Long time waiting for this! Lots of thanks 
!
Take the state of the props you want to keep the same, e.g.:
@app.callback([
Output('graph', 'figure'),
Output('data-table', 'data'),
Output('data-table', 'columns'),
Output('container', 'style')
], [Input('data-dropdown', 'value')],
[State('graph', 'figure'),
State('data-table', 'data'),
State('data-table', 'columns'),
State('container', 'style')])
def multi_output(value, graph_figure, dt_data, dt_columns, container_style):
if condition_1:
...
return [graph_figure, b, c, d]
elif condition_2:
...
return [a, dt_data, c, d]
else:
...
return [a, b, c, container_style]
2 Likes
The app is running on local host but is showing error when I uploaded on AWS. I have attached the jupyter notebook logs for reference. I have also attached the output on Local host and output on AWS. Output on AWS should be similar to the output on Local host
app.layout = html.Div([
html.H1('Smoothie Fixed Benefit Prices'),
html.P("These prices are common for all routes in India."),
html.P("Peak months are:-Jan,June, July, August, November, December."),
html.P("Peak Hours ( During Peak Months ):-9 A.M. to Midnight"),
html.P("Peak Hours ( During Non Peak Months ):-12 P.M. - 12 A.M."),
html.H3('Select Airline'),
dcc.Dropdown(
id='datasource-1',
options=[
{'label': i, 'value': i} for i in ['Low Delay Airlines (6E, UK)','High Delay Airlines (9W,AI,SG,G8)']
],
),
html.H3('Select Peak/Non-Peak Month'),
dcc.Dropdown(
id='datasource-2',
options=[
{'label': i, 'value': i} for i in ['Peak Month','Non Peak Month']
]
),
html.Hr(),
html.Div('Select Peak/Non Peak Hour and Threshold Delay'),
html.Div(
id='controls-container'
),
html.Hr(),
html.Div('Output'),
html.Div(
id='output-container'
)
])
def generate_control_id(value):
return 'Control {}'.format(value)
DYNAMIC_CONTROLS = {
'Low Delay Airlines (6E, UK)': dcc.Dropdown(
id=generate_control_id('Low Delay Airlines (6E, UK)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='Low Delay Airlines (6E, UK)'].unique())]
),
'High Delay Airlines (9W,AI,SG,G8)': dcc.Dropdown(
id=generate_control_id('High Delay Airlines (9W,AI,SG,G8)'),
options=[{'label': '{}'.format(i), 'value': i} for i in list(price['Hour Peaks'][price['Airlines']=='High Delay Airlines (9W,AI,SG,G8)'].unique())]
),
'Peak Month': dcc.Dropdown(
id=generate_control_id('Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
),
'Non Peak Month': dcc.Dropdown(
id=generate_control_id('Non Peak Month'),
options=[{'label': '{}'.format(i), 'value': i} for i in [60,90,120,150,180]]
)
}
@app.callback(
Output('controls-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# generate 2 dynamic controls based off of the datasource selections
return html.Div([
DYNAMIC_CONTROLS[datasource_1_value],
DYNAMIC_CONTROLS[datasource_2_value],
])
def generate_output_id(value1, value2):
return '{} {} container'.format(value1, value2)
@app.callback(
Output('output-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# create a unique output container for each pair of dyanmic controls
return html.Div(id=generate_output_id(
datasource_1_value,
datasource_2_value
))
def prem(a,b,c,d):
return (price['Office Premium ( INR )'][(price['Hour Peaks']==a)&(price['Threshold Delay ( Min )']==b)&(price['Airlines']==c)&(price['Month Peaks']==d)])
def incidence(a,b,c,d):
return (price['Incidence Rate (%)'][(price['Hour Peaks']==a)&(price['Threshold Delay ( Min )']==b)&(price['Airlines']==c)&(price['Month Peaks']==d)])
def generate_output_callback(datasource_1_value, datasource_2_value):
def output_callback(control_1_value, control_2_value):
# This function can display different outputs depending on
# the values of the dynamic controls
premium=prem(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
incidence_rate=incidence(control_1_value,control_2_value,datasource_1_value,datasource_2_value)
return '''
For the selected values, premium in INR is {} and incidence rate is {} %
'''.format(
list(premium)[0],
list(incidence_rate)[0]
)
return output_callback
app.config.supress_callback_exceptions = True
# create a callback for all possible combinations of dynamic controls
# each unique dynamic control pairing is linked to a dynamic output component
for value1, value2 in itertools.product(
[o['value'] for o in app.layout['datasource-1'].options],
[o['value'] for o in app.layout['datasource-2'].options]):
app.callback(
Output(generate_output_id(value1, value2), 'children'),
[Input(generate_control_id(value1), 'value'),
Input(generate_control_id(value2), 'value')])(
generate_output_callback(value1, value2)
)
if __name__ == '__main__':
application.run(port=8080)
The error is very clear, DYNAMIC_CONTROLS has no key None.
This code here is not catching on initial load that the Inputs could have a null value.
@app.callback(
Output('controls-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
# generate 2 dynamic controls based off of the datasource selections
return html.Div([
DYNAMIC_CONTROLS[datasource_1_value],
DYNAMIC_CONTROLS[datasource_2_value],
])
Put some checks in the function, e.g.:
@app.callback(
Output('controls-container', 'children'),
[Input('datasource-1', 'value'),
Input('datasource-2', 'value')])
def display_controls(datasource_1_value, datasource_2_value):
if datasource_1_value is None or datasource_2_value is None:
raise dash.exceptions.PreventUpdate
# generate 2 dynamic controls based off of the datasource selections
return html.Div([
DYNAMIC_CONTROLS[datasource_1_value],
DYNAMIC_CONTROLS[datasource_2_value],
])I tried this. Although there are no logs error. It is still not working when I upload it on AWS.
What should I do ?
Ask a new question about deploying to AWS, explain what your setup is, and try and come up with a minimal set of code that produces the problem. Most people aren’t reading announcement threads to help solve problems.
I have this:
app.callback([
Output('SeqR', 'children'),
Output('Plat', 'children')],
[Input('submit-button','n_clicks')],
[State('ID_selector', 'value')])
def update_output(n_clicks, input_ID):
if input_ID:
seqR = "12312"
plat = "12356"
return html.Div(seqR), html.Div(plat)
But I get error when trying this code
@lcalcagni
could you post the error code
Consider yourself lucky that the solution to this has come out not too long ago: just put in dash.no_update on the output line for variables you want to leave unchanged.
2 Likes
Very useful!
Is it possible to return only one value and use this as the Output to multiple objects?
For example:
I have multiple dropdown menus to select which column of a data table should be used for what.
Like: Select the column of x values, select the column of y values etc.
These dropdown menus need to be updated when data is uploaded, and they of course should all have the same options.
So when I have a function that returns me the names of the columns like:
@app.callback([Output('classifier_choice', 'options'),
Output('identifier_selector', 'options'),
Output('timepoint_selector', 'options')],
[Input('output-data-upload', 'children')])
def update_dropdown(contents):
columns=df.columns
print(columns)
return [{'label' :k, 'value' :k} for k in columns].
Is it possible to use this return value for all the outputs?
This is truly a gamechanger, thank you!
you can just return that 4 times - ie a list of length 4, with that value as each element.
A post was split to a new topic: Multiple output when enable multiple select option in dropdown
A post was split to a new topic: Looking for help with multiple outputs
Hier is my function,with multiple output,why i receive a dash.exceptions.InvalidCallbackReturnValue??
data_dict = {‘lasso_selection’: }
@app.callback([
Output(‘graph’, ‘figure’),
Output(‘polygon_lan_lot-value’, ‘data’)],
[Input(‘graph’, ‘selectedData’)])
def display_data(selectedData):
if type(selectedData) is dict:
if 'lassoPoints' in selectedData.keys():
l = []
for i in range(len(selectedData["points"])):
l.append(selectedData["points"][i]['lon'])
data_set = pd.DataFrame(data=selectedData['lassoPoints']['mapbox'],
columns=['lon', 'lat'])
data_dict['lasso_selection'] = [data_set]
figure = {
'data': [
go.Scattermapbox(
lat=[51.48165],
lon=[7.21648],
text='time',
mode='markers',
opacity=0.7,
marker={
'size': 10},
name='Others'),
],
'layout': go.Layout(
autosize=False,
width=1400,
height=700,
hovermode='closest',
dragmode='zoom',
mapbox=dict(
style='basic',
accesstoken=mapbox_access_token,
bearing=0,
center=dict(
lat=51.48165,
lon=7.21648
),
zoom=13
), )}
return figure, data_dict