Archive for livecoding

Ableton Livecoding with Caffeine

Posted in Uncategorized with tags , , , , , , on 5 June 2021 by Craig Latta
Livecoding access can tame the complexity of Ableton Live.

I’ve written a proxy system to communicate with Ableton Live from Caffeine, for interactive music composition and performance. Live includes Max for Live (M4L), an embedded version of the Max media programming system. M4L has, in turn, access to both Node.JS, a server-side JavaScript engine embedded as a separate process, and to an internal JS engine extension of its own object system. Caffeine can connect to Node.JS through a websocket, Node.JS can send messages to Max, Max can call user-written JS functions, and those JS functions can invoke the Live Object Model, an API for manipulating Live. This stack of APIs also supports returning results back over the websocket, and for establishing callbacks.

getting connected

Caffeine creates a websocket connection to a server running in M4L’s Node.JS, using the JS WebSocket function provided by the web browser. A Caffeine object can use this connection to send a JSON string describing a Live function it would like to invoke. Node.JS passes the JSON string to Max, through an output of a Max object in a Max program, or patcher:

connecting the Node.JS server with JS Live API function invocation

Max is a visual dataflow system, in which objects inputs and outputs are connected, and their functions are run by a real-time scheduler. There are two special objects in the patcher above. The first is node.script, which controls the operation of a Node.JS script. It’s running the Node.JS script “caffeine-server.js”, which creates a websocket server. That script has access to a Max API, which it uses to send data through the output of the node.script object.

The second special object is js, which runs “caffeine-max.js”. That script parses the JSON function invocation request sent by Caffeine, invokes the desired Live API function, and sends the result back to Caffeine through the Node.JS server.

proxying

With this infrastructure in place, we can create a proxy object system in Caffeine. In class Live, we can write a method which invokes Live functions:

invoking a Live function from Caffeine

This method uses a SharedQueue for each remote message sent; the JS bridge callback process delivers results to them. This lets us nest remote message sends among multiple processes. The JSON data identifies the function and argument of the invocation, the identifier of receiving Live object, and the desired Smalltalk class of the result.

The LiveObject proxy class can use this invoking function from its doesNotUnderstand method:

forwarding a message from a proxy

Now that we have message forwarding, we can represent the entire Live API as browsable Smalltalk classes. I always find this of huge benefit when doing mashups with external code libraries, but especially so with Live. The Live API is massive, and while the documentation is complete, it’s not very readable. It’s much more pleasant to learn about the API with the Smalltalk browsing tools. As usual, we can extend the API with composite methods of our own, aggregating multiple Live API calls into one. With this we can effectively extend the Live API with new features.

extending the Live API

One area of Live API extension where I’m working now is in song composition. Live has an Arrangement view, for a traditional recording studio workflow, and a Session view, for interactive performance. I find the “scenes” feature of the Session view very useful for sketching song sections, but Live’s support for playing them in different orders is minimal. With Caffeine objects representing scenes, I can compose larger structures from them, and play them however I like.

How would you extend the Live API? How would you simplify it?

The Node.JS server, JS proxying code, and the Max patcher that connects them are available as a self-contained M4L device, which can be applied to any Live track. Look for it in the devices folder of the Caffeine repository.

Beatshifting: playing music in sync and out of phase

Posted in Appsterdam, Caffeine, consulting, Context, livecoding, music, Smalltalk, SqueakJS with tags , , , , , , , on 27 April 2021 by Craig Latta
two Beatshifting timelines

I’ve written a Caffeine app implementation of the Beatshifting algorithm, for collaborative remote music performance that is synchronized and out-of-phase. Beatshifting uses network latency as a rhythmic element, using offsets from beats as timestamps, with a shared metronome and score.

I was inspired to write the Beatshifting app by NINJAM, a similar system that has hosted many hours of joyous sessions. There are a few interesting twists I think I can bring to the technology, through late-binding of audio rendering.

NINJAM also synchronizes distributed streams of rhythmic music. It works by using a server to collect an entire measure of audio from the performers’ timestamped streams, stamps them all with an upcoming measure number, and sends them back to each performer. Each performer’s system plays the collected measures with the start times aligned. In effect, each performer plays along with what everyone else did a measure ago. Each performer must receive audio only by the start of the upcoming measure, rather than fast enough to create the illusion of simultaneity.

Beatshifting gives more control over the session to each performer, and to an audience as well. Each performer can modify not only the local volume levels of the other performers, but also their delays and instruments. Each performer can also change the tempo and time signature of the session. A session can have an audience as well, and each audience member is really a performer who hasn’t played anything yet.

It’s straightforward to have an arbitrary number of participants in a session because Beatshifting takes the form of a web app. Each participant only needs to visit a session link in a web browser, rather than use a special digital audio workstation (DAW) app. By default, Beatshifting uses MIDI event messages instead of audio, using much less bandwidth even with a large group.

To deliver events to each participant’s web browser, Beatshifting uses the Croquet replication service. Croquet is able to replicate and synchronize any JavaScript object in every participant’s web browser, up to 60 times per second. Beatshifting uses this to provide a shared score. Music events like notes and fader movements can be scheduled into the score by any participant, and from code run by the score itself.

One piece of code the score runs broadcasts events indicating that measures have elapsed, so that the web browsers can render metronome clicks. There are three kinds of metronome clicks, for ticks, beats, and measures. For example, with a time signature of 6/8, there are two beats per measure, and three ticks per beat. Each tick is an eighth-note, so each beat is a dotted-quarter note. The sequence of clicks one hears is:

  • measure
  • tick
  • tick
  • beat
  • tick
  • tick

At a tempo of 120 beats per minute, or 240 clicks per 60,000 milliseconds, there are 250 milliseconds between clicks. Each time a web browser receives a measure-elapsed event, it schedules MIDI events for the next measure’s clicks with the local MIDI output interface. Since each web browser knows the starting time of the session in its output MIDI interface’s timescale, it can calculate the timestamps of all ensuing clicks.

When a performer plays a note, their web browser notes the offset in milliseconds between when the note was played and the time of the most recent click. The web browser then publishes an event-scheduling message, to which the score is subscribed. The score then broadcasts a note-played event to all the web browsers. Again, it’s up to each web browser to schedule a corresponding MIDI note with its local MIDI output interface. The local timestamp of that note is chosen to be the same millisecond offset from some future click point. How far in the future that click is can be chosen based on who played the note, or any other element of the event’s data. Each web browser can also choose other parameters for each event, like instrument, volume level, and panning position.

Quantities like tempo are part of the score’s state, and can be changed by any performer or audience member. Croquet ensures that the changed JavaScript variables are synchronized in all the participants’ web browsers.

With so many decisions about how music events are rendered left to each web browser, the mix that each participant hears can be wildly different. The only constants are the millisecond beat offsets of each performer’s notes. I think it’ll be fun to compare recordings of these mixes after the fact, and to make new ones from individual recorded tracks.

There’s no server that any participant needs to set up, and the Croquet service knows nothing of the Beatshifting protocol. This makes it very easy to start and join new sessions.

next steps

The current Beatshifting UI has controls for joining a session, enabling the local scheduling of metronome clicks, and changing the tempo and time signature of a session.

the current Beatshifting UI

If one is using a MIDI output interface connected to a DAW, then one may use the DAW to control instruments, volume, panning, and so on. I’d also like to provide the option of all MIDI event rendering performed by the web browser, and a UI for controlling and recording that. I’ve established the use of the ToneJS audio framework for rendering events, and am now developing the UI.

I led a debut performance of Beatshifting as part of the Netherlands Coding Live concert series, on 23 April 2021.

I’ve written an animated 3D visualization of the Beatshifting algorithm, which can be driven from live session data. This movie is an annotated slow-motion version:

visualizing the Beatshifting algorithm

I’m excited about the creative potential of Beatshifting sessions. Please contact me if you’re interested in playing or coding for this medium!

team livecoding features

Posted in Uncategorized with tags , , , , , , , , on 10 November 2019 by Craig Latta
What IDE information would you like to share with your teammates as you work?

Caffeine can now:

  • provide an IDE as a DOM element
  • provide an IDE as a Chrome DevTools panel
  • run headlessly in a web browser worker thread, NodeJS server worker thread, or NodeJS main thread.

We have all the components we need to connect teams of livecoders, sharing information from their IDEs as they work. What information would we like to share?

proactive conflict resolution

I’d like to share information that makes code integration easier, by spreading awareness of potential conflicts as soon as possible. Imagine, for example, that you’ve found a bug in a longstanding system method, and decide to start editing it. Before the commit of your change (which may still be days or weeks away), someone else on your team also happens to start editing that method. Wouldn’t it be nice to know that both of you are interested in changing the method?

If both of you are connected to a team network, your IDEs can notify each other when a potential conflict situation like this begins, and the two of you can resolve it through discussion. Such a feature could be vital in a team where responsibility for methods and classes is clearly and completely divided between authors.

The servers in this network can provide history services, too, acting as repositories of all the versions of methods and classes that have been committed by team members. This could aid in unit testing, sharing of works-in-progress, and deployment.

How would you use it?

How would you like to use such a system? How would your needs change when acting as a developer, or as a manager? I’m writing a specification now, and would love to hear your thoughts. Thanks!

Exploring the Netflix player with the Caffeine Chrome extension

Posted in Caffeine, consulting, Context, livecoding, music, Smalltalk, SqueakJS with tags , , , , , , , , , , on 22 September 2019 by Craig Latta
debugging Better Call Saul with Caffeine

With the latest version of the Caffeine Chrome extension, you can run Caffeine in a Chrome DevTools panel, with access to all the Chrome debugging APIs. I’ve been using it to explore the Netflix video player, for an app I’m writing that enables the viewer to edit narratives by rearranging scenes.

From a quick look at the DOM element tree for the player, it’s apparent that it’s a React app. By following a reference chain from a user interface element (like the skip-forward button), through the bound “this” object of its click-event listener, I found the internal React properties for all the player’s UI elements, and all the player functions they use (for example, for seeking forward in a video).

With those functions in hand, I made a Netflix player class in Smalltalk, which can manipulate the Netflix player React app interactively from Smalltalk code. Other objects I made representing show elements (like scenes, episodes, seasons, and series) can use my player to compile analytic information about shows, and present them in different ways. For example, you could watch an episode of Better Call Saul consisting only of scenes that include a certain character, or that take place at a certain location, or with flashbacks placed in chronological order. This is for a webapp I’m writing called Arc.

I’m eager to see what else you explore using the Caffeine extension in the DevTools!

The Big Shake-Out

Posted in Appsterdam, Caffeine, consulting, Context, livecoding, Naiad, Smalltalk, Spoon, SqueakJS with tags , , , , , , , , , , , , , , , , , on 25 March 2019 by Craig Latta

Golden Retriever shaking off water

Some of those methods were there for a very long time!

I have adapted the minimization technique from the Naiad module system to Caffeine, my integration of OpenSmalltalk with the Web and Node platforms. Now, from a client Squeak, Pharo, or Cuis system in a web browser, I can make an EditHistory connection to a history server Smalltalk system, remove via garbage collection every method not run since the client was started, and imprint needed methods from the server as the client continues to run.

This is a garbage collection technique that I had previously called “Dissolve”, but I think the details are easier to explain with a different metaphor: “shaking” loose and removing everything which isn’t attached to the system through usage. This is a form of dynamic dead code elimination. The technique has two phases: “fusing” methods that must not be removed, and “shaking” loose all the others, removing them. This has a cascading effect, as the literals of removed methods without additional references are also removed, and further objects without references are removed as well.

After unfused methods and their associated objects are removed, the subsystems that provided them are effectively unloaded. For the system to use that functionality again, the methods must be reloaded. This is possible using the Naiad module system. By connecting a client system to a history server before shaking, the client can reload missing methods from the server as they are needed. For example, if the Morphic UI subsystem is shaken away, and the user then attempts to use the UI, the parts of Morphic needed by the user’s interactions are reloaded as needed.

This technology is useful for delineating subsystems that were created without regard to modularity, and creating deployable modules for them. It’s also useful for creating minimal systems suited to a specific purpose. You can fuse all the methods run by the unit tests for an app, and shake away all the others, while retaining the ability to debug and extend the system.

how it works

Whether a method is fused or not is part of the state of the virtual machine running the system, and is reset when the virtual machine starts. On system resumption, no method is fused. Each method can be told to fuse itself manually, through a primitive interface. Otherwise, methods are fused by the virtual machine as they are run. A class called Shaker knows which methods in a typical system are essential for operation. A Shaker instance can ensure those methods are fused, then shake the system.

Shaking itself invokes a variant of the normal OpenSmalltalk garbage collector. It replaces each unfused method with a special method which, when run, knows how to install the original method from a connected history server. In effect, all unfused methods are replaced by a single method.

Reinstallation of a method uses Naiad behavior history metadata, obtained by remote messaging with a history server, to reconstruct the method and put it in the proper method dictionary. The process creates any necessary prerequisites, such as classes and shared pools. No compiler is needed, because methods are constructed from previously-generated instructions; source code is merely an optional annotation.

the benefits of livecoding all the way down

I developed the virtual machine support for this feature with Bert Freudenberg‘s SqueakJS virtual machine, making heavy use of the JavaScript debugger in a web browser. I was struck by how much faster this sort of work is with a completely livecoded environment, rather than the C-based environment in which we usually develop the virtual machine. It’s similar to the power of Squeak’s virtual machine simulator. The tools, living in JavaScript, aren’t as powerful as Smalltalk-based ones, but they operate on the final Squeak virtual machine, rather than a simulation that runs much more slowly. Rebuilding the virtual machine amounts to reloading the web page in which it runs, and takes a few seconds, rather than the ordeal of a C-based build.

Much of the work here involved trial and error. How does Shaker know which methods are essential for system operation? I found out directly, by seeing where the system broke after being shaken. One can deduce some of the answer; for example, it’s obvious that the methods used by method contexts of current processes should be fused. Most of the essential methods yet to run, however, are not obvious. It was only because I had an interactive virtual machine development environment that it was feasible to restart the system and modify the virtual machine as many times as I needed (many, many times!), in a reasonable timeframe. Being able to tweak the virtual machine in real time from Smalltalk was also indispensable for debugging and feature development.

I want to thank Bert again for his work on SqueakJS. Also, many thanks to Dan Ingalls and the rest of the Lively team for creating the environment in which SqueakJS was originally built.

release schedule

I’m preparing Shaker for the next seasonal release of Caffeine, on the first 2019 solstice, 21 June 2019. I’ll make the virtual machine changes available for all OpenSmalltalk host platforms, in addition to the Web and Node platforms that Caffeine uses via the SqueakJS virtual machine. There may be alpha and beta releases before then.

If this technology sounds interesting to you, please let me know. I’m interested in use cases for testing. Thanks!

Livecoding other tabs with the Chrome Remote Debugging Protocol

Posted in Appsterdam, consulting, Context, Smalltalk, SqueakJS with tags , , , , , , , on 24 July 2017 by Craig Latta

Chrome Debugging Protocol

We’ve seen how to use Caffeine to livecode the webpage in which we’re running. With its support for the Chrome Remote Debugging Protocol (CRDP), we can also use it to livecode every other page loaded in the web browser.

Some Help From the Inside

To make this work, we need to coordinate with the Chrome runtime engine. For CRDP, there are two ways of doing this. One is to communicate using a WebSocket connection; I wrote about this last year. This is useful when the CRDP client and target pages are running in two different web browsers (possibly on two different machines), but with the downside of starting the target web browser in a special way (so that it starts a conventional webserver).

The other way, possible when both the CRDP client and target pages are in the same web browser, is to use a Chrome extension. The extension can communicate with the client page over an internal port object, created by the chrome.runtime API, and expose the CRDP APIs. The web browser need not be started in a special way, it just needs to have the extension installed. I’ve published a Caffeine Helper extension, available on the Chrome Web Store. Once installed, the extension coordinates communication between Caffeine and the CRDP.

Attaching to a Tab

In Caffeine, we create a connection to the extension by creating an instance of CaffeineExtension:

CaffeineExtension new inspect

As far as Chrome is concerned, Caffeine is now a debugger, just like the built-in DevTools. (In fact, the DevTools do what they do by using the very same CRDP APIs; they’re just another JavaScript application, like Caffeine is.) Let’s open a webpage in another tab, for us to manipulate. The Google homepage makes for a familiar example. We can attach to it, from the inspector we just opened, by evaluating:

self attachToTabWithTitle: 'Google'

Changing Feelings

Now let’s change something on the page. We’ll change the text of the “I’m Feeling Lucky” button. We can get a reference to it with:

tabs onlyOne find: 'Feeling'

When we attached to the tab, the tabs instance variable of our CaffeineExtension object got an instance of ChromeTab added to it. ChromeTabs provide a unified message interface to all the CRDP APIs, also known as domains. The DOM domain has a search function, which we can use to find the “I’m Feeling Lucky” button. The CaffeineExtension>>find: method which uses that function answers a collection of search results objects. Each search result object is a proxy for a JavaScript DOM object in the Google page, an instance of the ChromeRemoteObject class.

In the picture above, you can see an inspector on a ChromeRemoteObject corresponding to the “I’m Feeling Lucky” button, an HTMLInputElement DOM object. Like the JSObjectProxies we use to communicate with JavaScript objects in our own page, ChromeRemoteObjects support normal Smalltalk messaging, making the JavaScript DOM objects in our attached page seem like local Smalltalk objects. We only need to know which messages to send. In this case, we send the messages of HTMLInputElement.

As with the JavaScript objects of our own page, instead of having to look up external documentation for messages, we can use subclasses of JSObject to document them. In this case, we can use an instance of the JSObject subclass HTMLInputElement. Its proxy instance variable will be our ChromeRemoteObject instead of a JSObjectProxy.

For the first message to our remote HTMLInputElement, we’ll change the button label text, by changing the element’s value property:

self at: #value put: 'I''m Feeling Happy'

The Potential for Dynamic Web Development

The change we made happens immediately, just as if we had done it from the Chrome DevTools console. We’re taking advantage of JavaScript’s inherent livecoding nature, from an environment which can be much more comfortable and powerful than DevTools. The form of web applications need not be static files, although that’s a convenient intermediate form for webservers to deliver. With generalized messaging connectivity to the DOM of every page in a web browser, and with other web browsers, we have a far more powerful editing medium. Web applications are dynamic media when people are using them, and they can be that way when we develop them, too.

What shall we do next?

 

Pharo comes to Caffeine and SqueakJS

Posted in Appsterdam, consulting, Context, GLASS, Naiad, Seaside, Smalltalk, Spoon, SqueakJS with tags , , , , , , , , , on 29 June 2017 by Craig Latta

Google ChromeScreenSnapz025

The Caffeine web livecoding project has added Pharo to the list of Smalltalk distributions it runs with SqueakJS. Bert Freudenberg and I spent some time getting SqueakJS to run Pharo at ESUG 2016 in Prague last summer, and it mostly worked. I think Bert got a lot further since then, because now there are just a few Pharo primitives that need implementing. All I’ve had to do so far this time is a minor fix to the input event loop and add the JavaScript bridge. The bridge now works from Pharo, and it’s the first time I’ve seen that.

Next steps include getting the Tether remote messaging protocol and Snowglobe app streaming working between Pharo and Squeak, all running in SqueakJS. Of course, I’d like to see fluid code-sharing of all kinds between Squeak, Pharo, and all the other Smalltalk implementations.

So, let the bugfixing begin! :)  You can run it at https://caffeine.js.org/pharo/. Please do get in touch if you find and fix things. Thanks!

Backend Caffeine with Node.js and Tweetcoding

Posted in Appsterdam, consulting, Context, Smalltalk, Spoon, SqueakJS with tags , , , , , , on 27 June 2017 by Craig Latta

tweetcodingWe’ve seen a couple of examples of frontend Caffeine development, using jQuery UI and voxel.js. Let’s look at something on the backend, using Node.js and something I like to call tweetcoding.

Social Livecoding

Livecoding means having all the capabilities of your development environment while your system is live. Runtime is all the time. Smalltalk programmers have always enjoyed this way of working. It is particularly effective in domains such as music performance, where the ability to make changes while your system is running is critical, both for fixing bugs and for artistic expression. One of my artistic goals with musical livecoding (writing code that makes live music for an audience) is audience accessibility. I want the audience to have some understanding of what’s going on in my code, even if they aren’t coders (yet).

Another aspect I like to incorporate is audience participation. If the audience actually does understand what I’m doing in my code, why not let them join in? Social media has become a ubiquitous communication platform; billions of people are using it with prose and pictures. I think the time has come to use it with live code as well. Nearly everyone in the audience has a powerful computer with social media access in a pocket. We can all livecode together.

Let’s Do This

We need three things to make this happen: a way for people to submit code, something that listens for that code and evaluates it, and a shared artifact everyone can see that shows the code’s effects. I like Twitter as a coding medium, for its minimalism. It also has a culture of hashtag use, and a streaming API, which make listening for code straightforward. For the shared artifact, we can use something viewed with Caffeine in a web browser.

For our first example, let’s use something simple for our coding domain, like turtle graphics. A person can tweet instructions to a turtle which draws on a square piece of paper, 100 units on a side. There are four commands:

  • color, for the turtle to change its pen for one of the given color
  • down, for the turtle to put its pen down on the paper
  • rotate, for the turtle to change direction
  • move, for the turtle to move some distance
  • up, for the turtle to take its pen up from the paper

We’ll say that that the turtle can be identified by some ID, and is initially at the center of the paper. A tweetcoded instruction for the turtle might look like:

FranzScreenSnapz002

Tweetcoding tweets start with the #tweetcoding hashtag, so people seeing one for the first time can look at others with that hashtag, to see what it’s about. This is followed by hashtags identifying our turtle-graphics protocol, and the turtle we’re using. We end the tweet with a drawing instruction, using our instruction set above.

Livecoding NodeJS

To detect these tweets, we’ll use the Twitter streaming API from Node.js. In the spirit of livecoding, we won’t use an application-specific Node.js module for this directly, but instead inject JavaScript code live into a Node.js instance, from Caffeine in a web browser. I’ve written a node-livecode Node.js module which takes commands over a websocket. It starts with three instructions:

  • require, for loading another Node.js module into itself with npm
  • add instruction, for adding an instruction to itself
  • eval, for evaluating JavaScript code

You can see the implementation at GitHub. It can use SSL to keep injected code secure in transit, so you may want to set up a certificate for your server with Let’s Encrypt. Also note that it exposes the listening server as a global variable, so that you can use it in your injected code.

Once we have node-livecode on a server listening for commands, we can inject code into it from Caffeine. First we’ll inject code to listen to #tweetcoding tweets from Twitter:

| websocket |

websocket := JS WebSocket newWithParameters: {'wss://yourserver:port'}.
JS top at: #websocket put:websocket.

websocket
  at: #onmessage
  put: [:message |
    Transcript
      cr;
      nextPutAll: message data asString;
      endEntry];
  at: #onopen
  put: (
    (JS Function) new: '
      window.top.ws.send(JSON.stringify({
        credential: ''shared secret'',
        verb: ''require'',
        parameters: {
          package: ''node-tweet-stream'',
          then: ''
            var Twitter = require(''node-tweet-stream'')
              , twitter = new Twitter({
                  consumer_key: '''',
                  consumer_secret: '''',
                  token: '''',
                  token_secret: ''''})

            twitter.on(
              ''tweet'',
              function (tweet) {
                if (instructions[''broadcast'']) {
                  instructions[''broadcast''](tweet)}}

            twitter.on(
              ''error'',
              function (err) {
                console.log(''error in uploaded code'')})

            twitter.track(''#tweetcoding #turtlegraphics '')''}})))

The example above uses handwritten JavaScript code, but we could also use Caffeine’s JavaScript code generation to produce it from Smalltalk code (see the method MethodNode>>javaScript for the implementation). Also, since we’ll be injecting several things, it would be nice to have a more compact way of writing it. Let’s move that workspace code to a class.

Next we’ll inject a new instruction, for initializing a set of drawing-command listeners:

| client |

client := (
  NodeJSLivecodingClient
    at: 'wss://yourserver:port'
    withCredential: 'shared secret').

client
  addInstruction: 'initialize listeners'
  from: '
    function () {
      global.listeners = []
      return ''initialized listeners''}'

To round out our tweetcoding protocol, we’ll add instructions for accepting listeners, and broadcasting tweets detected from Twitter:

client
  addInstruction: 'start listening'
  from: '
    function () {
      listeners.push(this)
      return ''added listener''}'
  addInstruction: 'stop listening'
  from: '
    function () {
      listeners.splice(listeners.indexOf(this), 1);
      return ''removed listener''}'
  addInstruction: 'broadcast'
  from: '
    function (payload) {
      listeners.forEach(
        function (listener) {listener.send(payload)})
      return ''broadcasted''}'

Putting It All Together

Now we can write other Smalltalk classes which subscribe to tracked tweets from the server, and collaborate to do something interesting with them in the web browser. I’ve implemented the following classes:

Object
  NodeJSLivecodingClient
    TweetcodingClient
      TurtleGraphicsTweetcodingClient
  Turtle
  Tweet

Instances of NodeJSLivecodingClient can inject code into a node-livecoding server, and invoke code added by other clients. Instances of TweetcodingClient can also set tracking filters for tweets, and process matching tweets when they occur. Instances of TurtleGraphicsTweetcodingClient can also control Turtles, which can draw on canvases in Caffeine windows. Instances of Tweet bundle up the text and metadata of tweets. For the implementation, clear your browser’s cache for caffeine.js.org (including IndexedDB), and reload https://caffeine.js.org/.

I’m also running a node-livecoding server injected with turtle-graphics tweetcoding code, at wss://frankfurt.demo.blackpagedigital.com:8087/. Once you get connected (and tweets are flowing), you might see something like this:

Google ChromeScreenSnapz014

After developing this system, I’ve realized I don’t really need to run SqueakJS from within NodeJS; just injecting code into it is fine. There are many possibilities here. :)

Have fun, and please let me know what you think!

 

Caffeine :: Livecode the Web!

Posted in Appsterdam, consulting, Context, Naiad, Smalltalk, Spoon, SqueakJS with tags , , , , , , , , , , , , , , on 22 June 2017 by Craig Latta

CaffeineFor the impatient… here it is.

Back to the Future, Again

With the arrival of Bert Freudenberg’s SqueakJS, it was finally time for me to revisit the weird and wonderful world of JavaScript and web development. My previous experiences with it, in my consulting work, were marked by awkward development tools, chaotic frameworks, and scattered documentation. Since I ultimately rely on debuggers to make sense of things, my first question when evaluating a development environment is “What is debugging like?”

Since I’m a livecoder, I want my debugger to run in the web browser I’m using to view the site I’m debugging. The best in-browser debugger I’ve found, Chrome DevTools (CDT), is decent if you’re used to a command-line interface, but lacking as a GUI. With Smalltalk, I can open new windows to inspect objects, and keep them around as those objects evolve. CDT has an object explorer integrated into its read-eval-print loop (REPL), and a separate tab for inspecting DOM trees, but using them extensively means a lot of scrolling in the REPL (since asynchronous console messages show up there as well) and switching between tabs. CDT can fit compactly onto the screen with the subject website, but doesn’t make good use of real estate when it has more. This interrupts the flow of debugging and slows down development.

The Pieces Are All Here

With SqueakJS, and its JavaScript bridge, we can make something better. We can make an in-browser development environment that compares favorably with external environments like WebStorm. I started from a page like try.squeak.org. The first thing we need is a way to move the main SqueakJS HTML5 canvas around the page. I found jQuery UI to be good for this, with its “draggable” effect. While we’re at it, we can also put each of Squeak‘s Morphic windows onto a separate draggable canvas. This moves a lot of the computation burden from SqueakJS to the web browser, since SqueakJS no longer has to do window management. This is a big deal, since Morphic window management is the main thing making modern Squeak UIs feel slow in SqueakJS today.

SqueakJS provides a basic proxy class for JavaScript objects, called JSObjectProxy. Caffeine has an additional proxy class called JSObject, which provides additional reflection features, like enumerating the subject JS object’s properties. It’s also a good place for documenting the behavior of the JS objects you’re using. Rather than always hunting down the docs for HTMLCanvasElement.getContext on MDN, you can summarize things in a normal method comment, in your HTMLCanvasElement class in Smalltalk.

Multiple Worlds

With a basic window system based on HTML5 canvases, we can draw whatever we like on those canvases, using the SqueakJS bridge and whatever other JS frameworks we care to load. I’ve started integrating a few frameworks, including React (for single-page-app development), three.js (for WebGL 3D graphics development), and morphic.js (a standalone implementation of Morphic which is faster than what’s currently in Squeak). I’ll write about using them from Caffeine in future blog posts.

Another framework I’ve integrated into Caffeine is Snowglobe (for Smalltalk app streaming and other remote GUI access), which I wrote about here previously. I think the Snowglobe demo is a lot more compelling when run from Caffeine, since it can co-exist with other web apps in the same page. You can also run multiple Snowglobes easily, and drag things between them. I’ll write more about that, too.

Fitting Into the JavaScript Ecosystem

To get the full-featured debugger UI I wanted, I wrote a Chrome extension called Caffeine Helper, currently available on the Chrome Web Store. It exposes the Chrome Debugging Protocol (CDP) support in the web browser to SqueakJS, letting it do whatever the CDT can do (CDT, like SqueakJS, is just another JavaScript-powered web app). The support for CDP that I wrote about previously uses a WebSocket-based CDP API that requires Chrome to be started in a special way. The Caffeine Helper extension provides a JavaScript API, without that requirement.

I also wrote support for generating Smalltalk code from JavaScript, using the esprima parsing framework, and vice-versa. With my debugger and code generation, I’m going to try developing for some file-based JS projects, using Smalltalk behind the scenes and converting to and from JavaScript when necessary. I think JS web development might actually not drive me crazy this way. :)

Please Try It Out!

So, please check out Caffeine, at caffeine.js.org! I would very much appreciate your feedback. I’m particularly interested to hear your use cases, as I plan the next development steps. I would love to have collaborators, too. Let’s build!

Caffeine: live web debugging with SqueakJS

Posted in Appsterdam, consulting, Context, Naiad, Smalltalk, Spoon with tags , , , , , , , , , , , , , , , , , , , , on 26 October 2016 by Craig Latta

In February 2015 I spoke about Bert Freudenberg’s SqueakJS at FOSDEM. We were all intrigued with the potential of this system to change both Smalltalk and web programming. This year I’ve had some time to pursue that potential, and the results so far are pretty exciting.

SqueakJS is a Squeak virtual machine implemented with pure JavaScript. It runs in all the web browsers, and features a bi-directional JavaScript bridge. You can invoke JavaScript functions from Smalltalk code, and pass Smalltalk blocks for JavaScript code to invoke as callbacks. This lets Smalltalk programmers take advantage of the myriad JavaScript frameworks available, as well as the extensive APIs exposed by the browsers themselves.

The most familiar built-in browser behavior is for manipulating the structure of rendered webpages (the Document Object Model, or “DOM”). Equally important is behavior for manipulating the operation of the browser itself. The Chrome Debugging Protocol is a set of JavaScript APIs for controlling every aspect of a web browser, over a WebSocket. The developer tools built into the Chrome browser are implemented using these APIs, and it’s likely that other browsers will follow.

Using the JavaScript bridge and the Chrome Debugging Protocol, I have SqueakJS controlling the web browser running it. SqueakJS can get a list of all the browser’s tabs, and control the execution of each tab, just like the built-in devtools can. Now we can use Squeak’s user interface for debugging and building webpages. We can have persistent inspectors on particular DOM elements, rather than having only the REPL console of the built-in tools. We can build DOM structures as Smalltalk object graphs, complete with scripted behavior.

I am also integrating my previous WebDAV work, so that webpages are manifested as virtual filesystems, and can be manipulated with traditional text editors and other file-oriented tools. I call this a metaphorical filesystem. It extends the livecoding ability of Smalltalk and JavaScript to the proverbial “favorite text editor”.

This all comes together in a project I call Caffeine. had fun demoing it at ESUG 2016 in Prague. Video to come…

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