/* Foundation fact: daily weather observations for 12 coffee-growing regions. */
/* Source: Open-Meteo (ERA5 reanalysis archive + forecast model for recent days) */
/* Landing: LANDING_DIR/weather/{location_id}/{year}/{date}.json.gz */
/* One file per (location_id, date). Content: flat Open-Meteo JSON per day. */
/* Open-Meteo returns parallel arrays; execute.py splits them into per-day files. */
/* Grain: (location_id, observation_date) — one row per location per day. */
/* Dedup key: hash(location_id, date) — past weather is immutable. */
/* location_id is parsed from filename: split(filename, '/')[-3] */
/* Path structure: .../weather/{location_id}/{year}/{date}.json.gz */
/* Crop stress flags: */
/*   is_frost       — temp_min_c < 2.0°C  (ICO Arabica frost damage threshold) */
/*   is_heat_stress — temp_max_c > 35.0°C (photosynthesis impairment) */
/*   is_drought     — precipitation_mm < 1.0 (agronomic dry day) */
/*   is_high_vpd    — vpd_max_kpa > 1.5 (significant plant water stress) */
/*   in_growing_season — simplified month-range flag by variety */
MODEL (
  name foundation.fct_weather_daily,
  kind INCREMENTAL_BY_TIME_RANGE (
    time_column observation_date
  ),
  grain (location_id, observation_date),
  start '2020-01-01',
  cron '@daily'
);

WITH src AS (
  /* Open-Meteo files are flat JSON: all variables at top level (no nested structs). */
  /* read_json(format='auto') infers column types directly from the numeric values. */
  SELECT
    *
  FROM READ_JSON(@weather_glob(), format = 'auto', compression = 'gzip', filename = TRUE)
), located AS (
  SELECT
    src.*,
    STR_SPLIT(filename, '/')[-3] AS location_id, /* location_id is the 3rd-from-last path segment: */
    /* e.g. .../weather/brazil_minas_gerais/2024/2024-01-15.json.gz → 'brazil_minas_gerais' */
    TRY_CAST(src."date" AS DATE) AS observation_date
  FROM src
), cast_and_clean AS (
  SELECT
    location_id,
    observation_date,
    /* Temperature (°C) */
    TRY_CAST(located.temperature_2m_min AS DOUBLE) AS temp_min_c,
    TRY_CAST(located.temperature_2m_max AS DOUBLE) AS temp_max_c,
    TRY_CAST(located.temperature_2m_mean AS DOUBLE) AS temp_mean_c,
    /* Precipitation (mm total for the day) */
    COALESCE(TRY_CAST(located.precipitation_sum AS DOUBLE), 0.0) AS precipitation_mm,
    /* Humidity (% — daily max) */
    TRY_CAST(located.relative_humidity_2m_max AS DOUBLE) AS humidity_max_pct,
    /* Cloud cover (% — daily mean) */
    TRY_CAST(located.cloud_cover_mean AS DOUBLE) AS cloud_cover_mean_pct,
    /* Wind (m/s max — Open-Meteo requested with wind_speed_unit=ms) */
    TRY_CAST(located.wind_speed_10m_max AS DOUBLE) AS wind_max_speed_ms,
    /* ET₀ (mm/day — FAO Penman-Monteith; direct crop water demand signal) */
    TRY_CAST(located.et0_fao_evapotranspiration AS DOUBLE) AS et0_mm,
    /* VPD (kPa — max; >1.5 kPa = significant plant water stress) */
    TRY_CAST(located.vapour_pressure_deficit_max AS DOUBLE) AS vpd_max_kpa,
    /* Crop stress flags */
    TRY_CAST(located.temperature_2m_min AS DOUBLE) < 2.0 AS is_frost,
    TRY_CAST(located.temperature_2m_max AS DOUBLE) > 35.0 AS is_heat_stress,
    COALESCE(TRY_CAST(located.precipitation_sum AS DOUBLE), 0.0) < 1.0 AS is_drought,
    TRY_CAST(located.vapour_pressure_deficit_max AS DOUBLE) > 1.5 AS is_high_vpd,
    HASH(location_id, src."date") AS hkey,
    filename
  FROM located
  WHERE
    NOT observation_date IS NULL AND NOT location_id IS NULL AND location_id <> ''
), deduplicated AS (
  SELECT
    ANY_VALUE(location_id) AS location_id,
    ANY_VALUE(observation_date) AS observation_date,
    ANY_VALUE(temp_min_c) AS temp_min_c,
    ANY_VALUE(temp_max_c) AS temp_max_c,
    ANY_VALUE(temp_mean_c) AS temp_mean_c,
    ANY_VALUE(precipitation_mm) AS precipitation_mm,
    ANY_VALUE(humidity_max_pct) AS humidity_max_pct,
    ANY_VALUE(cloud_cover_mean_pct) AS cloud_cover_mean_pct,
    ANY_VALUE(wind_max_speed_ms) AS wind_max_speed_ms,
    ANY_VALUE(et0_mm) AS et0_mm,
    ANY_VALUE(vpd_max_kpa) AS vpd_max_kpa,
    ANY_VALUE(is_frost) AS is_frost,
    ANY_VALUE(is_heat_stress) AS is_heat_stress,
    ANY_VALUE(is_drought) AS is_drought,
    ANY_VALUE(is_high_vpd) AS is_high_vpd,
    hkey
  FROM cast_and_clean
  GROUP BY
    hkey
)
SELECT
  d.observation_date,
  d.location_id,
  loc.name AS location_name,
  loc.country,
  loc.lat,
  loc.lon,
  loc.variety,
  d.temp_min_c,
  d.temp_max_c,
  d.temp_mean_c,
  d.precipitation_mm,
  d.humidity_max_pct,
  d.cloud_cover_mean_pct,
  d.wind_max_speed_ms,
  d.et0_mm,
  d.vpd_max_kpa,
  d.is_frost,
  d.is_heat_stress,
  d.is_drought,
  d.is_high_vpd,
  CASE loc.variety
    WHEN 'Arabica'
    THEN EXTRACT(MONTH FROM d.observation_date) BETWEEN 4 AND 10
    WHEN 'Robusta'
    THEN EXTRACT(MONTH FROM d.observation_date) BETWEEN 4 AND 11
    ELSE FALSE
  END AS in_growing_season /* Growing season: simplified month-range flag by variety. */
  /* Arabica: Apr–Oct (covers northern + southern hemisphere risk windows). */
  /* Robusta: Apr–Nov (Vietnam/Indonesia main cycle). */
FROM deduplicated AS d
LEFT JOIN seeds.weather_locations AS loc
  ON d.location_id = loc.location_id
WHERE
  d.observation_date BETWEEN @start_ds AND @end_ds
