RyanGreenup

# Refer to:
#How to extract meta description from urls using python? - Stack Overflow:
#https://stackoverflow.com/questions/38009787/how-to-extract-meta-description-#from-urls-using-python

import appex
import clipboard


def main():
	if not appex.is_running_extension():

RyanGreenup

git log | grep '^commit' | sed 's/^commit\ //' |\
    fzf --preview 'git diff {}^! |\
     bat --color always'  

RyanGreenup

# using PyPlot
using GR
using ColorSchemes

N = 2000
try
    mkdir("~/Sync/Documents/tmp/gifs")
catch
end

RyanGreenup

library(ggplot2)

# Enter the data in such a way to match the Plot

data <-
  rbind(
    c("C", 0.97, 1135),
    c("C++", 0.84, 3542),
    c("Go", 3.75, 894),
    c("Rust", 0.93, 763),

RyanGreenup

#!/bin/bash
IFS="\n"

# Set Directories ............................................
DotFiles="~/DotFiles/"
R_DotFiles="${DotFiles}R/"

# Main Function.............................................
main() {
	## Make the directory

RyanGreenup

#!/bin/bash
SERVER_DIR="/srv/http/"
DB="${SERVER_DIR}/mediawiki/data/my_wiki.sqlite"
IP="localhost"
PORT="80"

page_name="$(sqlite3 "${DB}" 'SELECT page_title FROM page;' | sk --ansi --preview "sqlite3 "${DB}" 'SELECT old_text FROM text WHERE old_id is ( SELECT content_id FROM content where content_sha1 is ( SELECT rev_sha1 FROM revision WHERE rev_id is ( SELECT page_latest FROM page WHERE page_title is \"{}\")));' | bat  --color=always -l org")"

firefox "http://${IP}:${PORT}/mediawiki/index.php/${page_name}"

RyanGreenup

## * Packages
library(mise)
mise()

## * Constnats .............................................
## Observed Values
obs <- rbind(
        c(1070, 1090, 1090),
        c(1090, 1020, 990)
    )

RyanGreenup

Create Root CA (Done once)

Create Root Key

Attention: this is the key used to sign the certificate requests, anyone holding this can sign certificates on your behalf. So keep it in a safe place!

openssl genrsa -des3 -out rootCA.key 4096

RyanGreenup

Using SysImages to Speed up Julia

Install Fezzik

First install Fezzik, this has been around since 2019 and actively maintained, but it's only available from source:

using Pkg

RyanGreenup

## Write in the data
o <- rbind(
    c(264, 127, 99),
    c(161, 116, 67)
)
colnames(o) <- c("Border", "Grass", "Sand")
rownames(o) <- c("Moringa", "Vicinus")

## First let's get our chi value
## Expected values