Data Transformations Package

Overview

The Data Transformations package contains helper utilities to wrestle with JSON,
XML and CSV data formats.

Add to project:
``
npm install @quadient/evolve-data-transformations
`

Table of Contents

- XML
- JSON
- CSV
- Streams

XML

Async streaming XML Parser and Writer.

XmlParser can be used to process strings with parts of the XML content.
The callback given to parser constructor receives events
of type XmlEvent.

XmlWriter is the opposite component. It receives XmlEvent objects through the
write method and the callback given to constructor receives a string with the
XML content.

To integrate XML processing with streams there are
TransformStream
classes StringToXmlTransformStream and XmlToStringTransformStream for convenient
use with streams.

$3

`javascript
const writer = new XmlWriter(async (str) => {
console.log(str);
});

const parser = new XmlParser(async (event) => {
if (event.type === XmlEventType.START_TAG) {
let elem = event.details as ElementDetails;
if (elem.name == "name") {
elem.name = "fixedName"
}
} else if (event.type === XmlEventType.END_TAG) {
if (event.details === "name") {
event.details = "fixedName"
}
}
await writer.write(event);
});

await parser.parse(Fred);
await parser.flush(); // must be called at the end of parsing
await writer.flush(); // must be called at the end of writing

`

Output:
`xml
Fred
`

JSON

Async streaming JSON Parser and Writer.

JsonParser can be used to process strings with parts of the JSON content.
The callback given to parser constructor receives events
of type JsonEvent.

JsonWriter is the opposite component. It receives JsonEvent objects in the
write method and the callback given to constructor receives a string with the
JSON content.

To integrate XML processing with streams there are
TransformStream
classes StringToJsonTransformStream and JsonToStringTransformStream for convenient
use with streams.




$3

`javascript
let writer = new JsonWriter(async (str) => {
console.log(str);
});

let parser = new JsonParser(async (event) => {
if(event.type === JsonEventType.PROPERTY_NAME && event.data === "name") {
event.data = "fixedName";
}
await writer.write(event);
})

await parser.parse({"person": {"name":"Fred"}});
await parser.flush(); // must be called at the end of parsing
await writer.flush(); // must be caleld at the end of writing
`

Output:
`
{"person":{"fixedName":"Fred"}}
`

$3


Processing JSON using events is efficient with respect to used memory during the transformation, but
is quiet intricate. Especially when compared to fully deserializing json to object using JSON.parse.
In most of the situations it will be possible to use a combination of both approaches. When dealing with large data
it often appears, that data structure contains some array with many members. In such case it would be useful
to handle all JSON input with streaming approach, but the members of array could be safely deserialized to objects as
the individual members of the array are small enough to fit in memory.

For this approach there is a set of helper classes used for partial materialization of the json data. One can specify which
parts of the json structure will be materialized (deserialized to object) with a json path.
A special event JsonEvent.ANY_VALUE will be triggered for those deserialized parts.

Here is an example using JsonMaterializingParser class:

`js
const inputJson = '{"people": [{"firtsName": "Mike", "lastName": "Smith"}, {"firstName": "Foo", "lastName": "Bar"}]}';
const materializedPaths = [".people[*]"];
const writer = new JsonWriter(async (s) => {
console.log(s);
});
const parserCallback = async function (event: JsonEvent) {
if (event.type === JsonEventType.ANY_VALUE) {
const o = event.data;
o.full_name = o.firstName + " " + o.lastName;
}
await writer.write(event);
}
const parser = new JsonMaterializingParser(parserCallback, { materializedPaths });
await parser.parse(inputJson);
await parser.flush();
await writer.flush();
`

Output:
`json
{"people":[
{"firstName":"Mike","lastName":"Smith","full_name":"Mike Smith"},
{"firstName":"Foo","lastName":"Bar","full_name":"Foo Bar"}
]}
`

And here follows example with streams, making use of JsonMaterializingTransformStream:

`js
const input = new StringReadableStream(
'{"people": [{"firstName": "Mike", "lastName": "Smith"}, {"firstName": "Foo", "lastName": "Bar"}]}'
);
const materializedPaths = [".people[*]"];
const transformer = new TransformStream({
transform(event, controller) {
if (event.type === JsonEventType.ANY_VALUE) {
const o = event.data;
o.full_name = o.firstName + " " + o.lastName;
}
controller.enqueue(event);
}
});
await input
.pipeThrough(new StringToJsonTransformStream())
.pipeThrough(new JsonMaterializingTransformStream({materializedPaths}))
.pipeThrough(transformer)
.pipeThrough(new JsonToStringTransformStream())
.pipeTo(new ConsoleLogWritableStream());

`

Output:
`json
{"people":[
{"firstName":"Mike","lastName":"Smith","full_name":"Mike Smith"},
{"firstName":"Foo","lastName":"Bar","full_name":"Foo Bar"}
]}
`

CSV

Async streaming CSV parser.

CsvParser can be used to process csv content as strings. It produces
event objects and sends them to a callback.

$3


`javascript
const p = new CsvParser(async (event) => {
console.log(event.type + " - " + event.data);
});
await p.parse('head')
await p.parse('er1,header2\nvalue1,value2');
await p.flush();
`

Output:
`
header - [ 'header1', 'header2' ]
values - [ 'value1', 'value2' ]
`

Streams

The following example illustrates how the stream-compatible helper classes can be used
in case the input is in the form of
ReadableStream.

`js
import {StringToXmlTransformStream, XmlEventType} from "@quadient/evolve-data-transformations";

(async function () {
const response = await fetch("https://httpbin.org/xml");
const stream = response.body;
stream
.pipeThrough(new TextDecoderStream())
.pipeThrough(new StringToXmlTransformStream())
.pipeTo(new ConsoleLogWritableStream());
})()

class ConsoleLogWritableStream extends WritableStream {
constructor() {
super({
write(chunk) {
console.log(chunk);
}
})
}
}
`

Following stream-compatible classes are available:

- StringToXmlTransformStream - transforms stream of strings to stream of XmlEvent objects (xml deserialization).
- XmlToStringTransformStream - transforms stream of XmlEvent objects to a string stream (xml serialization).
- StringToJsonTransformStream - transforms stream of strings to stream of JsonEvent objects (json deserialization).
- JsonToStringTransformStream - transforms stream of JsonEvent objects to a string stream (json serialization).
- JsonMaterializingTransformStream - transforms stream of JsonEvent objects to JsonEvent objects. Some events just
pass through, some are consumed and translated to special event containing
an object representing the materialized part of the JSON part.
- StringToCsvTransformStream - transforms stream of strings to CsvEvent` objects (csv deserialization).
-