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in Dobrica Pavlinušić's random unstructured stuff
Exhibit facet browsing

We have few mp3 players which no longer work, but are still under warranty. So idea was to pick another device (which will hopefully work longer). However, on-line shops leave a lot to be desired if you want to just do quick filtering of data.

As a very fortunate incident, I stumbled upon Exhibit from SMILE project at MIT which brought us such nice tools as Timeline and Potluck.

So, I scraped web, converted it to CSV and tried to do something with it. In the process I again re-visited the problem of semi-structured data: while data is separated in columns, one column has generic description, player name and all characteristics in it.

So, what did I do? Well, I started with CPAN and few hours later I had a script which is rather good in parsing semi-structured CSV files. It supports following:

  • guess CSV delimiter on it's own (using `Text::CSV::Separator`)
  • recognize 10 Kb and similar sizes and normalize them (using `Number::Bytes::Human`)
  • splitting of comma (,) separated values within single field
  • strip common prefix from all values in one column
  • group values and produce additional properties in data
  • generate specified number of groups for numeric data, useful for price ranges
  • produce JSON output for Exhibit using `JSON::Syck`

"
 So how does it look?"http://blog.rot13.org/demo/links/links.html

In the end, it is very similar to the way Dabble DB parses your input. But, I never actually had any luck importing data into Dabble DB, so this one works better for me :-)

This will probably evolve to universal munger from CSV to arbitrary hash structure. What would be good name? Text::CSV::Mungler?

This is a first post in series of posts which will cover one hack a week on my blog. This will (hopefully) force me to write at least one post a week on one side, and provide some historic trace about my work for later.

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