realtime_dashboard.py

# I saved my API key in a separate file and import the key here
# Please comment out this line and define your API key as openweathermap_api_key = 'XXXXXX'
from openweathermap_api_key import openweathermap_api_key

import operator as op
import numpy as np
import pandas as pd
import requests
import param
import panel as pn
import hvplot.pandas
import hvplot.streamz
import holoviews as hv
from holoviews.element.tiles import EsriImagery
from holoviews.selection import link_selections
from datashader.utils import lnglat_to_meters
from streamz.dataframe import PeriodicDataFrame


def weather_data(cities, openweathermap_api_key=openweathermap_api_key):
    """
    Get weather data for a list of cities using the openweathermap API
    """
    L = []
    for c in cities:
        res = requests.get(f'http://api.openweathermap.org/data/2.5/weather?q={c}&appid={openweathermap_api_key}&units=imperial')
        L.append(res.json())

    df = pd.DataFrame(L)
    df['lon'] = df['coord'].map(op.itemgetter('lon'))
    df['lat'] = df['coord'].map(op.itemgetter('lat'))
    df['Temprature'] = df['main'].map(op.itemgetter('temp'))
    df['Humidity'] = df['main'].map(op.itemgetter('humidity'))
    df['Wind Speed'] = df['wind'].map(op.itemgetter('speed'))
    return df[['name','lon', 'lat','Temprature','Humidity','Wind Speed']]
    
# REAL TIME 
def streaming_weather_data(**kwargs):
    """
    callback function 
    get San Francisco weather data 
    """
    df = weather_data(['San Francisco'])
    df['time'] = [pd.Timestamp.now()]
    return df.set_index('time')

# Make a streaming dataframe 
df = PeriodicDataFrame(streaming_weather_data, interval='30s')
# panel dashboard for streaming data 
pn_realtime = pn.Column(
    pn.Row(
        df[['Temprature']].hvplot.line(title='Temprature', backlog=1000),
        df[['Humidity']].hvplot.line(title='Humidity', backlog=1000)),
    df[['Wind Speed']].hvplot.line(title='Wind Speed', backlog=1000)
)


cities = ['San Francisco', 'Los Angeles', 'Santa Barbara', 'Sacramento', 'Fresno','San Diego', 'San Luis Obispo']

def weather_plot(col, cities=cities):
    """
    plot weather data on a map 
    col: 'Temprature', 'Humidity', 'Wind Speed'
    """
    df = weather_data(cities)
    df['x'], df['y'] = lnglat_to_meters(df['lon'], df['lat'])
    table = hv.Table(df[['name', col]]).opts(width=800)
    points = df.hvplot.scatter('x','y', c=col, cmap='bkr', hover_cols=['name'])
    map_tiles  = EsriImagery().opts(alpha=0.5, width=900, height=480, bgcolor='white')
    return  pn.Column(points * map_tiles, table)
    
    
# REFRESH
class refresh_weather_dashboard(param.Parameterized):
    action = param.Action(lambda x: x.param.trigger('action'), label='Refresh')
    select_column = param.ObjectSelector(default='Temprature', objects=['Temprature', 'Humidity', 'Wind Speed'])

       
    @param.depends('action', 'select_column')
    def get_plot(self):
        return weather_plot(self.select_column)

    
weather_dashboard = refresh_weather_dashboard()

pn_weather = pn.Column(
       pn.panel(weather_dashboard.param, show_labels=True, show_name=False, margin=0),
       weather_dashboard.get_plot, width=400
)

# COMBINE TWO DASHBOARDS
pane = pn.Tabs(
    ('Real Time', pn_realtime),
    ('Refresh Weather Dashboard', pn_weather)
    ).servable()

pane