@samverschueren/stream-to-observable
v0.3.1
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Convert Node Streams into ECMAScript-Observables
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stream-to-observable
Convert Node Streams into ECMAScript-Observables
Observables
are rapidly gaining popularity. They have much in common with Streams, in that they both represent data that arrives over time. Most Observable implementations provide expressive methods for filtering and mutating incoming data. Methods like .map()
, .filter()
, and .forEach
behave very similarly to their Array counterparts, so using Observables can be very intuitive.
Note: This module was forked from stream-to-observable
and released under a different name due to inactivity.
Install
$ npm install --save @samverschueren/stream-to-observable
stream-to-observable
relies on any-observable
, which will search for an available Observable implementation. You need to install one yourself:
$ npm install --save zen-observable
or
$ npm install --save rxjs
If your code relies on a specific Observable implementation, you should likely specify one using any-observable
s registration shortcuts.
Usage
const fs = require('fs');
const split = require('split');
const streamToObservable = require('@samverschueren/stream-to-observable');
const readStream = fs
.createReadStream('./hello-world.txt', {encoding: 'utf8'})
.pipe(split());
streamToObservable(readStream)
.filter(chunk => /hello/i.test(chunk))
.map(chunk => chunk.toUpperCase())
.forEach(chunk => {
console.log(chunk); // only the lines containing "hello" - and they will be capitalized
});
The split
module above will chunk the stream into individual lines. This is often very handy for text streams, as each observable event is guaranteed to be a line.
API
streamToObservable(stream, [options])
stream
Type: ReadableStream
Note:
stream
can technically be any EventEmitter
instance. By default, this module listens to the standard Stream events (data
, error
, and end
), but those are configurable via the options
parameter. If you are using this with a standard Stream, you likely won't need the options
parameter.
options
await
Type: Promise
If provided, the Observable will not "complete" until await
is resolved. If await
is rejected, the Observable will immediately emit an error
event and disconnect from the stream. This is mostly useful when attaching to the stdin
or stdout
streams of a child_process
. Those streams usually do not emit error
events, even if the underlying process exits with an error. This provides a means to reject the Observable if the child process exits with an unexpected error code.
endEvent
Type: String
or false
Default: "end"
If you are using an EventEmitter
or non-standard Stream, you can change which event signals that the Observable should be completed.
Setting this to false
will avoid listening for any end events.
Setting this to false
and providing an await
Promise will cause the Observable to resolve immediately with the await
Promise (the Observable will remove all it's data
event listeners from the stream once the Promise is resolved).
errorEvent
Type: String
or false
Default: "error"
If you are using an EventEmitter
or non-standard Stream, you can change which event signals that the Observable should be closed with an error.
Setting this to false
will avoid listening for any error events.
dataEvent
Type: String
Default: "data"
If you are using an EventEmitter
or non-standard Stream, you can change which event causes data to be emitted to the Observable.
Learn about Observables
- Overview
- Formal Spec
- egghead.io lesson - Video
rxjs
observables - Observables implementationzen-observables
- Observables implementation
Transform Streams
data
events on the stream will be emitted as events in the Observable. Since most native streams emit chunks
of binary data, you will likely want to use a TransformStream
to convert those chunks of binary data into an object stream. split
is just one popular TransformStream that splits streams into individual lines of text.
Caveats
It's important to note that using this module disables back-pressure controls on the stream. As such, it should not be used where back-pressure throttling is required (i.e. high volume web servers). It still has value for larger projects, as it can make unit testing streams much cleaner.
License
MIT