Where will all the web developers go?

I’ve been thinking recently about what happens when we all get older. Now, I’m not actually referring to everyone here but more specifically what I’m going to call second generation web developers. I don’t mean Tim and friends here, or the early entrepreneurs of Yahoo! and Netscape. I mean the people who came along when the commercial web design and development industry had settled down a little bit, lets say 10 years ago. People like me.

Work seems to exist in lots of places; big in-house teams, small in-house teams, agencies, startups and freelancers. Where the jobs are at any given point seems to be tied to economic conditions and location. Most people I seem to speak to have tended to work in one of these areas, but I’ve not really got anything but vague memories to back that accusation up. I’m a little odd here in having previously worked mainly for agencies followed by a stint of freelancing, and now work for a decent sized in-house team at Global Radio.

As I see it the industry rules are predominantly made up by people involved as they go along. Their is no real impetus behind any trade body that I’m aware of, no real understanding within education and no consensus on organisational structure and jobs within it. That means, unlike accountants or people in many other professions, we’ve very little idea about what will happen in the long term.

So. What happens in 10-20 years time to the now quite large number of professional web developers.

Do we all just do the same thing we’re doing now. Just with higher version numbers? The problem with this is maintaining the challenge. If the core problems remain the same will it be much fun? I fear their are only so many times you can learn a new programming language and then solve the same problem you worked on at your last job before the world catches on.

Do we all become managers? The problem then is who do we manage? If the industry just gets bigger and bigger this works. But that sounds unreasonable. So if their are a limited number of managerial positions who gets them? The people their first?

Is their another industry that will have us? Computer games are starting to look to the web for ideas about community and collaboration, pretty much at the same time as the web is looking at games for thoughts on experience and engagement. But long term I can’t see a mass exodus or a huge cross over of people, just a huge overlap of ideas.

Do some of the areas like agencies, in-house teams, etc. disappear, or at least employ less skilled people? Experience costs money, and not always because it’s worth the extra expense.

Or is it simply that the world in twnety years time will be so different to now that we don’t really have a clue. And that a large group of computer savvy problem solvers will find something to do?

The real question I guess is what does the demand for skilled professional web developers look like in ten to twenty years? In reality most of the people currently doing the job won’t be getting to retirement age any time soon. That means every newly trained graduate or kid with a computer getting their first job adds to the size of the workforce. And how big do we think that workforce can get before it reaches a nice equilibrium? Certainly in London at the moment their are jobs aplenty. Many good friends have just left Yahoo! rather promptly and I’d be worried for them if I didn’t know how many people will be knocking down their doors.

I’d love it if their were numbers somewhere on this that you could graph. Maybe spot a plateau coming. It’s the sort of thing the Institute of Physics or the Chartered Institute of Marketing do. But as I said, we don’t have anything similar.

So maybe their is another option when the workforce has expanded as much as it’s going to do. We could get all work for The Institute of Web Development.

App Engine Samples

It’s probably old hat to those who have been using Google Appengine for a while but I just found some sample apps on Google Code. I prefer learning from actual code like this, at least until the App Engine books make it out next year.


Stuart at work has been playing with a nice Python web crawler recently. I’ve used Harvestman before but it’s not the most straightforward thing to work with. Spyder has a really nifty callback based approach and a couple of hooks which allows you to write code like:

pre. crawler = Spyder() crawler.register(my_custom_method, ‘post_fetch_html’) crawler.run(URL)

On a side note I wish Launchpad was as clean and tidy as GitHub though. I can see GitHub adding some of the features that Launchpad has eventually, but I hope they fit them in around the existing features.

CSS Test on GitHub

I upload the work I’ve done so far on testing CSS. It’s still work in progress obviously but if you’re interested do let me know. I’ve stared with the image approach but will hopefully have something up demonstrating the selenium/rendered DOM position approach as well.

I Love GitHub Two

I’d been meaning to write a quick article about GitHub, but then Mike and Neil beat me to it and stole most of the best bits. Read both of those articles then come back if you want. I agree whole heartedly.

Now I’ve used public hosted source control before. But Google Code, Sourceforge or Launchpad never felt like this. Their were always their for people to download your code if they wanted. Maybe you collaborated with a few people on a specific project. But GitHub, through a combination of neat visualisations and social features, is encouraging people to just upload all their code. All those lines of throw away scripts. All that code written on the train learning a new language. All that configuration stuff that normally gets missed.

Talk of emerging programming languages often shifts to the need for a killer application. I want to learn more about Git so I can do more with GitHub. For me, that makes GitHub a likely driving force behind a sea of Git adoption in the coming year or so. I’m also interested to see what comes out of a reasonable sized network of like-minded people absentmindedly hacking away. Already I’m seeing people branch other peoples code within my network of contacts. Often just small tweaks and changes - like a code fairy cleaning up a few rough edges or adding an extra line here.

So, if you write code head over to GitHub and signup. Create a few repositories of the things you’re hacking on at the moment and jump through the pre-portable-social-network dance just one more time. I promise it’s worth it this time.


CSSDOC looks like a good idea. I’m sure a few people mentioned this last year at @media after the talk by the people from The Guardian but nothing came from it. Hopefully tools will start to come about soon.

CSSDOC is a convention to comment Cascading Style Sheets (CSS) to help individuals and teams to improve writing/coding/styling/managing CSS files. It is an adoption of the well known JavaDoc / DocBlock based way of commenting source-code. That’s putting style, docblocks and tags together.

Django Performance Tip - Profile Your Filters

I’ve been doing some performance profiling of this here blog. Not because I really need to due to huge amounts of traffic unfortunately, more because I’m planning on releasing the code and wanted to give it a good once over before I do.

pre. 69396 function calls (67324 primitive calls) in 0.479 CPU seconds Ordered by: internal time, call count ncalls tottime percall cumtime percall filename:lineno(function) 123 0.138 0.001 0.154 0.001 build/bdist.macosx-10.5-i386/egg/textile.py:2478(qtags) 6300 0.058 0.000 0.079 0.000 build/bdist.macosx-10.5-i386/egg/textile.py:453(preg_replace) 15705 0.045 0.000 0.059 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/re.py:219(_compile) 20 0.025 0.001 0.026 0.001 /Users/gareth.rushgrove/Documents/www/django/django/db/backends/sqlite3/base.py:165(execute) 1087 0.021 0.000 0.026 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/re.py:136(sub) 123 0.014 0.000 0.017 0.000 build/bdist.macosx-10.5-i386/egg/textile.py:2701(links) 18 0.012 0.001 0.030 0.002 build/bdist.macosx-10.5-i386/egg/textile.py:892(split_text) 12719 0.011 0.000 0.063 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/re.py:178(compile) 123 0.011 0.000 0.104 0.001 build/bdist.macosx-10.5-i386/egg/textile.py:2372(glyphs) 123 0.009 0.000 0.009 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/re.py:159(findall) 191 0.008 0.000 0.008 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/re.py:154(split) 18 0.005 0.000 0.005 0.000 build/bdist.macosx-10.5-i386/egg/textile.py:803(grab_links) 11 0.005 0.000 0.005 0.000 /Users/gareth.rushgrove/Documents/www/django/django/utils/text.py:52(truncate_html_words)

The above profile is from the home page which seemed a good starting point. The majority of the other pages are more straightforward, generally displaying just one article with a few related bits and pieces.

What jumped out was that the majority of the slow traces (the list is ordered with the slowest calls first) were to do with the use of the textile filter packaged with Django. Textile is a simple markup language which converts to HTML, I’ve used it for all my writing activities since I used Textpattern on this blog many moons ago. It’s not just the traces that explicitly mentioned textile either - the regular expression calls are also to do with template filters.

I quickly added a hidden html field to my model and a custom save method. On saving an article I now automatically transform the textile version of the content and save it in the html field. In the template where I used to have article.content|textile I now have article.html. A quick check of the profile on the same page showed a dramatic increase in performance:

pre. 15054 function calls (13248 primitive calls) in 0.081 CPU seconds Ordered by: internal time, call count ncalls tottime percall cumtime percall filename:lineno(function) 20 0.017 0.001 0.018 0.001 /Users/gareth.rushgrove/Documents/www/django/django/db/backends/sqlite3/base.py:165(execute) 97854 0.003 0.000 0.006 0.000 /System/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/copy.py:144(deepcopy) 821 0.003 0.000 0.069 0.069

From nearly half a second (0.479 CPU seconds) to 0.081 CPU seconds - roughly a 500% improvement in performance!

If you are using text transforming filters in Django that make use of regular expressions I would look to try and get rid of them and move the conversion into a save method. You might not see quite as much of a performance gain as I did here but I’d be surprised if it’s not taking an awful lot longer than you might thing.

Their are a few tools that are handy to have around if you’re wanting to profile your own applications. Django Snippets has a handy profiling middleware and the really rather nice Command Extensions provides a few more tools including profile graph generation.

Simulating Rails like Environments in Django

I was always a fan of Rail environments and as part of some work upgrading this site to the latest version of Django I decided to clean up my whole deployment process. Part of that involved replacing everything in settings.py with the following snippet of code:

pre. ENV = “development” try: exec “from environments.” + ENV + “ import *“ except ImportError: print “You must specify a valid environment” exit()

I now have two settings files stored in an environments module containing all the usual django settings; one for my development environment and one suitable for live. The settings.py above is for my local development environment, with only one small change for live (this file doesn’t get deployed along with the source code for the site, so doesn’t get overwritten).

pre. ENV = ‘live’

This isn’t quite the same as the Rails implementation obviously. I run completely different server setups so I’m not too bothered about a flag on the runserver command like the -e flag for mongel. I could also probably do something to autodetect the environment but this works fine for me.

Unit Testing CSS - Looking for a Solution

I think it’s an epic failure of web standards that CSS is the only essentially untestable technology invented in last decade - Tomasz

Talking today on Twitter with Tomasz got me thinking again about one of those problems that I come back to once in a while. Unit testing CSS. CSS development is a pain, even with some sort of system. Admit it. I actually like CSS most of the time but it’s still painful at times. Hopefully with that out of the way you feel better.

unit testing is a method of testing that verifies the individual units of source code are working properly. A unit is the smallest testable part of an application.

All testing past simple validation of CSS seems to be done visually at present. Thinking about this from the point of view of CSS seems straight forward, but turns out not to be so for a variety of reasons. The problem lies in the cascading and compounding nature of the beast. Each individual CSS rule might do something which is self contained, but the chances on a real site are probably slim. For instance:

pre. body { font-size: 100%; } p { font-size: 2em; }

What is the size of the font size of a paragraph? It turns out it depends. Not just on more than one unit of source code (we have two rules here) but also on things like the browser. And how do we get this font size from a browser in the first place? I generally dislike Selenium but does it provide a mechanism for getting at the calculated DOM attribute values? Do we have to interface directly with a browser at a lower level?

wxMozilla, wxWebKit or maybe pywebkitgtz might prove useful, but I’m not sure at what level they operate. What I’m imagining here is maybe something like (excuse the Python, hopefully you get the idea):

pre. def test_text_size_is_12px(self): response = fetch_with_browser(‘http://www.google.com') self.assertEquals(12, response.search(“p”).fontSize

So we could use CSS selectors (ie. p) to find elements and then assert various DOM properties (ie. fontSize) are equal to values we specify. The magic is in getting access to those calculated DOM attribute values from an actual browser engine.

Another approach would seem to be looking at visual rendering and comparing against a known good version. This seems to be something that the Mozilla folks got up to a while back to test different browser versions. Their are a few tools that might help us out here too; BrowserCam provides a paid for service, Webkit2png is a handy command line script I’ve had fun with in the past and IECapt appears to be a similar beast for Internet Explorer. CutyCapt is another cross platform webkit based utility. I can see a few gotchas lurking here. Animations or slow loading javascript would obviously throw this into disarray. But disabling these in the browser might get up somewhere. How to compare images produced I’m not yet sure, but I reasons someone reading this might have a good idea?

As the title would suggest this post does not contain the answer, only a few useful links and two possible approaches to the problem. The questions at this stage are:

  • Does any of this exist already? If so who do we need to cuddle up to to get access to it?
  • Are any of the technical hurdles to either of the approaches mentioned above insurmountable? If not what is the best solution?
  • Does anyone except me and Tomasz even want this?

I reason their are a fair few things that would be needed to make this first practical and later standard; nice APIs, run times in various languages, and working out whether or not it actually helps CSS development to name but a few. But right now I’d go for a limited proof of concept that works on my machine. If anyone has any links to thinks that might be good starting points please let me know. Other ideas welcome as well.

One last thing; Mozilla’s latest employees are looking at the whole spectrum of developer tools. I’d love for them to start with something like this.

Google App Engine PyUnit Test Runner

I’m starting to play around with using App Engine again for small projects. It’s great for simple, somewhat throwaway apps as long as you don’t need anything too fancy. Actually all I want really is long running processes but I digress.

I’m increasingly writing test suites as well for even small projects and was missing the convenience of the Django test runner for running them against App Engine code. So I’ve spent a little time writing a simple test running script to use for non-Django Python projects. I’ve posted it over on the App Engine Cookbook for anyone else who might want to do the same.

I ended up writing something myself as I couldn’t find anything else which quite met my needs, so it’s the typical programmers itch code and as such is provided as works for me software. The other approaches out their didn’t quite meet my needs but might be useful to know about if you want to start testing your apps.

  • Nose GAE uses the nose testing framework which I’m less familiar with.
  • GAE Unit uses PyUnit but presents it’s results in a browser rather than on the command line.