The Nextjournal Julia Environment

Default environments for Julia 1.0 and 0.7.

This article builds reusable environments for Julia runtimes, based on minimal Bash environments. The exact versions are nil and nil, installed from the generic linux binary packages.

To make use of an environment from this article, follow these steps:

  • Create a new article, and insert a Julia cell.
  • Activate the runtime settings in the sidebar (see image below).
  • Bring up the Environments dropdown.
  • Select the Transclude environment… item.
  • Search for this article, nextjournal/julia-environment, by entering 'julia' into the search field.
  • Select it to list all environments within.
  • Select the desired environment.

1.
Showcase

The following packages are included in Nextjournal's Julia 1.0 environment.

1.1.
System Packages and Basics

A wide variety of support libraries are installed, as well as gcc v7 and ImageMagick. We also install a static build of FFmpeg, for generating animations.

Version nil of the SoftGlobalScope package is available—this adjusts scope-handling to be more like Julia 0.6, providing a more REPL-like interface.

1.2.
Plotting

The default environment comes with GR vnil, PlotlyBase vnil, and PlotlyJS vnil , as well as version nil of the Plots framework. Makie version nil is also installed.

1.2.1.
Plots

The JuliaPlots framework provides a unified interface to multiple graphical backends. The default backend is GR, which efficiently generates static plots and animations.

using Plots

# define the Lorenz attractor
mutable struct Lorenz
    dt; σ; ρ; β; x; y; z
end

function step!(l::Lorenz)
    dx = l.σ*(l.y - l.x)       ; l.x += l.dt * dx
    dy = l.x*(l.ρ - l.z) - l.y ; l.y += l.dt * dy
    dz = l.x*l.y - l.β*l.z     ; l.z += l.dt * dz
end

attractor = 
  Lorenz((dt = 0.02, σ = 10., ρ = 28., β = 8//3, x = 1., y = 1., z = 1.)...)

# initialize a 3D plot with 1 empty series
plt = plot3d(1, xlim=(-25,25), ylim=(-25,25), zlim=(0,50),
             title = "Lorenz Attractor", marker = 2)

# build an animated gif by pushing new points to the plot, saving every 10th frame
anim = @animate for i=1:1500
    step!(attractor)
    push!(plt, attractor.x, attractor.y, attractor.z)
end every 10

gif(anim,"/results/anim.gif")

Switching to the Plotly backend adds some interactivity to the output.

plotly(lw=3)
x = -100:100

Plots.plot(x, 100x.^2)
Plots.plot!(x, x.^3 - x.^2)

1.2.2.
Makie

The Makie package can use a GPU to quickly generate beautiful visualizations.

using Makie, LinearAlgebra

n = 20
f   = (x,y,z) -> x*exp(cos(y)*z)
∇f  = (x,y,z) -> Point3f0(exp(cos(y)*z), -sin(y)*z*x*exp(cos(y)*z), x*cos(y)*exp(cos(y)*z))
∇ˢf = (x,y,z) -> ∇f(x,y,z) - Point3f0(x,y,z)*dot(Point3f0(x,y,z), ∇f(x,y,z))

θ = [0;(0.5:n-0.5)/n;1]
φ = [(0:2n-2)*2/(2n-1);2]
x = [cospi(φ)*sinpi(θ) for θ in θ, φ in φ]
y = [sinpi(φ)*sinpi(θ) for θ in θ, φ in φ]
z = [cospi(θ) for θ in θ, φ in φ]

pts = vec(Point3f0.(x, y, z))
∇ˢF = vec(∇ˢf.(x, y, z)) .* 0.1f0
Makie.surface(x, y, z, resolution = (800,800))
arrows!(pts, ∇ˢF, arrowsize = 0.03, linecolor = (:white, 0.6), linewidth = 3)

1.3.
Data Structures

Several data-related packages are installed in the default environment.

  • For handling their relative datatypes and I/O for associated files, we install a variety of packages, including JLD vnil, CSV vnil, HDF5 vnil, and JSON vnil.
  • The FileIO vnil framework provides a unified interface for loading files of many types via multiple backends, including ImageMagick.
  • DataFrames vnil defines and handles objects similar to those found in R and the Python pandas toolkit, with a comparable interface.

1.3.1.
File Handling

The HDF5 package provides a Julia interface to the HDF5 library. It is also used by the JLD and MAT packages. Let's look at some example temperature data.

NEONDSTowerTemperatureData.hdf5
using HDF5

# Some methods to traverse the first path in an h5 file.
dd(node::HDF5File) = dd(node[names(node)[1]])
dd(node::HDF5Group) = dd(node[names(node)[1]])
dd(node::HDF5Dataset) = node

dspath = h5open(NEONDSTowerTemperatureData.hdf5) do h5
  name(dd(h5))
end
print("First path: $dspath.")

data = h5read(NEONDSTowerTemperatureData.hdf5, dspath)

using Plots

Plots.plot([x.data[1] for x in data],[y.data[3] for y in data],
  xrotation=45,legend=:none)

The JLD package provides a type-preserving way to save Julia objects to file.

using JLD

struct testData
  x::Int64
  y::String
end

foo = testData(7,"test")

save("/tmp/blah.jld", "foo", foo)
load("/tmp/blah.jld")

1.3.2.
FileIO

FileIO provides a unified set of methods to access data in files: query(), load(), and save(), as well as loadstreaming() and savestreaming() for large files. The functions can automatically recognize files using headers or extensions, but you can also provide format information as below, where we load the Iris Dataset from a CSV file.

iris.csv
using FileIO

load(File(format"CSV",iris.csv))

1.3.3.
DataFrames

DataFrame objects represent tabular data as a set of vectors.

using DataFrames

df = DataFrame(A = 1:5, B = 1:2:10, C = ["a","b","c","d","q"])

Column names are referenced with Julia Symbols, not strings.

df[:A] + df[Symbol("B")]

1.3.4.
JSON

Import and export JSON using the JSON package, which is always loaded on Nextjournal. In the example below, a Julia data structure input results in JSON output. The change from nothing to null is a clear indicator.

json(["foo", Dict("bar" => ("baz", nothing, 1.0, 2))])

2.
Setup

2.1.
Julia 1.0

2.1.1.
Build a Minimal Julia 1.0 Environment

We'll base our environment off of our Minimal Bash image. Note that the Julia version is set as an environment variable on the runtime.

Julia 1.0 Minimal
Julia 1.0 Minimal (Bash)Minimal Bash
exporting environment
Type: Nextjournal
Environment:Minimal Bash
Resources:
Environment Variables:
PATH/usr/local/julia/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
JULIA_PATH/usr/local/julia
JULIA_VERSION1.0.2
Download this environment as a Docker image from:

The exact version we're installing is nil. Here we download the archive and signatures.

tarArch='x86_64'
dirArch='x64'
JULIA_VERSION_SHORT=${JULIA_VERSION/-rc/}
FILENAME="julia-${JULIA_VERSION}-linux-${tarArch}.tar.gz"
FILEURL="https://julialang-s3.julialang.org/bin/linux/${dirArch}/${JULIA_VERSION_SHORT%[.-]*}/${FILENAME}"

echo "Downloading ${FILEURL}."

curl -fL -o julia.sha256 \
  "https://julialang-s3.julialang.org/bin/checksums/julia-${JULIA_VERSION}.sha256"
curl -fL -o julia.tar.gz.asc "${FILEURL}.asc"
curl -fL -o julia.tar.gz "${FILEURL}"

echo `grep $FILENAME julia.sha256 | cut -d " " -f1` > j256sig

Check the signatures to verify our download.

sha256=`cat j256sig`
echo "${sha256} *julia.tar.gz" | sha256sum -c -

export GNUPGHOME="$(mktemp -d)"
JULIA_GPG="3673DF529D9049477F76B37566E3C7DC03D6E495"
gpg --keyserver ha.pool.sks-keyservers.net --recv-keys "$JULIA_GPG"
gpg --batch --verify julia.tar.gz.asc julia.tar.gz
command -v gpgconf > /dev/null && gpgconf --kill all
rm -rf "$GNUPGHOME" julia.tar.gz.asc julia.sha256

Install and remove the archive.

mkdir -p "$JULIA_PATH"
tar -xzf julia.tar.gz -C "$JULIA_PATH" --strip-components 1
rm julia.tar.gz j256sig

And verify it runs.

julia -v

The JSON package is required to run on Nextjournal.

julia -E 'using Pkg

pkg"update"
pkg"add JSON"
pkg"build"
pkg"precompile"'

2.1.2.
Build the Default Julia 1.0 Environment

We'll add a number of packages as well as the libraries and support programs required by them. The major packages installed are JuliaPlots along with the GR and PlotlyJS backends, Makie, and the DataFrames, CSV, and HDF5 data-handling packages. The setup requires a GPU node for Makie to successfully precompile, but not to transclude and use unless Makie itself is needed.

First we'll check that the minimal Julia env works.

"$VERSION"

Some Julia packages require gcc to compile, so first we'll install that, as well as various required tools and libraries.

apt-get -qq update
apt-get install --no-install-recommends \
  imagemagick libhdf5-dev hdf5-tools mesa-utils \
  build-essential gfortran cmake automake libtool libltdl-dev pkg-config \
  libxt6 libxrender1 libgl1-mesa-glx libqt5widgets5 `# for GR` \
  libhttp-parser2.7.1 `# for PlotlyJS` \
  libxrandr-dev libxinerama-dev libxcursor-dev libglfw3-dev `# for Makie`
apt-get clean
rm -r /var/lib/apt/lists/* # Clear package list so it isn't stale

Plots also needs FFmpeg to create animations, so we'll install a 64-bit static build from an install package we download in the Appendix.

IDIR="/usr/local/ffmpeg"

mkdir -p $IDIR
cd $IDIR

tar -Jxf ffmpeg-release-amd64-static.tar.xz --strip 1

for ex in $IDIR/{ffmpeg,ffmpeg-10bit,ffprobe,qt-faststart}; do
  ln -s $ex /usr/local/bin/
done

Next the Julia package installs. Bugfix: Makie release fails to precompile, recommendation is using #master for Makie, GLMakie, and AbstractPlotting—mpd, 9 Dec 2018.

using Pkg

pkg"update"
pkg"add SoftGlobalScope DataFrames JLD CSV CSVFiles Netpbm NRRD MeshIO HDF5 FileIO JSExpr CSSUtil StatsBase StatPlots Observables Interact WebSockets HTTP Blink WebIO PlotlyBase PlotlyJS RecipesBase GR Plots ImageCore ImageShow ImageMagick Colors BenchmarkTools FixedPointNumbers AbstractPlotting#master GLMakie#master Makie#master"

Build all packages.

pkg"build"

And finally precompilation of any qualifying packages.

pkg"precompile"

2.1.3.
Test Default 1.0 Env

using SoftGlobalScope, DataFrames, JLD, CSV, CSVFiles, Netpbm, NRRD, MeshIO, HDF5, FileIO, JSExpr, CSSUtil, StatsBase, StatPlots, Observables, Interact, WebSockets, HTTP, Blink, WebIO, PlotlyBase, PlotlyJS, RecipesBase, GR, Plots, ImageCore, ImageShow, ImageMagick, Colors, Makie, BenchmarkTools, FixedPointNumbers
"$(Pkg.installed()["SoftGlobalScope"])"
"$(Pkg.installed()["GR"])"
"$(Pkg.installed()["PlotlyBase"])"
"$(Pkg.installed()["PlotlyJS"])"
"$(Pkg.installed()["Plots"])"
"$(Pkg.installed()["Makie"])"
"$(Pkg.installed()["JLD"])"
"$(Pkg.installed()["CSV"])"
"$(Pkg.installed()["HDF5"])"
"$(Pkg.installed()["JSON"])"
"$(Pkg.installed()["FileIO"])"
"$(Pkg.installed()["DataFrames"])"

2.2.
Julia 0.7

2.2.1.
Julia 0.7 Minimal

We're installing version nil. All of the installation steps are identical for 0.7, so we can just import code from the cells above.





2.2.2.
Julia 0.7 Default

"$VERSION"

Fixing Plots at v0.19.3, the current final 0.7 version. This seems to clear up some other version/dep issues. —mpd, 16 Dec 2018.

using Pkg

pkg"update"
pkg"add SoftGlobalScope DataFrames JLD CSV CSVFiles Netpbm NRRD MeshIO HDF5 FileIO JSExpr CSSUtil StatsBase StatPlots Observables Interact WebSockets HTTP Blink WebIO PlotlyBase PlotlyJS RecipesBase GR Plots#v0.19.3 ImageCore ImageShow ImageMagick Colors BenchmarkTools FixedPointNumbers AbstractPlotting#master GLMakie#master Makie#master"

2.2.3.
Test Default 0.7 Env

using SoftGlobalScope, DataFrames, JLD, CSV, CSVFiles, Netpbm, NRRD, MeshIO, HDF5, FileIO, JSExpr, CSSUtil, StatsBase, StatPlots, Observables, Interact, WebSockets, HTTP, Blink, WebIO, PlotlyBase, PlotlyJS, RecipesBase, GR, Plots, ImageCore, ImageShow, ImageMagick, Colors, BenchmarkTools, FixedPointNumbers, Makie
© 2018 Nextjournal GmbH