How can we create data columns in Dash Table dynamically using callback with a function providing the dataframe

In your Dash callback you are supposed to be returning 2 separate values to the 2 separate outputs:[Output('table', 'data'),Output('table', 'columns')]

You are returning:

return html.Div([                dt.DataTable(            id='table',            columns=mycolumns,            data=df.to_dict("rows")         )        ])

which is only 1 output.

Dash expects 2 return values in either a list, or a tuple like so:

return("output1" , outputVariable2)

or

return[ Html.Div("text") , "output Text 2"]

in order to fix the problem, either return 2 values in a tuple or list, or edit your output requirements so only one value is necessary.

From the looks of it you are trying to return a Div with a Datatable in it, so you could just make the following changes:

    html.Div(        id = 'tableDiv',        className = 'tableDiv'    )...  @app.callback([Output('tableDiv', 'children')]          [Input('submit', 'n_clicks')],          [State('ID', 'value'),  State('pattern_desc', 'value'),         State('file_path', 'value')])   def update_table(n_clicks, ID, pattern_desc, file_path):         df = someFunc(ID, pattern_desc, file_path)    mycolumns = [{'name': i, 'id': i} for i in df.columns]        return html.Div([                dt.DataTable(            id='table',            columns=mycolumns,            data=df.to_dict("rows")         )        ])

If I've understood you correctly, then you can simply create another callback which outputs the updated value for the columns prop. You could also use a multi-output callback to update both at the same time.

@app.callback(Output('table', 'columns'),    [Input('submit', 'n_clicks')],    [State('ID', 'value'),  State('pattern_desc', 'value'),      State('file_path', 'value')])def update_table(n_clicks, ID, pattern_desc, file_path):    mydata = someFunc(ID, pattern_desc, file_path)    # here you would use the dataframe columns to create the new column values    return new_column_values