Notes on codes, projects and everything
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).
array_map function is a function that I use the most in my php scripts recently. However, there are times where I want to pass some non-array into it, therefore often times I have code like the snippet shown below:
$result = array_map(
'some_callback',
array_fill(0, count($some_array), 'some_string'),
array_fill(0, count($some_array), 'some_other_string'),
$some_array
)
It doesn’t look good IMO, as it makes the code looks complicated. Hence, after seeing how the code may vary in all different scenarios, I created some functions to clean up the array_map call as seen above. Code snippet after the jump
After comparing my own implementation of MVC with CodeIgniter’s, now I’m comparing Kohana’s and Zend’s. I have just shifted from CodeIgniter to Kohana recently in work and is currently learning on how to use Zend Framework to build my web-app. As everybody knows, Zend Framework is more like a collection of library classes than a framework a la Ruby on Rails, using MVC in Zend Framework would require one to begin from bootstrapping stage. However, in Kohana, just like other frameworks, bootstrapping is done by the framework itself so the developer will get an installation that almost just works (after a little bit of configuration).
This update took me quite a bit more time than I initially expected. Anyway, I have done some refactoring work to the original code, and thought it would be nice to document the changes. Overall, most of the changes involved the refactoring of function names. I am not sure if this would stick, but I am quite satisfied for now.
While JSON is a fine data-interchange format, however it does have some limitations. It is well-known for its simplicity, that even a non-programmer can easily compose a JSON file (but humanity will surprise you IRL). Therefore, it is found almost everywhere, from numerous web APIs, to geospatial data (GeoJSON), and even semantic web (RDF/JSON).
Recently I switched my search code to Annoy because the input dataset is huge (7.5mil records with 20k dictionary count). It wasn’t without issues though, however I would probably talk about it next time. In order to figure out what each parameters meant, I spent some time watching through the talk given by the author @fulhack.