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YUI Library Examples: DataSchema Utility: DataSchema.JSON

DataSchema Utility: DataSchema.JSON

DataSchema.JSON normalizes arbitrary JSON data against a given schema into an object with known properties.

View example in new window.

Basic example

Data
{
    "total":10,
    "results":[
        {"n":1, "fname":"George", "lname":"Washington"},
        {"n":2, "fname":"John", "lname":"Adams"},
        {"n":3, "fname":"Thomas", "lname":"Jefferson"},
        {"n":4, "fname":"James", "lname":"Madison"},
        {"n":5, "fname":"James", "lname":"Monroe"},
        {"n":6, "fname":"John", "mname":"Quincy", "lname":"Adams"},
        {"n":7, "fname":"Andrew", "lname":"Jackson"},
        {"n":8, "fname":"Martin", "lname":"Van Buren"},
        {"n":9, "fname":"William", "mname":"Henry", "lname":"Harrison"},
        {"n":10, "fname":"John", "lname":"Tyler"}
    ]
}
Schema
{
    metaFields: {total:"total"},
    resultListLocator: "results",
    resultFields: [{key:"n"}, {key:"fname"}, {key:"lname"}]
}
Normalized data

Complex example

Data
{
    "profile":{
        "current":160,
        "target":150
    },
    "reference": [
        {
            "category":"exercise",
            "type":"expenditure",
            "activities":[
                {"name":"biking", "calories":550},
                {"name":"golf", "calories":1000},
                {"name":"running", "calories":650},
                {"name":"swimming", "calories":650},
                {"name":"walking", "calories":225}
            ]
        },
        {
            "category":"nutrition",
            "type":"intake",
            "fruit":[
                {"name":"apple", "calories":70},
                {"name":"banana", "calories":70},
                {"name":"orange", "calories":90},
            ],
            "vegetables":[
                {"name":"baked potato", "calories":150},
                {"name":"broccoli", "calories":50},
                {"name":"green beans", "calories":30}
            ]
        }
    ],
    "program": [
        {
            "category":"exercise",
            "schedule":[
                {"day":"sunday", "activity":"swimming"},
                {"day":"monday", "activity":"running"},
                {"day":"tuesday", "activity":"biking"},
                {"day":"wednesday", "activity":"running"},
                {"day":"thursday", "activity":"swimming"},
                {"day":"friday", "activity":"running"},
                {"day":"saturday", "activity":"golf"}
            ]
        },
        {
            "category":"diet",
            "schedule":[
            ]
        }
    ]
}
Schema
{
    metaFields: {current:"profile.current", target:"profile.target",
        reference:"reference[0].activities"},
    resultListLocator: "program[0].schedule",
    resultFields: [{key:"day"}, {key:"activity"}]
}
Normalized data

In order to use DataSchema.JSON, input data must be a JavaScript object.

  1. YUI().use("dataschema-json", function(Y) {
  2.     var data_in = {
  3.             total:10,
  4.             results:[
  5.                 {n:1, fname:"George", lname:"Washington"},
  6.                 {n:2, fname:"John", lname:"Adams"},
  7.                 {n:3, fname:"Thomas", lname:"Jefferson"},
  8.                 {n:4, fname:"James", lname:"Madison"},
  9.                 {n:5, fname:"James", lname:"Monroe"},
  10.                 {n:6, fname:"John", mname:"Quincy", lname:"Adams"},
  11.                 {n:7, fname:"Andrew", lname:"Jackson"},
  12.                 {n:8, fname:"Martin", lname:"Van Buren"},
  13.                 {n:9, fname:"William", mName:"Henry", lname:"Harrison"},
  14.                 {n:10, fname:"John", lname:"Tyler"}
  15.             ]
  16.         },
  17.         schema = {
  18.             metaFields: {total:"total"},
  19.             resultListLocator: "results",
  20.             // Or simply: ["n", "fname", "lname"]
  21.             resultFields: [{key:"n"}, {key:"fname"}, {key:"lname"}]
  22.         },
  23.         data_out = Y.DataSchema.JSON.apply(schema, data_in));
  24.  
  25.     alert(data_out);
  26. });
YUI().use("dataschema-json", function(Y) {
    var data_in = {
            total:10,
            results:[
                {n:1, fname:"George", lname:"Washington"},
                {n:2, fname:"John", lname:"Adams"},
                {n:3, fname:"Thomas", lname:"Jefferson"},
                {n:4, fname:"James", lname:"Madison"},
                {n:5, fname:"James", lname:"Monroe"},
                {n:6, fname:"John", mname:"Quincy", lname:"Adams"},
                {n:7, fname:"Andrew", lname:"Jackson"},
                {n:8, fname:"Martin", lname:"Van Buren"},
                {n:9, fname:"William", mName:"Henry", lname:"Harrison"},
                {n:10, fname:"John", lname:"Tyler"}
            ]
        },
        schema = {
            metaFields: {total:"total"},
            resultListLocator: "results",
            // Or simply: ["n", "fname", "lname"]
            resultFields: [{key:"n"}, {key:"fname"}, {key:"lname"}]
        },
        data_out = Y.DataSchema.JSON.apply(schema, data_in));
 
    alert(data_out);
});

The data itself can get fairly complex, with deeply nested arrays and objects. In your schema, you can use dot notation and the array-index syntax to define these locations. When necessary, you can also use object-bracket notation to define locations that might otherwise be invalid with dot notation.

  1. YUI().use("dataschema-json", function(Y) {
  2.         var data_in = {
  3.             "profile":{
  4.                 "current":160,
  5.                 "target":150
  6.             },
  7.             "reference": [
  8.                 {
  9.                     "category":"exercise",
  10.                     "type":"expenditure",
  11.                     "activities":[
  12.                         {"name":"biking", "calories":550},
  13.                         {"name":"golf", "calories":1000},
  14.                         {"name":"running", "calories":650},
  15.                         {"name":"swimming", "calories":650},
  16.                         {"name":"walking", "calories":225}
  17.                     ]
  18.                 },
  19.                 {
  20.                     "category":"nutrition",
  21.                     "type":"intake",
  22.                     "fruit":[
  23.                         {"name":"apple", "calories":70},
  24.                         {"name":"banana", "calories":70},
  25.                         {"name":"orange", "calories":90},
  26.                     ],
  27.                     "vegetables":[
  28.                         {"name":"baked potato", "calories":150},
  29.                         {"name":"broccoli", "calories":50},
  30.                         {"name":"green beans", "calories":30}
  31.                     ]
  32.                 }
  33.             ],
  34.             "program": [
  35.                 {
  36.                     "category":"exercise",
  37.                     "weekly schedule":[
  38.                         {"day":"sunday", "activity":"swimming"},
  39.                         {"day":"monday", "activity":"running"},
  40.                         {"day":"tuesday", "activity":"biking"},
  41.                         {"day":"wednesday", "activity":"running"},
  42.                         {"day":"thursday", "activity":"swimming"},
  43.                         {"day":"friday", "activity":"running"},
  44.                         {"day":"saturday", "activity":"golf"}
  45.                     ]
  46.                 },
  47.                 {
  48.                     "category":"diet",
  49.                     "schedule":[
  50.                     ]
  51.                 }
  52.             ]
  53.         },
  54.         schema = {
  55.             metaFields: {current:"profile.current", target:"profile.target",
  56.                 reference:"reference[0].activities"},
  57.             resultListLocator: "program[0]['weekly schedule']",
  58.             // Or simply: ["day", "activity"]
  59.             resultFields: [{key:"day"}, {key:"activity"}]
  60.         },
  61.         data_out = Y.DataSchema.Array.apply(schema, data_in));
  62.  
  63.     alert(data_out);
  64. });
YUI().use("dataschema-json", function(Y) {
        var data_in = {
            "profile":{
                "current":160,
                "target":150
            },
            "reference": [
                {
                    "category":"exercise",
                    "type":"expenditure",
                    "activities":[
                        {"name":"biking", "calories":550},
                        {"name":"golf", "calories":1000},
                        {"name":"running", "calories":650},
                        {"name":"swimming", "calories":650},
                        {"name":"walking", "calories":225}
                    ]
                },
                {
                    "category":"nutrition",
                    "type":"intake",
                    "fruit":[
                        {"name":"apple", "calories":70},
                        {"name":"banana", "calories":70},
                        {"name":"orange", "calories":90},
                    ],
                    "vegetables":[
                        {"name":"baked potato", "calories":150},
                        {"name":"broccoli", "calories":50},
                        {"name":"green beans", "calories":30}
                    ]
                }
            ],
            "program": [
                {
                    "category":"exercise",
                    "weekly schedule":[
                        {"day":"sunday", "activity":"swimming"},
                        {"day":"monday", "activity":"running"},
                        {"day":"tuesday", "activity":"biking"},
                        {"day":"wednesday", "activity":"running"},
                        {"day":"thursday", "activity":"swimming"},
                        {"day":"friday", "activity":"running"},
                        {"day":"saturday", "activity":"golf"}
                    ]
                },
                {
                    "category":"diet",
                    "schedule":[
                    ]
                }
            ]
        },
        schema = {
            metaFields: {current:"profile.current", target:"profile.target",
                reference:"reference[0].activities"},
            resultListLocator: "program[0]['weekly schedule']",
            // Or simply: ["day", "activity"]
            resultFields: [{key:"day"}, {key:"activity"}]
        },
        data_out = Y.DataSchema.Array.apply(schema, data_in));
 
    alert(data_out);
});

More DataSchema Utility Resources:

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