Thoughts filed in: Computing

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Show a video's duration with Media: YouTube and Computed Field

I build quite a few Drupal sites that use embedded YouTube videos, and my module of choice for handling this is Media: YouTube, which is built upon the popular Media module. The Media: YouTube module generally works great; but on one site that I recently built, I discovered one of its shortcomings. It doesn't let you display a YouTube video's duration.

I thought up a quick, performant and relatively easy way to solve this. With just a few snippets of custom code, and the help of the Computed Field module, showing video duration (in hours / minutes / seconds) for a Media: YouTube managed asset, is a walk in the park.


Rendering a Silex (Symfony2) app via Drupal 7

There's been a lot of talk recently regarding the integration of the Symfony2 components, as a fundamental part of Drupal 8's core system. I won't rabble on repeating the many things that have already been said elsewhere; however, to quote the great Bogeyman himself, let me just say that "I think this is the beginning of a beautiful friendship".

On a project I'm currently working on, I decided to try out something of a related flavour. I built a stand-alone app in Silex (a sort of Symfony2 distribution); but, per the project's requirements, I also managed to heavily integrate the app with an existing Drupal 7 site. The app does almost everything on its own, except that: it passes its output to drupal_render_page() before returning the request; and it checks that a Drupal user is currently logged-in and has a certain Drupal user role, for pages where authorisation is required.

The result is: an app that has its own custom database, its own routes, its own forms, its own business logic, and its own templates; but that gets rendered via the Drupal theming system, and that relies on Drupal data for authentication and authorisation. What's more, the implementation is quite clean (minimal hackery involved) – only a small amount of code is needed for the integration, and then (for the most part) Drupal and Silex leave each other alone to get on with their respective jobs. Now, let me show you how it's done.


Node.js itself is blocking, only its I/O is non-blocking

I've recently been getting my feet wet, playing around with Node.js (yes, I know – what took me so long?). I'm having a lot of fun, learning new technologies by the handful. It's all very exciting.

I just thought I'd stop for a minute, however, to point out one important detail of Node.js that had me confused for a while, and that seems to have confused others, too. More likely than not, the first feature of Node.js that you heard about, was its non-blocking I/O model.

Now, please re-read that last phrase, and re-read it carefully. Non. Blocking. I/O. You will never hear anywhere, from anyone, that Node.js is non-blocking. You will only hear that it has non-blocking I/O. If, like me, you're new to Node.js, and you didn't stop to think about what exactly "I/O" means (in the context of Node.js) before diving in (and perhaps you weren't too clear on "non-blocking", either), then fear not.

What exactly – with reference to Node.js – is blocking, and what is non-blocking? And what exactly – also with reference to Node.js – is I/O, and what is not I/O? Let me clarify, for me as much as for you.


Batch updating Drupal 7 field data

On a number of my recently-built Drupal sites, I've become a fan of using the Computed Field module to provide a "search data" field, as a Views exposed filter. This technique has been documented by other folks here and there (I didn't invent it), so I won't cover its details here. Basically, it's a handy way to create a search form that searches exactly the fields you're interested in, thus providing you with more fine-grained control than the core Drupal search module, and with much less installation / configuration overhead than Apache Solr.

On one such site, which has about 4,000+ nodes that are searchable via this technique, I needed to add another field to the index, and re-generate the Computed Field data for every node. This data normally only gets re-generated when each individual node is saved. In my case, that would not be sufficient - I needed the entire search index refreshed immediately.

The obvious solution, would be to whip up a quick script that loops through all the nodes in question, and that calls node_save() on each pass through the loop. However, this solution has two problems. Firstly, node_save() is really slow (particularly when the node has a lot of other fields, such as was my case). So slow, in fact, that in my case I was fighting a losing battle against PHP "maximum execution time exceeded" errors. Secondly, node_save() is slow unnecessarily, as it re-saves all the data for all a node's fields (plus it invokes a bazingaful of hooks), whereas we only actually need to re-save the data for one field (and we don't need any hooks invoked, thanks).

In the interests of both speed and cutting-out-the-cruft, therefore, I present here an alternative solution: getting rid of the middle man (node_save()), and instead invoking the field_storage_write callback directly. Added bonus: I've implemented it using the Batch API functionality available via Drupal 7's hook_update_N().


Introducing the Drupal Handy Block module

I've been noticing more and more lately, that for every new Drupal site I build, I define a lot of custom blocks. I put the code for these blocks in one or more custom modules, and most of them are really simple. For me, at least, the most common task that these blocks perform, is to display one or more fields of the node (or other entity) page currently being viewed; and in second place, is the task of displaying a list of nodes from a nodequeue (as I'm rather a Nodequeue module addict, I tend to have nodequeues strewn all over my sites).

In short, I've gotten quite bored of copy-pasting the same block definition code over and over, usually with minimal changes. I also feel that such simple block definitions don't warrant defining a new custom module – as they have zero interesting logic / functionality, and as their purpose is purely presentational, I'd prefer to define them at the theme level. Additionally, every Drupal module has both administrative overhead (need to install / enable it on different environments, need to manage its deployment, etc), and performance overhead (every extra PHP include() call involves opening and reading a new file from disk, and every enabled Drupal module is a minimum of one extra PHP file to be included); so, less enabled modules means a faster site.

To make my life easier – and the life of anyone else in the same boat – I've written the Handy Block module. (As the project description says,) if you often have a bunch of custom modules on your site, that do nothing except implement block hooks (along with block callback functions), for blocks that do little more than display some fields for the entity currently being viewed, then Handy Block should… well, it should come in handy! You'll be able to do the same thing in just a few lines of your template.php file; and then, you can delete those custom modules of yours altogether.


Introducing the Drupal Template Field Variables module

Drupal 7's new Field API is a great feature. Unfortunately, theming an entity and its fields can be quite a daunting task. The main reason for this, is that the field variables that get passed to template files are not particularly themer-friendly. Themers are HTML markup and CSS coders; they're not PHP or Drupal coders. When themers start writing their node--page.tpl.php file, all they really want to know is: How do I output each field of this page [node type], exactly where I want, and with minimal fuss?

It is in the interests of improving the Drupal Themer Experience, therefore, that I present the Template Field Variables module. (As the project description says,) this module takes the mystery out of theming fieldable entities. For each field in an entity, it extracts the values that you actually want to output (from the infamous "massive nested arrays" that Drupal provides), and it puts those values in dead-simple variables.


Flattening many-to-many fields for MySQL to CSV export

Relational databases are able to store, with minimal fuss, pretty much any data entities you throw at them. For the more complex cases – particularly cases involving hierarchical data – they offer many-to-many relationships. Querying many-to-many relationships is usually quite easy: you perform a series of SQL joins in your query; and you retrieve a result set containing the combination of your joined tables, in denormalised form (i.e. with the data from some of your tables being duplicated in the result set).

A denormalised query result is quite adequate, if you plan to process the result set further – as is very often the case, e.g. when the result set is subsequently prepared for output to HTML / XML, or when the result set is used to populate data structures (objects / arrays / dictionaries / etc) in programming memory. But what if you want to export the result set directly to a flat format, such as a single CSV file? In this case, denormalised form is not ideal. It would be much better, if we could aggregate all that many-to-many data into a single result set containing no duplicate data, and if we could do that within a single SQL query.

This article presents an example of how to write such a query in MySQL – that is, a query that's able to aggregate complex many-to-many relationships, into a result set that can be exported directly to a single CSV file, with no additional processing necessary.


Enriching user-entered HTML markup with PHP parsing

I recently found myself faced with an interesting little web dev challenge. Here's the scenario. You've got a site that's powered by a PHP CMS (in this case, Drupal). One of the pages on this site contains a number of HTML text blocks, each of which must be user-editable with a rich-text editor (in this case, TinyMCE). However, some of the HTML within these text blocks (in this case, the unordered lists) needs some fairly advanced styling – the kind that's only possible either with CSS3 (using, for example, nth-child pseudo-selectors), with JS / jQuery manipulation, or with the addition of some extra markup (for example, some first, last, and first-in-row classes on the list item elements).

Naturally, IE7+ compatibility is required – so, CSS3 selectors are out. Injecting element attributes via jQuery is a viable option, but it's an ugly approach, and it may not kick in immediately on page load. Since the users will be editing this content via WYSIWYG, we can't expect them to manually add CSS classes to the markup, or to maintain any markup that the developer provides in such a form. That leaves only one option: injecting extra attributes on the server-side.

When it comes to HTML manipulation, there are two general approaches. The first is Parsing HTML The Cthulhu Way (i.e. using Regular Expressions). However, you already have one problem to solve – do you really want two? The second is to use an HTML parser. Sadly, this problem must be solved in PHP – which, unlike some other languages, lacks an obvious tool of choice in the realm of parsers. I chose to use PHP5's built-in DOMDocument library, which (from what I can tell) is one of the most mature and widely-used PHP HTML parsers available today. Here's my code snippet.


Django Facebook user integration with whitelisting

It's recently become quite popular for web sites to abandon the tasks of user authentication and account management, and to instead shoulder off this burden to a third-party service. One of the big services available for this purpose is Facebook. You may have noticed "Sign in with Facebook" buttons appearing ever more frequently around the 'Web.

The common workflow for Facebook user integration is: user is redirected to the Facebook login page (or is shown this page in a popup); user enters credentials; user is asked to authorise the sharing of Facebook account data with the non-Facebook source; a local account is automatically created for the user on the non-Facebook site; user is redirected to, and is automatically logged in to, the non-Facebook site. Also quite common is for the user's Facebook profile picture to be queried, and to be shown as the user's avatar on the non-Facebook site.

This article demonstrates how to achieve this common workflow in Django, with some added sugary sweetness: maintaning a whitelist of Facebook user IDs in your local database, and only authenticating and auto-registering users who exist on this whitelist.


Don't trust Facebook with your data

It's been five years since it opened its doors to the general public; and, despite my avid hopes that it DIAF, the fact is that Facebook is not dead yet. Far from it. The phenomenon continues to take the world by storm, now ranking as the 2nd most visited web site in the world (after Google), and augmenting its loyal ranks with every passing day.

I've always hated Facebook. I originally joined not out of choice, but out of necessity, there being no other way to contact numerous friends of mine who had decided to boycott all alternative methods of online communication. Every day since joining, I've remained a reluctant member at best, and an open FB hater to say the least. The recent decisions of several friends of mine to delete their FB account outright, brings a warm fuzzy smile to my face. I haven't deleted my own FB account — I wish I could; but unfortunately, doing so would make numerous friends of mine uncontactable to me, and numerous social goings-on unknowable to me, today as much as ever.

There are, however, numerous features of FB that I have refused to utilise from day one, and that I highly recommend that all the world boycott. In a nutshell: any feature that involves FB being the primary store of your important personal data, is a feature that you should reject outright. Facebook is an evil company, and don't you forget it. They are not to be trusted with the sensitive and valuable data that — in this digital age of ours — all but defines who you are.

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