One of the frequently expressed frustrations with JavaScript, especially from users coming from more static languages, is the lack of typing capabilities in JavaScript. Typing provides the ability to define and enforce contracts between interfaces such that interactions can be validated before violated assumptions result in later difficult-to-find bugs. On the other hand, many users that have grown fond of JavaScript have come to enjoy the fast and free style, and the minimalism of simply defining behavior without needing to make extra type definitions. However, these two coding preferences do not need to be mutually exclusive.

The abandoned ES4 effort made a valiant attempt to add typing (without losing dynamism) via gradual typing; however this still demanded the inclusion of intrusive typing annotations—thus adding type constraints to code polluted the otherwise simple direct JavaScript programming style necessitating more complex, difficult-to-follow code. Other efforts include libraries to define types on functions without extending syntax.

It is now possible to unobtrusively define type constraints on properties and methods in JavaScript with portable JSON schema based definitions called JSON schema interfaces (JSI). JSI is a typing system for JavaScript that does not force any new syntax on JavaScript. Schema structures can be used to define the type constraints in a way that works with existing JavaScript classes and objects.

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REST Channels provides a mechanism for receiving notifications of data changes and integrates Comet-style asynchronous server sent messages with a RESTful data-oriented architecture. Dojo includes a REST Channels client module which integrates completely with Dojo’s JsonRestStore, allowing messages to be delivered through the Dojo Data API seamlessly to consuming widgets, with minimal effort. The REST Channels module will automatically connect to a REST Channels server, like Persevere (which offers REST Channels out of the box). However, existing infrastructure may necessitate the use of an alternate Comet server like Jetty’s cometD server. REST Channels can be used on top of another Comet protocol like Bayeux’s long-polling protocol and with a little bit of reconfiguration, you can use Dojo’s REST Channels with a cometD server to achieve Comet-REST integration.

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During the interaction design phase, we determined that Netflix’s current drag and drop reordering feature was well thought out — so we set out to create the same reordering behavior in Queued. As Revin mentioned before, we also wanted to keep Queued as light as possible; because of this, we decided early on to not use any of the Dijit infrastructure to create the queue listings. Not only that, but the Dojo Grid would not work for the queues because it doesn’t support drag and drop reordering of rows. This meant we would have to come up with something which would be flexible (yet fast) to render the queue.

In the user interface design phase, we decided that each of the lists in the “Your Queue” section would be based on HTML tables. In Queued, only the DVD queue and the Instant list can be reordered, so we’ll focus on the DVD queue.

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In Part I of Queued and AIR issues, I talked about some of the challenges we faced during the development of Queued, our AIR application that allows you to manage your Netflix queues. In this post, I’ll discuss five other issues we ran across.

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As part of our series on how we built Queued, today we’re going to talk about theming the Queued application, and touch on a few examples of what made putting the skin on Queued so much fun.

The foundation for the beautiful theme for Queued was laid down by colleagues Damon Dimmick and Torrey Rice, and their amazing wireframe and mockup work (respectively) provided the building blocks for laying down Queued’s skin.

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SitePen is excited to announce Stocker, which demonstrates some of the more advanced capabilities of Dojo, including the newly released DataChart, the DataGrid, Data Store, Comet, Persevere, and BorderContainer. SitePen is also offering a one-day workshop where you will learn how to create Stocker yourself, but I’m here to give you a sneak peak of what Stocker is and how it works.

Stocker uses these technologies to emulate a stock monitoring application. We’re using made up data, but that’s actually more interesting. The Persevere server generates new stock items at certain intervals, and then pushes them to the browser with Comet. Then the Data Store updates its items and triggers an onSet notification. The DataGrid and DataChart are both connected to the same store, and are listening to that event. They then update their displays and show the stock items and their latest data.

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During the course of developing Queued, we ran across a number of challenges developing with AIR that we needed to solve. Some were very difficult to get around, while others were the result of our team needing to think outside the web-based paradigm. In this post, I’ll talk about four issues we ran across that ended up shaping part of the Queued codebase.

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At SitePen, we work very hard to to provide our customers and fellow developers with useful web app development services. We’re currently deconstructing the development of Queued, our Netflix Queue management application built with Dojo and Adobe AIR. Having presented on dojo.deferred and related topics at the Ajax Experience, and having heard that the Queued team ran into a few problems with them, I thought it would be interesting to review problems that are sometimes encountered when using Deferreds. What is the source of these problems, are these problems related to bugs or because there are misunderstandings, and how should we address this going forward?

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Dojo is a very flexible toolkit; it doesn’t dictate how you organize your code or create your widgets. It simply provides tools, and it’s up to you to decide how you want to fit them together. Developing with AIR puts you squarely in the browser-based application model, but aside from that it mostly stays out of your way as well. As part of our series on the Queued development process, I’m going to take a look at the decisions we made and the philosophies we adopted for the project. It should provide some insight into our process.

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The latest addition in the Dojo 1.3 release is the new dojox.charting class, DataChart. Its primary purpose is to make connecting a chart to a Data Store a simple process. There are also other benefits with DataChart: less parameters are needed to create a basic chart, and more defaults and convenience methods get you up and running quickly with Dojox Charting.

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