Notes on codes, projects and everything
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.
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).
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…)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.
After a year and half, a lot of things changed, and annoy also changed the splitting strategy too. However, I always wanted to do a proper follow up to the original post, where I compared boosting to Annoy. I still remember the reason I started that (flawed) experiment was because I found boosting easy.
(more…)I finally put in some time and effort learning myself a bit of Rust. Though I am still struggling with ownership and lifetimes (which is essentially everything about the language, to be honest), I find it more interesting compared to Golang, which is relatively boring, though being functional (no pun intended). While learning the language, the one thing I came across often is the Option
enum, then I remembered that I read something about Monad.
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.