pull-stream

Minimal Pipeable Pull-stream

In classic-streams, streams push data to the next stream in the pipeline. In new-streams, data is pulled out of the source stream, into the destination. pull-stream is a minimal take on streams, pull streams work great for "object" streams as well as streams of raw text or binary data.

Quick Example

Stat some files:

pull(
  pull.values(['file1', 'file2', 'file3']),
  pull.asyncMap(fs.stat),
  pull.collect(function (err, array) {
    console.log(array)
  })
)

Note that pull(a, b, c) is basically the same as a.pipe(b).pipe(c).

To grok how pull-streams work, read through pull-streams by example

How do I do X with pull-streams?

There is a module for that!

Check the pull-stream FAQ and post an issue if you have a question that is not covered.

Compatibily with node streams

pull-streams are not directly compatible with node streams, but pull-streams can be converted into node streams with pull-stream-to-stream and node streams can be converted into pull-stream using stream-to-pull-stream correct back pressure is preserved.

Readable & Reader vs. Readable & Writable

Instead of a readable stream, and a writable stream, there is a readable stream, (aka "Source") and a reader stream (aka "Sink"). Through streams is a Sink that returns a Source.

See also:

• Sources
• Throughs
• Sinks

Source (readable stream that produces values)

A Source is a function read(end, cb), that may be called many times, and will (asynchronously) call cb(null, data) once for each call.

To signify an end state, the stream eventually returns cb(err) or cb(true). When signifying an end state, data must be ignored.

The read function must not be called until the previous call has called back. Unless, it is a call to abort the stream (read(Error || true, cb)).

var n = 5;
 
// random is a source 5 of random numbers.
function random (end, cb) {
  if(end) return cb(end)
  // only read n times, then stop.
  if(0 > --n) return cb(true)
  cb(null, Math.random())
}
 

Sink (reader or writable stream that consumes values)

A Sink is a function reader(read) that calls a Source (read(null, cb)), until it decides to stop (by calling read(true, cb)), or the readable ends (read calls cb(Error || true)

All Throughs and Sinks are reader streams.

// logger reads a source and logs it.
function logger (read) {
  read(null, function next(end, data) {
    if(end === true) return
    if(end) throw end
 
    console.log(data)
    read(null, next)
  })
}

Since Sources and Sinks are functions, you can pass them to each other!

logger(random) //"pipe" the streams.
 

but, it's easier to read if you use's pull-stream's pull method

var pull = require('pull-stream')
 
pull(random, logger)

Creating reusable streams

When working with pull streams it is common to create functions that return a stream. This is because streams contain mutable state and so can only be used once. In the above example, once random has been connected to a sink and has produced 5 random numbers it will not produce any more random numbers if connected to another sink.

Therefore, use a function like this to create a random number generating stream that can be reused:

 
// create a stream of n random numbers
function createRandomStream (n) {
  return function randomReadable (end, cb) {
    if(end) return cb(end)
    if(0 > --n) return cb(true)
    cb(null, Math.random())
  }
}
 
pull(createRandomStream(5), logger)

Through

A through stream is both a reader (consumes values) and a readable (produces values). It's a function that takes a read function (a Sink), and returns another read function (a Source).

// double is a through stream that doubles values.
function double (read) {
  return function readable (end, cb) {
    read(end, function (end, data) {
      cb(end, data != null ? data * 2 : null)
    })
  }
}
 
pull(createRandomStream(5), double, logger)

Pipeability

Every pipeline must go from a source to a sink. Data will not start moving until the whole thing is connected.

pull(source, through, sink)

some times, it's simplest to describe a stream in terms of other streams. pull can detect what sort of stream it starts with (by counting arguments) and if you pull together through streams, it gives you a new through stream.

var tripleThrough =
  pull(through1(), through2(), through3())
// The three through streams become one.
 
pull(source(), tripleThrough, sink())

pull detects if it's missing a Source by checking function arity, if the function takes only one argument it's either a sink or a through. Otherwise it's a Source.

Duplex Streams

Duplex streams, which are used to communicate between two things, (i.e. over a network) are a little different. In a duplex stream, messages go both ways, so instead of a single function that represents the stream, you need a pair of streams. {source: sourceStream, sink: sinkStream}

pipe duplex streams like this:

var a = duplex()
var b = duplex()
 
pull(a.source, b.sink)
pull(b.source, a.sink)
 
//which is the same as
 
b.sink(a.source); a.sink(b.source)
 
//but the easiest way is to allow pull to handle this
 
pull(a, b, a)
 
//"pull from a to b and then back to a"
 

Design Goals & Rationale

There is a deeper, platonic abstraction, where a streams is just an array in time, instead of in space. And all the various streaming "abstractions" are just crude implementations of this abstract idea.

classic-streams, new-streams, reducers

The objective here is to find a simple realization of the best features of the above.

Type Agnostic

A stream abstraction should be able to handle both streams of text and streams of objects.

A pipeline is also a stream.

Something like this should work: a.pipe(x.pipe(y).pipe(z)).pipe(b) this makes it possible to write a custom stream simply by combining a few available streams.

Propagate End/Error conditions.

If a stream ends in an unexpected way (error), then other streams in the pipeline should be notified. (this is a problem in node streams - when an error occurs, the stream is disconnected, and the user must handle that specially)

Also, the stream should be able to be ended from either end.

Transparent Backpressure & Laziness

Very simple transform streams must be able to transfer back pressure instantly.

This is a problem in node streams, pause is only transfered on write, so on a long chain (a.pipe(b).pipe(c)), if c pauses, b will have to write to it to pause, and then a will have to write to b to pause. If b only transforms a's output, then a will have to write to b twice to find out that c is paused.

reducers reducers has an interesting method, where synchronous tranformations propagate back pressure instantly!

This means you can have two "smart" streams doing io at the ends, and lots of dumb streams in the middle, and back pressure will work perfectly, as if the dumb streams are not there.

This makes laziness work right.

handling end, error, and abort.

in pull streams, any part of the stream (source, sink, or through) may terminate the stream. (this is the case with node streams too, but it's not handled well).

source: end, error

A source may end (cb(true) after read) or error (cb(error) after read) After ending, the source must never cb(null, data)

sink: abort

Sinks do not normally end the stream, but if they decide they do not need any more data they may "abort" the source by calling read(true, cb). A abort (read(true, cb)) may be called before a preceding read call has called back.

handling end/abort/error in through streams

Rules for implementing read in a through stream:

1. Sink wants to stop. sink aborts the through

   just forward the exact read() call to your source, any future read calls should cb(true).

2. We want to stop. (abort from the middle of the stream)

   abort your source, and then cb(true) to tell the sink we have ended. If the source errored during abort, end the sink by cb read with cb(err). (this will be an ordinary end/error for the sink)

3. Source wants to stop. (read(null, cb) -> cb(err||true))

   forward that exact callback towards the sink chain, we must respond to any future read calls with cb(err||true).

In none of the above cases data is flowing! 4) If data is flowing (normal operation: read(null, cb) -> cb(null, data)

forward data downstream (towards the Sink)
do none of the above!

There either is data flowing (4) OR you have the error/abort cases (1-3), never both.

1:1 read-callback ratio

A pull stream source (and thus transform) returns exactly one value per read.

This differs from node streams, which can use this.push(value) and in internal buffer to create transforms that write many values from a single read value.

Pull streams don't come with their own buffering mechanism, but there are ways to get around this.

Minimal bundle

If you need only the pull function from this package you can reduce the size of the imported code (for instance to reduce a Browserify bundle) by requiring it directly:

var pull = require('pull-stream/pull')
 
pull(createRandomStream(5), logger())

Further Examples

• dominictarr/pull-stream-examples
• ./docs/examples

Explore this repo further for more information about sources, throughs, sinks, and glossary.

License

MIT