Notes on codes, projects and everything
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).
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
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).
I used to develop a bot, partly for work, that fetches current latest petrol retail price in Malaysia. The bot was really an experiment, but at the time it worked well. Then a few years later, out of boredom, I revisited the project after finding the telegram bot library is moving towards asyncio. It was great (at least a lot of people rave about it), but also at the same time intimidating, I learned about coroutines and used gevent in the past, but not asyncio itself.
(more…)Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.
After a miserable trip back to academic world, I finally re-gained the courage to get back to job-market. For the time spent in university, I spent quite some time reading about Semantic Web and RDF. Then I thought, I should have published more in this format in future. However, that didn’t really happen, mostly because I am too lazy.