Notes on codes, projects and everything
I need a slide show script for my portfolio pages but couldn’t find a good one anywhere so I decided to write one myself. The slide show script will be able to display image and the respective description in a predefined order. However, in this version, visitors would not be able to directly jump to a particular slide yet. The script is written in prototype‘s object-orientation approach hence you need to have prototype called.
A friend of mine recently posted a screenshot containing a code snippet for a fairly straight forward problem. So after reading the solution I suddenly had the itch to propose another solution that I initially thought would be better (SPOILER: Turns out it isn’t). Then mysteriously I stuck myself to my seat and started coding an alternative solution to it instead of playing Diablo 3 just now.
After being frustrated of not getting consistent and accurate result via standard DOM methods especially
html_element.setAttribute('key', 'value');, I came across some YUI library components that provides abstractions to various DOM methods. Some interesting DOM-related tools covered in this post are
So I first heard about Panda probably a year ago when I was in my previous job. It looked nice, but I didn’t really get the chance to use it. So practically it is a library that makes data looks like a mix of relational database table and excel sheet. It is easy to do query with it, and provides a way to process it fast if you know how to do it properly (no, I don’t, so I cheated).
Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.
While working on a text classification task, I spent quite some time preparing the training set for a given document collection. The project is supposed to be a pure golang implementation, so after some quick searching I found some libraries that are either a wrapper to libsvm, or a re-implementation. So I happily started to prepare my training set in the libsvm format.