OpenMeteoSource

Downloads weather forecast data from Open-Meteo Previous Runs API. No API key required.

Basic Usage

import pandas as pd
from epftoolbox2.data.sources import OpenMeteoSource

source = OpenMeteoSource(
    latitude=52.2297,   # Warsaw
    longitude=21.0122,
    horizon=7,
    prefix="warsaw",
)

df = source.fetch(
    start=pd.Timestamp("2024-01-01", tz="UTC"),
    end=pd.Timestamp("2024-06-01", tz="UTC"),
)

Parameters

Parameter	Type	Required	Default	Description
`latitude`	float	Yes	-	Location latitude (-90 to 90)
`longitude`	float	Yes	-	Location longitude (-180 to 180)
`horizon`	int	No	7	Days ahead for forecasts
`model`	str	No	`"jma_seamless"`	Weather model
`columns`	List[str]	No	DEFAULT_COLUMNS	Weather variables
`prefix`	str	No	`""`	Prefix for column names

Rate Limiting

Output Column Naming

Columns are named: {prefix}_{variable}_d+{horizon}

# Example output columns:
# warsaw_temperature_2m_d+1
# warsaw_temperature_2m_d+2
# ...
# warsaw_temperature_2m_d+7

Default Weather Variables

Variable	Description
`temperature_2m`	Temperature at 2m (°C)
`rain`	Rain amount (mm)
`showers`	Shower amount (mm)
`snowfall`	Snowfall amount (cm)
`relative_humidity_2m`	Relative humidity (%)
`dew_point_2m`	Dew point (°C)
`apparent_temperature`	Feels-like temperature (°C)
`precipitation`	Total precipitation (mm)
`weather_code`	WMO weather code
`surface_pressure`	Surface pressure (hPa)
`pressure_msl`	Sea-level pressure (hPa)
`cloud_cover`	Cloud cover (%)
`wind_speed_10m`	Wind speed at 10m (km/h)
`wind_direction_10m`	Wind direction at 10m (°)

Example: Multiple Locations

from epftoolbox2.pipelines import DataPipeline
from epftoolbox2.data.sources import OpenMeteoSource

cities = {
    "warsaw": (52.2297, 21.0122),
    "krakow": (50.0647, 19.9450),
    "gdansk": (54.3520, 18.6466),
}

pipeline = DataPipeline()
for name, (lat, lon) in cities.items():
    pipeline.add_source(OpenMeteoSource(
        latitude=lat,
        longitude=lon,
        horizon=7,
        prefix=name,
    ))

df = pipeline.run(start="2024-01-01", end="2024-06-01", cache=True)

Output

Data is returned with a UTC DatetimeIndex:

print(df.columns[:5].tolist())
# ['warsaw_temperature_2m_d+1', 'warsaw_temperature_2m_d+2', ...]