Retrieve observations from a single station

Features

• Added the ability to retrieve observations from a single station at a time.
• Updated tests and documentation to reflect these additions See #21

by @JacquesOpaux

0.2.5

Fixes :

• Depending on the indicators, the geographic boundary envelope of the indicators may have a height component or other components. The current code does not take this into account. See PR #62

Support for single-point forecast retrieval

Features

• Added a way to call the get_coverage method of WeatherForecast with floats for lat, long (instead of tuples only) to get forecast at a specific location (nearest grid point).
• Added a check on the lat, long parameters of get_coverage so that the closest gridpoint is used
• Added min and max available coordinates to get_coverage_description output
• Updated tests and documentation to reflect these changes

by @JacquesOpaux

Indicators now computed from capabilities

Bugfix :

• INDICATORS and INSTANT_INDICATORS attributes of WeatherForecast object where not always in sync with
  the actual capabilities. Changed these attributes to properties that compute these lists dynamically
  from the capabilities attribute. Changed their name to lowercase (indicators, instant_indicators), since they are not constants anymore.
  (DeprecationWarning about use of INDICATORS and INSTANT_INDICATORS)
  Fix #54.

New forecasts models : PE-ARPEGE & PE-AROME

Features:

• Support for Météo-France ensemble model PE-ARPEGE and PE-AROME by @mattchdt (#38)

Support Python 3.12 and 3.13

Maintenance:

• Support Python 3.12 and 3.13 (#44)

New forecasts models : AROME PI & PIAF

Features:

• Allow user to specify the directory where to store the API result before un-gribbing it #28 by @ThomasBouche in #33
• Support for Météo-France models PIAF and AROME INSTANTANE #26 by @GratienDSX in #27

Fixes:

• Tests run in 2s instead of 20s by @yoyonel in #34
• Wrong function name to fetch bulletin #29 by @TimKeff in #31
• Wrong argument in a tutorial #30 by @TimKeff in #32

0.1.1

Features :

• Raise ImportError with clear help when cfgrib not installed (#11)
• Remove deprecated property .indicators (#23)

Documentation :

• Update README.md (#20, #22)
• Details on logger usage (#25)
• Details on latitude/longitude arguments (#25)

0.1.0b1

Release v0.1.0b1 - Meteole

We are excited to announce the first release of Meteole, a Python library designed to simplify access to weather data from the Météo-France APIs. With Meteole, you can effortlessly integrate weather forecasts into your projects thanks to its powerful and intuitive features:

• Automated token management: Simplify authentication with a single application_id.
• Unified model usage: Access AROME and ARPEGE forecasts through a consistent interface.
• User-friendly parameter handling: Intuitively manage key weather forecasting parameters.
• Seamless data integration: Directly export forecasts as Pandas DataFrames.
• Vigilance bulletins: Retrieve real-time weather warnings across France.

Whether you are a data scientist, meteorologist, or developer, Meteole is the perfect tool to effortlessly integrate weather forecasts into your projects.