pyweatherbit 2.1.0

A python weather api wrapper for the Weatherbit.io API.

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Python Weather API - Pyweatherbit

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This is a wrapper for the Weatherbit API.

The Weatherbit IO allows you to access forecasts, current data, and historical data. This library wraps this functionality, and makes it accessible with Python.

Installation

You should use pip to install pyweatherbit.

• To install: pip install pyweatherbit
• To remove: pip uninstall pyweatherbit

Requirements

• You need an API key to use it. Sign up for the free api key to get started.

Basic Use

For additional information, refer to the Weatherbit.io API documentation .

To use the wrapper:

	from weatherbit.api import Api
	api_key = "YOUR API KEY"
	lat = 38.00
	lon = -125.75

	api = Api(api_key)

	# Set the granularity of the API - Options: ['daily','hourly','subhourly']
	# Depends on supported granularity of API - please see https://www.weatherbit.io/api
	# Currently supported:
	# History: daily, hourly, subhourly
	# Forecast: daily, hourly
	# Air quality: hourly
	# Will only affect forecast requests.
	api.set_granularity('daily')

	# Query by lat/lon
	forecast = api.get_forecast(lat=lat, lon=lon)

	# You can also query by city:
	forecast = api.get_forecast(city="Raleigh,NC")

	# Or City, state, and country:
	forecast = api.get_forecast(city="Raleigh", state="North Carolina", country="US")

	# To get a daily forecast of temperature, and precipitation:
	print(forecast.get_series(['temp','precip','solar_rad']))


	# Get an hourly air quality forecast for a lat/lon
	forecast_AQ = api.get_forecast(source='airquality', lat=lat, lon=lon)
	print(forecast_AQ.get_series(['aqi','pm10','no2']))


	### HISTORY

	# Get sub-hourly history by lat/lon:
	api.set_granularity('subhourly')
	history = api.get_history(lat=lat, lon=lon, start_date='2018-02-01',end_date='2018-02-02')

	# To get a daily time series of temperature, precipitation, and rh:
	print history.get_series(['precip','temp','rh'])

	# Get hourly history by lat/lon
	api.set_granularity('hourly')
	history = api.get_history(lat=lat, lon=lon, start_date='2018-02-01',end_date='2018-02-02')
	
	# To get an hourly time series of temperature, precipitation, and rh:
	print(history.get_series(['precip','temp','rh','solar_rad']))

	# Get historical air quality data
	history_AQ = api.get_history(source='airquality', lat=lat, lon=lon, start_date='2018-02-01',end_date='2018-02-02')
	print(history_AQ.get_series(['aqi','pm10','no2']))


	### Current Conditions

	# Get current air quality
	AQ = api.get_current(source='airquality', city="Raleigh", state="North Carolina", country="US")
	print(AQ.get_series(['aqi','pm10','pm25']))

	# Get current conditions
	current_weather = api.get_current(city="Raleigh", state="North Carolina", country="US")
	print(current_weather.get_series(['weather','temp','precip']))

	...

The get_forecast() method requires named parameters. The current choices are either (lat=..., lon=...), (city="City,ST"), or (city=..., state=..., country=...)

Advanced

function weatherbit.Api.get_forecast(lat=..., lon=...)

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This makes an API request and returns a Forecast object (see below).

Parameters:

• key - Your API key from https://www.weatherbit.io.
• lat - The latitude of the location for the forecast
• lon - The longitude of the location for the forecast
• units - (optional) A string of the preferred units of measurement. Choices are currently 'S' for scientific, 'M' for Metric, or 'I' for imperial units.

function weatherbit.Api.get_forecast(city=..., state=..., country=...)

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This makes an API request and returns a Forecast object (see below).

Parameters:

• key - Your API key from https://www.weatherbit.io.
• city - The City to search by. This can be appended with a state like -> "City,ST".
• state - (optional) State of location.
• country - (optional) Country of location
• units - (optional) A string of the preferred units of measurement. Choices are currently 'S' for scientific, 'M' for Metric, or 'I' for imperial units.

function weatherbit.Api.get_history(lat=..., lon=...)

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This makes an API request and returns a History object (see below).

Parameters:

• key - Your API key from https://www.weatherbit.io.
• lat - The latitude of the location for the forecast
• lon - The longitude of the location for the forecast
• units - (optional) A string of the preferred units of measurement. Choices are currently 'S' for scientific, 'M' for Metric, or 'I' for imperial units.

function weatherbit.Api.get_history(city=..., state=..., country=...)

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This makes an API request and returns a History object (see below).

Parameters:

• key - Your API key from https://www.weatherbit.io.
• city - The City to search by. This can be appended with a state like -> "City,ST".
• state - (optional) State of location.
• country - (optional) Country of location
• units - (optional) A string of the preferred units of measurement. Choices are currently 'S' for scientific, 'M' for Metric, or 'I' for imperial units.

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class forecastio.models.Forecast

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The Forecast object, it contains both weather data and the HTTP response from Weatherbit

Attributes

• http_headers
  - A dictionary of response headers.
• json - A dictionary containing the json data returned from the API call.
• city_name
  - City Name of the forecast points.
• country_code - Country Code of the forecast points
• state_code - State Code of the forecast points
• lat
  - Latitude of the forecast points
• lon
  - Longitude of the forecast points
• points
  • Array of forecast data Point objects.

Methods

• get_series([var1, var2, ... , varn])
  - Returns list of dicts sorted by datetime, containing the desired variables in a time series.
• update()
  - Refreshes the forecast data by making a new request.

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class forecastio.models.History

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The History object, it contains both weather data and the HTTP response from Weatherbit

Attributes

• response
  - The Response object returned from requests request.get() method.
• http_headers
  - A dictionary of response headers.
• json
  - A dictionary containing the json data returned from the API call.
• city_name
  - City Name of the historical points.
• country_code
  - Country Code of the historical points
• state_code
  - State Code of the historical points
• lat
  - Latitude of the historical points
• lon
  - Longitude of the historical points
• points
  • Array of historical data Point objects.

Methods

• get_series([var1, var2, ... , varn])
  - Returns list of dicts sorted by datetime, containing the desired variables in a time series.
• update()
  - Refreshes the forecast data by making a new request.

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class weatherbit.models.Point

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Contains data about a history or forecast over time.

Attributes

• snow
  - Total Snowfall.
• precip - Total Liquid equivalent precipitation.
• snow6h
  - 6h Total Snowfall.
• precip6h
  - 6h Total Liquid equivalent precipitation.
• datetime
  - Datetime object - Datetime (UTC).
• wind_dir
  - Average Wind direction in degrees (0-360).
• wind_spd
  - Average Wind speed.
• rh
  - Average Relative Humidity (%).
• clouds
  - Average Cloud cover (%).
• slp
  - Average Sea level pressure in millibars.
• temp
  - Average Temperature.
• max_temp
  - Maximum Temperature. (daily only)
• min_temp
  - Minimum Temperature. (daily only)
• weather
  - Dict containing day/night weather icon, description, and code.

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class weatherbit.models.SingleTimePoint

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Contains data about a single point in time - Current weather data.

Attributes

• snow
  - Total Snowfall.
• precip - Total Liquid equivalent precipitation.
• datetime
  - Datetime object - Datetime (UTC).
• sunrise
  - Datetime object - Sunrise time (UTC).
• sunset
  - Datetime object - Sunset time (UTC).
• wind_dir
  - Wind direction in degrees (0-360).
• wind_spd
  - Wind speed.
• rh
  - Relative Humidity (%).
• slp
  - Sea level pressure in millibars.
• temp
  - Temperature.
• clouds
  - Cloud cover (%).
• visibility
  - Visibility text (for METAR observations only).
• station
  - Station ID.
• weather
  - Dict containing day/night weather icon, description, and code.

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