# Import required libraries
import pandas as pd
import dash
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output
import plotly.express as px

# Read the airline data into pandas dataframe
spacex_df = pd.read_csv("spacex_launch_dash.csv")
max_payload = spacex_df['Payload Mass (kg)'].max()
min_payload = spacex_df['Payload Mass (kg)'].min()

# Create a dash application
app = dash.Dash(__name__)
# Unique Launch Sites
uniquelaunchsite = spacex_df['Launch Site'].unique().tolist()
launchsites=[]
launchsites.append({'label':'All Sites','value':'All Sites'})
for site in uniquelaunchsite:
    launchsites.append({'label':site,'value':site})
# Create an app layout
app.layout = html.Div(children=[html.H1('SpaceX Launch Records Dashboard',
                                        style={'textAlign': 'center', 'color': '#503D36',
                                               'font-size': 40}),
                                # TASK 1: Add a dropdown list to enable Launch Site selection
                                # The default select value is for ALL sites
                                dcc.Dropdown(id='site-dropdown',
                                            options=launchsites,
                                            value='ALL',
                                            placeholder="Select a Launch Site here",
                                            searchable=True
                                            ),
                                html.Br(),

                                # TASK 2: Add a pie chart to show the total successful launches count for all sites
                                # If a specific launch site was selected, show the Success vs. Failed counts for the site
                                html.Div(dcc.Graph(id='success-pie-chart')),
                                html.Br(),

                                html.P("Payload range (Kg):"),
                                # TASK 3: Add a slider to select payload range
                                dcc.RangeSlider(id='payload-slider',
                                                min=0, max=10000, step=1000,
                                                marks={
                                                    0: '0',
                                                    100: '100'
                                                },
                                                value=[min_payload, max_payload]
                                                ),

                                # TASK 4: Add a scatter chart to show the correlation between payload and launch success
                                html.Div(dcc.Graph(id='success-payload-scatter-chart')),
                                ])

# TASK 2:
# Add a callback function for `site-dropdown` as input, `success-pie-chart` as output
@app.callback(
    Output(component_id='success-pie-chart', component_property='figure'),
    Input(component_id='site-dropdown',component_property='value')
    )
def update_graph(site_dropdown):
    if (site_dropdown == 'All Sites'):
        df  = spacex_df[spacex_df['class'] == 1]
        fig = px.pie(df, names = 'Launch Site',hole=.3,title = 'Total Success Launches By all sites')
    else:
        df  = spacex_df.loc[spacex_df['Launch Site'] == site_dropdown]
        fig = px.pie(df, names = 'class',hole=.3,title = 'Total Success Launches for site '+site_dropdown)
    return fig
        
# TASK 4:
# Add a callback function for `site-dropdown` and `payload-slider` as inputs, `success-payload-scatter-chart` as output
@app.callback(
    Output(component_id='success-payload-scatter-chart', component_property='figure'),
    [Input(component_id='site-dropdown',component_property='value'),
     Input(component_id='payload-slider',component_property='value')]
)
def update_scattergraph(site_dropdown,payload_slider):
    if site_dropdown == 'All Sites':
        low, high = payload_slider
        df  = spacex_df
        mask = (df['Payload Mass (kg)'] > low) & (df['Payload Mass (kg)'] < high)
        fig = px.scatter(
            df[mask], x="Payload Mass (kg)", y="class", 
            color="Booster Version",
            size='Payload Mass (kg)',
            hover_data=['Payload Mass (kg)'])
    else:
        low, high = payload_slider
        df  = spacex_df.loc[spacex_df['Launch Site'] == site_dropdown]
        mask = (df['Payload Mass (kg)'] > low) & (df['Payload Mass (kg)'] < high)
        fig = px.scatter(
            df[mask], x="Payload Mass (kg)", y="class", 
            color="Booster Version",
            size='Payload Mass (kg)',
            hover_data=['Payload Mass (kg)'])
    return fig
# Run the app
if __name__ == '__main__':
    app.run_server()
