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Library for fetching weather information from Finnish Meteorological Institute (FMI)

Project description

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Finnish Meteorological Institute Weather

Library for fetching weather information from Finnish Meteorological Institute (FMI).

Originally build for personal use because I wanted to create FMI integration for Home Assistant.

BETA WARNING! This is still under heavy development. The public API is not frozen yet so DO NOT consider it to be stable. Any version can have breaking changes.

How to use

Working example can be found in example.py.

Install

$ pip install fmi-weather-client 

Get a weather by place name

import fmi_weather_client

weather = fmi_weather_client.weather_by_place_name("Mäkkylä, Espoo")

Selected weather station depends on FMI service. Be aware, that sometimes FMI service does pretty poor job at selecting a station that provides meaningful data. For example, at the time of writing weather from Sipoo returns data from a station that measures cloud coverage and nothing more. Another example is Kaivopuisto, Helsinki which returns data from a station that seems to be unavailable or broken.

If place name is not known or weather data is not available, the following exception is thrown:

fmi_weather_client.errors.NoWeatherDataError

Get a weather by coordinates

import fmi_weather_client

weather = fmi_weather_client.weather_by_coordinates(63.361604, 27.392607)

Returned data is from the closest weather station. Just like with place name search, station might return very little data or nothing at all. If there are no stations within 90 km or weather data is not available, the following exception is thrown:

fmi_weather_client.errors.NoWeatherDataError

Get a combination weather

import fmi_weather_client

weather = fmi_weather_client.weather_multi_station(69.016989, 21.465569)

Returned data is combination of multiple stations. Closest station is checked first and if some variables are missing, next station is checked. This way it is likely to get all variables it is possible that some data comes from a station that is quite far away.

Returned station name and observation time is always the closest station. If there are no stations within 90 km or weather data is not available, the following exception is thrown:

fmi_weather_client.errors.NoWeatherDataError

Get a forecast

You can get the forecast using a place name or coordinates and the behaviour is the same. The code tries to fetch the forecast for the next 6 days but looks like FMI provides it only for the next 3. You can also define the timestep between forecasts. Default is 24 hours.

forecast = fmi_weather_client.forecast_by_place_name("Jäppilä, Pieksämäki")
forecast2 = fmi_weather_client.forecast_by_coordinates(28.62406, 67.6894, timestep_hours=12)

Weather data

Available weather information depends on the weather station. Currently supported fields:

  • Station name
  • Station latitude
  • Station longitude
  • Observation time
  • Temperature (°C)
  • Humidity (%)
  • Wind speed (m/s)
  • Wind gust (m/s)
    • Maximum gust wind in the past 10 minutes
  • Wind direction (°)
  • Dew point (°C)
  • Precipitation amount (mm)
    • Amount of rain in the past hour
  • Precipitation intensity (mm/h)
  • Pressure (hPa)
  • Visibility (m)
  • Cloud coverage
    • Cloud coverage is indicated as 1/8 sky.
    • 0.0 means no clouds
    • 4.0 means half cloudy
    • 8.0 means overcast
  • Snow depth (cm)
  • Current weather as WaWa code (Documentation in Finnish)

Observation data contains two fields: value and unit. You can also just print the observation object to get a string representation:

print('Temperature: %s' % weather.temperature)

# Output: Temperature: 1.4 °C

Forecast data

  • Geopotential height (m)
  • Temperature (°C)
  • Pressure (hPa)
  • Humidity (%)
  • Wind direction (°)
  • Wind speed (m/s)
  • Wind U component (m/s)
  • Wind V component (m/s)
  • Wind max (m/s)
  • Wind gust (m/s)
  • Dew point (°)
  • Cloud cover (%)
  • Symbol Documentation in Finnish
  • Precipitation amount 1h (mm/h)
  • Precipitation amount (mm)

There are also other data regarding cloud coverage, radiation and land-sea mask. I have no idea what these really are so it is best to check FMI documentation.

Development

Setup

Create and activate a virtual environment

$ python -m venv venv
$ source venv/bin/activate

Install required packages

$ python -m pip install -r requirements.txt
$ python -m pip install -r requirements-dev.txt

When you stop working, deactivate virtual environment

$ deactivate

Run tests

$ pytest

Run code quality tools

$ flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics --exclude venv
$ flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127  --exclude venv

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