# Copyright (c) 2022 Cisco and/or its affiliates. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at: # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Instantiate the Report Dash application. """ import dash from dash import dcc from dash import html from dash import dash_table from .data import read_stats from .data import read_trending_mrr, read_trending_ndrpdr from .data import read_iterative_mrr, read_iterative_ndrpdr from .layout import html_layout def init_report(server): """Create a Plotly Dash dashboard. :param server: Flask server. :type server: Flask :returns: Dash app server. :rtype: Dash """ dash_app = dash.Dash( server=server, routes_pathname_prefix=u"/report/", external_stylesheets=[ u"/static/dist/css/styles.css", u"https://fonts.googleapis.com/css?family=Lato", ], ) # Custom HTML layout dash_app.index_string = html_layout # Create Layout dash_app.layout = html.Div( children=[ html.Div( children=create_data_table( read_stats().dropna(), u"database-table-stats" ) ), html.Div( children=create_data_table( read_trending_mrr().dropna(), u"database-table-mrr" ) ), html.Div( children=create_data_table( read_trending_ndrpdr().dropna(), u"database-table-ndrpdr" ) ), html.Div( children=create_data_table( read_iterative_mrr().dropna(), u"database-table-iterative-mrr" ) ), html.Div( children=create_data_table( read_iterative_ndrpdr().dropna(), u"database-table-iterative-ndrpdr" ) ) ], id=u"dash-container", ) return dash_app.server def create_data_table(df, id): """Create Dash datatable from Pandas DataFrame. DEMO """ table = dash_table.DataTable( id=id, columns=[{u"name": i, u"id": i} for i in df.columns], data=df.to_dict(u"records"), fixed_rows={'headers': True}, sort_action=u"native", sort_mode=u"native", page_size=5, style_header={ 'overflow': 'hidden', 'textOverflow': 'ellipsis', 'minWidth': 95, 'maxWidth': 95, 'width': 95, } ) return table