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A Dash / Plotly component providing Tabulator capabilities

Nov 17, 2020
A Dash / Plotly component providing Tabulator capabilities

dash_tabulator

Dash tabulator is a Dash / Plotly component providing Tabulator capabilities. This is not a fully comprehensive implementation of Tabulator just the basics necessary to get the application working. Under the covers this uses react-tabulator

This is built on the shoulders of the Dash Plotly team, the Tabulator team, and the React Tabulator team. This readme is probably longer than the code, due to the work of those individuals!

Features

  • Tabulator Column settings
    • Sorting / Filtering etc.
  • Data loading through Dash Plotly callbacks
  • Row Click Callbacks
  • Data Changed Callbacks (contains the new data table, note warning on this)
  • Cell Edit Callbacks, capture the cell that was just changed, requires setting "editor":"input" etc.. on column header
  • Download button to export as csv / xlsx / pdf
    • XLSX & PDF require 3 party js scripts, see above link for details

Installation

Installation can be done with pip in your dash project

pip install dash_tabulator

Usage

Sample usage

import dash_tabulator import dash from dash.dependencies import Input, Output import dash_html_components as html import dash_core_components as dcc from textwrap import dedent as d import json # 3rd party js to export as xlsx external_scripts = ['https://oss.sheetjs.com/sheetjs/xlsx.full.min.js'] # bootstrap css external_stylesheets = ['https://stackpath.bootstrapcdn.com/bootstrap/4.1.3/css/bootstrap.min.css'] # initialize your dash app as normal app = dash.Dash(__name__, external_scripts=external_scripts, external_stylesheets=external_stylesheets) styles = { 'pre': { 'border': 'thin lightgrey solid', 'overflowX': 'scroll' } } # Setup some columns # This is the same as if you were using tabulator directly in js # Notice the column with "editor": "input" - these cells can be edited # See tabulator editor for options http://tabulator.info/docs/4.8/edit columns = [ { "title": "Name", "field": "name", "width": 150, "headerFilter":True, "editor":"input"}, { "title": "Age", "field": "age", "hozAlign": "left", "formatter": "progress" }, { "title": "Favourite Color", "field": "col", "headerFilter":True }, { "title": "Date Of Birth", "field": "dob", "hozAlign": "center" }, { "title": "Rating", "field": "rating", "hozAlign": "center", "formatter": "star" }, { "title": "Passed?", "field": "passed", "hozAlign": "center", "formatter": "tickCross" } ] # Setup some data data = [ {"id":1, "name":"Oli Bob", "age":"12", "col":"red", "dob":""}, {"id":2, "name":"Mary May", "age":"1", "col":"blue", "dob":"14/05/1982"}, {"id":3, "name":"Christine Lobowski", "age":"42", "col":"green", "dob":"22/05/1982"}, {"id":4, "name":"Brendon Philips", "age":"125", "col":"orange", "dob":"01/08/1980"}, {"id":5, "name":"Margret Marmajuke", "age":"16", "col":"yellow", "dob":"31/01/1999"}, {"id":6, "name":"Fred Savage", "age":"16", "col":"yellow", "rating":"1", "dob":"31/01/1999"}, {"id":6, "name":"Brie Larson", "age":"30", "col":"blue", "rating":"1", "dob":"31/01/1999"}, ] # Additional options can be setup here # these are passed directly to tabulator # In this example we are enabling selection # Allowing you to select only 1 row # and grouping by the col (color) column options = { "groupBy": "col", "selectable":1} # downloadButtonType # takes # css => class names # text => Text on the button # type => type of download (csv/ xlsx / pdf, remember to include appropriate 3rd party js libraries) # filename => filename prefix defaults to data, will download as filename.type downloadButtonType = {"css": "btn btn-primary", "text":"Export", "type":"xlsx"} # Add a dash_tabulator table # add empty columns and data arrays to setup the react props # columns=[], # data=[], # not doing will give you ugly recursive errors # and nothing will work app.layout = html.Div([ dash_tabulator.DashTabulator( id='tabulator', columns=[], data=[], options=options, downloadButtonType=downloadButtonType, ), html.Div(id='output'), dcc.Interval( id='interval-component-iu', interval=1*10, # in milliseconds n_intervals=0, max_intervals=0 ) ]) # dash_tabulator can be populated from a dash callback @app.callback([ Output('tabulator', 'columns'), Output('tabulator', 'data')], [Input('interval-component-iu', 'n_intervals')]) def initialize(val): return columns, data # dash_tabulator can register a callback on rowClicked, cellEdited, dataChanged # to receive a dict of the row values @app.callback(Output('output', 'children'), [ Input('input', 'rowClicked'), Input('input', 'cellEdited'), Input('input', 'dataChanged')]) def display_output(row, cell, dataChanged): print(row) print(cell) print(dataChanged) return 'You have clicked row {} ; cell {}'.format(row, cell) if __name__ == '__main__': app.run_server(debug=True)

Be aware registering a callback for dataChanged will send the entire table back each time a change occurs
Make sure you are conscious of the amount of data you are round tripping.

GitHub

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