Welcome to forecast-weather’s documentation!¶
Overview¶
forecast-weather is a library that allows a user to easily obtain weather data (temperatures, pressure, humidity, precipitation, wind, cloud coverage, etc.) across various locations and dates. The library will make calls to a public weather API and will organize the returned data for ease of use. Some extra functionality in consideration include some form of visual plot/graph generation.
Install¶
pip install forecast-weather
API Key¶
Go to weatherapi.com to register an account for your free api key. Create a new file ./api_key and paste your api key here.
Usage¶
import forecast_weather as fw
fw.show_current(location = "10027")
fw.show_forecast(location = "10027", days = "2")
current = fw.get_current(location = "10027")
forecast = fw.get_forecast(location = "10027", days = "3")
Examples¶
Running the following code
import forecast_weather as fw fw.show_current(location = "10027")
Outputs something like this to the console
Current weather at New York is: Temperature: 68.0 F/ 20.0 C Condition: Overcast Wind speed: 2.2 mph Pressure: 1017.0 mb Precipitation: 0.0 in Humidity: 55% Cloud coverage: 100% UV: 4.0
Running the following code
import forecast_weather as fw d = fw.get_current(location = "10027")
Saves a dictionary like
{ 'name': 'New York', 'condition': 'Clear', 'temp_c': 17.8, 'temp_f': 64.0, 'wind_mph': 2.2, 'pressure_mb': 1019.0, 'precip_in': 0.0, 'humidity': 73, 'cloud': 0, 'uv': 1.0 }
Running the following code
import forecast_weather as fw fw.show_forecast(location = "10027", days = "2")
Outputs something like this to the console
2023-04-04 weather forecast of New York is: Average temperature: 55.7 F/ 13.2 C Condition: Cloudy Max wind speed: 8.3 mph Total precipitation: 0.0 in Average humidity: 84.0% UV: 3.0 2023-04-05 weather forecast of New York is: Average temperature: 51.0 F/ 10.6 C Condition: Overcast Max wind speed: 12.5 mph Total precipitation: 0.0 in Average humidity: 92.0% UV: 3.0
Running the following code
import forecast_weather as fw d = fw.get_forecast(location = "10027", days = "2")
Saves a dictionary like
{ 'name': 'New York', '2023-04-04': { 'avgtemp_f': 55.7, 'avgtemp_c': 13.2, 'condition': 'Cloudy', 'maxwind_mph': 8.3, 'totalprecip_in': 0.0, 'avghumidity': 84.0, 'uv': 3.0 }, '2023-04-05': { 'avgtemp_f': 51.0, 'avgtemp_c': 10.6, 'condition': 'Overcast', 'maxwind_mph': 12.5, 'totalprecip_in': 0.0, 'avghumidity': 92.0, 'uv': 3.0 } }
Demo¶
