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

Project description

MeteoFrance_PublicAPI: A Python Wrapper for the MétéoFrance API !

Supported Python versions License GitHub Actions Workflow Status

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

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