Peterbe.com

A blog and website by Peter Bengtsson

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MozTrap is what's called a "test case management system". Basically, software QA people need a structure and pattern to their testing. What to test, what versions to test on and what hardware/operatting system etc all is part of a "test suite". That's what MozTrap manages.

So this project was built by Mozilla's automation and tools team. It is currently not an actively developed project. Not because it's not needed or used but because it basically maps all the features we need. A large part of the code base was originally written by a personal friend of mine who I respect wholeheartedly; Carl Meyer of Django/pip/virtualenv/etc fame. I'm grateful for the awesome documentation he left behind amongst many other things.

Together with the team we sat down and listed all the biggest pain points as of today. Basically, the number one thing is speed. Pages load too slowly. Normally when web developers worry themselves with web performance it's a matter of shaving milliseconds off a page where a clients perception equals lost or gained profits. Here's not a problem of milliseconds but a problem of seconds. After some quick poking around on the production site and looking at some code the conclusion is simple: The site is so darn slow because the HTML sent from the server is way too MASSIVE. And baked into that is a mixture of the poor web server having to produce a massive HTML blob and it being sent over the wire.

One test run I made said it took 14 seconds to render a certain page.

Why is it so slow?

So how did this happen and why is it not Carl's fault? :) The reason it happened was because of the underestimated number of options added to the advanced filtering drop-downs. On a local dev version you never notice these things because you set up some options, for example tags, and the drop-down never gets larger than 10-20 options. For example, the "Creator" drop-down today has 1,664 different choices.

If you take all those choices and turn thing into a HTML like this: <option value="1">Adam</option>\n<option value="2">Bram</option>... etc. you get 66Kb of just HTML. However, MozTrap doesn't work like that. Instead it uses pretty drop-downs that don't look like regular HTML drop-downs. See for yourself; go to https://moztrap.mozilla.org/results/runs/ and click the "Advanced Filtering" button.
So, that means that the HTML for each option instead looks like this:

<li class="filter-item">
  <input name="filter-creator" data-name="creator" value="1" id="id-filter-creator-1" class="check" type="checkbox">
  <span class="onoff">
    <label for="id-filter-creator-1" class="onoffswitch">Adam</label>
                <span class="pinswitch"></span>
    <span class="content" title="creator: Adam">Adam</span>
  </span>
</li>

Now you get 620Kb of just HTML just for the "Creators" field. Granted, that is the biggest field of all the drop-downs but lots of them are massive.

So, this makes the page weigh a total of about 1.1Mb just for the HTML. Not only is it a lot of work for the (Django) server to generate this but it's also a heck of a lot of data to send across the Internet on every page request.

So what was the solution?

An ideal solution would have been a significant re-write whereby much of the values of the page gets rewritten as later AJAX calls. I.e. load a skeleton that loads superfast, and then load some AJAX in the background. That AJAX could potentially be cached in the browser with localStorage or something so that you get something to show very quickly whilst you wait for the AJAX request to complete. But this would have been too big a change and the way the filtering works on these pages, you actually need all the options in the drop-downs on immediate load because of the way "pinned filters" work.

So the solution was to replace all the repeated HTML chunks with 1 JSON string and then a piece of Javascript template rendering. So, in the Django template code instead of:

{% for field in filters %}
  {% include "lists/_filter_group.html" with advanced=1 prefix="filter" pinable=1 %}
{% endfor %}

We now replace this with:

<script>
var FILTERS = {% filterset_to_json filters with advanced=1 prefix="filter" pinable=1 %}
</script>
<script id="filter_group" type="text/html">
<section class="filter-group {{ field.cls }}" data-name="{{ field.key }}">
  <h5 class="category-title">
    {{ _field_name_lower }}
    {{# field.switchable }}
    ...

What that basically is is some Mustache code that I use to generate the HTML DOM nodes and insert into the page after load.

In conclusion

So basically nothing changes. Nothing of the Django view had to change. Visually there's no difference and the same actual user data is sent from the server to the client but just packed in a more optimal way.

There are multiple pages where these massive "Advanced Filtering" options exist but on one page I measured the whole page went from weighing 1.1Mb down to 132Kb.

On Friday I did a Show HN and got featured on the front page for HTML Tree.

Google Analytics
Amazingly, out of the 3,858 visitors (according to Google Analytics today) 2,034 URLs were submitted and tested on the app. Clearly a lot of people just clicked the example submission but out of those 1,634 were unique. Granted, some people submitted more than one URL but I think a large majority of people came up with a URL of their own to try. Isn't that amazing! What a turnout of a Friday afternoon hack (with some Sunday night hacking to make it into a decent looking website).

The lesson to learn here is that the Hacker News crowd is excellent for getting engagement. Yes, there are a lot of blather and almost repetitive submissions but by and large it's a very engaging community. Suck on that those who make fun of HN!

I have now closed issue #2 on github-pr-triage. So, now you can have a dashboad of every GitHub project whose pull requests you care about.

The only format of using just 1 repo works too. E.g. /owner/project) and should hopefully not break anybody's bookmarks. The new format for having multiple repos across (possibly) multiple owners is like this:

owner1:projectA,projectB;owner2:projectX,projectY,projectZ

See screenshot:

A couple of different projects

To set yours up, here's a running instance available on https://prs.paas.allizom.org

grymt is a python tool that takes a directory full of .html, .css and .js and prepares the html for optimial production use.

For a teaser:

  1. Look at the "input"

  2. Look at the "output" (Note! You have to right-click and view source)

So why did I write my own tool and not use Grunt?!

Glad you asked! The reason is simple: I couldn't get Grunt to work.

Grunt is a framework. It's a place where you say which "recipes" to execute and how. It's effectively a common config framework. Like make.
However, I tried to set up a bunch of recipes in my Gruntfile.js and most of them worked well individually but it was a hellish nightmare to get it all to work together just the way I want it.

For example, the grunt-contrib-uglify is fine for doing the minification but it doesn't work with concatenation and it doesn't deal with taking one input file and outputting to a different file.
Basically, I spent two evenings getting things to work but I could never get exactly what I wanted. So I wrote my own and because I'm quite familiar with this kind of stuff, I did it in Python. Not because it's better than Node but just because I had it near by and was able to quicker build something.

So what sweet features do you get out of grymt?

  1. You can easily make an output file have a hash in the filename. E.g. vendor-$hash.min.js becomes vendor-64f7425.min.js and thus the filename is always unique but doesn't change in between deployments unless you change the files.

  2. It automatically notices which files already have been minified. E.g. no need to minify somelib.min.js but do minify otherlib.js.

  3. You can put $git_revision anywhere in your HTML and this gets expanded automatically. For example, view the source of buggy.peterbe.com and look at the first 20 lines.

  4. Images inside CSS get rewritten to have unique names (based on files' modified time) so they can be far-future cached aggresively too.

  5. You never have to write down any lists of file names in soome Gruntfile.js equivalent file

  6. It copies ALL files from a source directory. This is important in case you have something like this inside your javascript code: $('<img>').attr('src', 'picture.jpg') for example.

  7. You can chose to inline all the minified and concatenated CSS or javascript. Inlining CSS is neat for single page apps where you have a majority of primed cache hits. Instead of one .html and one .css you get just one .html and the amount of bytes is the same. Not having to do another HTTP request can save a lot of time on web performance.

  8. The generated (aka. "dist" directory) contains everything you need. It does not refer back to the source directory in any way. This means you can set up your apache/nginx to point directly at the root of your "dist" directory.

So what's the catch?

  1. It's not Grunt. It's not a framework. It does only what it does and if you want it to do more you have to work on grymt itself.

  2. The files you want to analyze, process and output all have to be in a sub directory.
    Look at how I've laid out the files here in this project for example. ALL files that you need is all in one sub-directory called app. So, to run grymt I simply run: grymt app.

  3. The HTML files you throw into it have to be plain HTML files. No templates for server-side code.

How do you use it?

pip install grymt

Then you need a directory it can process, e.g ./client/ (assumed to contain a .html file(s)).

grymt ./client

For more options, check out

grymt --help

What's in the future of grymt?

If people like it and want to add features, I'm more than happy to accept pull requests. Some future potential feature work:

  • I haven't needed it immediately, yet, myself, but it would be nice to add things like coffeescript, less, sass etc into pre-processing hooks.

  • It would be easy to automatically generate and insert a reference to a appcache manifest. Since every file used and mentioned is noticed, we could very accurately generate an appcache file that is less prone to human error.

  • Spitting out some stats about number bytes saved and number of files reduced.

Screenshot
Buggy is a singe-page webapp that relies entirely on the Bugzilla Native REST API. And it works offline. Sort of. I say "sort of" because obviously without a network connection you're bound to have outdated information from the bugzilla database but at least you'll have what you had when you went offline.

When you post a comment from Buggy, the posted comment is added to an internal sync queue and if you're online it immediately processes that queue. There is, of course, always a risk that you might close a bug when you're in a tunnel or on a plane without WiFi and when you later get back online the sync fails because of some conflict.

The reason I built this was partly to scratch an itch I had ("What's the ideal way possible for me to use Bugzilla?") and also to experiment with some new techniques, namely AngularJS and localforage.

Live-search

So, the way it works is:

  1. You pick your favorite product and components.

  2. All bugs under these products and components are downloaded and stored locally in your browser (thank you localforage).

  3. When you click any bug it then proceeds to download its change history and its comments.

  4. Periodically it checks each of your chosen product and components to see if new bugs or new comments have been added.

  5. If you refresh your browser, all bugs are loaded from a local copy stored in your browser and in the background it downloads any new bugs or comments or changes.

  6. If you enter your username and password, an auth token is stored in your browser and you can thus access secure bugs.

I can has charts

Pros and cons

The main advantage of Buggy compared to Bugzilla is that it's fast to navigate. You can instantly filter bugs by status(es), components and/or by searching in the bug summary.

The disadvantage of Buggy is that you can't see all fields, file new bugs or change all fields.

The code

The code is of course open source. It's available on https://github.com/peterbe/buggy and released under a MPL 2 license.

The code requires no server. It's just an HTML page with some CSS and Javascript.

Everything is done using AngularJS. It's only my second AngularJS project but this is also part of why I built this. To learn AngularJS better.

Much of the inspiration came from the CSS framework Pure and one of their sample layouts which I started with and hacked into shape.

The deployment

YSlow
Because Buggy doesn't require a server, this is the very first time I've been able to deploy something entirely on CDN. Not just the images, CSS and Javascript but the main HTML page as well. Before I explain how I did that, let me explain about the make.py script.

I really wanted to use Grunt but it just didn't work for me. There are many positive things about Grunt such as the ease with which you can easily add plugins and I like how you just have one "standard" file that defines how a bunch of meta tasks should be done. However, I just couldn't get the concatenation and minification and stuff to work together. Individually each tool works fine, such as the grunt-contrib-uglify plugin but together none of them appeared to want to work. Perhaps I just required too much.

In the end I wrote a script in python that does exactly what I want for deployment. Its features are:

  • Hashes in the minified and concatenated CSS and Javascript files (e.g. vendor-8254f6b.min.js)
  • Custom names for the minified and concatenated CSS and Javascript files so I can easily set far-future cache headers (e.g. /_cache/vendor-8254f6b.min.js)
  • Ability to fold all CSS minified into the HTML (since there's only one page, theres little reason to make the CSS external)
  • A Git revision SHA into the HTML of the generated ./dist/index.html file
  • All files in ./client/static/ copied intelligently into ./dist/static/
  • Images in CSS to be given hashes so they too can have far-future cache headers

So, the way I have it set up is that, on my server, I have a it run python make.py and that generates a complete site in a ./dist/ directory. I then point Nginx to that directory and run it under http://buggy-origin.peterbe.com. Then I set up a Amazon Cloudfront distribution to that domain and then lastly I set up a CNAME for buggy.peterbe.com to point to the Cloudfront distribution.

The future

I try my best to maintain a TODO file inside the repo. That's where I write down things to come. (it's also works as a changelog) since I also use this file to write down what's been done.

One of the main features I want to add is the ability to add bugs that are outside your chosen products and components. It'll be a "fake" component called "Misc". This is for bugs outside the products and components you usually monitor and work in but perhaps bugs you've filed or been assigned to. Or just other bugs you're interested in in general.

Another major feature to work on is the ability to choose to see more fields and ability to edit these too. This will require some configuration on the individual users' behalf. For example, some people use the "Target Milestone" a lot. Some use the "Importance" a lot. So, some generic solution is needed to accomodate all these non-basic fields.

And last but not least, the Bugzilla team here at Mozilla is working on a very exciting project that allows you to register a certain list of bugs with a WebSocket and have it push to you as soon as these bugs change. That means that I won't have to periodically query bugzilla every 30 seconds if certain bugs have changed but instead get instant notifications when they do. That's going to be major! I confidently speculate that that will be implemented some time summer this year.

Give it a go. What are you waiting for? :) Go to http://buggy.peterbe.com/, pick your favorite products and components and try to use it for a week.

Screenshot
Last week I built a little tools called github-pr-triage. It's a single page app that sits on top of the wonderful GitHub API v3.

Its goal is to try to get an overview of what needs to happen next to open pull requests. Or rather, what needs to happen next to get it closed. Or rather, who needs to act next to get it closed.

It's very common, at least in my team, that someone puts up a pull request, asks someone to review it and then walks away from it. She then doesn't notice that perhaps the integrated test runner fails on it and the reviewer is thinking to herself "I'll review the code once the tests don't fail" and all of a sudden the ball is not in anybody's court. Or someone makes a comment on a pull request that the author of the pull requests misses in her firehose of email notifictions. Now she doesn't know that the comment means that the ball is back in her court.

Ultimately, the responsibility lies with the author of the pull request to pester and nag till it gets landed or closed but oftentimes the ball is in someone elses court and hopefully this tool makes that clearer.

Here's an example instance: https://prs.paas.allizom.org/mozilla/socorro

Currently you can use prs.paas.allizom.org for any public Github repo but if too many projects eat up all the API rate limits we have I might need to narrow it down to use mozilla repos. Or, you can simply host your own. It's just a simple Flask server

About the technology

I'm getting more and more productive with Angular but I still consider myself a beginner. Saying that also buys me insurance when you laugh at my code.

So it's a single page app that uses HTML5 pushState and an angular $routeProvider to make different URLs.

The server simply acts as a proxy for making queries to api.github.com and bugzilla.mozilla.org/rest and the reason for that is for caching.

Every API request you make through this proxy gets cached for 10 minutes. But here's the clever part. Every time it fetches actual remote data it stores it in two caches. One for 10 minutes and one for 24 hours. And when it stores it for 24 hours it also stores its last ETag so that I can make conditional requests. The advantage of that is you quickly know if the data hasn't changed and more importantly it doesn't count against you in the rate limiter.

tl;dr 36

For some time now, I've been running an experiment where I analyze how many different domains any website depends on. For example, you might have Google Analytics on your site (that's www.google-analytics.com) and you might have a Facebook Like button (that's platform.twitter.com and/or s-static.ak.facebook.com) and you might serve your images from a CDN (that's d1ac1bzf3lrf3c.cloudfront.net). That there is 3-4 distinct domains.

Independent of how many requests come from each domain, I wanted to measure how many distinct domains a website depends on so I wrote a script and started collecting random URLs across the web. Most of the time, to get a sample of different URLs I would take the RSS feed on Digg.com and the RSS feed on Hacker News on a periodic basis.

Network tab on the Dev Tools console for a page on the-toast.net
The results are amazing! Some websites depend on over 100 different domain names!

Take this page on The Toast for example, it depends on 143 different domains. Loading it causes your browser to make 391 requests, download 4.8Mb and takes 29 seconds (in total, not necessarily till you can start reading it). What were they thinking!?!

I think what this means is that website makers will probably continue to make websites like this. What we, as web software engineers, can not tell people it's a bad idea but instead to try to do something about it. It's quite far from my expertise but clearly if you want to make the Internet faster, DNS would be an area to focus on.

Test it out for yourself here: Number of Domains

I have and have had many sites that I run. They're all some form of side-project.

What they almost all have in common is two things

  1. They have very little traffic (thus not particularly mission critical)
  2. I run everything on one server (no need for "spinning up" new VMs here and there)

Many many years ago, when current interns I work with were mere babies, I started a very simple "procedure".

  1. On the server, in the user directory where the site is deployed, I write a script called something like upgrade_myproject.sh which is executable and does what the name of the script is: it upgrades the site.

  2. In the server's root home directory I write a script called restart_myproject.sh which also does exactly what the name of the script is: it restarts the service.

  3. On my laptop, in my ~/bin directory I create a script called UpgradeMyproject.sh (*) which runs upgrade_myproject.sh on the server and runs restart_myproject.sh also on the server.

And here is, if I may say so, the cleverness of this; I use ssh to execute these scripts remotely by simply piping the commands to ssh. For example:

#!/bin/bash
echo "./upgrade_generousfriends.sh" | ssh -A django@ec2-54-235-210-62.compute-1.amazonaws.com
echo "./restart_generousfriends.sh" | ssh root@ec2-54-235-210-62.compute-1.amazonaws.com

That's an example I use for Wish List Granted.

This works so darn well, and has done for years, that this is why I've never really learned to use more advanced tools like Fabric, Salt, Puppet, Chef or <insert latest deployment tool name>.

This means that all I need to do run a deployment is just type UpgradeMyproject.sh[ENTER] and the simple little bash scripts takes care of everything else.

The reason I keep these on the server and not on my laptop is simply because that's where they naturally belong and if I'm ssh'ed in and mess around I don't have to exit out to re-run them.

Here's an example of the upgrade_generousfriends.sh I use for Wish List Granted:

#!/bin/bash
cd generousfriends
source venv/bin/activate
git pull origin master
find . | grep '\.pyc$' | xargs rm -f
pip install -r requirements/prod.txt
./manage.py syncdb --noinput
./manage.py migrate webapp.main
./manage.py collectstatic --noinput
./manage.py compress --force
echo "Restart must be done by root"

I hope that, by blogging about this, that someone else sees that it doesn't really have to be that complicated. It's not rocket science and most complex tools are only really needed when you have a significant bigger scale in terms of people- and skill-complexity.

In conclusion

Keep it simple.

(*) The reason for the capitalization of my scripts is also an old habit. I use that habit to differentiate my scripts for stuff I install from any third parties.

On Wednesday this week, I managed to get a link to Wish List Granted onto Hacker News. It had enough upvotes to be featured on the front page for a couple of hours. I'm very grateful for the added traffic but not quite so impressed with the ultimate conversions.

  • 4,428 unique visitors
  • 43 Wish Lists created
  • 2 Usersnap pieces of constructive feedback
  • 0 payments made

Google Analytics
So that's 1% conversion of people setting up a wish list. But kinda disappointing that no body ever made a payment. Actually, one friend did make a payment. But he's a colleague and a friend so not a stranger who stumbled onto it from Hacker News.

Also, it's now been 3 days since those 43 wish lists were created and still no payments. That's kinda disappointing too.

I'm starting to fear that Wish List Granted is one of those ideas that people think it's a great idea but have no interest in using.

Logo
I built something. It's called Wish List Granted.

It's a mash-up using Amazon.com's Wish List functionality. What you do is you hook up your Amazon wish list onto wishlistgranted.com and pick one item. Then you share that page with friends and familiy and they can then contribute a small amount each. When the full amount is reached, Wish List Granted will purchase the item and send it to you.

The Rules page has more details if you're interested.

The problem it tries to solve is that you have friends would want something and even if it's a good friend you might be hesitant to spend $50 on a gift to them. I'm sure you can afford it but if you have many friends it gets unpractical. However, spending $5 is another matter. Hopefully Wish List Granted solves that problem.

Wish List Granted started as one of those insomnia late-night project. I first wrote a scraper using pyQuery then a couple of Django models and views and then tied it up by integrating Balanced Payments. It was actually working on the first night. Flawed but working start to finish.

When it all started, I used Persona to require people to authenticate to set up a Wish List. After some thought I decided to ditch that and use "email authentication" meaning they have to enter an email address and click a secure link I send to them.

One thing I'm very proud of about Wish List Granted is that it does NOT store any passwords, any credit cards or any personal shipping addresses. Despite being so totally void of personal data I thought it'd look nicer if the whole site is on HTTPS.

More information on the Help & Frequently Asked Questions page.