from typing import cast

from dash import (
    Dash,
    html,
    dcc,
    callback,
    Output,
    Input,
    State,
    dash_table,
)
import plotly.express as px
import pandas as pd
from pandas import DataFrame

from lang_main import load_pickle
from lang_main.types import TimelineCandidates, ObjectID

#df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminder_unfiltered.csv')

# ** data
data = cast(DataFrame, load_pickle('./data.pkl'))
cands = cast(TimelineCandidates, load_pickle('./map_candidates.pkl'))
texts = cast(dict[ObjectID, str], load_pickle('./map_texts.pkl'))
table_feats = [
    'ErstellungsDatum',
    'ErledigungsDatum',
    'VorgangsTypName',
    'VorgangsBeschreibung',
]
table_feats_dates = [
    'ErstellungsDatum',
    'ErledigungsDatum',
]

# ** graph config
markers = {
    'size': 12,
    'color': 'yellow',
    'line': {
        'width': 2,
        'color': 'red',
    },
}
hover_data = {
    'ErstellungsDatum': '|%d.%m.%Y',
    'VorgangsBeschreibung': True,
}


app = Dash(prevent_initial_callbacks=True)

app.layout = [
    html.H1(children='Demo Zeitreihenanalyse', style={'textAlign':'center'}),
    html.Div(children=[
        html.H2('Wählen Sie ein Objekt aus (ObjektID):'),
        dcc.Dropdown(
            list(cands.keys()),
            id='dropdown-selection',
            placeholder="ObjektID auswählen...",
        )
    ]),
    html.Div(children=[
        html.H3(id='object_text'),
        dcc.Dropdown(id='choice-candidates'),
        dcc.Graph(id='graph-output'),
    ]),
    html.Div(children=[
        dash_table.DataTable(id='table-candidates')
    ]),
]

@callback(
    Output('object_text', 'children'),
    Input('dropdown-selection', 'value'),
    prevent_initial_call=True,
)
def update_obj_text(obj_id):
    obj_id = int(obj_id)
    obj_text = texts[obj_id]
    headline = f'HObjektText: {obj_text}'
    return headline

@callback(
    Output('choice-candidates', 'options'),
    Input('dropdown-selection', 'value'),
    prevent_initial_call=True,
)
def update_choice_candidates(obj_id):
    obj_id = int(obj_id)
    cands_obj_id = cands[obj_id]
    choices = list(range(1, len(cands_obj_id)+1))
    return choices

@callback(
    Output('graph-output', 'figure'),
    Input('choice-candidates', 'value'),
    State('dropdown-selection', 'value'),
    prevent_initial_call=True,
)
def update_timeline(index, obj_id):
    obj_id = int(obj_id)
    # title
    obj_text = texts[obj_id]
    title = f'HObjektText: {obj_text}'
    # cands
    cands_obj_id = cands[obj_id]
    cands_choice = cands_obj_id[int(index)-1]
    # data
    df = data.loc[list(cands_choice)].sort_index()
    # figure
    fig = px.line(
        data_frame=df,
        x='ErstellungsDatum',
        y='ObjektID',
        title=title,
        hover_data=hover_data,
    )
    fig.update_traces(
        mode='markers+lines',
        marker=markers,
        marker_symbol='diamond'
    )
    fig.update_xaxes(
        tickformat="%B\n%Y",
        rangeslider_visible=True,
    )
    fig.update_yaxes(type='category')
    fig.update_layout(hovermode="x unified")
    return fig

@callback(
    [Output('table-candidates', 'data'),
     Output('table-candidates', 'columns')],
    Input('choice-candidates', 'value'),
    State('dropdown-selection', 'value'),
    prevent_initial_call=True,
)
def update_table_candidates(index, obj_id):
    obj_id = int(obj_id)
    # cands
    cands_obj_id = cands[obj_id]
    cands_choice = cands_obj_id[int(index)-1]
    # data
    df = data.loc[list(cands_choice)].sort_index()
    df = (df
          .filter(items=table_feats, axis=1)
          .sort_values(by='ErstellungsDatum', ascending=True))
    cols = [{"name": i, "id": i} for i in df.columns]
    # convert dates to strings
    for col in table_feats_dates:
        df[col] = df[col].dt.strftime(r'%Y-%m-%d')
    
    table_data = df.to_dict('records')
    return table_data, cols

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