aymericbeaumet

Ever wanted to delete all your likes/favorites from Twitter but only found broken/expensive tools? You are in the right place.

1. Go to: https://twitter.com/{username}/likes
2. Open the console and run the following JavaScript code:

setInterval(() => {
  for (const d of document.querySelectorAll('div[data-testid="unlike"]')) {
    d.click()
 }

tinkertim

Description

This is a simple egg pasta recipe that I've been refining over the years of making fresh pasta for my family. It's based on a recipe I picked up while I was a line cook at a family Italian place about 20 years ago that has long since gone out of business; I've put it back together and adjusted it so it scales down as easily as it does up. Originally, this was made in 10kg (20+ pound) batches.

This dough isn't suitable for extruders, it is intended for rolling and cutting. That means you can make pretty much any kind of noodle, or lasagna sheet out of it. If you want to make ravioli or other stuffed pasta, you want to use a recipe with quite a bit more egg in it, and more steps for drying. If you want to make shaped pasta, such as shells, you probably want a durum wheat & water (eggless) dough recipe instead.

Yield

mndrake

# originally from: http://stackoverflow.com/questions/42528400/plot-brushing-or-accessing-drawn-shape-geometry-for-spatial-subsets-in-shiny-lea
# uses https://github.com/bhaskarvk/leaflet.extras

library(shiny)
library(leaflet)
library(leaflet.extras)
library(sp)

cities <- structure(list(AccentCity = c("Saint Petersburg", "Harare", "Qingdao", 
                                        "Addis Abeba", "Xian", "Anshan", "Rongcheng", "Kinshasa", "New York", 

ramhiser

# The data set and model are described in the *brms* vignette
library(brms)

url <- paste0("https://raw.githubusercontent.com/mages/diesunddas/master/Data/ClarkTriangle.csv")
loss <- read.csv(url)

set.seed(42)

# Generated a random continuous feature
loss$ramey <- runif(nrow(loss))

wch

library(shiny)

# Example usage:
# lmGadget(mtcars, "wt", "mpg")
#
# Returns a list with two items:
#   $data: Data with excluded rows removed.
#   $model: lm (model) object.
lmGadget <- function(data, xvar, yvar) {
  library(miniUI)

mbostock

license: gpl-3.0

hadley

ks.default <- function(rows) seq(2, max(3, rows %/% 4))

many_kmeans <- function(x, ks = ks.default(nrow(x)), ...) {
  ldply(seq_along(ks), function(i) {
    cl <- kmeans(x, centers = ks[i], ...)
    data.frame(obs = seq_len(nrow(x)), i = i, k = ks[i], cluster = cl$cluster)
  })
}

all_hclust <- function(x, ks = ks.default(nrow(x)), point.dist = "euclidean", cluster.dist = "ward") {