meteofrance-publicapi 0.1.5

A wrapper of the portail-api.meteofrance.fr datasets

MeteoFrance_PublicAPI: A Python Wrapper for the MétéoFrance API !

python wrapper of the portail-api.meteofrance.fr datasets

It especially allows to manage easily the API key.

Documentation: antoinetavant.github.io/meteofranceapi (WIP)

Source Code: github.com/antoinetavant/meteofranceapi

Disclaimer

The tool is not officially provided by MétéoFrance.

It is build by trials-and-errors and revers-engineering by an amateur.

Most of the functionalities should work, but it may not be the best way to achieve it.

Installation

Using pip

pip install meteofrance-publicapi

Usage

To use the ressources, you need an account at MeteoFrance. It is free (as in free-beer).

How to get the API key

First register on portail-api.meteofrance.fr

Once your account is activated, several options are possible to use meteofrance-publicapi :

• an API key for the API requested
• a token for the API requested (limited to max 1 hour)
• an Application ID to the classes which will manage the API token.

The Application ID is the recommended use, as it allows to requests dynamically new tokens.

However, you need to keep it a secret !

Obtaining the Application ID

From the website portail-api.meteofrance.fr

• click on the Bonjour User Name button (upper right corner)
• click Mes API
• click "Générer Token" for any API
• scroll down to the curl field
• The Application Key is the last field of the curl commend : curl -k -X POST [... ... ...] "Authorization: Basic <YourAPPLICATION_ID>

Examples

Accessing observation data

Observation data are measured by a station. The list of the stations can be accessed by

import meteofrance_publicapi as mpa
observation_client = mpa.Observations(application_id=<YourApplicationID>)
observation_client.list_stations()

	Id_station	Id_omm	Nom_usuel	Latitude	Longitude	Altitude	Date_ouverture	Pack
0	01014002	NaN	ARBENT	46.278167	5.669000	534	2003-10-01	RADOME
1	01027003	NaN	BALAN_AERO	45.833000	5.106667	196	2014-05-26	ETENDU
2	01034004	NaN	BELLEY	45.769333	5.688000	330	2001-09-13	RADOME
3	01064001	NaN	VERIZIEU	45.777167	5.487167	281	2015-01-01	ETENDU
4	01071001	NaN	CESSY	46.310333	6.080333	507	2002-05-01	RADOME
...	...	...	...	...	...	...	...	...
2098	98832004	91588	MTGNE SOURCES	-22.143833	166.593167	773	1989-08-01	ETENDU
2099	98832005	NaN	OUINNE	-21.984000	166.680500	54	1974-01-01	ETENDU
2100	98832006	NaN	RIVIERE BLANCHE	-22.132667	166.726333	171	2000-11-01	ETENDU
2101	98832101	NaN	GORO_ANCIENNE_PEPINIERE	-22.269167	166.967500	298	1995-01-01	ETENDU
2102	98833002	NaN	MEA	-21.455500	165.767333	571	1988-01-01	ETENDU

Accessing Arome Forecasts

See the notebook Arome Forecast for examples of accessing the forecast of the AROME model.

TODO

• Add local cache capabilities, for instance with joblib
• Add persistent storage, locally or with a could provider