tableau_analytics_connection_openweathermap_basic.py

import requests
import pandas as pd
from datetime import datetime, timezone

api_key = 'xxxxxxxxxx'  # Replace with your OpenWeatherMap API key
location_name = "San Diego"
lon = -117.16017202682153
lat = 32.7054914849287


def wind_deg_to_windrose(deg):
    # convert degrees to windrose direction
    directions = ['N', 'NNE', 'NE', 'ENE', 'E', 'ESE', 'SE', 'SSE', 'S', 'SSW', 'SW', 'WSW', 'W', 'WNW', 'NW', 'NNW']
    idx = int((deg + 11.25) / 22.5) % 16
    return directions[idx]

def convert_data(data):
    # convert weather data from OWM to a table expected by Tableau

    # Create a list to hold the daily data
    daily_data = []

    for day in data['daily']:
        # Extract the date and temperature information
        day_data = {
            'date': datetime.fromtimestamp(day['dt'], tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
            'temp_min': day['temp']['min'],
            'temp_max': day['temp']['max'],
            'temp_day': day['temp']['day'],
            'temp_night': day['temp']['night'],
            'temp_eve': day['temp']['eve'],
            'temp_morn': day['temp']['morn'],
            'feels_like_day': day['feels_like']['day'],
            'feels_like_night': day['feels_like']['night'],
            'feels_like_eve': day['feels_like']['eve'],
            'feels_like_morn': day['feels_like']['morn'],

            'pressure': day['pressure'],
            'humidity': day['humidity'] / 100,
            'dew_point': day['dew_point'],
            'wind_speed': day['wind_speed'],

            'wind_deg': day['wind_deg'],
            'wind_gust': day['wind_gust'],

            'weather_0_id': day['weather'][0]['id'],
            'weather_0_main': day['weather'][0]['main'],
            'weather_0_description': day['weather'][0]['description'],
            'weather_0_icon': day['weather'][0]['icon'],
            'weather_0_icon_url': 'https://openweathermap.org/img/wn/' + day['weather'][0]['icon'] + '@2x.png',

            'weather_clouds': day['clouds'],
            'weather_pop': day['pop'],
            'weather_uvi': day['uvi'],

            'sunrise': datetime.fromtimestamp(day['sunrise'], tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
            'sunset': datetime.fromtimestamp(day['sunset'], tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
            'moonrise': datetime.fromtimestamp(day['moonrise'], tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
            'moonset': datetime.fromtimestamp(day['moonset'], tz=timezone.utc).strftime('%Y-%m-%d %H:%M:%S'),
            'moon_phase': day['moon_phase'],
            'summary': day['summary']
        }
        daily_data.append(day_data)

    # Convert the list of dictionaries to a DataFrame
    df = pd.DataFrame(daily_data)

    # Convert 'date' column to datetime type
    df['date'] = pd.to_datetime(df['date'])

    # Convert datetime fields to string to make them JSON serializable
    df['date'] = df['date'].dt.strftime('%Y-%m-%d %H:%M:%S')

    # Add all temperature conversions
    temp_fields = ['temp_min', 'temp_max', 'temp_day', 'temp_night', 'temp_eve', 'temp_morn',
                   'feels_like_day', 'feels_like_night', 'feels_like_eve', 'feels_like_morn', 'dew_point']

    for field in temp_fields:
        df[f'{field}_celsius'] = df[field] - 273.15
        df[f'{field}_fahrenheit'] = (df[field] - 273.15) * 9 / 5 + 32

    # Convert wind_deg to windrose location
    df['windrose'] = df['wind_deg'].apply(wind_deg_to_windrose)

    return df.to_dict(orient='list')

def get_weather(location_name, lon, lat, api_key):
    # get the weather data from OWM
    url = f"https://api.openweathermap.org/data/3.0/onecall?lat={lat}&lon={lon}&exclude=hourly&appid={api_key}"
    response = requests.get(url)
    data = response.json()
    if response.status_code == 200:
        return data
    else:
        return data.get('message', 'Error fetching data')

# Fetch weather data and process it
weather_data = get_weather(location_name, lon, lat, api_key)
tabdata = convert_data(weather_data)

# Call the function and print the result
return(tabdata)