def callback(__n_intervals__, *args, **kwargs):
result_key = json.dumps({"args": list(args), "kwargs": kwargs})
progress_key = result_key + "-progress"
result = cache.get(result_key)
progress = cache.get(progress_key)
if result is not None:
return dict(result=result, interval_disabled=True)
elif progress is not None:
return dict(
result=html.Progress(
value=str(progress[0]),
max=str(progress[1]),
id=progress_id,
style=progress_style,
),
interval_disabled=False,
)
else:
target = make_update_cache(fn, cache, result_key, progress_key)
p = Process(target=target, args=args, kwargs=kwargs)
p.start()
return dict(
result=html.Progress(id=progress_id, style=progress_style),
interval_disabled=False,
)
def get_loader(df=data):
"""
This function generates a loading bar that shows the current data you are working with and
its proportion to all data.
:param df: Initial data
:return: Loading bar for data used
:rtype: dcc.Loading
"""
return dcc.Loading(className='loader',
id='loading',
type='default',
children=[
dcc.Markdown(
id='data_summary_filtered',
children=f'{len(df):,d} taxi trips selected'),
html.Progress(id='selected_progress',
max=f'{initial_length}',
value=f'{len(df)}'),
])
import dash_core_components as dcc
from flask import Flask
from flask_socketio import SocketIO
from threading import Timer
eventlet.monkey_patch()
server = Flask(__name__, static_url_path='')
socket = SocketIO(server, async_mode='eventlet')
app = dash.Dash(__name__, server=server)
app.scripts.config.serve_locally = True
app.css.config.serve_locally = True
app.layout = html.Div([
sockettest.sockettest(),
html.Progress(id='progress', max=10, value=0),
dcc.Slider(id='slider', value=0, min=0, max=10, step=1),
html.Div(id='divspace'),
html.Div(id='dummy'),
html.Div(id='dummy1'),
html.Div(id='dummy2')
])
@app.callback(Output('dummy', 'children'), [Input('progress', 'value')])
def func(value):
print('progress', value)
return None
@app.callback(Output('dummy1', 'children'), [Input('divspace', 'children')])
'value': 'gao_dataset_noshap'
},
# {'label': 'waseem', 'value': 'waseem_dataset'},
# {'label': 'mnist-mini', 'value': 'mnist'},
],
clearable=False,
searchable=False,
value='')
submit_dataset = html.Button('Submit', id='start', autoFocus=True)
queries = dcc.Loading(html.Div(id='queries'))
url = dcc.Location(id='url')
progress_bar = html.Progress(id='progress', value=0, max=100)
###################
color = dcc.RadioItems(id='color',
options=[
{
'label': 'Color-code explanations',
'value': True
},
{
'label': 'No color-code for explanations',
'value': False
},
],
value=False)
_layout = html.Div(
className='row',
id=PAGE_ID,
children=[
# Controls | Html table
html.Div(className='four columns',
children=[
html.Div(dcc.Dropdown(id=ID('category'),
value=[],
multi=True,
placeholder='Category ...',
options=category_options()),
style={'display': 'block'}),
html.Div('loading ...', id=DISPLAY)
]),
html.Progress(max=100, value=60),
# modal display
html.Div(html.Div(html.Div(
[
html.Div([
html.
I(id=ID('modal-close'),
n_clicks=0,
className='fas fa-times w3-button w3-display-topright'),
html.H1(' ', id=ID('modal-header')),
],
className='w3-container w3-teal'),
html.Div(
[
dcc.Interval(
import dash
import dash_html_components as html
import dash_core_components as dcc
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
app.layout = html.Div([
dcc.Interval(id="progress-interval", n_intervals=0, interval=110),
html.Progress(id="html_progress",
max='100',
contentEditable="Yes",
children='Ohh Yess'),
dbc.Spinner(color="primary")
])
@app.callback(
[Output("html_progress", "value"),
Output("html_progress", "style")],
[Input("progress-interval", "n_intervals")],
)
def update_progress(n):
# check progress of some background process, in this example we'll just
# use n_intervals constrained to be in 0-100
progress = min(n % 110, 100)
#print(progress)
# only add text after 5% progress to ensure text isn't squashed too much
return str(progress), {
'content': 'progress',
'position': 'absolute',
def __init__(self, long_callback_manager=None):
"""
Parameters
----------
long_callback_manager
Optional callback manager for long callbacks.
See https://dash.plotly.com/long-callbacks
"""
super(BranchProInferenceApp, self).__init__()
self.app = dash.Dash(__name__,
external_stylesheets=self.css,
long_callback_manager=long_callback_manager)
self.app.title = 'BranchproInf'
self.session_data = {
'data_storage': None,
'interval_storage': None,
'posterior_storage': None
}
button_style = {
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
}
self.app.layout = html.Div([
dbc.Container(
[
html.H1('Branching Processes', id='page-title'),
html.Div([]), # Empty div for top explanation texts
html.H2('Incidence Data'),
dbc.Row(
dbc.Col(
dcc.Graph(figure=bp.IncidenceNumberPlot().figure,
id='data-fig'))),
dbc.Row(
[
dbc.Col(children=[
html.H6([
'You can upload your own ',
html.Span(
'incidence data',
id='inc-tooltip',
style={
'textDecoration': 'underline',
'cursor': 'pointer'
},
), ' here. It will appear as bars.'
]),
dbc.Modal(
self._inc_modal,
id='inc_modal',
size='xl',
),
html.Div([
'Data must be in the following column '
'format: `Time`, `Incidence number`, '
'`Imported Cases` (optional), '
'`R_t` (true value of R, optional).'
]),
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files',
style={
'text-decoration':
'underline'
}), ' to upload your Incidence \
Number data.'
]),
style=button_style,
# Allow multiple files to be uploaded
multiple=True),
html.Div(id='incidence-data-upload')
]),
dbc.Col(children=[
html.H6([
'You can upload your own ',
html.Span('serial interval',
id='si-tooltip',
style={
'textDecoration':
'underline',
'cursor': 'pointer'
}), ' here.'
]),
dbc.Modal(
self._si_modal,
id='si_modal',
size='lg',
),
html.Div([
'Data must contain one or more serial '
'intervals to be used for constructing'
' the posterior distributions each '
'included as a column.'
]),
dcc.Upload(
id='upload-interval',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files',
style={
'text-decoration':
'\
underline'
}), ' to upload your Serial \
Interval.'
]),
style=button_style,
# Allow multiple files to be uploaded
multiple=True),
html.Div(id='ser-interval-upload')
])
],
align='center',
),
html.H2('Plot of R values'),
html.Progress(id='progress_bar'),
html.Div(
id='first_run', # see flip_first_run() in the app
children='True',
style={'display': 'none'}),
dbc.Row(
[
dbc.Col(children=dcc.Graph(
figure=bp.ReproductionNumberPlot().figure,
id='posterior-fig',
style={'display': 'block'})),
dbc.Col(self.update_sliders(), id='all-sliders')
],
align='center',
),
html.Div([]), # Empty div for bottom text
html.Div(id='data_storage', style={'display': 'none'}),
html.Div(id='interval_storage', style={'display': 'none'}),
html.Div(id='posterior_storage', style={'display': 'none'})
],
fluid=True),
self.mathjax_script
])
# Set the app index string for mathjax
self.app.index_string = self.mathjax_html
# Save the locations of texts from the layout
self.main_text = self.app.layout.children[0].children[1].children
self.collapsed_text = self.app.layout.children[0].children[-4].children
dash_table.DataTable(
id='table_results',
data=df4.to_dict('records'),
columns=[{'id': c, 'name': c} for c in df4.columns],
style_cell={'textAlign': 'center', 'width': '100px', 'minWidth': '100px', 'maxWidth': '100px'},
fixed_rows={'headers': True, 'data': 0},
style_header={'fontWeight': 'bold'},
style_table={'overflowX': 'auto'},
editable=True
),
html.Button('Send to My works', id='send-results-button', n_clicks=0,
style={'backgroundColor': 'rgba(255, 0, 0, 0.8)', 'color': 'white'}),
html.Button('Send To Analysis', id='analysis-button', n_clicks=0,
style={'backgroundColor': 'rgba(255, 0, 0, 0.8)', 'color': 'white'}),
html.Progress(id="progress", value="70", max="100")
], className='twelve columns'),
], className='twelve columns'),
html.Div(id='stock-table', className='twelve columns'),
html.Div(id='hidden-div', style={'display': 'none'}),
])
@app.callback(
Output(component_id='hidden-div', component_property='children'),
[Input(component_id='send-results-button', component_property='n_clicks'),
Input(component_id='analysis-button', component_property='n_clicks')],
def serve_layout():
session_id = str(uuid.uuid4())
print(f"-------------------------------")
print(f"New session: {session_id}")
return html.Div([
html.Div(session_id, id='session-id', style={'display': 'none'}),
dcc.Interval(id='status-check', interval=2000, n_intervals=0),
dcc.Interval(id='result-check', interval=5000, n_intervals=0),
dcc.Store(id="node_status"),
html.Div([
html.Div(html.A(html.Img(src=app.get_asset_url("pyplan-logo.png"),
id="pyplan-image",
style={
"height": "60px",
"width": "auto",
}),
href='https://www.pyplan.org',
target='_blank'),
className="threet columns"),
html.H2("Pyplan/Dash Integration",
className="text-center six columns"),
html.Div(html.A(html.Img(src=app.get_asset_url("dash-logo.png"),
id="plotly-image",
style={
"height": "60px",
"width": "auto",
}),
href='https://plotly.com/dash/',
target='_blank'),
className="threet columns text-right"),
]),
html.Div([
html.Div([
html.H4("Integrated Business Planning"),
html.H5("Overview:"),
html.
P("This app is a commercial, operations and financial planning demo showcasing the integration of Pyplan with Dash. Open the Input Panel to change parameters, select scenarios and check the results on the projected P&L Statement."
),
html.
P("Explore the underlaying model logic by single clicking a node in the diagram and selecting the Code</> tab to inspect the Python code calculating business planning outcomes. Double click any node to run it an analyse its output as table and graph."
),
],
className="twelve columns"),
],
className="row title"),
html.Div([
html.Progress(
id='progress', value='0', max=30, style={"width": "100%"}),
html.Div([
html.Img(src=app.get_asset_url("wait_for_session.png"),
style={
"width": "100%",
"height": "auto",
})
],
id='pyplan-container',
style={'height': '800px'})
],
className="row"),
html.H6('Profit and Loss Statement:'),
html.Div([
dcc.Loading(
id="loading_charts",
type="default",
children=html.Div([
dash_table.DataTable(
id='pl_table',
fixed_rows={
"headers": True,
"data":
0
},
fixed_columns={
"headers": True,
"data":
1
},
style_table={
'width': '100%',
},
style_as_list_view=True,
column_selectable=False,
style_cell={
'padding':
'5px',
'fontSize':
'11px',
'fontFamily':
'Open Sans", HelveticaNeue, "Helvetica Neue", Helvetica, Arial, sans-serif'
},
style_header={
'backgroundColor': '#f2f2f2',
'fontWeight': 'bold'
},
style_data_conditional=[
{
'if': {
'filter_query':
'{Report index} eq "Revenue" or {Report index} eq "Operation Margin" or {Report index} eq "EBITDA" or {Report index} eq "Net Income" or {Report index} eq "EBIT" or {Report index} eq "Profit b/tax"',
},
'backgroundColor': '#f6f6f6',
'fontWeight': 'bold',
},
{
'if': {
'column_id': 'Report index'
},
'backgroundColor': '#f2f2f2',
'textAlign': 'left'
},
],
data=[],
),
dcc.Graph(id="pl_chart",
figure={
'data': [],
'layout': {
'height': 390
}
})
]))
],
className="row box"),
],
className="container")
id='loader-trigger-1',
style={"display": "none"}),
html.Div(
id='loader-trigger-2',
style={"display": "none"}),
html.Div(
id='loader-trigger-3',
style={"display": "none"}),
html.Div(
id='loader-trigger-4',
style={"display": "none"}),
dcc.Markdown(
id='data_summary_filtered',
children=data_summary_filtered_md),
html.Progress(
id="selected_progress",
max=f"{len(df_original)}",
value=f"{len(df_original)}"),
]),
]),
html.Div(className="four columns pretty_container",
children=[
html.Label('Select pick-up hours'),
dcc.RangeSlider(
id='hours',
value=[0, 23],
min=0,
max=23,
marks={i: str(i)
for i in range(0, 24, 3)}),
]),
html.Div(className="four columns pretty_container",
