Initial commit: astrape-oracle split out of the combined Astrape tree

The forecasting runtime gibil pilots: weather ingest (Open-Meteo
forecasts and the Ecowitt station), the oracle and weather stores, the
snapshot daemon, the forecast evaluator, and the TCN training
scheduler.

classes/datasets.py holds the shapes the stores return for display.
They sit beside the stores deliberately: a store's return type belongs
to the store, and keeping them with the renderers would mean this repo
importing the dashboard, which is backwards.

Extracted from a single repository where the forecasting engine, the
database plumbing, the hardware client, the ingest daemons and the web
UI all imported each other freely. Verified that every module imports
with gibil resolved from its own installed checkout.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
rpotter6298
2026-08-30 14:19:04 +02:00
commit ccd4e7a48c
23 changed files with 3165 additions and 0 deletions
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from __future__ import annotations
from datetime import datetime, timezone
from typing import Any
from urllib.request import urlopen
import json
import re
from gibil.classes.models import WeatherStationObservation
class EcowittGw3000Client:
"""Fetches local live data from an Ecowitt GW3000/GW3000A gateway."""
def __init__(self, host: str, timeout_seconds: float = 5) -> None:
self.host = host.removeprefix("http://").removeprefix("https://").rstrip("/")
self.timeout_seconds = timeout_seconds
def fetch_observation(self) -> WeatherStationObservation:
received_at = datetime.now(timezone.utc)
with urlopen(self._live_data_url(), timeout=self.timeout_seconds) as response:
payload = json.loads(response.read().decode("utf-8"))
return EcowittGw3000Parser().parse(
payload=payload,
received_at=received_at,
)
def _live_data_url(self) -> str:
return f"http://{self.host}/get_livedata_info"
class EcowittGw3000Parser:
"""Normalizes GW3000 live-data JSON into a station observation."""
common_id_names = {
"0x02": "temperature_c",
"0x07": "relative_humidity_pct",
"0x03": "dew_point_c",
"0x0B": "wind_speed_m_s",
"0x0C": "wind_gust_m_s",
"0x19": "wind_max_m_s",
"0x0A": "wind_direction_deg",
"0x15": "solar_radiation_w_m2",
"0x17": "uv_index",
}
rain_id_names = {
"0x0D": "rain_event_mm",
"0x0E": "rain_rate_mm_h",
"0x7C": "rain_hourly_mm",
"0x10": "rain_daily_mm",
"0x11": "rain_weekly_mm",
"0x12": "rain_monthly_mm",
"0x13": "rain_yearly_mm",
}
def parse(
self,
payload: dict[str, Any],
received_at: datetime | None = None,
) -> WeatherStationObservation:
if received_at is None:
received_at = datetime.now(timezone.utc)
common = self._parse_id_list(payload.get("common_list", []))
rain = self._parse_id_list(payload.get("rain", []))
indoor = self._parse_indoor(payload.get("wh25", []))
return WeatherStationObservation(
observed_at=received_at,
received_at=received_at,
source="ecowitt_gw3000",
temperature_c=common.get("temperature_c"),
relative_humidity_pct=common.get("relative_humidity_pct"),
dew_point_c=common.get("dew_point_c"),
wind_speed_m_s=common.get("wind_speed_m_s"),
wind_gust_m_s=common.get("wind_gust_m_s"),
wind_max_m_s=common.get("wind_max_m_s"),
wind_direction_deg=common.get("wind_direction_deg"),
solar_radiation_w_m2=common.get("solar_radiation_w_m2"),
uv_index=common.get("uv_index"),
rain_rate_mm_h=rain.get("rain_rate_mm_h"),
rain_event_mm=rain.get("rain_event_mm"),
rain_hourly_mm=rain.get("rain_hourly_mm"),
rain_daily_mm=rain.get("rain_daily_mm"),
rain_weekly_mm=rain.get("rain_weekly_mm"),
rain_monthly_mm=rain.get("rain_monthly_mm"),
rain_yearly_mm=rain.get("rain_yearly_mm"),
indoor_temperature_c=indoor.get("indoor_temperature_c"),
indoor_humidity_pct=indoor.get("indoor_humidity_pct"),
absolute_pressure_hpa=indoor.get("absolute_pressure_hpa"),
relative_pressure_hpa=indoor.get("relative_pressure_hpa"),
metadata={
"raw_payload": payload,
"debug": payload.get("debug", []),
},
)
def _parse_id_list(self, rows: object) -> dict[str, float]:
parsed: dict[str, float] = {}
if not isinstance(rows, list):
return parsed
for row in rows:
if not isinstance(row, dict):
continue
row_id = str(row.get("id", ""))
key = self.common_id_names.get(row_id) or self.rain_id_names.get(row_id)
if key is None:
continue
value = self._parse_number(row.get("val"))
if value is None:
continue
if key in {"wind_speed_m_s", "wind_gust_m_s", "wind_max_m_s"}:
value = self._knots_to_m_s(value)
parsed[key] = value
return parsed
def _parse_indoor(self, rows: object) -> dict[str, float]:
if not isinstance(rows, list) or not rows:
return {}
row = rows[0]
if not isinstance(row, dict):
return {}
values = {
"indoor_temperature_c": self._parse_number(row.get("intemp")),
"indoor_humidity_pct": self._parse_number(row.get("inhumi")),
"absolute_pressure_hpa": self._parse_number(row.get("abs")),
"relative_pressure_hpa": self._parse_number(row.get("rel")),
}
return {
key: value
for key, value in values.items()
if value is not None
}
def _parse_number(self, value: object) -> float | None:
if value is None:
return None
if isinstance(value, (int, float)):
return float(value)
match = re.search(r"-?\d+(?:\.\d+)?", str(value))
if match is None:
return None
return float(match.group(0))
def _knots_to_m_s(self, value: float) -> float:
return value * 0.514444
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from __future__ import annotations
from datetime import date, datetime, timezone
from typing import Any
from urllib.parse import urlencode
from urllib.request import urlopen
import json
from gibil.classes.models import (
WeatherForecastPoint,
WeatherForecastRun,
WeatherResolvedTruth,
)
class OpenMeteoClient:
"""Fetches external weather forecasts from Open-Meteo."""
base_url = "https://api.open-meteo.com/v1/forecast"
def build_url(
self,
latitude: float,
longitude: float,
forecast_hours: int = 48,
timezone_name: str = "UTC",
) -> str:
params = {
"latitude": latitude,
"longitude": longitude,
"hourly": ",".join(
[
"temperature_2m",
"shortwave_radiation",
"cloud_cover",
]
),
"forecast_hours": forecast_hours,
"timezone": timezone_name,
}
return f"{self.base_url}?{urlencode(params)}"
def fetch_forecast(
self,
latitude: float,
longitude: float,
forecast_hours: int = 48,
) -> WeatherForecastRun:
url = self.build_url(latitude, longitude, forecast_hours)
with urlopen(url, timeout=10) as response:
payload = json.loads(response.read().decode("utf-8"))
return OpenMeteoParser().parse_forecast(
payload=payload,
latitude=latitude,
longitude=longitude,
issued_at=datetime.now(timezone.utc),
)
class OpenMeteoArchiveClient:
"""Fetches historical weather data from Open-Meteo archive."""
base_url = "https://archive-api.open-meteo.com/v1/archive"
def build_url(
self,
latitude: float,
longitude: float,
start_date: date,
end_date: date,
timezone_name: str = "UTC",
) -> str:
params = {
"latitude": latitude,
"longitude": longitude,
"start_date": start_date.isoformat(),
"end_date": end_date.isoformat(),
"hourly": ",".join(
[
"temperature_2m",
"shortwave_radiation",
"cloud_cover",
]
),
"timezone": timezone_name,
}
return f"{self.base_url}?{urlencode(params)}"
def fetch_resolved_truth(
self,
latitude: float,
longitude: float,
start_date: date,
end_date: date,
) -> list[WeatherResolvedTruth]:
url = self.build_url(latitude, longitude, start_date, end_date)
with urlopen(url, timeout=20) as response:
payload = json.loads(response.read().decode("utf-8"))
return OpenMeteoArchiveParser().parse_resolved_truth(payload)
class OpenMeteoParser:
"""Converts Open-Meteo JSON into clean external forecast records."""
def parse_forecast(
self,
payload: dict[str, Any],
latitude: float,
longitude: float,
issued_at: datetime,
) -> WeatherForecastRun:
hourly = payload.get("hourly", {})
times = hourly.get("time", [])
temperatures = hourly.get("temperature_2m", [])
radiation = hourly.get("shortwave_radiation", [])
cloud_cover = hourly.get("cloud_cover", [])
points: list[WeatherForecastPoint] = []
for index, raw_time in enumerate(times):
target_at = self._parse_time(raw_time)
horizon_hours = max(
0, round((target_at - issued_at).total_seconds() / 3600)
)
points.append(
WeatherForecastPoint(
issued_at=issued_at,
target_at=target_at,
horizon_hours=horizon_hours,
temperature_c=self._at(temperatures, index),
shortwave_radiation_w_m2=self._at(radiation, index),
cloud_cover_pct=self._at(cloud_cover, index),
)
)
return WeatherForecastRun(
issued_at=issued_at,
source="open_meteo",
latitude=latitude,
longitude=longitude,
points=points,
)
def _parse_time(self, raw_time: str) -> datetime:
parsed = datetime.fromisoformat(raw_time)
if parsed.tzinfo is None:
return parsed.replace(tzinfo=timezone.utc)
return parsed.astimezone(timezone.utc)
def _at(self, values: list[Any], index: int) -> float | None:
if index >= len(values):
return None
value = values[index]
if value is None:
return None
return float(value)
class OpenMeteoArchiveParser:
"""Converts Open-Meteo archive JSON into resolved truth records."""
def parse_resolved_truth(self, payload: dict[str, Any]) -> list[WeatherResolvedTruth]:
hourly = payload.get("hourly", {})
times = hourly.get("time", [])
temperatures = hourly.get("temperature_2m", [])
radiation = hourly.get("shortwave_radiation", [])
cloud_cover = hourly.get("cloud_cover", [])
truth: list[WeatherResolvedTruth] = []
for index, raw_time in enumerate(times):
truth.append(
WeatherResolvedTruth(
resolved_at=self._parse_time(raw_time),
temperature_c=self._at(temperatures, index),
shortwave_radiation_w_m2=self._at(radiation, index),
cloud_cover_pct=self._at(cloud_cover, index),
source="open_meteo_archive",
)
)
return truth
def _parse_time(self, raw_time: str) -> datetime:
parsed = datetime.fromisoformat(raw_time)
if parsed.tzinfo is None:
return parsed.replace(tzinfo=timezone.utc)
return parsed.astimezone(timezone.utc)
def _at(self, values: list[Any], index: int) -> float | None:
if index >= len(values):
return None
value = values[index]
if value is None:
return None
return float(value)
class WeatherBuilder:
"""Builds a clean database-ready set of external weather forecast records."""
def build_forecast_run(
self,
source: str,
latitude: float,
longitude: float,
points: list[WeatherForecastPoint],
issued_at: datetime | None = None,
) -> WeatherForecastRun:
if issued_at is None:
issued_at = datetime.now(timezone.utc)
clean_points = [
WeatherForecastPoint(
issued_at=issued_at,
target_at=point.target_at,
horizon_hours=max(
0, round((point.target_at - issued_at).total_seconds() / 3600)
),
temperature_c=point.temperature_c,
shortwave_radiation_w_m2=point.shortwave_radiation_w_m2,
cloud_cover_pct=point.cloud_cover_pct,
source=source,
)
for point in sorted(points, key=lambda item: item.target_at)
]
return WeatherForecastRun(
issued_at=issued_at,
source=source,
latitude=latitude,
longitude=longitude,
points=clean_points,
)
def points_for_horizon(
self,
forecast_runs: list[WeatherForecastRun],
horizon_hours: int,
) -> list[WeatherForecastPoint]:
points: list[WeatherForecastPoint] = []
for run in forecast_runs:
points.extend(
point
for point in run.points
if point.horizon_hours == horizon_hours
)
return sorted(points, key=lambda point: point.target_at)
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from __future__ import annotations
from contextlib import contextmanager
from dataclasses import dataclass
from datetime import datetime, timedelta, timezone
from os import environ
from typing import Iterator
from gibil.classes.models import (
WeatherForecastPoint,
WeatherForecastRun,
WeatherResolvedTruth,
WeatherStationObservation,
)
from astrape_oracle.classes.datasets import (
WeatherDisplayDataset,
WeatherStationDisplayDataset,
)
class WeatherStoreConfigurationError(RuntimeError):
pass
@dataclass(frozen=True)
class WeatherStoreConfig:
database_url: str
@classmethod
def from_env(cls) -> "WeatherStoreConfig":
database_url = environ.get("ASTRAPE_DATABASE_URL")
if not database_url:
raise WeatherStoreConfigurationError(
"ASTRAPE_DATABASE_URL is required for weather storage"
)
return cls(database_url=database_url)
class WeatherStore:
"""Persists external weather forecasts and resolved truth in TimescaleDB."""
def __init__(self, config: WeatherStoreConfig) -> None:
self.config = config
@classmethod
def from_env(cls) -> "WeatherStore":
return cls(WeatherStoreConfig.from_env())
def initialize(self) -> None:
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.execute("CREATE EXTENSION IF NOT EXISTS timescaledb")
cursor.execute(
"""
CREATE TABLE IF NOT EXISTS weather_forecast_points (
issued_at TIMESTAMPTZ NOT NULL,
target_at TIMESTAMPTZ NOT NULL,
horizon_hours INTEGER NOT NULL,
source TEXT NOT NULL,
latitude DOUBLE PRECISION NOT NULL,
longitude DOUBLE PRECISION NOT NULL,
temperature_c DOUBLE PRECISION,
shortwave_radiation_w_m2 DOUBLE PRECISION,
cloud_cover_pct DOUBLE PRECISION,
inserted_at TIMESTAMPTZ NOT NULL DEFAULT now(),
PRIMARY KEY (issued_at, target_at, source)
)
"""
)
cursor.execute(
"""
SELECT create_hypertable(
'weather_forecast_points',
'target_at',
if_not_exists => TRUE
)
"""
)
cursor.execute(
"""
CREATE TABLE IF NOT EXISTS weather_resolved_truth (
resolved_at TIMESTAMPTZ NOT NULL,
source TEXT NOT NULL,
temperature_c DOUBLE PRECISION,
shortwave_radiation_w_m2 DOUBLE PRECISION,
cloud_cover_pct DOUBLE PRECISION,
inserted_at TIMESTAMPTZ NOT NULL DEFAULT now(),
PRIMARY KEY (resolved_at, source)
)
"""
)
cursor.execute(
"""
ALTER TABLE weather_resolved_truth
ADD COLUMN IF NOT EXISTS cloud_cover_pct DOUBLE PRECISION
"""
)
cursor.execute(
"""
SELECT create_hypertable(
'weather_resolved_truth',
'resolved_at',
if_not_exists => TRUE
)
"""
)
cursor.execute(
"""
CREATE TABLE IF NOT EXISTS weather_station_observations (
observed_at TIMESTAMPTZ NOT NULL,
received_at TIMESTAMPTZ NOT NULL,
source TEXT NOT NULL,
temperature_c DOUBLE PRECISION,
relative_humidity_pct DOUBLE PRECISION,
dew_point_c DOUBLE PRECISION,
pressure_hpa DOUBLE PRECISION,
wind_speed_m_s DOUBLE PRECISION,
wind_gust_m_s DOUBLE PRECISION,
wind_max_m_s DOUBLE PRECISION,
wind_direction_deg DOUBLE PRECISION,
solar_radiation_w_m2 DOUBLE PRECISION,
uv_index DOUBLE PRECISION,
rain_rate_mm_h DOUBLE PRECISION,
rain_event_mm DOUBLE PRECISION,
rain_hourly_mm DOUBLE PRECISION,
rain_daily_mm DOUBLE PRECISION,
rain_weekly_mm DOUBLE PRECISION,
rain_monthly_mm DOUBLE PRECISION,
rain_yearly_mm DOUBLE PRECISION,
indoor_temperature_c DOUBLE PRECISION,
indoor_humidity_pct DOUBLE PRECISION,
absolute_pressure_hpa DOUBLE PRECISION,
relative_pressure_hpa DOUBLE PRECISION,
metadata JSONB NOT NULL DEFAULT '{}'::jsonb,
inserted_at TIMESTAMPTZ NOT NULL DEFAULT now(),
PRIMARY KEY (observed_at, source)
)
"""
)
cursor.execute(
"""
SELECT create_hypertable(
'weather_station_observations',
'observed_at',
if_not_exists => TRUE
)
"""
)
connection.commit()
def save_forecast_run(self, forecast_run: WeatherForecastRun) -> int:
rows = [
(
point.issued_at,
point.target_at,
point.horizon_hours,
forecast_run.source,
forecast_run.latitude,
forecast_run.longitude,
point.temperature_c,
point.shortwave_radiation_w_m2,
point.cloud_cover_pct,
)
for point in forecast_run.points
]
if not rows:
return 0
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.executemany(
"""
INSERT INTO weather_forecast_points (
issued_at,
target_at,
horizon_hours,
source,
latitude,
longitude,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (issued_at, target_at, source)
DO UPDATE SET
horizon_hours = EXCLUDED.horizon_hours,
latitude = EXCLUDED.latitude,
longitude = EXCLUDED.longitude,
temperature_c = EXCLUDED.temperature_c,
shortwave_radiation_w_m2 = EXCLUDED.shortwave_radiation_w_m2,
cloud_cover_pct = EXCLUDED.cloud_cover_pct,
inserted_at = now()
""",
rows,
)
connection.commit()
return len(rows)
def save_resolved_truth(self, truth_points: list[WeatherResolvedTruth]) -> int:
rows = [
(
point.resolved_at,
point.source,
point.temperature_c,
point.shortwave_radiation_w_m2,
point.cloud_cover_pct,
)
for point in truth_points
]
if not rows:
return 0
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.executemany(
"""
INSERT INTO weather_resolved_truth (
resolved_at,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
)
VALUES (%s, %s, %s, %s, %s)
ON CONFLICT (resolved_at, source)
DO UPDATE SET
temperature_c = EXCLUDED.temperature_c,
shortwave_radiation_w_m2 = EXCLUDED.shortwave_radiation_w_m2,
cloud_cover_pct = EXCLUDED.cloud_cover_pct,
inserted_at = now()
""",
rows,
)
connection.commit()
return len(rows)
def save_zero_hour_forecast_as_truth(
self, forecast_run: WeatherForecastRun
) -> int:
truth_points = [
WeatherResolvedTruth(
resolved_at=point.issued_at,
source="open_meteo_zero_hour",
temperature_c=point.temperature_c,
shortwave_radiation_w_m2=point.shortwave_radiation_w_m2,
cloud_cover_pct=point.cloud_cover_pct,
)
for point in forecast_run.points
if point.horizon_hours == 0
]
return self.save_resolved_truth(truth_points)
def save_station_observation(
self,
observation: WeatherStationObservation,
) -> int:
with self._connection() as connection:
with connection.cursor() as cursor:
try:
from psycopg.types.json import Jsonb
except ImportError as error:
raise WeatherStoreConfigurationError(
"Install dependencies with `python3 -m pip install -r requirements.txt`"
) from error
cursor.execute(
"""
INSERT INTO weather_station_observations (
observed_at,
received_at,
source,
temperature_c,
relative_humidity_pct,
dew_point_c,
pressure_hpa,
wind_speed_m_s,
wind_gust_m_s,
wind_max_m_s,
wind_direction_deg,
solar_radiation_w_m2,
uv_index,
rain_rate_mm_h,
rain_event_mm,
rain_hourly_mm,
rain_daily_mm,
rain_weekly_mm,
rain_monthly_mm,
rain_yearly_mm,
indoor_temperature_c,
indoor_humidity_pct,
absolute_pressure_hpa,
relative_pressure_hpa,
metadata
)
VALUES (
%s, %s, %s, %s, %s, %s, %s, %s, %s, %s,
%s, %s, %s, %s, %s, %s, %s, %s, %s, %s,
%s, %s, %s, %s, %s
)
ON CONFLICT (observed_at, source)
DO UPDATE SET
received_at = EXCLUDED.received_at,
temperature_c = EXCLUDED.temperature_c,
relative_humidity_pct = EXCLUDED.relative_humidity_pct,
dew_point_c = EXCLUDED.dew_point_c,
pressure_hpa = EXCLUDED.pressure_hpa,
wind_speed_m_s = EXCLUDED.wind_speed_m_s,
wind_gust_m_s = EXCLUDED.wind_gust_m_s,
wind_max_m_s = EXCLUDED.wind_max_m_s,
wind_direction_deg = EXCLUDED.wind_direction_deg,
solar_radiation_w_m2 = EXCLUDED.solar_radiation_w_m2,
uv_index = EXCLUDED.uv_index,
rain_rate_mm_h = EXCLUDED.rain_rate_mm_h,
rain_event_mm = EXCLUDED.rain_event_mm,
rain_hourly_mm = EXCLUDED.rain_hourly_mm,
rain_daily_mm = EXCLUDED.rain_daily_mm,
rain_weekly_mm = EXCLUDED.rain_weekly_mm,
rain_monthly_mm = EXCLUDED.rain_monthly_mm,
rain_yearly_mm = EXCLUDED.rain_yearly_mm,
indoor_temperature_c = EXCLUDED.indoor_temperature_c,
indoor_humidity_pct = EXCLUDED.indoor_humidity_pct,
absolute_pressure_hpa = EXCLUDED.absolute_pressure_hpa,
relative_pressure_hpa = EXCLUDED.relative_pressure_hpa,
metadata = EXCLUDED.metadata,
inserted_at = now()
""",
(
observation.observed_at,
observation.received_at,
observation.source,
observation.temperature_c,
observation.relative_humidity_pct,
observation.dew_point_c,
observation.pressure_hpa,
observation.wind_speed_m_s,
observation.wind_gust_m_s,
observation.wind_max_m_s,
observation.wind_direction_deg,
observation.solar_radiation_w_m2,
observation.uv_index,
observation.rain_rate_mm_h,
observation.rain_event_mm,
observation.rain_hourly_mm,
observation.rain_daily_mm,
observation.rain_weekly_mm,
observation.rain_monthly_mm,
observation.rain_yearly_mm,
observation.indoor_temperature_c,
observation.indoor_humidity_pct,
observation.absolute_pressure_hpa,
observation.relative_pressure_hpa,
Jsonb(observation.metadata),
),
)
connection.commit()
return 1
def load_latest_forecast_points(
self,
start_at: datetime,
end_at: datetime,
) -> list[WeatherForecastPoint]:
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.execute(
"""
SELECT
issued_at,
target_at,
horizon_hours,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
FROM (
SELECT
issued_at,
target_at,
horizon_hours,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct,
ROW_NUMBER() OVER (
PARTITION BY target_at
ORDER BY issued_at DESC
) as rn
FROM weather_forecast_points
WHERE target_at >= %s AND target_at <= %s
) as ranked
WHERE rn = 1
ORDER BY target_at
LIMIT 5000
""",
(start_at, end_at),
)
rows = cursor.fetchall()
return [
WeatherForecastPoint(
issued_at=row[0],
target_at=row[1],
horizon_hours=row[2],
source=row[3],
temperature_c=row[4],
shortwave_radiation_w_m2=row[5],
cloud_cover_pct=row[6],
)
for row in rows
]
def load_forecast_history(
self,
start_at: datetime,
end_at: datetime,
) -> dict[datetime, list[dict[str, object]]]:
"""Every forecast issued for each target in the window, oldest first.
Unlike `load_latest_forecast_points`, this keeps all vintages of a
forecast, so a training example can be shown the forecast that was
actually available at the time it was issued rather than the best one
known in hindsight.
"""
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.execute(
"""
SELECT
issued_at,
target_at,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
FROM weather_forecast_points
WHERE target_at >= %s
AND target_at <= %s
ORDER BY target_at, issued_at
""",
(start_at, end_at),
)
rows = cursor.fetchall()
by_target: dict[datetime, list[dict[str, object]]] = {}
for row in rows:
by_target.setdefault(row[1], []).append(
{
"issued_at": row[0],
"target_at": row[1],
"temperature_c": row[2],
"shortwave_radiation_w_m2": row[3],
"cloud_cover_pct": row[4],
}
)
return by_target
def load_display_dataset(
self,
start_at: datetime | None = None,
end_at: datetime | None = None,
) -> WeatherDisplayDataset:
now = datetime.now(timezone.utc)
if start_at is None:
start_at = now - timedelta(hours=24)
if end_at is None:
end_at = now + timedelta(hours=48)
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.execute(
"""
SELECT
issued_at,
target_at,
horizon_hours,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
FROM (
SELECT
issued_at,
target_at,
horizon_hours,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct,
ROW_NUMBER() OVER (PARTITION BY target_at, horizon_hours ORDER BY issued_at DESC) as rn
FROM weather_forecast_points
WHERE target_at >= %s AND target_at <= %s
) as ranked
WHERE rn = 1
ORDER BY target_at, horizon_hours
LIMIT 5000
""",
(start_at, end_at),
)
forecast_rows = cursor.fetchall()
cursor.execute(
"""
SELECT
resolved_at,
source,
temperature_c,
shortwave_radiation_w_m2,
cloud_cover_pct
FROM weather_resolved_truth
WHERE resolved_at >= %s AND resolved_at <= %s
ORDER BY resolved_at
LIMIT 5000
""",
(start_at, now),
)
truth_rows = cursor.fetchall()
return WeatherDisplayDataset(
forecast_points=[
WeatherForecastPoint(
issued_at=row[0],
target_at=row[1],
horizon_hours=row[2],
source=row[3],
temperature_c=row[4],
shortwave_radiation_w_m2=row[5],
cloud_cover_pct=row[6],
)
for row in forecast_rows
],
resolved_truth=[
WeatherResolvedTruth(
resolved_at=row[0],
source=row[1],
temperature_c=row[2],
shortwave_radiation_w_m2=row[3],
cloud_cover_pct=row[4],
)
for row in truth_rows
],
)
def load_station_display_dataset(
self,
start_at: datetime | None = None,
end_at: datetime | None = None,
) -> WeatherStationDisplayDataset:
now = datetime.now(timezone.utc)
if start_at is None:
start_at = now - timedelta(days=7)
if end_at is None:
end_at = now
with self._connection() as connection:
with connection.cursor() as cursor:
cursor.execute(
"""
SELECT
observed_at,
received_at,
source,
temperature_c,
relative_humidity_pct,
dew_point_c,
pressure_hpa,
wind_speed_m_s,
wind_gust_m_s,
wind_max_m_s,
wind_direction_deg,
solar_radiation_w_m2,
uv_index,
rain_rate_mm_h,
rain_event_mm,
rain_hourly_mm,
rain_daily_mm,
rain_weekly_mm,
rain_monthly_mm,
rain_yearly_mm,
indoor_temperature_c,
indoor_humidity_pct,
absolute_pressure_hpa,
relative_pressure_hpa,
metadata
FROM weather_station_observations
WHERE observed_at >= %s AND observed_at <= %s
ORDER BY observed_at
LIMIT 100000
""",
(start_at, end_at),
)
rows = cursor.fetchall()
return WeatherStationDisplayDataset(
observations=[
WeatherStationObservation(
observed_at=row[0],
received_at=row[1],
source=row[2],
temperature_c=row[3],
relative_humidity_pct=row[4],
dew_point_c=row[5],
pressure_hpa=row[6],
wind_speed_m_s=row[7],
wind_gust_m_s=row[8],
wind_max_m_s=row[9],
wind_direction_deg=row[10],
solar_radiation_w_m2=row[11],
uv_index=row[12],
rain_rate_mm_h=row[13],
rain_event_mm=row[14],
rain_hourly_mm=row[15],
rain_daily_mm=row[16],
rain_weekly_mm=row[17],
rain_monthly_mm=row[18],
rain_yearly_mm=row[19],
indoor_temperature_c=row[20],
indoor_humidity_pct=row[21],
absolute_pressure_hpa=row[22],
relative_pressure_hpa=row[23],
metadata=row[24] or {},
)
for row in rows
]
)
@contextmanager
def _connection(self) -> Iterator[object]:
try:
import psycopg
except ImportError as error:
raise WeatherStoreConfigurationError(
"Install dependencies with `python3 -m pip install -r requirements.txt`"
) from error
with psycopg.connect(self.config.database_url) as connection:
yield connection