Store dash components, strings, dictionaries, numbers, None, or lists of those

memory

• default
• the memory store reverts to the default on every page refresh

local

• Share data between multiple pages in a browser, and keep it until it is cleared
• Restarting the browser does not lose data
• Different browsers keep differnt copies

session

• Keep data in a single page
• Not share data with other pages
• Refreshing page does not lose data
• Closing page will lose data

import dash
from dash import dcc
from dash import html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
from os import path

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
server = app.server

app.layout = html.Div([
        dcc.Input(id = 'input'),
        html.H1(id = 'content'),
        dcc.Store(id='cache') # default, memory
        #dcc.Store(id='cache', storage_type='local') # local
        #dcc.Store(id='cache', storage_type='session') # session
    ], className='container')

@app.callback(
    Output('cache', 'data'),
    Input('input', 'value'),
)
def update_output_1(value):
    if not value:
        raise PreventUpdate
    print(value)
    return value

@app.callback(
    Output('content', 'children'),
    Input('cache', 'data'),
)
def update_output_2(data):
    return data

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

import collections
import dash
import pandas as pd

from dash.dependencies import Output, Input
from dash.exceptions import PreventUpdate

from dash import html
from dash import dcc
from dash import dash_table
import plotly.graph_objects as go

app = dash.Dash(__name__)

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')

countries = set(df['country'])

app.layout = html.Div([
    dcc.Store(id='memory-output'),
    dcc.Dropdown(id='memory-countries', options=[
        {'value': x, 'label': x} for x in countries
    ], multi=True, value=['Canada', 'United States']),
    dcc.Dropdown(id='memory-field', options=[
        {'value': 'lifeExp', 'label': 'Life expectancy'},
        {'value': 'gdpPercap', 'label': 'GDP per capita'},
    ], value='lifeExp'),
    html.Div([
        dcc.Graph(id='memory-graph'),
        dash_table.DataTable(
            id='memory-table',
            columns=[{'name': i, 'id': i} for i in df.columns]
        ),
    ])
])


@app.callback(Output('memory-output', 'data'),
              Input('memory-countries', 'value'))
def filter_countries(countries_selected):
    if not countries_selected:
        # Return all the rows on initial load/no country selected.
        return df.to_dict('records')

    filtered = df.query('country in @countries_selected')

    return filtered.to_dict('records')


@app.callback(Output('memory-table', 'data'),
              Input('memory-output', 'data'))
def on_data_set_table(data):
    if data is None:
        raise PreventUpdate

    return data


@app.callback(Output('memory-graph', 'figure'),
              Input('memory-output', 'data'),
              Input('memory-field', 'value'))
def on_data_set_graph(data, field):
    if data is None:
        raise PreventUpdate

    temp = pd.DataFrame.from_dict(data)
    countries = set(temp['country'].unique()) 

    fig = go.Figure()
    for country in countries:
        country_data = temp[temp['country'] == country]
        fig.add_trace(go.Scatter(x=country_data['year'], y=country_data[field], name=country))

    return fig

if __name__ == '__main__':
    app.run_server(debug=True, threaded=True, port=10450)
		

import collections
import dash
import pandas as pd
 
from dash.dependencies import Output, Input
from dash.exceptions import PreventUpdate
 
from dash import html
from dash import dcc
from dash import dash_table
import plotly.graph_objects as go
 
app = dash.Dash(__name__)
 
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')
 
countries = set(df['country'])
 
app.layout = html.Div([
    dcc.Store(id='memory-output'),
    dcc.Dropdown(id='memory-countries', options=[
        {'value': x, 'label': x} for x in countries
    ], multi=True, value=['Canada', 'United States']),
    dcc.Dropdown(id='memory-field', options=[
        {'value': 'lifeExp', 'label': 'Life expectancy'},
        {'value': 'gdpPercap', 'label': 'GDP per capita'},
    ], value='lifeExp'),
    html.Div([
        dcc.Graph(id='memory-graph'),
        dash_table.DataTable(
            id='memory-table',
            columns=[{'name': i, 'id': i} for i in df.columns]
        ),
    ])
])
 
 
@app.callback(Output('memory-output', 'data'),
              Input('memory-countries', 'value'))
def filter_countries(countries_selected):
    if not countries_selected:
        # Return all the rows on initial load/no country selected.
        return df.to_dict('records')
 
    filtered = df.query('country in @countries_selected')
 
    return {'data': filtered.to_dict('records'), 'load': True}
 
 
@app.callback(Output('memory-table', 'data'),
              Input('memory-output', 'data'))
def on_data_set_table(data):
    if data is None:
        raise PreventUpdate
 
    return data['data']
 
 
@app.callback(Output('memory-graph', 'figure'),
              Input('memory-output', 'data'),
              Input('memory-field', 'value'))
def on_data_set_graph(data, field):
    if data is None:
        raise PreventUpdate
 
    print(data['load'])
    temp = pd.DataFrame.from_dict(data['data'])
    countries = set(temp['country'].unique()) 
 
    fig = go.Figure()
    for country in countries:
        country_data = temp[temp['country'] == country]
        fig.add_trace(go.Scatter(x=country_data['year'], y=country_data[field], name=country))
 
    return fig
 
if __name__ == '__main__':
    app.run_server(debug=True, threaded=True, port=10450)
		

Documentation