openweathermapy
Python package wrapping OpenWeatherMap.org's API 2.5.
As OpenWeatherMap.org returns data mostly in the form of nested dictionaries, openweathermapy gives a simple API to access items in a comfortable way:
# classic access
item = data["main"]["temp"]
# openweathermapy access
item = data("main.temp")
# access multiple items at once
>>> items = data("main.temp", "wind.speed")Status
Development (Beta)
Version
0.6.7
Pandas support added in latest version
You can download the latest version from branch pandas_support giving you the possibility
to return forecast and historical data as pandas.DataFrame objects.
Installation
# via pip
~$ pip install openweathermapy
# or fetch latest version from git ...
~$ git clone https://github.com/crazycapivara/openweathermapy/
~$ cd openweathermapy
~$ python setup.py installDocumentation
The latest Documentation can always be found at Read The Docs. Furthermore you can use Python's builtin help functionality and take a look at the examples in this file.
Usage
>>> import openweathermapy.core as owmAll parameters defined in OpenWeatherMap's API documentation can be passed to the functions
in openweathermapy as keyword arguments **params.
The query string always depends on the request (API call), but unsupported parameters will (normally) not raise an error. Most common ones to be used are units, lang and (if needed) APPID. So, it may be a good idea to pass them
in the form of a settings dictionary:
>>> settings = {"units": "metric", "lang": "DE"}
>>> data = owm.get_current("Kassel,DE", **settings)
# settings containing APIKEY
>>> settings = {"APPID": 1111111111, "units": "metric"}Data objects and views
The main data object is openweathermapy.utils.NestedDict, which extends Python's builtin dict
by methods giving a more flexible access to the items as shown above. If a list of weather data (objects) is returned
openweathermapy.utils.NestedDictList or openweathermapy.core.DataBlock is used. The latter one just adds
an attribute meta to the NestedDictList containing the meta data of the responses.
A view is just a list of keys to extract data from the responses. So, you can define views like summary, minimal etc. depending on your needs. This keeps everything as flexible as possible:
>>> views = {
... "summary": ["main.temp", "main.pressure", "main.humidity"]
... }
>>> data = owm.get_current("London,UK", units="metric")
>>> data(*views["summary"])
(18.56, 1011, 63)
# return complete keys
>>> data.get_dict(views["summary"])
{'main.temp': 18.56, 'main.humidity': 63, 'main.pressure': 1011}
# return only last key
>>> data.get_dict(views["summary"], split_keys=True)
{'pressure': 1011, 'temp': 18.56, 'humidity': 63} You can also load views from files in json format for example by using openweathermapy.utils.load_config.
Current weather data
City can be given as name, id, or geographic coordinates.
If you want to stay as close as possible to the original API, you can also skip the
first argument and use the parameters q, id, lat and lon or zip instead.
For details see OpenWeatherMap's API documentation.
# get data by city name and country code
>>> data = owm.get_current("Kassel,DE")
# get data by city id and set language to german (DE)
>>> data = owm.get_current(2892518, lang="DE")
# get data by latitude and longitude and return temperatures in Celcius
>>> location = (51.32, 9.5)
>>> data = owm.get_current(location, units="metric")
# optional: skip city argument and get data by zip code
>>> data = owm.get_current(zip="34128,DE")
# access single item
>>> data("main.temp")
11.06
# access multiple items at once
>>> keys = ["main.temp", "main.humidity", "wind.speed"]
>>> data.get_many(keys)
(11.06, 58, 6.2)
# alternative access
>>> data(*keys)
(11.06, 58, 6.2)
# get data for 'Malaga,ES', 'Kassel,DE', 'New York,US'
>>> city_ids = (2892518, 2514256, 5128581)
>>> data = owm.get_current_for_group(city_ids, units="metric", lang="DE")
>>> data_malaga = data[0]
# find city by name and return data for match(es)
>>> data = owm.find_city("Malaga")
# get data for 5 cities around geographic coordinates
>>> location = (51.32, 9.5)
>>> data = owm.find_cities_by_geo_coord(location, 5)
# get data from station
>>> data = owm.get_current_from_station(4926)
# get stations by geographic coordinates
>>> location = (51.32, 9.5)
>>> data = owm.find_stations_by_geo_coord(location)Forecast data
City can be given as shown in the examples above.
# get 3h forecast data
>>> data = owm.get_forecast_hourly("Kassel,DE", lang="DE")
# get daily forecast data for 7 days
>>> data = owm.get_forecast_daily("Kassel,DE", 7, units="metric")
# show meta data
>>> data.meta
{u'city': {u'country': u'DE', u'population': 0, u'id': 2892518,
u'coord': {u'lat': 51.316669, u'lon': 9.5}, u'name': u'Kassel'},
u'message': 0.0185, u'cod': u'200', u'cnt': 7}
# get coordinates and id
>>> data.meta(*["city.coord", "city.id"])
({u'lat': 51.316669, u'lon': 9.5}, 2892518)
# select columns
>>> selection = data.select(["dt", "temp.min", "temp.max"])
>>> for line in selection:
... line
...
(1437044400, 16.63, 24.99)
(1437130800, 18.21, 30.17)
(1437217200, 14.96, 26.35)
(1437303600, 15.82, 23.49)
(1437390000, 15.52, 23.95)
(1437476400, 18.77, 29.11)
(1437562800, 14.67, 27.11)
# convert column "dt" to datetime string
>>> from datetime import datetime as dt
>>> conv = {"dt": lambda ts: str(dt.utcfromtimestamp(ts))}
>>> selection = data.select(["dt", "temp.min", "temp.max"], converters=conv)
>>> for line in selection:
... line
...
('2015-07-16 11:00:00', 16.63, 24.99)
('2015-07-17 11:00:00', 18.21, 30.17)
('2015-07-18 11:00:00', 14.96, 26.35)
('2015-07-19 11:00:00', 15.82, 23.49)
('2015-07-20 11:00:00', 15.52, 23.95)
('2015-07-21 11:00:00', 18.77, 29.11)
('2015-07-22 11:00:00', 14.67, 27.11)Historical data
For a complete list of parameters as start, end etc., which can be passed, please refer
to OpenWeatherMap's API documention.
# get historical data for city
>>> data = owm.get_history("Kassel,DE")
# get historical data from station
>>> data = owm.get_history_from_station(4926)Customization
You can customize or extend the lib to your needs by using the wrapper function wrap_get or the decorator
class GetDecorator. Both are more or less the same. As first argument the appendix to the base url needs
to be given. Optionally a dictionary with parameters and a data converter can be passed.
# show base url
>>> owm.BASE_URL
'http://api.openweathermap.org/data/2.5/'
# base url for fetching current weather data
>>> appendix = "weather"
>>> owm.BASE_URL+appendix
'http://api.openweathermap.org/data/2.5/weather'
# create a function to get current weather data and return temperatures in Celsius (units="metric")
>>> f = wrap_get("weather", dict(units="metric"))
>>> data = f("London,UK")
>>> data_de = f(zip="34128,DE", lang="DE")
