lang-main/test-notebooks/dashboard/app.py

import time
import webbrowser
from pathlib import Path
from threading import Thread
from typing import cast

import pandas as pd
import plotly.express as px
from dash import (
    Dash,
    Input,
    Output,
    State,
    callback,
    dash_table,
    dcc,
    html,
)
from lang_main import CALLER_PATH
from lang_main.io import load_pickle
from lang_main.types import ObjectID, TimelineCandidates
from pandas import DataFrame

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

# ** data
# p_df = Path(r'.\test-notebooks\dashboard\Pipe-TargetFeature_Step-3_remove_NA.pkl')
p_df = CALLER_PATH.joinpath('./Pipe-TargetFeature_Step-3_remove_NA.pkl')
# p_tl = Path(
#     r'.\test-notebooks\dashboard\Pipe-Timeline_Analysis_Step-4_get_timeline_candidates.pkl'
# )
p_tl = CALLER_PATH.joinpath('./Pipe-Timeline_Analysis_Step-4_get_timeline_candidates.pkl')
ret = cast(DataFrame, load_pickle(p_df))
data = ret[0]
ret = cast(tuple[TimelineCandidates, dict[ObjectID, str]], load_pickle(p_tl))
cands = ret[0]
texts = ret[1]

# p_df = Path(r'.\test-notebooks\dashboard\data.pkl')
# p_cands = Path(r'.\test-notebooks\dashboard\map_candidates.pkl')
# p_map = Path(r'.\test-notebooks\dashboard\map_texts.pkl')
# data = cast(DataFrame, load_pickle(p_df))
# cands = cast(TimelineCandidates, load_pickle(p_cands))
# texts = cast(dict[ObjectID, str], load_pickle(p_map))

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


def _start_webbrowser():
    host = '127.0.0.1'
    port = '8050'
    adress = f'http://{host}:{port}/'
    time.sleep(2)
    webbrowser.open_new(adress)


def main():
    webbrowser_thread = Thread(target=_start_webbrowser, daemon=True)
    webbrowser_thread.start()
    app.run(debug=True)


if __name__ == '__main__':
    main()