Name Date Size

.. 2011-10-19 22:02:33 100

build.array.properties 2011-07-09 02:18:39 749

build.array.xml 2011-07-09 02:18:39 332

build.base.properties 2011-07-09 02:18:39 779

build.base.xml 2011-07-09 02:18:39 331

build.json.properties 2011-07-09 02:18:39 752

build.json.xml 2011-07-09 02:18:39 331

build.text.properties 2011-07-09 02:18:39 747

build.text.xml 2011-07-09 02:18:39 331

build.xml 2011-07-09 02:18:39 805

build.xml.properties 2011-07-09 02:18:39 745

build.xml.xml 2011-07-09 02:18:39 330

docs 2011-10-19 22:02:33 11

HISTORY.md 2011-09-27 08:41:41 1.8 KiB

js 2011-08-20 00:27:04 7

meta 2011-05-27 20:45:05 3

README.md 2011-06-25 00:12:40 1,015

tests 2011-07-09 00:59:51 4

README.md

DataSchema Utility
==================
Use the DataSchema Utility to translate data in various input formats into a
standard record-based structure like this:
{
results: [
{ fieldA: valueA1, fieldB: valueB2, ... },
{ fieldA: valueA2, fieldB: valueB2, ... },
...
],
meta: {
whatever : "you",
configured: "to capture",
...
}
}
Available processors
====================
1. `Y.DataSchema.Array` - (`dataschema-array`) Input is an Array
2. `Y.DataSchema.JSON` - (`dataschema-json`) Input is an Object or JSON string
3. `Y.DataSchema.XML` - (`dataschema-xml`) Input is an XML node
4. `Y.DataSchema.Text` - (`dataschema-text`) Input is a delimited text string
The important method for each processor is the `apply(schema, data)` method, so
for example:
var results = Y.DataSchema.JSON.apply({ schema config }, dataObject);
See the user guide for details about schema definitions for each processor.