Let’s play a game of “Fortunately, Unfortunately“. Respond the previous post (the first comment below this post) by replying this post (not the previous post!)
I’ll start with: “I found this website.“
The wasteof crawler/scraper has been running for 7 hours as a test run.
It’d already scraped 1.2 GBs worth of data….
I think I’ve not obfuscated it enough
I’ll let you guys do it yourself
-- Take your age.
-- Subtract 2.
-- Then add 2.
-- That's your age.
age x = ($) ((.) `foldl` id) [(-2+), (2+)] $ x
-- Take your age.
-- Subtract 2.
-- Then add 2.
-- That's your age.
age x = ($) ((.) `foldl` id) [(-2+), (2+)] $ x
Chapter 1: Introduction
1.1 Background
1.2 Problem
1.3 Purpose
Chapter 2: Explanation
Chapter 3: Conclusion
The size of ½ million depends on the context.
If it’s ½ million bytes, that’s small
If it’s ½ million queries, that’s big
Was in a middle of an ad skipping spree on YouTube when I heard (at a glimpse) the sentence “Patrick’s Parabox”.
Now what, Baba is You ads?
It’s time for a final exam!
… and I’m late at the first day. That’s 5 minutes wasted then.
Now for a non-weird question:
I’m going to implement searching for TBG REST. However, I’m not sure what query syntax I should use. Here’s the list:
Raw : /search/posts?keywords=keyword&author=author&forums=2&forums=5&search_in=0&sort_by=0&sort_dir=DESC
Ocular style: /search/posts?q=keyword +username:"author" +category:"TBG" +category:"RPG"&sort=0&order=DESC
GitHub style: /search/posts?q=keyword user:author in:TBG in:RPG sort:time-desc (you can also use `sort=` and `order=` queries if you want)
not URI encoded for readabilty (for humans at least)
Which one should I choose?
What’s with the dip every December 26 here?
https://npmtrends.com/axios-vs-got-vs-node-fetch-vs-request-vs-superagent
You know how current text-to-image models work, right? They start out with noise and they transform it to make an image.
I wonder what happens if I do that with text
I have a survey for picking a major
I'm unsure what should I pick from these:
Software Engineering (since as you can probably predict, I like coding stuff)
Data Science (since I do also like messing up with data, my main is Python for a reason)
Information System (it's where I get my data anyway, also I'm kinda fascinated with this as well)
(no, I can only select one)