data.fetch_data.fetch_weather_data

data.fetch_data.fetch_weather_data(
    cov_start,
    cov_end,
    latitude=51.5136,
    longitude=7.4653,
    timezone='UTC',
    freq='h',
    fallback_on_failure=True,
    cache_home=None,
)

Fetch weather data for the dataset period plus forecast horizon.

Creates a weather DataFrame using the Open-Meteo API with optional caching. Caching is controlled solely by the cache_home argument: when a path is provided the service reads from / writes to a parquet cache file inside that directory; when None (the default) no caching is performed.

Parameters

Name	Type	Description	Default
cov_start	str	Start date for covariate data.	required
cov_end	str	End date for covariate data.	required
latitude	float	Latitude of the location for weather data. Default is 51.5136 (Dortmund).	`51.5136`
longitude	float	Longitude of the location for weather data. Default is 7.4653 (Dortmund).	`7.4653`
timezone	str	Timezone for the weather data.	`'UTC'`
freq	str	Frequency of the weather data.	`'h'`
fallback_on_failure	bool	Whether to use fallback data in case of failure.	`True`
cache_home	Optional[Union[str, Path]]	Optional path to cache directory. When provided, fetched weather data is cached in `<cache_home>/weather_cache.parquet`. When None (default), no caching is performed.	`None`

Returns

Name	Type	Description
	pd.DataFrame	pd.DataFrame: DataFrame containing weather information.

Examples

from spotforecast2_safe.data.fetch_data import fetch_weather_data
weather_df = fetch_weather_data(
    cov_start='2023-01-01T00:00',
    cov_end='2023-01-11T00:00',
    latitude=51.5136,
    longitude=7.4653,
    timezone='UTC',
    freq='h',
    fallback_on_failure=True,
    cache_home='~/.spotforecast2_cache')
weather_df.head()

	temperature_2m	relative_humidity_2m	precipitation	rain	snowfall	weather_code	pressure_msl	surface_pressure	cloud_cover	cloud_cover_low	cloud_cover_mid	cloud_cover_high	wind_speed_10m	wind_direction_10m	wind_gusts_10m
datetime
2023-01-01 00:00:00+00:00	16.6	43	0.0	0.0	0.0	3	1010.4	998.2	97	0	100	6	35.2	228	63.7
2023-01-01 01:00:00+00:00	16.6	42	0.0	0.0	0.0	3	1010.3	998.1	100	0	99	87	32.6	229	64.8
2023-01-01 02:00:00+00:00	15.9	43	0.0	0.0	0.0	3	1011.0	998.8	100	0	99	100	29.1	222	60.1
2023-01-01 03:00:00+00:00	15.1	46	0.0	0.0	0.0	3	1011.3	999.0	100	0	100	99	28.4	218	54.0
2023-01-01 04:00:00+00:00	14.6	50	0.0	0.0	0.0	3	1011.7	999.4	100	5	100	94	28.4	219	55.1