John Myles White johnmyleswhite

Write a blog post criticizing the Julia programming language

As a powerful high-level dynamic programming language, Julia has gained a lot of popularity among data scientists, engineers, and researchers. It is often considered a more efficient alternative to Python, R, and MATLAB, with a syntax that is easy to read and write. However, despite its strengths, there are some criticisms of Julia that should be taken into consideration.

First and foremost, the Julia programming language has a relatively small ecosystem compared to other programming languages. While it does have a growing community of developers, it does not have the same level of support and resources as languages like Python or Java. This can make it difficult for developers to find the necessary tools and libraries to accomplish their tasks.

Another major criticism of Julia is its lack of backwards compatibility. The language is still in its early stages of development, and as a result, changes to the syntax and features are common. While t

	x <- 1
	x <- 2
	x <- 3
	x <- 4
	x <- 5
	x <- 6
	x <- 7
	x <- 8
	x <- 9
	x <- 10

	julia> import Printf: @printf

	julia> f(x) = 1 / (x - floor(Int, x))
	f (generic function with 1 method)

	julia> function g(n, x₀ = 0.43233208718590286890)
	x = x₀
	for i in 1:n
	x = f(x)
	@printf("%d\t%s\n", i, x)

	johnmyleswhite@foobar:~/R-4.1.2$ bin/R
	do_invisible
	do_invisible
	do_invisible
	do_invisible
	do_invisible
	do_invisible
	do_invisible
	do_invisible
	do_invisible

	> visible_plus_one <- function (x) {x}
	>
	> invisible_plus_one <- function (x) {invisible(x)}
	>
	> visible_plus_one(1)
	[1] 1
	> invisible_plus_one(1)
	>
	> visible_plus_one(1) + 1
	[1] 2

	import MacroTools: postwalk

	function missing_check(es)
	if length(es) == 0
	false
	elseif length(es) == 1
	Expr(:call, :ismissing, es[1])
	elseif length(es) == 2
	Expr(
	:call,

	struct ExpressionThunk
	source::Any
	thunk::Any
	end

	macro thunk(e)
	quote
	ExpressionThunk(
	$(QuoteNode(e)),
	() -> $(esc(e))

	x = [1, 2]
	y = [3, 4]
	z = [x, y]

	z′ = copy(z)

	z′[1] === x

	import DataFrames: DataFrame

	import Plots

	r = range(0.0, 1.0, length=512)

	p = Plots.plot(
	r,
	x -> x^2 * (1 - x)^2,
	)

	Plots.png(p, "output2.png")

	#!/usr/bin/Rscript

	png("output.png")
	curve(x^2 * (1 - x)^2, from = 0, to = 1)
	dev.off()

	# time Rscript example.R
	# null device
	# 1
	#