Error when returning a tuple to multiple dcc.Download Outputs

Dash Python
1

The example is a significantly reduced version of my app.

The app functions correctly but upon initiation, it throws the traceback below.

I am attempting to return a tuple of dcc.Download to two different Outputs. I have tried unpacking the tuple and putting each element in the return as well but still get the same error.

What I don’t understand is how it states that I am returning a None type, when I am actually returning a tuple.

Traceback:

dash._grouping.SchemaTypeValidationError: Schema: [<Output `rprt1.data`>, <Output `rprt2.data`>]
Path: ()
Expected type: (<class 'tuple'>, <class 'list'>)
Received value of type <class 'NoneType'>: None

Functioning Code:

import dash
from dash import html, Input, Output
from dash import dcc
import pandas as pd

app = dash.Dash(__name__)

app.layout = html.Div([
    dcc.Download(id='rprt1'),
    dcc.Download(id='rprt2'),
    html.Button('A', id='button', n_clicks=0)
])

def multi_dnwld(df1, df2, names):
    tup = (df1, df2)
    dwnld = []
    for df, name in zip(tup, names):
        filename = name + ' - ' + '.csv'
        dwnld.append(dcc.send_data_frame(df.to_csv, filename, index=False))
    dwnld = tuple(dwnld)
    return dwnld

df1 = pd.DataFrame([[1,2],[3,4]], columns = ['a', 'b'])
df2 = pd.DataFrame([[1,2],[3,4]], columns = ['a', 'b'])

@app.callback(
    Output('rprt1', 'data'),
    Output('rprt2', 'data'),
    Input('button', 'n_clicks'),
    prevent_initial_callback=True
)
def summary(n_clicks):
    if n_clicks>0:
        names = ['Sum1', 'Sum2']
        return multi_dnwld(df1, df2, names)

if __name__ == '__main__':
    app.run_server(debug=True)
2 
import dash
from dash import html, Input, Output
from dash import dcc
import pandas as pd
from dash.exceptions import PreventUpdate

app = dash.Dash(__name__)

app.layout = html.Div([
    dcc.Download(id='rprt1'),
    dcc.Download(id='rprt2'),
    html.Button('A', id='button')
])


def multi_dnwld(df1, df2, names):
    tup = (df1, df2)
    dwnld = []
    for df, name in zip(tup, names):
        filename = name + ' - ' + '.csv'
        dwnld.append(dcc.send_data_frame(df.to_csv, filename, index=False))
    #dwnld = tuple(dwnld)
    return dwnld


df1 = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])
df2 = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])


@app.callback(
    Output('rprt1', 'data'),
    Output('rprt2', 'data'),
    Input('button', 'n_clicks'),
    #prevent_initial_callback=True
)
def summary(n_clicks):
    if n_clicks is None:
        raise PreventUpdate

    names = ['Sum1', 'Sum2']
    return multi_dnwld(df1, df2, names)


if __name__ == '__main__':
    app.run_server(debug=True)