This document covers the basics of how to write node.js programs with streams.
"We should have some ways of connecting programs like garden hose--screw in
another segment when it becomes necessary to massage data in
another way. This is the way of IO also."
Doug McIlroy. October 11, 1964
Streams come to us from the
earliest days of unix
and have proven themselves over the decades as a dependable way to compose large
systems out of small components that
do one thing well.
In unix, streams are implemented by the shell with | pipes.
In node, the built-in
stream module
is used by the core libraries and can also be used by user-space modules.
Similar to unix, the node stream module's primary composition operator is called
.pipe() and you get a backpressure mechanism for free to throttle writes for
slow consumers.
Streams can help to separate your concerns because they restrict the implementation surface area into a consistent interface that can be reused. You can then plug the output of one stream to the input of another and use libraries that operate abstractly on streams to institute higher-level flow control.
Streams are an important component of small-program design and unix philosophy but there are many other important abstractions worth considering. Just remember that technical debt is the enemy and to seek the best abstractions for the problem at hand.
I/O in node is asynchronous, so interacting with the disk and network involves passing callbacks to functions. You might be tempted to write code that serves up a file from disk like this:
var http = require('http');
var fs = require('fs');
var server = http.createServer(function (req, res) {
fs.readFile(__dirname + '/data.txt', function (err, data) {
if (err) {
res.statusCode = 500;
res.end(String(err));
}
else res.end(data);
});
});
server.listen(8000);This code works but it's bulky and buffers up the entire data.txt file into
memory for every request before writing the result back to clients. If
data.txt is very large, your program could start eating a lot of memory as it
serves lots of users concurrently. The latency will also be high as users will
need to wait for the entire file to be read before they start receiving the
contents.
Luckily both of the (req, res) arguments are streams, which means we can write
this in a much better way using fs.createReadStream() instead of
fs.readFile():
var http = require('http');
var fs = require('fs');
var server = http.createServer(function (req, res) {
var stream = fs.createReadStream(__dirname + '/data.txt');
stream.on('error', function (err) {
res.statusCode = 500;
res.end(String(err));
});
stream.pipe(res);
});
server.listen(8000);Here .pipe() takes care of listening for 'data' and 'end' events from the
fs.createReadStream(). This code is not only cleaner, but now the data.txt
file will be written to clients one chunk at a time immediately as they are
received from the disk.
Using .pipe() has other benefits too, like handling backpressure automatically
so that node won't buffer chunks into memory needlessly when the remote client
is on a really slow or high-latency connection.
But this example, while much better than the first one, is still rather verbose. The biggest benefit of streams is their versatility. We can use a module that operates on streams to make that example even simpler:
var http = require('http');
var filed = require('filed');
var server = http.createServer(function (req, res) {
filed(__dirname + '/data.txt').pipe(res);
});
server.listen(8000);With the filed module we get mime types, etag caching, and error handling for free in addition to a nice streaming API.
Want compression? There are streaming modules for that too!
var http = require('http');
var filed = require('filed');
var oppressor = require('oppressor');
var server = http.createServer(function (req, res) {
filed(__dirname + '/data.txt')
.pipe(oppressor(req))
.pipe(res)
;
});
server.listen(8000);Now our file is compressed for browsers that support gzip or deflate! We can just let oppressor handle all that content-encoding stuff.
Once you learn the stream api, you can just snap together these streaming modules like lego bricks or garden hoses instead of having to remember how to push data through wonky non-streaming custom APIs.
Streams make programming in node simple, elegant, and composable.
Streams are just EventEmitters that have a .pipe() function and expected to act in a certain way depending if the stream is readable, writable, or both (duplex).
To create a new stream, just do:
var Stream = require('stream');
var s = new Stream;This new stream doesn't yet do anything because it is neither readable nor writable.
To make that stream s into a readable stream, all we need to do is set the
readable property to true:
s.readable = trueReadable streams emit many 'data' events and a single 'end' event.
Your stream shouldn't emit any more 'data' events after it emits the 'end'
event.
This simple readable stream emits one 'data' event per second for 5 seconds,
then it ends. The data is piped to stdout so we can watch the results as they
var Stream = require('stream');
function createStream () {
var s = new Stream;
s.readable = true
var times = 0;
var iv = setInterval(function () {
s.emit('data', times + '\n');
if (++times === 5) {
s.emit('end');
clearInterval(iv);
}
}, 1000);
return s;
}
createStream().pipe(process.stdout);substack : ~ $ node rs.js
0
1
2
3
4
substack : ~ $
In this example the 'data' events have a string payload as the first argument.
Buffers and strings are the most common types of data to stream but it's
sometimes useful to emit other types of objects.
Just make sure that the types you're emitting as data is compatible with the types that the writable stream you're piping into expects. Otherwise you can pipe into an intermediary conversion or parsing stream before piping to your intended destination.
Writable streams are streams that can accept input. To create a writable stream,
set the writable attribute to true and define write(), end(), and
destroy().
This writable stream will count all the bytes from an input stream and print the
result on a clean end(). If the stream is destroyed it will do nothing.
var Stream = require('stream');
var s = new Stream;
s.writable = true;
var bytes = 0;
s.write = function (buf) {
bytes += buf.length;
};
s.end = function (buf) {
if (arguments.length) s.write(buf);
s.writable = false;
console.log(bytes + ' bytes written');
};
s.destroy = function () {
s.writable = false;
};If we pipe a file to this writable stream:
var fs = require('fs');
fs.createReadStream('/etc/passwd').pipe(s);$ node writable.js
2447 bytes written
One thing to watch out for is the convention in node to treat end(buf) as a
write(buf) then an end(). If you skip this it could lead to confusion
because people expect end to behave the way it does in core.
Backpressure is the mechanism that streams use to make sure that readable streams don't emit data faster than writable streams can consume data.
Note: the API for handling backpressure is changing substantially in future
versions of node (> 0.8). pause(), resume(), and emit('drain') are
scheduled for demolition. The notice has been on display in the local planning
office for months.
In order to do backpressure correctly readable streams should
implement pause() and resume(). Writable streams return false in
.write() when they want the readable streams piped into them to slow down and
emit 'drain' when they're ready for more data again.
When a writable stream wants a readable stream to slow down it should return
false in its .write() function. This causes the pause() to be called on
each readable stream source.
When the writable stream is ready to start receiving data again, it should emit
the 'drain' event. Emitting 'drain' causes the resume() function to be
called on each readable stream source.
When pause() is called on a readable stream, it means that a downstream
writable stream wants the upstream to slow down. The readable stream that
pause() was called on should stop emitting data but that isn't always
possible.
When the downstream is ready for more data, the readable stream's resume()
function will be called.
.pipe() is the glue that shuffles data from readable streams into writable
streams and handles backpressure. The pipe api is just:
src.pipe(dst)
for a readable stream src and a writable stream dst. .pipe() returns the
dst so if dst is also a readable stream, you can chain .pipe() calls
together like:
a.pipe(b).pipe(c).pipe(d)which resembles what you might do in the shell with the | operator:
a | b | c | d
The a.pipe(b).pipe(c).pipe(d) usage is the same as:
a.pipe(b);
b.pipe(c);
c.pipe(d);
The stream implementation in core is just an event emitter with a pipe function.
pipe() is pretty short. You should read
the source code.
These terms are useful for talking about streams.
Through streams are simple readable/writable filters that transform input and produce output.
Duplex streams are readable/writable and both ends of the stream engage in a two-way interaction, sending back and forth messages like a telephone. An rpc exchange is a good example of a duplex stream. Any time you see something like:
a.pipe(b).pipe(a)you're probably dealing with a duplex stream.
A big upgrade is planned for the stream api in node 0.9.
The basic apis with .pipe() will be the same, only the internals are going to
be different. The new api will also be backwards compatible with the existing
api documented here for a long time.
You can check the readable-stream repo to see what these future streams will look like.
These streams are built into node itself.
This readable stream contains the standard system input stream for your program.
It is paused by default but the first time you refer to it .resume() will be
called implicitly on the
next tick.
If process.stdin is a tty (check with
tty.isatty())
then input events will be line-buffered. You can turn off line-buffering by
calling process.stdin.setRawMode(true) BUT the default handlers for key
combinations such as ^C and ^D will be removed.
This writable stream contains the standard system output stream for your program.
write to it if you want send data to stdout
This writable stream contains the standard system error stream for your program.
write to it if you want send data to stderr
This function returns a [duplex stream] that connects over tcp to a remote host.
You can start writing to the stream right away and the writes will be buffered
until the 'connect' event fires.
scuttlebutt can be used for peer-to-peer state synchronization with a mesh topology where nodes might only be connected through intermediaries and there is no node with an authoritative version of all the data.
The kind of distributed peer-to-peer network that scuttlebutt provides is especially useful when nodes on different sides of network barriers need to share and update the same state. An example of this kind of network might be browser clients that send messages through an http server to each other and backend processes that the browsers can't directly connect to. Another use-case might be systems that span internal networks since IPv4 addresses are scarce.
scuttlebutt uses a gossip protocol to pass messages between connected nodes so that state across all the nodes will eventually converge on the same value everywhere.
Using the scuttlebutt/model interface, we can create some nodes and pipe them
to each other to create whichever sort of network we want:
var Model = require('scuttlebutt/model');
var am = new Model;
var as = am.createStream();
var bm = new Model;
var bs = bm.createStream();
var cm = new Model;
var cs = cm.createStream();
var dm = new Model;
var ds = dm.createStream();
var em = new Model;
var es = em.createStream();
as.pipe(bs).pipe(as);
bs.pipe(cs).pipe(bs);
bs.pipe(ds).pipe(bs);
ds.pipe(es).pipe(ds);
em.on('update', function (key, value, source) {
console.log(key + ' => ' + value + ' from ' + source);
});
am.set('x', 555);The network we've created is an undirected graph that looks like:
a <-> b <-> c
^
|
v
d <-> e
Note that nodes a and e aren't directly connected, but when we run this
script:
$ node model.js
x => 555 from 1347857300518
the value that node a set finds its way to node e by way of nodes b and
d. Here all the nodes are in the same process but because
scuttlebutt uses a
simple streaming interface, the nodes can be placed on any process or server and
connected with any streaming transport that can handle string data.
Next we can make a more realistic example that connects over the network and increments a counter variable.
Here's the server which will set the initial count value to 0 and count ++
every 320 milliseconds, printing all updates to count:
var Model = require('scuttlebutt/model');
var net = require('net');
var m = new Model;
m.set('count', '0');
m.on('update', function (key, value) {
console.log(key + ' = ' + m.get('count'));
});
var server = net.createServer(function (stream) {
stream.pipe(m.createStream()).pipe(stream);
});
server.listen(8888);
setInterval(function () {
m.set('count', Number(m.get('count')) + 1);
}, 320);Now we can make a client that connects to this server, updates the count on an interval, and prints all the updates it receives:
var Model = require('scuttlebutt/model');
var net = require('net');
var m = new Model;
var s = m.createStream();
s.pipe(net.connect(8888, 'localhost')).pipe(s);
m.on('update', function cb (key) {
// wait until we've gotten at least one count value from the network
if (key !== 'count') return;
m.removeListener('update', cb);
setInterval(function () {
m.set('count', Number(m.get('count')) + 1);
}, 100);
});
m.on('update', function (key, value) {
console.log(key + ' = ' + value);
});The client is slightly trickier since it should wait until it has an update from somebody else to start updating the counter itself or else its counter would be zeroed.
Once we get the server and some clients running we should see a sequence like this:
count = 183
count = 184
count = 185
count = 186
count = 187
count = 188
count = 189
Occasionally on some of the nodes we might see a sequence with repeated values like:
count = 147
count = 148
count = 149
count = 149
count = 150
count = 151
These values are due to scuttlebutt's history-based conflict resolution algorithm which is hard at work ensuring that the state of the system across all nodes is eventually consistent.
Note that the server in this example is just another node with the same privledges as the clients connected to it. The terms "client" and "server" here don't affect how the state synchronization proceeds, just who initiates the connection. Protocols with this property are often called symmetric protocols. See dnode for another example of a symmetric protocol.
Use this module to parse and stringify json data from streams.
If you need to pass a large json collection through a slow connection or you have a json object that will populate slowly this module will let you parse data incrementally as it arrives.
dnode lets you call remote functions through any kind of stream.
Here's a basic dnode server:
var dnode = require('dnode');
var net = require('net');
var server = net.createServer(function (c) {
var d = dnode({
transform : function (s, cb) {
cb(s.replace(/[aeiou]{2,}/, 'oo').toUpperCase())
}
});
c.pipe(d).pipe(c);
});
server.listen(5004);then you can hack up a simple client that calls the server's .transform()
function:
var dnode = require('dnode');
var net = require('net');
var d = dnode();
d.on('remote', function (remote) {
remote.transform('beep', function (s) {
console.log('beep => ' + s);
d.end();
});
});
var c = net.connect(5004);
c.pipe(d).pipe(c);Fire up the server, then when you run the client you should see:
$ node client.js
beep => BOOP
The client sent 'beep' to the server's transform() function and the server
called the client's callback with the result, neat!
The streaming interface that dnode provides here is a duplex stream since both
the client and server are piped to each other (c.pipe(d).pipe(c)) with
requests and responses coming from both sides.
The craziness of dnode begins when you start to pass function arguments to stubbed callbacks. Here's an updated version of the previous server with a multi-stage callback passing dance:
var dnode = require('dnode');
var net = require('net');
var server = net.createServer(function (c) {
var d = dnode({
transform : function (s, cb) {
cb(function (n, fn) {
var oo = Array(n+1).join('o');
fn(s.replace(/[aeiou]{2,}/, oo).toUpperCase());
});
}
});
c.pipe(d).pipe(c);
});
server.listen(5004);Here's the updated client:
var dnode = require('dnode');
var net = require('net');
var d = dnode();
d.on('remote', function (remote) {
remote.transform('beep', function (cb) {
cb(10, function (s) {
console.log('beep:10 => ' + s);
d.end();
});
});
});
var c = net.connect(5004);
c.pipe(d).pipe(c);After we spin up the server, when we run the client now we get:
$ node client.js
beep:10 => BOOOOOOOOOOP
It just works!™
The basic idea is that you just put functions in objects and you call them from the other side of a stream and the functions will be stubbed out on the other end to do a round-trip back to the side that had the original function in the first place. The best thing is that when you pass functions to a stubbed function as arguments, those functions get stubbed out on the other side!
This approach of stubbing function arguments recursively shall henceforth be known as the "turtles all the way down" gambit. The return values of any of your functions will be ignored and only enumerable properties on objects will be sent, json-style.
It's turtles all the way down!
Since dnode works in node or on the browser over any stream it's easy to call functions defined anywhere and especially useful when paired up with mux-demux to multiplex an rpc stream for control alongside some bulk data streams.
The append-only module can give us a convenient append-only array on top of scuttlebutt which makes it really easy to write an eventually-consistent, distributed chat that can replicate with other nodes and survive network partitions.
TODO: the rest
We can build a socket.io-style event emitter api over streams using some of the libraries mentioned earlier in this document.
First we can use shoe to create a new websocket handler server-side and emit-stream to turn an event emitter into a stream that emits objects. The object stream can then be fed into JSONStream to serialize the objects and from there the serialized stream can be piped into the remote browser.
var EventEmitter = require('events').EventEmitter;
var shoe = require('shoe');
var emitStream = require('emit-stream');
var JSONStream = require('JSONStream');
var sock = shoe(function (stream) {
var ev = new EventEmitter;
emitStream(ev)
.pipe(JSONStream.stringify())
.pipe(stream)
;
...
});Inside the shoe callback we can emit events to the ev function. Here we'll
just emit different kinds of events on intervals:
var intervals = [];
intervals.push(setInterval(function () {
ev.emit('upper', 'abc');
}, 500));
intervals.push(setInterval(function () {
ev.emit('lower', 'def');
}, 300));
stream.on('end', function () {
intervals.forEach(clearInterval);
});Finally the shoe instance just needs to be bound to an http server:
var http = require('http');
var server = http.createServer(require('ecstatic')(__dirname));
server.listen(8080);
sock.install(server, '/sock');Meanwhile on the browser side of things just parse the json shoe stream and pass
the resulting object stream to eventStream(). eventStream() just returns an
event emitter that emits the server-side events:
var shoe = require('shoe');
var emitStream = require('emit-stream');
var JSONStream = require('JSONStream');
var parser = JSONStream.parse([true]);
var stream = parser.pipe(shoe('/sock')).pipe(parser);
var ev = emitStream(stream);
ev.on('lower', function (msg) {
var div = document.createElement('div');
div.textContent = msg.toLowerCase();
document.body.appendChild(div);
});
ev.on('upper', function (msg) {
var div = document.createElement('div');
div.textContent = msg.toUpperCase();
document.body.appendChild(div);
});Use browserify to build this
browser source code so that you can require() all these nifty modules
browser-side:
$ browserify main.js -o bundle.js
Then drop a <script src="/bundle.js"></script> into some html and open it up
in a browser to see server-side events streamed through to the browser side of
things.
With this streaming approach you can rely more on tiny reusable components that only need to know how to talk streams. Instead of routing messages through a global event system socket.io-style, you can focus more on breaking up your application into tinier units of functionality that can do exactly one thing well.
For instance you can trivially swap out JSONStream in this example for stream-serializer to get a different take on serialization with a different set of tradeoffs. You could bolt layers over top of shoe to handle reconnections or heartbeats using simple streaming interfaces. You could even add a stream into the chain to use namespaced events with eventemitter2 instead of the EventEmitter in core.
If you want some different streams that act in different ways it would likewise be pretty simple to run the shoe stream in this example through mux-demux to create separate channels for each different kind of stream that you need.
As the requirements of your system evolve over time, you can swap out each of these streaming pieces as necessary without as many of the all-or-nothing risks that more opinionated framework approaches necessarily entail.