Hey,
currently I am working on an app, in this app i want to take a loaded dataframe, create synthetic data via oversampling and store this new generated data in a different dcc.store object.
I’ve been facing this issue for quite some time right now. Even though my code runs perfectly smooth in my multipage app I receive this error message:
A nonexistent object was used in an Input of a Dash callback. The id of this object is imb_data_drpdwn and the property is value. The string ids in the current layout are: […]
One can use the app completely normally, the only annoying thing is the bug popping up.
Although the imb_data_drpdwn is clearly defined and operationable in this callback. I digged deeper into the code and figured that it has to do with the way I create my dcc.store object. If I remove the data output the error doesn’t show.
Here is my callback in my callback file:
# Implement Default Rate over time and general information:
@app.callback(
Output(component_id='synthetic_datasets', component_property="data"),
[Input(component_id='imbalanced_data_tabs', component_property="active_tab"),
Input(component_id='imb_data_drpdwn', component_property="value"),
Input(component_id='imb_data_percentage', component_property="value"),
Input(component_id='imb_data_tune_btn', component_property="n_clicks")],
[State (component_id='synthetic_datasets', component_property="data"),
State(component_id='chosen_dataset', component_property="data")],
prevent_initial_call=True
)
def update_data_overview_graph(active_tab, algorithm, weight, tune_btn, synthetic_datastore, chosen_data):
if active_tab == 'tab_oversampling_data':
y = DATASETS[chosen_data]['MODEL_CALI_DATA']["RDS"]['y_emp']
X = DATASETS[chosen_data]['MODEL_CALI_DATA']["RDS"]['X']
button_id = [p['prop_id'] for p in dash.callback_context.triggered][0]
if 'imb_data_tune_btn' in button_id:
X_res, y_res = over_under_sampling(X, y,algorithm, weight)
synthetic_datastore['X_res'] = X_res
synthetic_datastore['y_res'] = y_res
return synthetic_datastore
That’s how I create the dcc store (In the index.py file)
# Storage for Datasets with Synthetic Defaults
dcc.Store(id='synthetic_datasets', storage_type='session', data={
'X_res': None,
'y_res': None}),
This is the code of the app, in a different function I return the .getlayout function if the tab is activated:
from dash import html, no_update, dcc, dash_table as dt
import dash_bootstrap_components as dbc
from aicreditrisk.modules_and_functions.data_quality.functions_and_plots.data_summary import provide_data_summary as pds
from aicreditrisk.dashboard.all_layouts.utils.card_headline_and_information_row import get_headline_and_information_row
from aicreditrisk.dashboard.all_layouts.utils.loading_circle import get_loading_circle_div
def get_layout():
oversampling_algos = ['SMOTE', 'BorderlineSMOTE', 'SMOTENC', 'SVMSMOTE', 'KMeansSMOTE']
return html.Div(children=[
dbc.Card(
dbc.CardBody([
get_headline_and_information_row("Oversample Dataset",
"Oversampling means to create synthetic data points,"
" to do that please select the percentage and the "
"corresponding algorithm you want to choose."
),
html.Label('Default Rate over time:'),
dbc.Col([
dbc.Spinner([
html.Div(id='imb_data_overview_df_rate_div')
], spinnerClassName="loader_fancy",
spinner_style={'textAlignment': 'center',
'paddingTop': '20px',
'paddingBottom': '20px'})
], width=12),
html.Label(id="imb_data_avg_df"),
html.Br(),
dbc.Row([
dbc.Col([
dbc.Row([
html.Label("Select Algorithm to Oversample:", style={'textAlign': 'left'}),
html.Br(),
dcc.Dropdown(id='imb_data_drpdwn', options=[{'label': data, 'value': data} for data in oversampling_algos])
]),
]),
dbc.Col([
dbc.Row([
html.Label("Select percentage of Defaults (Regular + Synthetic):", style={'textAlign': 'left'}),
html.Br(),
dbc.Input(id="imb_data_percentage",
type="number",
placeholder="Please input number in between 0-100")
]),
html.Br()
]),
]),
html.Br(),
dbc.Row([
dbc.Col([
dbc.Row([
html.Label("To identify the synthetic datapoints we asign the CUSTOMER_ID: 99999, REFERENCE_DATE: 01.__.____(corresponding to the first date of the month)", style={'textAlign': 'left'}),
html.Br(),
]),
]),
]),
]), className='w-100 card-style',
),
html.Br(),
dbc.Card(
dbc.CardBody([
dbc.Row([
dbc.Col([
dbc.Row([
html.Label("Create Synthetic Data:", style={'textAlign': 'left'},),
html.Br(),
html.Button('Create Synthetic Data Points', id='imb_data_tune_btn', n_clicks=0,
className="d-grid gap-2 col-2 mx-auto button_fancy type1")
]),
]),
dbc.Col([
dbc.Row([
html.Label("Continue to use new dataset:", style={'textAlign': 'left'}),
html.Br(),
html.Button('Change Dataframe', id='imb_data_ctn_btn', n_clicks=0,
className="d-grid gap-2 col-2 mx-auto button_fancy type1")
]),
html.Br()
]),
])
]), className='w-100 card-style',
),
html.Br(),
dbc.Card(
dbc.CardBody([
get_headline_and_information_row("Synthetic Data Graphical Display",
"Here one can see the distribution of the just created synthetic data."
" Select two riskdrivers to see the data in a two dimensional space."
),
dbc.Row([
dbc.Col([
dbc.Row([
html.Label("Select Riskdriver:", style={'textAlign': 'left'}),
html.Br(),
dcc.Dropdown(id='imb_data_first_rd',
options=[{'label': data, 'value': data} for data in oversampling_algos])
]),
]),
dbc.Col([
dbc.Row([
html.Label("Select Riskdriver:", style={'textAlign': 'left'}),
html.Br(),
dcc.Dropdown(id='imb_data_scd_rd',
options=[{'label': data, 'value': data} for data in oversampling_algos])
]),
html.Br()
]),
])
]), className='w-100 card-style',
),
html.Br(),
dbc.Card(
dbc.CardBody([
get_headline_and_information_row("Export Dataframe"),
dbc.Row([
dbc.Col([
dbc.Row([
html.Label("press button to export new generated Dataframe:", style={'textAlign': 'left'}),
html.Br(),
html.Button('Export Dataframe', id='imb_data_export', n_clicks=0,
className="d-grid gap-2 col-2 mx-auto button_fancy type1")
]),
]),
])
]), className='w-100 card-style',
),
],
)
It would be nice to know how to fix that error message.
Sincerely,
Peter
Callbacks are also triggered when an Input is added to the layout (see 