Jordi Rosell jrosell

commonkmark's markdown nested tags alternatives

What if we don't want to use raw html?

<div>What's <div>There</div></div>

What other tags can we nest using commonkmark without raw html?

title	Merging R objects like dictionaries in R
format	html

Let's explore how to merge lists, enviroments or vectors like dictionaries in R.

pak::pak(c(
  "purrr",

	library(ggplot2)

	# expected plot gg_manual
	manual_plots <- list()
	manual_plots[[1]] <- ggplot(penguins, aes(bill_len, m[,1])) +
	geom_point() +
	labs(title = "Column 1")
	manual_plots[[2]] <- ggplot(penguins, aes(bill_len, m[,2])) +
	geom_point() +
	labs(title = "Column 2")

	# Get your API Key with Broser rendering permissions here: https://dash.cloudflare.com/profile/api-tokens

	CLOUDFLARE_ACCOUNT_ID="<your_cloudflare_account_id>"
	CLOUDFLARE_API_TOKEN="<your_cloudflare_api_token>"

	curl -X POST "https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/browser-rendering/crawl" \
	-H "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \
	-H 'Content-Type: application/json' \
	-d '{
	"url": "https://www.thediar.com/"

	# Reference: By Josh Goldstein from Dirk Eddelbuettel on https://mastodon.social/@eddelbuettel/116132645744985793

	library(data.table)
	cw <- data.table(ChickWeight)

	# fmt: skip
	cw21 <- (
	cw[Time %in% c(0, 21)]
	[, Weight := weight]
	[, Group := factor(paste0("Diet_", Diet))]

	# pak::pak("r-lib/nanonext")
	library(nanonext)

	conns <- list()
	handlers <- list(
	handler_stream("/stream",
	on_request = function(conn, req) {
	conn$set_header("Content-Type", "application/x-ndjson")
	conns[[as.character(conn$id)]] <<- conn
	conn$send('{"status":"connected"}\n')

	---
	title: "Create and search image embeddings using torch, mobilenet v3, rchroma and R"
	---

	Prepare torch, and mobilenet v3 embeddings.

	```{r}
	if (!rlang::is_installed("torch")) {
	# https://torch.mlverse.org/docs/articles/installation#pre-built
	options(timeout = 90000)

	{
	"lib": {
	"prefix": "lib",
	"body": "library(${1:package})",
	"description": "Attach an R package"
	},
	"src": {
	"prefix": "src",
	"body": "source(\"${1:file.R}\")",
	"description": "Source an R file"

	library(purrr)

	# The intial information
	elements <- tibble::tribble(
	~key , ~values ,
	"Barbie" , "shoes" ,
	"Oppenheimer" , "history"
	)

	# Aditional values we want to proces