How to use the Frogcast weather REST API?

Here, you'll get the total cloud cover (tcc) data and the temperature p80 quantile (t2m) for the desired location for the next 10 days with a time step of 30 minutes.

As you can see, the request uses a simple address (https://api.frogcast.com/api/v1/forecast/) to which a set of parameters (some optional) can be associated:
➡️ Latitude/longitude (mandatory)
➡️ Fields (mandatory): the list of weather variables you want (or use a GET request to access the list of available meteorological variables : https://api.frogcast.com/api/v1/allfields/)
➡️ Horizon (optional, default = 21600): forecast horizon in minutes,
➡️ Time_step (optional, default=60): data time step in minutes, available: 1,5,10,15,30,60. An interpolation is performed to go below the hour, we recommend keeping the hour as the working base.
➡️ Format (optional, available default, json, recommended to use json)
➡️ Precision (optional, default = 2 digits)

Of course, for the development of your applications, you do not make calls in your browser; however, the final URL will remain the same, only your credentials will need to be transmitted additionally.


Python code exemple:

import pandas as pd

import requests
headers = {'Authorization':'Token {your token}'}

url = 'https://api.frogcast.com/api/v1/forecast/'

parameters = {'latitude':45.63562,
'longitude': 5.63256,
'time_step':60,
'horizon':2880,
'fields':"ghi"}

api_data = requests.get(url=url,params=parameters,headers=headers).json()

forecast = pd.DataFrame(data=api_data['data'], index=api_data['index'], columns=api_data['columns'])

print(forecast)

We have added in this example the formatting of the data into a dataframe, which is a basic structure for using data in Python.