My friend needed a way to determine the Flesch-Kincaid readability score for a selected paragraph, and was using Microsoft Word for that. I wrote a script to automatically parse the scores for all txt files provided, then started to wonder how different books fared in that aspect, how readability scores map to language proficiency levels, and what can be told about the book in general using simple analysis tools. It was a fun project but the readability scores were far from expected — eg I hate Joseph Conrad’s Heart of Darkness and always find it frustrating to read but the readability score is actually not that low.
I would expect a lot of the CDPr employees to not be actual employees but contractors (forcing people to set up a single-person company, „jednoosobowa działalność gospodarcza”, is a poular practice here) which would put the workers in an even worse situation.
At the same time, while refusing to work overtime may be a bad look at some companies, a lot of others have very strict policies on actually being able to have their overtime even classified as such (because overtime results in either extra pay or holiday time).
Honestly, I don’t believe most of the developers, QAs, etc really want this crunch but they know their careers might be silently ruined if they don’t agree with those higher in the ladder.
1password has the option to give access to your passwords to whoever you choose after you die. The way it works is, you define the person and the time limit and if they request to get access to your passwords and you don't decline it for the defined time limit, they get it.
I gave plotnine a go in one of my personal Python projects (I'm a big fan of ggplot2 and tidyverse in general over pandas and seaborn) and after struggling for a while with a more complicated graph I went back to using seaborn.
Not to mention writing R-like code in Python will prevent you from being immediately understood by both R and Python developers. It's just not worth it.
If you want to have Jupyter Notebook support then I suggest using Pelican. There's a plugin specifically for parsing Jupyter Notebooks, and you can also write simple md files. It's a bit more complicated to start with than Jekyll (meaning 2 afternoons instead of 1 :)) but it really works for me.
Source: I've been using Pelican with the said plugin for my personal website for the past few months.
Having deleted my account months ago, I still keep receiving an email about one particular guy (who I don't know) wanting to become part of my network. I tried their unsubscribe link multiple times, to no avail. First I just didn't want to have an account anymore, now I hate them.
My friend needed a way to determine the Flesch-Kincaid readability score for a selected paragraph, and was using Microsoft Word for that. I wrote a script to automatically parse the scores for all txt files provided, then started to wonder how different books fared in that aspect, how readability scores map to language proficiency levels, and what can be told about the book in general using simple analysis tools. It was a fun project but the readability scores were far from expected — eg I hate Joseph Conrad’s Heart of Darkness and always find it frustrating to read but the readability score is actually not that low.