Notes on codes, projects and everything
In recent years, I start to make my development environment decouple from the tools delivered by the package manager used by the operating system. The tools (compiler, interpreters, libraries etc) are usually best left unmodified so other system packages that rely on them keeps working as intended. Also another reason for the setup is I wanted to follow the latest release as much as possible, which cannot be done unless I enroll myself to a rolling release distro.
(more…)This is the second part of the golang learning rant log. Previously on (note (code cslai)) I managed to make each line in the CSV into a hash map. So today I am going to make it into JSON Lines.
I was invited to try Go (the programming language, not that board game) a few months ago, however I didn’t complete back then. The main reason was because it felt raw, compared to other languages that I know a fair bit better (for example Ruby). There was no much syntatic sugar around, and getting some work done with it feels “dirty”.
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).
I was thinking whether it is possible to avoid exposing PDO and PDOStatement objects to the users of my database library (mainly just me). While I was working on my project I sort of notice that there is a almost fixed pattern whenever I work with the database. With this in mind, I added in some new functions to the library, and decided to make a quick release for this.
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.
After coded enough Javascript few months back, I found that there are a couple of functions that I kept re-using in different projects. Therefore I took some time to refactor them and re-arrange them into a single file. The common code that I keep reusing even today consists of functions that does prototypical inheritance, scope maintenance, some jquery stuff, google maps api stuff and some general ajax application related code.
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.