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# 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
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