dash_tabulator

- Dash Tabulator
- Features
- Installation
- Usage
- Themes
- Advanced Usage
- Multiple Row Selection
- Javascript
- Javascript Cell Formatting Example
- Javascript column resizing capture
- Links

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

!Dash 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
* Javascript bindings
* Contributed by Emil Haldrup Eriksen https://github.com/emilhe
* See pull request https://github.com/preftech/dash-tabulator/pull/11

Installation

Installation can be done with pip in your dash project
``bash
pip install dash_tabulator
pip install dash_extensions
`

Usage

Sample usage

`python
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"}

clearFilterButtonType

takes

css => class names

text => Text on the button

clearFilterButtonType = {"css": "btn btn-outline-dark", "text":"Clear Filters"}

Add a dash_tabulator table

columns=columns,

data=data,

Can be setup at initialization or added with a callback as shown below

thank you @AnnMarieW for that fix

app.layout = html.Div([
dash_tabulator.DashTabulator(
id='tabulator',
#columns=columns,
#data=data,
options=options,
downloadButtonType=downloadButtonType,
clearFilterButtonType=clearFilterButtonType
),
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 => a cell with a header that has "editor":"input" etc.. will be returned with row, initial value, old value, new value

dataChanged => full table upon change (use with caution)

dataFiltering => header filters as typed, before filtering has occurred (you get partial matching)

dataFiltered => header filters and rows of data returned

to receive a dict of the row values

@app.callback(Output('output', 'children'),
[Input('tabulator', 'rowClicked'),
Input('tabulator', 'cellEdited'),
Input('tabulator', 'dataChanged'),
Input('tabulator', 'dataFiltering'),
Input('tabulator', 'dataFiltered')])
def display_output(row, cell, dataChanged, filters, dataFiltered):
print(row)
print(cell)
print(dataChanged)
print(filters)
print(dataFiltered)
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.

dataFiltering will return the filters before a match has occurred, usually a partial match
`python
[{'field': 'col', 'type': 'like', 'value': 'yello'}]
`

dataFiltered will return the header filter and the row data e.g.
`python
{
'filters': [{'field': 'col', 'type': 'like', 'value': 'yellow'}],
'rows': [
None,
None,
{'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'}
]
}
`

Themes


React-Tabulator comes with several themes that can be used in Dash-Tabulator
Dash-Tabulator uses the default theme tabulator.min.css
The theme can be set in the Dash-Tabulator constructor
e.g.
`python
app.layout = html.Div([
dash_tabulator.DashTabulator(
id='tabulator',
theme='tabulator_simple', #optional
options=options,
downloadButtonType=downloadButtonType,
clearFilterButtonType=clearFilterButtonType,
),
....
])
`
The following are the built in react-tabulator themes
- tabulator or default => react-tabulator/lib/css/tabulator.min.css
- tabulator_modern => react-tabulator/lib/css/tabulator_modern.min.css
- tabulator_midnight => react-tabulator/lib/css/tabulator_midnight.min.css
- tabulator_simple => react-tabulator/lib/css/tabulator_simple.min.css
- tabulator_site => react-tabulator/lib/css/tabulator_site.min.css
- bootstrap/tabulator_bootstrap => react-tabulator/lib/css/bootstrap/tabulator_bootstrap.min.css
- bootstrap/tabulator_bootstrap4 => react-tabulator/lib/css/bootstrap/tabulator_bootstrap4.min.css
- bulma/tabulator_bulma => react-tabulator/lib/css/bulma/tabulator_bulma.min.css
- materialize/tabulator_materialize => react-tabulator/lib/css/materialize/tabulator_materialize.min.css
- semantic-ui/tabulator_semantic-ui => react-tabulator/lib/css/semantic-ui/tabulator_semantic-ui.min.css

Advanced Usage

Multiple Row Selection

Tabulator supports multiple row selection
To Enable the table option selectable must be set to the STRING true
`python
options = { "selectable":"true", ....}
`

Once selectable is set
`python
@app.callback(Output('output', 'children'),
[Input('tabulator', 'rowClicked'),
Input('tabulator', 'multiRowsClicked')]
def clickedRows(rowClicked, multiRowsClicked):
......
......
`
multiRowsClicked will now contain an array of all the rows selected
e.g.
`python
[
{'id': 6, 'name': 'Fred Savage', 'age': '16', 'col': 'yellow', 'rating': '1', 'dob': '31/01/1999', 'print': 'foo'},
{'id': 5, 'name': 'Margret Marmajuke', 'age': '16', 'col': 'yellow', 'dob': '31/01/1999', 'print': 'foo'},
{'id': 4, 'name': 'Brendon Philips', 'age': '125', 'col': 'orange', 'dob': '01/08/1980', 'print': 'foo'},
{'id': 3, 'name': 'Christine Lobowski', 'age': '42', 'col': 'green', 'dob': '22/05/1982', 'print': 'foo'}
]
`

Select all / deselect all can be accomplished with a header formatter called rowSelection.

`python
columns = [
{"formatter":"rowSelection", "titleFormatter":"rowSelection", "hozAlign":"center", "headerSort":"false"},
{ "title": "Name", "field": "name", "width": 150, "headerFilter":True, "editor":"input"},
`
For more options check out http://tabulator.info/docs/4.8/select




Javascript

Tabulator offers a significate amount of callbacks that allow for interactivity with tables to be captured
and modified http://tabulator.info/docs/4.8/callbacks
To enable this functionality we can use Dash-Extensions

Create an assets folder, add a javascript file with your custom functions
An example is provided in assets/custom_tabulator.js
Please follow the examples below

Javascript Cell Formatting Example

Contributed in https://github.com/preftech/dash-tabulator/pull/11
Tabulator offers Javascript formatting of cells http://tabulator.info/docs/3.4?#formatting
This a browser side javascript method attached to a header colum.

* Create an assets directory
* See https://dash.plotly.com/external-resources for customization options
* Add a javascript file with a window. method (below we call it myNamespace)
* An example is provided in the assets/custom_tabulator.js file
* Note the Namespace and the function printIcon
* Register that method in your python app
* Using dash_extensions.javascript.Namespace
* Add the registered function to your colums formatter


Python code:
`python
from dash_extensions.javascript import Namespace
...
ns = Namespace("myNamespace", "tabulator")
...
columns = [{"formatter": ns("printIcon")}, ...]
`

Javascript code:
`javascript
window.myNamespace = Object.assign({}, window.myNamespace, {
tabulator: {
printIcon: function (cell, formatterParams, onRendered) {
return "";
}
}
});
`

Javascript column resizing capture

Capturing a column resize, when a user drags a column width
From tabulators callbacks page http://tabulator.info/docs/4.8/callbacks#column
We see there's a columnsResized callback
in our python code in the options dict we can specify a javascript method

assets/custom_tabulator.js
`javascript
window.myNamespace = Object.assign({}, window.myNamespace, {
tabulator: {
columnResized : function (column, table) {
// column is the tabulator column component
// table is the tabulator instance, can be used for table.setProps() to send data back to dash
console.log("Column is resized");
console.log(column)

// send data back to dash, still under work, only updates when state changes
// be aware of table rendering and resetting back to original display
table.props.setProps({"columnResized": column._column.field})
}
}
});
`

Within your python code, you can register this method as a tabulator option

`python
from dash_extensions.javascript import Namespace
...
ns = Namespace("CustomNamespace", "tabulator")
...
options = { "groupBy": "col", "selectable":"true", "columnResized" : ns("columnResized")}
``

A full list of callbacks available exists http://tabulator.info/docs/4.8/callbacks

Links

* Home Page https://github.com/preftech/dash-tabulator
* Tabulator from @olifolkerd http://tabulator.info/
* React-Tabulator from @ngduc https://github.com/ngduc/react-tabulator
* Dash / Plotly from @plotly https://plotly.com/dash/