade serves (same store row).
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grade = client.get("/thermograph/api/v2/grade", params=Q)
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assert grade.json() == slices["grade"]["data"]
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assert grade.headers["etag"] == slices["grade"]["etag"]
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r304 = client.get("/thermograph/api/v2/cell", params=Q,
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headers={"If-None-Match": r.headers["etag"]})
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assert r304.status_code == 304
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def test_suggest_falls_back_to_upstream_geocoder(client, monkeypatch):
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upstream = [{"name": "Seattle", "admin1": "Washington", "country": "United States",
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"country_code": "US", "lat": 47.6, "lon": -122.33, "population": 737015}]
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monkeypatch.setattr(climate, "geocode", lambda q, count=5: list(upstream))
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r = client.get("/thermograph/api/v2/suggest", params={"q": "seattle-fallback-probe"})
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assert r.status_code == 200
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body = r.json()
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assert body["results"][0]["name"] == "Seattle"
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assert body["corrected"] is None
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def test_cell_neighbors_flag_enqueues_warming(client, monkeypatch):
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from web import app as appmod
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monkeypatch.setattr(appmod, "_WARM_SEEN", {})
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# No lifespan in TestClient without a context manager, so no worker drains
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# the queue — enqueued cells just accumulate for inspection.
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monkeypatch.setattr(appmod, "_warm_queue", __import__("queue").Queue())
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r = client.get("/thermograph/api/v2/cell", params={"lat": 35.0, "lon": 25.0, "neighbors": 1})
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assert r.status_code == 200
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assert appmod._warm_queue.qsize() == 8
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assert len(appmod._WARM_SEEN) == 8
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# Same spot again within the TTL: nothing new enqueued.
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client.get("/thermograph/api/v2/cell", params={"lat": 35.0, "lon": 25.0, "neighbors": 1},
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headers={"If-None-Match": r.headers["etag"]})
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assert appmod._warm_queue.qsize() == 8
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def test_warm_cell_materializes_history_slices(client, tmp_store, monkeypatch, history):
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from web import app as appmod
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from data import grid
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from api import payloads
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cell = grid.snap(-33.87, 151.21)
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appmod._warm_cell(cell)
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token = payloads.history_token(history)
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start_ts, end_ts = payloads.cal_span(history, None, None, 24)
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assert tmp_store.get_payload("calendar", cell["id"],
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payloads.calendar_key(start_ts, end_ts, 24), token) is not None
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last = history["date"].max()
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assert tmp_store.get_payload("day", cell["id"], payloads.day_key(last), token) is not None
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def test_warm_cell_never_fetches_upstream(client, monkeypatch):
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from web import app as appmod
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def boom(cell):
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raise AssertionError("warming must never fetch weather upstream")
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monkeypatch.setattr(climate, "get_history", boom)
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monkeypatch.setattr(climate, "get_recent_forecast", boom)
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monkeypatch.setattr(climate, "load_cached_history", lambda cell: None)
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appmod._warm_cell({"id": "1_1", "center_lat": 0.03, "center_lon": 0.03}) # cold: no-op
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def _score_history(years=45, seed=5):
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import datetime
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import numpy as np
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import polars as pl
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end = datetime.date(2026, 7, 11)
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start = datetime.date(end.year - years, end.month, end.day)
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dates = [start + datetime.timedelta(days=i) for i in range((end - start).days + 1)]
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n = len(dates)
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rng = np.random.default_rng(seed)
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doy = np.array([d.timetuple().tm_yday for d in dates])
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tmax = 55 + 30 * np.sin((doy - 100) / 366.0 * 2 * np.pi) + rng.normal(0, 8, n)
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return pl.DataFrame({
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"date": dates, "tmax": np.round(tmax, 1), "tmin": np.round(tmax - 15, 1),
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"feels": np.round(tmax + 1, 1), "humid": np.round(np.clip(12 + rng.normal(0, 3, n), 1, None), 1),
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"wetbulb": np.round(tmax - 12, 1), "wind": np.round(np.clip(8 + rng.normal(0, 3, n), 0, None), 1),
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"gust": np.round(np.clip(16 + rng.normal(0, 5, n), 0, None), 1),
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"precip": np.where(rng.random(n) < 0.3, 0.2, 0.0),
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}).with_columns(pl.col("date").dt.ordinal_day().cast(pl.Int16).alias("doy"))
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@pytest.fixture
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def score_client(monkeypatch):
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hist = _score_history()
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monkeypatch.setattr(climate, "get_history",
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lambda cell: (hist.clone(), {"cached": True, "cache_age_days": 3}))
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monkeypatch.setattr(climate, "reverse_geocode", lambda lat, lon: "Testville, Washington")
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return TestClient(appmod.app)
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def test_score_shape_and_conditional_revalidation(score_client):
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r = score_client.get("/thermograph/api/v2/score", params=Q)
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assert r.status_code == 200
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body = r.json()
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assert body["place"] == "Testville, Washington"
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s = body["scores"]
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assert set(s["slices"]) == {"annual", "djf", "mam", "jja", "son"}
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assert s["slices"]["annual"]["overall"]["score"] is not None
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etag = r.headers["etag"]
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r304 = score_client.get("/thermograph/api/v2/score", params=Q,
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headers={"If-None-Match": etag})
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assert r304.status_code == 304 and r304.headers["etag"] == etag
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# Second GET replays the exact same bytes from the derived store.
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r2 = score_client.get("/thermograph/api/v2/score", params=Q)
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assert r2.status_code == 200 and r2.content == r.content
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