PyCafe - Dash - Ultraviolet Index plotting app

app.py
requirements.txt
app.py
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import requests
import pandas as pd
import datetime as dt
import dash
from dash import dcc, html
import plotly.graph_objs as go

csv_url = 'https://docs.google.com/spreadsheets/d/16bEpYUm1Z2FpAjQOAQi8JEC3tRvOoAJZgV005v6RuEw/gviz/tq?tqx=out:csv'

def get_df():
    # Realiza la solicitud GET para descargar el CSV
    response = requests.get(csv_url)

    f = str(response.content)
    a = f.split(r'\n')[2:]

    lls = []
    c = len(a)
    for n,line in enumerate(a):
        ll = [i[1:-1] for i in line.split(',')]
        if n+1 == c:
            ll[-1] = ll[-1][:-1]
        lls.append(ll)


    df = pd.DataFrame(lls, columns=['datetime','val','iuv'])
    df = df[['datetime','iuv']]
    df['iuv'] = df.iuv.astype(float)
    df['datetime'] = pd.to_datetime(df.datetime, format = '%d/%m/%Y %H:%M')
    return df

df = get_df()
# Cargar datos
today = dt.datetime.now()
today_date = today.date()
df['datetime'] = pd.to_datetime(df.datetime, format='%d/%m/%Y %H:%M')
df['date'] = df.datetime.dt.date
today_data = df[df.date == today_date]

# Límites y colores
lims = [0, 3, 6, 8, 11, 20]
clrs = ['green', 'yellow', 'orange', 'red', 'blueviolet']

# Crear la aplicación Dash
app = dash.Dash(__name__)

# Definir la disposición de la aplicación
app.layout = html.Div([
    dcc.Graph(id='uv-graph'),
    dcc.Interval(
        id='interval-component',
        interval=60 * 1000,  # Actualiza cada 60 segundos
        n_intervals=0
    )
])

# Callback para generar la gráfica
@app.callback(
    dash.dependencies.Output('uv-graph', 'figure'),
    [dash.dependencies.Input('interval-component', 'n_intervals')]
)
def update_graph(n):
    # Cargar datos cada vez que se actualiza
    df = get_df()
    df['datetime'] = pd.to_datetime(df.datetime, format='%d/%m/%Y %H:%M')
    df['date'] = df.datetime.dt.date
    today_data = df[df.date == today_date]

    traces = []



    # Rellenar áreas
    for i in range(len(lims) - 1):
        traces.append(go.Scatter(
            x=[today_data['datetime'].min(), today_data['datetime'].max()],
            y=[lims[i+1], lims[i+1]],
            fill='tonexty',
            mode='lines',
            line=dict(color=clrs[i]),
            name='Rango UV',
            showlegend=False
        ))
    

    # Gráfica del Índice Ultravioleta
    traces.append(go.Scatter(
        x=today_data['datetime'],
        y=today_data['iuv'],
        mode='lines',
        name='Índice UV',
        line=dict(color='black')
    ))

    # Configuración de la gráfica
    layout = go.Layout(
        title=f'Índice UV Cota Cota {dt.datetime.strftime(today, "%d %b %Y")}',
        xaxis=dict(
            title='Hora Local',
            tickformat='%H:%M',
            dtick='1h',
            range=[today.replace(hour=7, minute=0), today.replace(hour=18, minute=0)],  # Limitar de 7 AM a 6 PM
            tickvals=pd.date_range(start=today.replace(hour=7, minute = 0), end=today.replace(hour=18, minute=0), freq='h'),  # Generar ticks
            ticktext=[(today.replace(hour=hour, minute = 0).strftime('%H:%M')) for hour in range(7, 19)]  # Formato de los ticks
        ),
        yaxis=dict(title='Índice Ultravioleta', range=[0, 20], tickmode='linear', tick0=0, dtick=5),
        showlegend=True,
        hovermode='closest'
    )

    figure = {'data': traces, 'layout': layout}
    return figure

if __name__ == '__main__':
    app.run_server(debug=True)
Py.Cafe

iuv_plotting

Ultraviolet Index plotting app
