m0rp43us / openmeteopy

openmeteopy is a client Python wrapper library for Open-Meteo web API. It allows quick and easy consumption of OM data from Python applications via a simple object model and in a human-friendly fashion.

OpenmeteoPy

Download Meteorological Data from OPEN-METEO API (https://open-meteo.com/en)

Open-Meteo collaborates with National Weather Services providing Open Data with 11 to 2 km resolution. Our high performance APIs select the best weather model for your location and provide data as a simple JSON API.

APIs are free without any API key for open-source developers and non-commercial use. You can embed them directly into your app.

What is it?

openmeteopy is a client Python wrapper library for Open-Meteo web API. It allows quick and easy consumption of Open-Meteo data from Python applications via a simple object model and in a human-friendly fashion.

You can use all Openmeteo's available APIs,which are 14 (explained in the table below).

openmeteopy runs on Python 3.6+.

Full documentation is reported here: DOCUMENTATION.

Installation (pypi)

working on it

Installation (manually)

git clone https://github.com/m0rp43us/openmeteopy
cd openmeteopy-main/
pip install .

APIs

API	Description	Documentation	Options Class	Hourly Class	Daily Class	15 Minutes Class
Weather forecast	Select your location, weather variables and start using the API.	Weather Forecast	ForecastOptions()	HourlyForecast()	DailyForecast()	-
Historical Weather	Discover how weather has shaped our world from 1940 until now	Historical Weather	HistoricalOptions()	HourlyHistorical()	DailyHistorical()	-
ECMWF Weather Forecast	Global High Frequency Forecasts at 0.4° resolution	ECMWF Weather Forecast	EcmwfOptions()	HourlyEcmwf()	-	-
GFS & HRRR Forecast	Global GFS model combined with hourly HRRR updates at 3-km resolution	GFS & HRRR Forecast	GfsOptions()	HourlyGfs()	DailyGfs()	-
MeteoFrance	Global ARPEGE model combined with high resolution AROME model	MeteoFrance	MeteoFranceOptions()	HourlyMeteoFrance()	DailyMeteoFrance()	-
DWD ICON	Open data weather forecasts from the German weather service DWD	DWD ICON	DwdOptions()	HourlyDwd()	DailyDwd()	FifteenMinutesDwd()
JMA	5-km high resolution forecasts for Japan, Korea, parts of China and Russia	JMA	JmaOptions()	HourlyJma()	DailyJma()	-
MET Norway	Hourly updates & 1 km forecasts for Scandinavia	MET Norway	MetnoOptions()	HourlyMetno()	-	-
GEM	2.5 km high resolution forecasts for North America	GEM	GemOptions()	HourlyGem()	DailyGem()	-
Marine Weather	Hourly wave forecasts at 5 km resolution	Marine Weather	MarineOptions()	HourlyMarine()	DailyMarine()	-
Air Quality	Pollutants and pollen forecast in 11 km resolution	Air Quality	AirQualityOptions()	HourlyAirQuality()	-	-
Geocoding	Search locations in any language globally	Geocoding	GeocodingOptions()	-	-	-
Elevation	90 meter resolution digital elevation model	Elevation	ElevationOptions()	-	-	-
Global Flood	Simulated river discharge at 5 km resolution from 1984 up to 7 months forecast	Global Flood	FloodOptions()	-	DailyForecast()	-

Output formats:

You can get your output in python dictionary, json string, pandas DataFrame, numpy array. Additionally, you can save APIs response to files in csv, excel or json format.

Output	Library function
dict (full server response)	client._fetch()
dict (cleaned version)	client.get_dict()
json string (cleaned version)	client.get_json_str()
numpy array	client.get_numpy()
pandas DataFrame (keys are dates,value are correspongding values)	client.get_pandas()
save to csv (keys are dates,value are correspongding values)	save_csv(<filepath>)
save to excel (keys are dates,value are correspongding values)	save_excel(<filepath>)
save to json	save_json(<filepath>)

Upcoming Changes,updates,things to do :

• Add the other 2 variables to ECWMF pressure level parameters
• remove pressure level variables from JMA (Remove inheritence from FranceMeteo)
• Add Support of Date Types (input and output)
• Add versionning and package to pypi