How to create a Pivot visualization of a WordPress blog

I’ve posted the Python script I used to make the Pivot visualization of this blog. I need to set it aside for now and do other things, but here’s a snapshot of the process for my future self and for anyone else who’s interested.

Using to create Deep Zoom images and collections

I’m using this Python component to create Deep Zoom images and collections. I made the following changes to it:

1. tile_size=256 (not 254) at line 59, line 160, and line 224

2. instead of source_path at line 291

3. destination + '.xml' instead of destination at line 341

Let’s assume that Python is installed, along with the Python Imaging Library, and that your current directory contains the files 001.jpg, 002.jpg, and 003.jpg:


For each image file, you could run thrice from the command line, like so:

python -d 001.xml 001.jpg
python -d 002.xml 002.jpg
python -d 003.xml 003.jpg

My script doesn’t actually do it that way, it enumerates JPEGs and instantiates’s ImageCreator object once for each. But either way, for each JPEG you end up with a DZI (Deep Zoom Image) package that consists of (for 001.jpg):

  • A settings file: 001.xml
  • A subdirectory: 001_files
  • More subdirectories (named 0, 1, etc.) inside 001_files
  • JPG files inside those subdirectories

Now, in this case, the current directory looks like this (using -> to mark additions):

-> 001.xml
-> 001_files
-> 002.xml
-> 002_files
-> 003.xml
-> 003_files

To build a collection, do something like this in Python:

from deepzoom import *
images = ['001.xml','002.xml', '003.xml']
creator = CollectionCreator()
creator.create(images, 'dzc_output')

Now the current directory looks like:

-> dzc_output.xml
-> dzc_output_files

The Pivot collection’s CXML file will refer to dzc_output.xml, like so:

<Items ImgBase="dzc_output.xml">

Using IECapt to grab screenshots

This tool uses Internet Explorer, so only works on Windows. There is also CutyCapt for WebKit, which I haven’t tried but would be curious to hear about.

Here’s an example of the IECapt command line I’m using:

iecapt –url=… –delay=1000 –out=tmp.jpg

The result in most cases is a tall skinny JPEG, because it renders the whole page — which can be very long — before imaging it. When I ran it over a 600-item collection, it hung a couple of times because of JavaScript errors. So I went to Internet Options->Browsing in IE, checked Disable script debugging, and unchecked Display a notification about every script error.

Using ImageMagic to crop screenshots

Here’s a picture of an image produced by IECapt, overlaid with a rectangle marking where I want to crop:

The rectangle’s origin is at x=30 and y=180. Its width is 530 pixels, and height 500. Here’s the ImageMagick command to crop a captured image in tmp.jpg into a cropped image in 001.jpg:

convert -quality 100 -crop 530×500+30+180 -border 1×1 -bordercolor Black tmp.jpg 001.jpg

I’m writing this down here mainly for myself. ImageMagic can do everything under the sun, but it always takes me a while to dig up the recipe for a given operation.

Parsing the WordPress export file

I found to my surprise that WordPress currently exports invalid XML. So the script starts with a search-and-replace that looks for this:


And replaces it with this:


Then it walks through the items in the Atom feed, extracting the various things that will become Pivot facets. For the description, it tries to parse the content:encoded element as XML, and find the first paragraph element within it. If that fails, it just treats the element as text and grabs the beginning of it.

Weaving the collection

There are two control files that need to be synchronized. First, there’s dzc_output.xml, for the Deep Zoom collection. It has elements like this:

<I Id=”596″ N=”596″ Source=”2245.xml”>

Then there’s pivot.cxml which drives the visualization. It has elements like this:

<Item Id="596" Img="#596" 
  Name="Freebase Gridworks: A power tool for data scrubbers" 
I've had many conversations with Stefano Mazzocchi and David Huynh [1, 2, 3] 
about the data magic they performed at MIT's Project Simile and now perform 
at Metaweb. If you're somebody who values clean data and has wrestled with 
the dirty stuff, these screencasts about a forthcoming product called 
Freebase Gridworks will make you weep with joy.
  <Facet Name="date">
    <DateTime Value="2010-03-26T00:00:00-00:00" />
<Facet Name="tag">
<String Value="freebase" />
<String Value="gridworks" />
<String Value="metaweb" />
  <Facet Name="comments">
    <Number Value="24" />

In this example, Source="2245.xml" in dzc_output.xml refers to a Deep Zoom image whose name comes from the WordPress post_id for that entry, which is:


But Id="596", which is the connection between dzc_output.xml and pivot.cxml, comes from a counter in the script that increments for each item processed. I don’t know why the numbering of items in the WordPress export file is sparse, but it is, hence the difference.

Things to do

Here are some ideas for next steps.

1. Check the comment logic. I just noticed the counts seem odd. Maybe because I’m counting all comments instead of approved comments?

2. Use HTML Tidy to ensure that item content will parse as XML, and then count various kinds of elements within it: tables, images, etc.

2. Use APIs of various services — Twitter,, etc. — to count reactions to each item.

A Pivot visualization of my WordPress blog

A Pivot experiment

Pivot, from Microsoft Live Labs, is a data browser that visualizes data facets represented as Deep Zoom images and collections. I’ve been meaning to try my hand at creating a Pivot collection. My first experiment is a visualization of my blog which, in its current incarnation at, has about 600 entries. That’s a reasonable number of items for the simplest (and most common) kind of collection in which data and visuals are pre-computed and cached in the viewer. Here’s the default Pivot view of those entries.

The default view

To create this collection, I needed a visual representation of each blog entry. I didn’t think screenshots would be very useful, but the method worked out better than I expected. At the default zoom level there’s not much to see, but you can pick out entries that include pictures.

A selected entry

When you select an entry, the view zooms about halfway in to focus on it.

A text-only entry

Here’s a purely textual entry at the same resolution. If you click to enlarge that picture, you’ll see that at this level the titles of the current entry and its surrounding entries are legible.

The Show Info control

Clicking the Show Info control opens up an information window that displays title, description, and metadata. I’ve included the first paragraph of each entry as the description.

Zooming closer

If I zoom in further, the text becomes fully legible.

Histogram of entries

Of course the screenshot doesn’t capture the entire entry, it’s just a picture of the first screenful. To read the full entry, you click the Open control to view the entire HTML page inside Pivot.

Pivot itself isn’t a reader, it’s a data browser. This becomes clear when you switch from item view to graph view. 2006 and 2010 are incomplete years, but the period 2007-2009 shows a clear decline. I suspect a lot of blogs would show a similar trend, reflecting Twitter’s eclipse of the blogosophere.

2007 distribution

Here’s the distribution for just the year 2007.

Histogram of comments

And here’s the comments facet, which counts the number of comments on each entry.

Histogram of entries with more than 20 comments

Adjusting the slider limits the view to entries with more than 20 comments.

Filtering by tags

Of course I can also view entries by tags or tag combinations.

Filtering by keywords

When I start typing a keyword, the wordwheel displays matches from two namespaces: tags and titles.

Other possible views

Facets can be anything you can enumerate and count. I could, for example, count the number of images, tables, and other kinds of HTML constructs in each entry. That isn’t just a gratuitous exercise. Some years back, I outfitted my blog with an XQuery service that could search for items that contained more than a few images or tables, and it was useful for finding items that I remembered that way.

It would also be nice to include facets based on the WordPress stats API. And since a lot of the flow to the blog nowadays comes through URLs on Twitter, a facet based on those referrals would be handy.

How I did it

Life’s too short to make 600 screenshots by hand, so the process had to be automated. Also, I want to be able to update this collection as I add entries to the blog. So I’m using IECapt to programmatically render pages as images, and the indispensable ImageMagick to crop the images in a standard way.

To automate the creation of Deep Zoom images (and XML files), I’m using (Note that I had to make two small changes to that version. At line 224, I changed tile_size=254 to tile_size=256. And at line 291 I changed to

To build the main CXML (collection XML) file, I export my WordPress blog and run a Python script against it. I hadn’t looked at that export file in a long time, and was surprised to find that currently it isn’t quite valid XML. The declaration of the Atom namespace is missing. My script does a search-and-replace to fix that before it parses the XML.

I haven’t uploaded the collection to a server yet, because there are a bazillion little files and I’m still tweaking. Once I’m happy with the results, though, I should be able to establish a baseline collection on a server and then easily extend it an entry at a time.

If there’s interest I’ll publish the script. It’ll be more compelling, I suspect, once Pivot becomes available as a Silverlight control. Currently you have to download and install the Windows version of Pivot to use this visualization. But imagine if could deliver something like this for all of its blogs as a zero-install, cross-platform, cross-browser feature. That would be handy.