This program calculates and outputs a snowboarding index (SBI) for a supplied location based on a weighted mix of 5 different data types. It calculates hourly indices and summarizes the next 8 hours, weighting the immediate and near future values higher.

• Snowfall rate (averaged over previous 3 hours), as a rough proxy for snow depth
• Snowfall rate (at timestamp)
• Temperature
• Wind speed
• 'Feels Like' temperature

Once installed, execute by python -m snowboarding_index. If no location is provided, IP address geolocation will be used.

python3 -m snowboarding_index -l 12345

python3 -m snowboarding_index -l "minneapolis, mn"

-l, --location: supply a location, either as a ZIP code or human readable name (e.g., Minneapolis, MN)

-j, --json: export a JSON string matching the AerisWeather Index API format

-h, --help: this information presented in the terminal.

See combined installation commands for quick copy-paste installation.

1. Download the code from Github manually or with git: git clone [email protected]:skydeo/API_Challenge.git
2. Navigate to the folder
3. (Optional) Create and activate a virutal environment: python3 -m venv venv/ source venv/bin/activate
4. Install requirements pip install -r requirements.txt
5. Configure a .env file in the root directory with an AerisWeather client_id and client_secret
6. Run the package python3 -m snowboarding_index

This assumes an .env files has already been created (step 5 above).

git clone [email protected]:skydeo/API_Challenge.git
cd API_Challenge
python3 -m venv venv/
source venv/bin/activate
pip install -r requirements.txt
python3 -m snowboarding_index