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).
Previously, I started practising recursions by implementing a type check on lat (list of atoms), and ismember
(whether an atom is a member of a given lat). Then in the third chapter, named “Cons the Magnificent”, more list manipulation methods are being introduced.
Recently I find some of my pet projects share a common pattern, they all are based on some kind of grids. So I find myself writing similar piece of code over and over again. While re-inventing wheels is quite fun, especially when you learn new way of getting things done with every iteration, it is actually quite tedious after a while.
In the last part, I implemented a couple of primitive functions so that they can be applied in the following chapters. The second chapter of the book, is titled “Do it again, and again, and again…”. The title already hints that readers will deal with repetitions throughout the chapter.
I saw this article from alistapart, which is about Javascript’s prototypal object orientation. So the article mentioned Douglas Crawford, and I was immediately reminded about my struggle in understanding the language itself. Back then I used to also refer to his site for a lot of notes in Javascript. So I went back to have a quick read, and found this article that discusses the similarity between Javascript and Lisp.
Sometimes, letting a piece of code evolving by itself without much planning does not usually end well. However I was quite pleased with a by-product of it and I am currently formalizing it. So the by-product is some sort of DSL for a rule engine that I implemented to process records. It started as some lambda functions in Python but eventually becomes something else.
So my cheat with dask worked fine and dandy, until I started inspecting the output (which was to be used as an input for another script). While the script seemed to work fine, however when I started to parse each line I was hit with some funny syntax errors. After some quick inspection I found some of the lines was not printed completely.
Often times, I am dealing with JSONL files, though panda’s DataFrame is great (and blaze to certain extend), however it is offering too much for the job. Most of the received data is in the form of structured text and I do all sorts of work with them. For example checking for consistency, doing replace based on values of other columns, stripping whitespace etc.
I came across a video on Youtube on Pi day. Coincidently it was about estimating the value of Pi produced by Matt Parker aka standupmaths. While I am not quite interested in knowing the best way to estimate Pi, I am quite interested in the algorithm he showed in the video however. Specifically, I am interested to find out how easy it is to implement in Python.
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 my static pages and site theme is still under construction, I went to CodeIgniter.com to see how to work with it and played the tutorial screencasts. The reason behind in considering CodeIgniter (CI) to be used in my next project is because I don’t feel like re-inventing the wheel. However to port my current project to use CI may cause some problems as there are differences in how we implement MVC structure.
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.
This post is purely based on my own speculation as there’s no experiment on real-life data to actually back the arguments. I am currently trying to document down a plan for my experiment(s) on recommender system (this reminds me that I have not release the Flickr data collection tool :/) and my supervisor advised to write a paragraph or two on some of the key things. Since he is not going to read it, so I might as well just post it here as a note.
Call me a cheapskate, as I still have not subscribe to a mobile data plan after purchasing my second smartphone, namely Nokia N9. There’s this ‘allow background connections’ option but it doesn’t care whether the connected network is a WLAN network or mobile data network. After finding out that Nokia has no interest in creating another separate option so that each type of network has their respective ‘allow background connections’ switch, I decided to make one for my own.
I haven’t got much time lately, so didn’t write about this new phone that I recently imported. For some reason, this new phone of mine do not act as mass storage device like its predecessors (to certain extend). Thankfully I can still ssh in the phone and this makes it possible to mount it as a sshfs volume.