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.
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.
You can use all Openmeteo's available APIs,which are 14 (explained in the table below).
openmeteopy runs on Python 3.6+.
print(mgr.get_data())
working on it
git clone https://github.com/m0rp43us/openmeteopy
cd openmeteopy-main/
pip3 install .
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() |
- |
You can get your output in json,dataframe or save it as csv or excel file as follows : get_data(output = 0,file = 0,filepath = None):
Ooutput | get_data Method values |
---|---|
json (server response) | get_data() |
json (keys are dates,value are correspongding values) | get_data(1) |
json (keys are dates,value are correspongding values) saved into a json file | get_data(1,1) |
csv (keys are dates,value are correspongding values) saved into a csv file | get_data(1,1,'path') |
excel (keys are dates,value are correspongding values) saved into a excel file | get_data(1,2,'path') |
dataframe in excel (keys are dates,value are correspongding values) saved into a excel file | get_data(1,3,'path') |
- Add the other 2 variables to ECWMF pressure level parameters
- Change
get_data()
method to a more developper friendly method - Add Documentation for
dataframit()
andjsonify()
- remove pressure level variables from JMA (Remove inheritence from FranceMeteo)
- Add Support of Date Types (input and output)
- Add versionning and package to pypi
- Clean and add corresponding comments
- Maybe Refactor OWmanager Class and add inheritence for a more Dev friendly Methods
- Readthedocs