Raspberry Pi 2023

Here are the commands required to reproduce the environment for running solutions on a Raspberry Pi Single Board Computer

The editor and language options available are:

VS Code

Python, Julia, R, Wolfram

Jupyter Lab

Python, Julia, R, Wolfram, Octave, SciLab, gnuplot

Pluto notebook

Julia

Octave

Octave

Raspberry Pi 2023

These commands were entered on Raspberry Pi OS Bullseye 64bit on a 4GB Raspberry Pi 

From https://downloads.raspberrypi.org/raspios_arm64/images/ downloaded 2023-05-03-raspios-bullseye-arm64.img.xz

Flashed to 32GB sd card with Balena Etcher

Booted on RPI4

Tick use English language Next

New password Next

Set Up Screen Next

Select wifi network Skip (cabled)

Update software Skip

Setup Complete Restart

Raspberry > Preferences > Raspberry Pi Configuration> Interfaces enable SSH and VNC

In terminal

sudo apt-get update

sudo apt-get full-upgrade

sudo reboot

mkdir Developer

sudo apt-get update 

sudo apt-get install wolfram-engine

From https://github.com/conda-forge/miniforge downloaded Miniforge3-Linux-aarch64

In terminal in Downaloads bash Miniforge3-Linux-aarch64.sh

Chose to Initialise miniforge3

Restart Terminal

conda create -n rp31011 python=3.10.11

conda activate rp31011

which python shows /home/pi/miniforge3/envs/rp31011co/bin/python

python -V shows Python 3.10.11

which pip shows /home/pi/miniforge3/envs/rp31011/bin/pip

conda install -c conda-forge jupyterlab

conda install -c conda-forge numpy

conda install -c conda-forge sympy

conda install -c conda-forge matplotlib

conda install -c conda-forge pandas

conda install -c conda-forge plotly

conda install -c conda-forge bokeh

conda install -c conda-forge scipy

conda install -c conda-forge seaborn

conda install -c conda-forge ipympl

conda install -c conda-forge watermark

conda install -c conda-forge stochastic

conda install -c conda-forge astropy plasmapy 

Conda install -c conda-forge r-base

sudo apt-get install octave

sudo apt-get install scilab

pip install octave-kernel scilab-kernel 

pip install gnuplot_kernel

python -m gnuplot_kernel install – -user

From julialang.org/downloads downloaded 64bit AArch64 of v1.9.1

Unzipped tar to /home/pi/julia-1.9.1

ln -s /home/raspberry/julia-1.9.1/bin/julia /home/raspberry/miniforge3/envs/rp31011/bin/julia

julia

using Pkg

Pkg.add(“IJulia”)

exit()

From https://nodes.org/en/downloads/current downloaded Linux binaries ARMv8

Extract files from node-v20.3.0-Linux-arm64.tar.xz to /home/pi/node-v20.3.0

ln -s /home/raspberry/node-v20.3.0-linux-arm64/bin/node /home/raspberry/miniforge3/envs/rp31011/bin/node

From github.com/WolframResearch/WolframLanguageForJupyter.git downloaded WolframLanguageForJupyter-0.9.3.zip

Unzipped to home/raspberry/wolfram

In p31011 environment in /home/raspberry/WolframLanguageForJupyter-0.9.3 directory ran

./configure-jupyter.wls add

R

install.packages(‘IRkernel’)

UK mirror

IRkernel::installspec()

quit()

n

sudo apt install code

code

Add Python, Jupyter, Julia, REditor, Wolfram Research support extensions

jupyter-lab build

jupyter labextension list

jupyter kernelspec list

jupyter nbextension list

jupyter-lab Verify working with test notebook Then shutdown

jupyter notebook –generate-config

jupyter notebook password

In rp31011 Julia add Pluto, import Pluto, Pluto.run(host=“=0.0.0.0”)

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