Server Side Processing with Flask
Server Side Processing with Flask
hdoran
Posts: 16Questions: 8Answers: 0
I have the code below to render a table in my browser. My tables can be huge, and so I'm trying to implement server side processing. I have added the following to the code below:
serverSide: true,
ajax: {
url: '/bank',
type: 'POST'
}
Without the code above, the function below works beautifully and everything operates as expected with pagination and other rendering, except that the table takes huge memory. However with this code, I get the entire table in the browser and lose rendering for pagination and my search boxes no longer operate.
I'm following the instructions here:
https://datatables.net/manual/server-side
Am I missing additional code I need to work with so my table render with pagination and also searches work as well?
$(document).ready(function() {
// Setup - add a text input to each footer cell
$('#mytable thead tr').clone(true).appendTo( '#mytable thead' );
$('#mytable thead tr:eq(1) th').each( function (i) {
var title = $(this).text();
$(this).html( '<input type="text" placeholder="Search '+title+'" />' );
$( 'input', this ).on( 'keyup change', function () {
if ( table.column(i).search() !== this.value ) {
table
.column(i)
.search( this.value )
.draw();
}
});
});
var table = $('#mytable').DataTable({
orderCellsTop: true,
fixedHeader: true,
serverSide: true,
ajax: {
url: '/bank',
type: 'POST'
}
dom: 'Blfrtip',
buttons: [
{
extend: 'csv',
text: 'Export as .csv'
}
]
});
});
This discussion has been closed.
Answers
You will need to write the server Python code to perform the paging, searching and sorting. Or you can use a pre-built library like this:
https://github.com/SergioLlana/datatables-flask-serverside
I haven't used it so not sure how well it works.
Kevin
Thank you, @kthorngren. Before I go any further with this work, is server side processing still the best option for dealing with extremely large tables? Or, do you or others know if other alternatives exist?
This FAQ explains the options for Datatables speed optimization.
Kevin