For example, our colModel definition might be as follows:
colModel:[ {name:'name',label:'Name', width:150,editable: true}, {name:'id',width:50, sorttype:"int", editable: true,formatter:strongFmatter}, {name:'email',label:'Email', width:150,editable: true,formatter:'email'}, {name:'stock',label:'Stock', width:60, align:"center", editable: true,formatter:'checkbox',edittype:"checkbox"}, {name:'item.price',label:'Price', width:100, align:"right", editable: true,formatter:'currency'}, {name:'item.weight',label:'Weight',width:60, align:"right", editable: true,formatter:'number'}, {name:'ship',label:'Ship Via',width:90, editable: true,formatter:'select', edittype:"select", editoptions:{value:"2:FedEx;1:InTime;3:TNT;4:ARK;5:ARAMEX"}}, {name:'note',label:'Notes', width:100, sortable:false,editable: true,edittype:"textarea", editoptions:{rows:"2",cols:"20"}} ]
Then our data:
{"page":"1","total":2,"records":"13", "rows":[ {id:"12345",name:"Desktop Computers",email:"josh@josh.com",item:{price:"1000.72", weight:"1.22"},note:"note",stock:"0",ship:"1"}, {id:"23456",name:"<var>laptop</var>",note:"Long text ",stock:"yes",item:{price:"56.72", weight:"1.22"},ship:"2"}, {id:"34567",name:"LCD Monitor",note:"note3",stock:"true",item:{price:"99999.72", weight:"1.22"},ship:"3"}, {id:"45678",name:"Speakers",note:"note",stock:"false",ship:"4"} ] }
Note how item is defined. This data will be intelligently interpreted from the grid.