2569718930@qq.com
222 lines
10 KiB
Python
222 lines
10 KiB
Python
from src.data_collection.nws_open_meteo_sources import (
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OPEN_METEO_MULTI_MODEL_ORDER,
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_parse_open_meteo_multi_model_daily,
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)
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import src.data_collection.open_meteo_cache as open_meteo_cache_module
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from src.data_collection.weather_sources import WeatherDataCollector
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from src.database.runtime_state import OpenMeteoRateLimitRepository, RuntimeStateDB
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def test_multi_model_parser_exposes_open_recommended_models():
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daily = {
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"time": ["2026-04-17", "2026-04-18"],
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"temperature_2m_max_ecmwf_ifs025": [20.1, 21.1],
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"temperature_2m_max_ecmwf_aifs025_single": [20.2, 21.2],
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"temperature_2m_max_icon_eu": [20.3, 21.3],
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"temperature_2m_max_icon_d2": [20.4, None],
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"temperature_2m_max_gem_global": [19.8, 20.8],
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"temperature_2m_max_gem_regional": [21.0, 22.0],
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"temperature_2m_max_gem_hrdps_continental": [21.5, None],
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}
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dates, forecasts, metadata, model_keys = _parse_open_meteo_multi_model_daily(daily)
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assert dates == ["2026-04-17", "2026-04-18"]
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assert forecasts["2026-04-17"]["ECMWF"] == 20.1
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assert forecasts["2026-04-17"]["ECMWF AIFS"] == 20.2
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assert forecasts["2026-04-17"]["ICON-EU"] == 20.3
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assert forecasts["2026-04-17"]["ICON-D2"] == 20.4
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assert forecasts["2026-04-17"]["GDPS"] == 19.8
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assert forecasts["2026-04-17"]["RDPS"] == 21.0
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assert forecasts["2026-04-17"]["HRDPS"] == 21.5
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assert "ICON-D2" not in forecasts["2026-04-18"]
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assert metadata["ECMWF AIFS"]["provider"] == "ECMWF"
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assert metadata["HRDPS"]["resolution_km"] == 2.5
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assert model_keys["RDPS"] == "gem_regional"
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def test_multi_model_order_includes_legacy_and_new_sources():
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assert "ecmwf_ifs025" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "ecmwf_aifs025_single" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "gfs_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "icon_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "icon_eu" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "icon_d2" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "gem_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "gem_global" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "gem_regional" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "gem_hrdps_continental" in OPEN_METEO_MULTI_MODEL_ORDER
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assert "jma_seamless" in OPEN_METEO_MULTI_MODEL_ORDER
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def test_fetch_all_sources_prioritizes_multi_model_before_forecast(monkeypatch, tmp_path):
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monkeypatch.setenv("OPEN_METEO_DISK_CACHE_PATH", str(tmp_path / "om-cache.json"))
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collector = WeatherDataCollector({})
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calls = []
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monkeypatch.setattr(collector, "_log_temperature_unit", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_settlement_sources", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_supports_aviationweather", lambda city: False)
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monkeypatch.setattr(collector, "_attach_turkish_mgm_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_korean_amos_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_china_amsc_awos_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_madis_hfmetar_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_singapore_mss_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_china_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_japan_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_fmi_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_knmi_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_hko_obs_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_cwa_settlement_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_global_nearby_cluster", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "fetch_ensemble", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "fetch_nws", lambda *args, **kwargs: None)
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def fake_multi_model(*args, **kwargs):
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calls.append("multi_model")
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return {"forecasts": {"ECMWF": 24.0, "GFS": 25.0}}
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def fake_open_meteo(*args, **kwargs):
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calls.append("open_meteo")
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return {"utc_offset": 10800, "daily": {"temperature_2m_max": [24]}}
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monkeypatch.setattr(collector, "fetch_multi_model", fake_multi_model)
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monkeypatch.setattr(collector, "fetch_from_open_meteo", fake_open_meteo)
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result = collector.fetch_all_sources(
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"ankara",
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lat=40.1281,
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lon=32.9951,
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include_ensemble=False,
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include_nearby=False,
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include_taf=False,
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include_mgm=False,
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)
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assert calls[:2] == ["multi_model", "open_meteo"]
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assert result["multi_model"]["forecasts"]["ECMWF"] == 24.0
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def test_force_refresh_preserves_open_meteo_model_caches_by_default(monkeypatch, tmp_path):
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monkeypatch.setenv("OPEN_METEO_DISK_CACHE_PATH", str(tmp_path / "om-cache.json"))
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collector = WeatherDataCollector({})
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captured = {}
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def fake_evict(*args, **kwargs):
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captured["keep_model_caches"] = kwargs.get("keep_model_caches")
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monkeypatch.setattr(collector, "_evict_city_caches", fake_evict)
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monkeypatch.setattr(collector, "_log_temperature_unit", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_settlement_sources", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_supports_aviationweather", lambda city: False)
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monkeypatch.setattr(collector, "fetch_multi_model", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "fetch_from_open_meteo", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_nws_and_models", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_turkish_mgm_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_korean_amos_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_china_amsc_awos_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_madis_hfmetar_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_singapore_mss_data", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_china_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_japan_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_fmi_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_knmi_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_hko_obs_official_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_cwa_settlement_nearby", lambda *args, **kwargs: None)
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monkeypatch.setattr(collector, "_attach_global_nearby_cluster", lambda *args, **kwargs: None)
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collector.fetch_all_sources(
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"ankara",
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lat=40.1281,
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lon=32.9951,
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force_refresh=True,
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include_ensemble=False,
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include_nearby=False,
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include_taf=False,
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include_mgm=False,
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)
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assert captured["keep_model_caches"] is True
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def test_persisted_open_meteo_cooldown_skips_outbound_request(monkeypatch, tmp_path):
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monkeypatch.setenv("POLYWEATHER_STATE_STORAGE_MODE", "sqlite")
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monkeypatch.setenv("POLYWEATHER_DB_PATH", str(tmp_path / "polyweather.db"))
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monkeypatch.setenv("OPEN_METEO_DISK_CACHE_PATH", str(tmp_path / "om-cache.json"))
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db = RuntimeStateDB(str(tmp_path / "polyweather.db"))
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rate_repo = OpenMeteoRateLimitRepository(db)
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rate_repo.set_until(9999999999.0, reason="test_429")
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monkeypatch.setattr(open_meteo_cache_module, "_open_meteo_rate_limit_repo", rate_repo)
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collector = WeatherDataCollector({})
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def fail_http(*args, **kwargs):
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raise AssertionError("Open-Meteo HTTP request should be skipped during persisted cooldown")
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monkeypatch.setattr(collector, "_http_get", fail_http)
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result = collector.fetch_multi_model(40.1281, 32.9951, city="ankara")
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assert result is None
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def test_multi_model_hourly_parser():
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from src.data_collection.nws_open_meteo_sources import _parse_open_meteo_multi_model_hourly
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hourly = {
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"time": ["2026-05-21T00:00", "2026-05-21T01:00"],
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"temperature_2m_ecmwf_ifs025": [15.2, 15.0],
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"temperature_2m_gfs_seamless": [14.8, None],
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"temperature_2m_icon_d2": [None, None], # completely empty, should be ignored
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}
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times, forecasts = _parse_open_meteo_multi_model_hourly(hourly)
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assert times == ["2026-05-21T00:00", "2026-05-21T01:00"]
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assert forecasts["ECMWF"] == [15.2, 15.0]
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assert forecasts["GFS"] == [14.8, None]
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assert "ICON-D2" not in forecasts
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def test_merge_multi_model_result_with_cache_hourly():
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from src.data_collection.nws_open_meteo_sources import _merge_multi_model_result_with_cache
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cached = {
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"forecasts": {"ECMWF": 20.0, "GFS": 19.5, "ICON-EU": 19.8},
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"daily_forecasts": {
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"2026-05-21": {"ECMWF": 20.0, "GFS": 19.5, "ICON-EU": 19.8}
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},
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"hourly_times": ["2026-05-21T00:00", "2026-05-21T01:00"],
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"hourly_forecasts": {
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"ECMWF": [15.2, 15.0],
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"GFS": [14.8, 14.5],
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"ICON-EU": [15.0, 14.8],
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},
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}
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fresh = {
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"forecasts": {"ECMWF": 20.2}, # Only ECMWF returned (e.g. subset refresh)
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"daily_forecasts": {
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"2026-05-21": {"ECMWF": 20.2}
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},
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"hourly_times": ["2026-05-21T01:00", "2026-05-21T02:00"], # time shifts forward
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"hourly_forecasts": {
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"ECMWF": [15.1, 15.3],
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},
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}
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merged = _merge_multi_model_result_with_cache(cached, fresh)
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# Standard checks
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assert merged["forecasts"]["ECMWF"] == 20.2
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assert merged["forecasts"]["GFS"] == 19.5
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assert merged["forecasts"]["ICON-EU"] == 19.8
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# Hourly merge and alignment checks
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assert merged["hourly_times"] == ["2026-05-21T01:00", "2026-05-21T02:00"]
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# At T01:00, fresh has ECMWF=15.1, cached has GFS=14.5, ICON-EU=14.8
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assert merged["hourly_forecasts"]["ECMWF"] == [15.1, 15.3]
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assert merged["hourly_forecasts"]["GFS"] == [14.5, None]
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assert merged["hourly_forecasts"]["ICON-EU"] == [14.8, None]
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