import pandas as pd
from dash import Dash, html, dash_table, dcc, callback
from dash.dependencies import Input, Output
import plotly.express as px
from datetime import datetime
import plotly.graph_objects as go

df = pd.read_csv('Data.csv')
df_reversed = df.iloc[::-1]

pressure = df['Barometric Pressure'].iloc[-1]
humidity = df['Humidity'].iloc[-1]


app = Dash(__name__)

app.layout = html.Div([
    html.H1('Wetter'),

    html.Div([
        dcc.Graph(id='temperature-indicator'),
        dcc.Graph(id='pressure-indicator'),
        dcc.Graph(id='humidity-indicator')
], style={'display': 'flex'}),
    dcc.RadioItems([{'label': 'Temperature', 'value': 'Temperature'},
                   {'label': 'Barometric Pressure', 'value': 'Barometric Pressure'},
                   {'label': 'Humidity', 'value': 'Humidity'}],
                  inline=True,
                  id='radioitem',
                  value='Barometric Pressure'),
    dcc.Graph(id='Pressure'),
    dash_table.DataTable(
        id='wetter',
        data=df_reversed.to_dict('records'),
        columns=[{'name': i, 'id': i} for i in df.columns],
        sort_mode='single',
        sort_action='native',
        style_cell={'textAlign': 'center'}),
    dcc.Interval(
        id='update',
        interval=10000,
        n_intervals=0)
])


@callback(Output('temperature-indicator', 'figure'),
          Input('update', 'n_intervals'))
def temp_update(n):
    df = pd.read_csv('Data.csv')
    temperature = df['Temperature'].iloc[-1]
    figure = go.Figure(
        go.Indicator(
            mode="gauge+number",
            value=temperature,
            title={'text': "Temperature (°C)"},
            gauge={'axis': {'range': [-20, 40]},
                   'bar': {'color': 'red'}}))
    return figure


@callback(Output('pressure-indicator', 'figure'),
          Input('update', 'n_intervals'))
def pressure_update(n):
    df = pd.read_csv('Data.csv')
    pressure = df['Barometric Pressure'].iloc[-1]
    figure = go.Figure(
        go.Indicator(
            mode="gauge+number",
            value=pressure,
            number={'valueformat': '.2f'},
            title={'text': "Barometric Pressure"},
            gauge={'axis': {'range': [500, 1300]}}))
    return figure


@callback(Output('humidity-indicator', 'figure'),
          Input('update', 'n_intervals'))
def temp_update(n):
    df = pd.read_csv('Data.csv')
    humidity = df['Humidity'].iloc[-1]
    figure = go.Figure(
        go.Indicator(
            mode="gauge+number",
            value=humidity,
            title={'text': "Humidity"},
            gauge={'axis': {'range': [0, 100]},
                   'bar': {'color': 'blue'}}))
    return figure


@callback(Output('wetter', 'data'),
          Input('update', 'n_intervals'))
def get_update(n):
    df = pd.read_csv('Data.csv')
    df_reversed = df.iloc[::-1]
    return df_reversed.to_dict('records')


@callback(Output('Pressure', 'figure'),
          Input('update', 'n_intervals'),
          Input('radioitem', 'value'))
def update_graph(n, x):
    df = pd.read_csv('Data.csv')
    today = datetime.today().date()
    df_filtered = df.tail(60).copy()
    df_filtered['Date'] = pd.to_datetime(df_filtered['Date'], dayfirst=True)
    df_filtered = df_filtered[df_filtered['Date'].dt.date == today]
    fig = px.line(df_filtered, x='Time', y=x)
    return fig


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