Project Jupyter not only revolutionizes data-heavy research across domains - it also boosts personal productivity for problems on a much smaller scale. Due to openness it is an amazing platform for exploring concepts and learning new things.

I started setting up a Jupyter Notebook Server on a Raspberry Pi following this blog post by Arun Durvasula. Convinced of the potential of the platform I followed the development.

My personal exercise soon taught me a great deal about the underlying architcture. Given Jupyter's complexity, speed of growth and scale, it is remarkable that such a system runs fine on a Raspberry Pi.

This repository isn't really anything genuine: I owe big thanks to many contributors in the Jupyter, Raspberry Pi, Linux, Python, Julia and greater Open Source communities for providing all the beautiful building blocks - small and large.

• Rather than installing the latest version of Python as I did the past, I decided that the new version would use the latest Python 3 version supported in Raspbian - as of this writing Python 3.5.3.
• Whilst this seems to be a step backwards, it is a in fact a giant step forward as you benefit from significant installation speedups made possible by the recently released piwheels project.
• The scripts work across the entire range of Raspberry Pis - perhaps with the exception of the early models with just 256MB of memory.
• Python support for GPIO, Sense HAT and PICAMERA is installed without the earlier worries of breaking things on system level.
• All Python modules are pip installed into a virtual environment following advice found online: You should never use sudo pip install -NEVER. Well I did this in the past and it certainly had me and users confused. We have to learn certain things the hard way to really appreciate the benefits of doing them right. It is worth reading up on this in this blogpost.
• You now install Python packages into a virtual environment created with venv using a requirements.txt file. This really achieves a more maintainable setup, opens up more possibilities and hopefully makes this project more useful for the Raspberry Pi and Jupyter communities.
• Python 3, Julia and Bash kernels are installed and configured during installation.
• JupyterLab is installed and ready to use.

• a Raspberry Pi model of your choice complete with micro-usb power-supply - I recommend a Raspberry Pi 3 but the setup should work across the entire range of Pi models, perhaps with the exception of the very early models that featured only 256MB of memory. I tested on a ZeroW, 1, 2 and 3.
• a (micro) SD card with 16GB capacity or more to suit your Pi model with Raspbian Stretch Lite installed and configured to permit access via ssh as user pi.
• an ethernet or wifi connection for the Pi
• internet access on the Pi
• a computer to carry out the installation connected to the same network as the Pi
• LESS TIME THAN EVER BEFORE due to the recent release of piwheels. Users new to this project might argue that the setup is still time-consuming. Believe me: In the past 6 hours+ were not uncommon and installing the system on a Raspberry Pi 1 was not impossible but required quite some patience and time. Note that some packages listed in requirements.txt may not yet be available as Python wheels. Such packages are then built from source and this takes some time...

• an increasing number of users seem to install on top of images that have 'nodejs' already installed.

• The scripts in this repository were initially designed to work based on Raspbian Stretch Lite as a starting point with the intention to run the server headless in order to maximise memory available for data analysis.

• One such starting point is the desktop version of Raspbian Stretch which comes withnodejs (and git) pre-installed. conf_jupyter.sh explained later now checks for the existence of node and only installs it if not yet present on the system.

• For the scripts to run properly on the desktop version of Raspbian or any other startingpoint with node installed, it is necessary that node is version 5 or higher !!!

• If you start with a fresh Raspbian Stretch Desktop image, you can uninstall node using apt purge nodejs and then execute the scripts.

• ssh into your Raspberry Pi with the the fresh install of Raspbian Stretch Lite as user pi. Then run sudo raspi-config and set the memory split to 16MB, expand the file-system and set a new password for the user pi. When done, reboot and log in again via ssh.

• If not yet present, install git:

sudo apt install -y git

• With preparations out of the way clone this repository into the home directory of user pi

git clone https://github.com/kleinee/jns

• Change into the new directory jns just created with git:

cd ~/jns

• To increase the size of swap_file to 2048MB run:

sudo sed -i -e 's/CONF_SWAPSIZE=100/CONF_SWAPSIZE=2048/' /etc/dphys-swapfile
sudo /etc/init.d/dphys-swapfile stop
sudo /etc/init.d/dphys-swapfile st

Technically you can now run sudo ./inst_jns.sh which is the installer script that combines the steps described below. If you follow along I assume that you run all scripts from inside the directory ~/jns.

sudo ./prep.sh

A couple of packages from the Raspbian repository are required during installation and later for a some Python packages to work properly. The script just fetches these packages and installs them.

#!/bin/bash
# script name:     prep.sh
# last modified:   2018/08/12
# sudo:            yes

script_name=$(basename -- "$0")

if ! [ $(id -u) = 0 ]; then
   echo "usage: sudo ./$script_name"
   exit 1
fi

apt update && apt -y upgrade
apt -y install pandoc
apt -y install libxml2-dev libxslt-dev
apt -y install libblas-dev liblapack-dev
apt -y install libatlas-base-dev gfortran
apt -y install libtiff5-dev libjpeg62-turbo-dev
apt -y install zlib1g-dev libfreetype6-dev liblcms2-dev
apt -y install libwebp-dev tcl8.5-dev tk8.5-dev
apt -y install libharfbuzz-dev libfribidi-dev
apt -y install libhdf5-dev
apt -y install libnetcdf-dev
apt -y install python3-pip
apt -y install python3-venv
apt -y install libzmq3-dev
apt -y install sqlite3 

# dependencies for python-opencv-headless
#------------------------------------------------------
apt -y install libjasper-dev
apt -y install libjpeg-dev libtiff5-dev libpng-dev
apt -y install libilmbase12
apt -y install libopenexr22
apt -y install libgstreamer1.0-0
apt -y install libavcodec-extra57
apt -y install libavformat-dev
apt -y install libilmbase12
apt -y install libavcodec-dev
apt -y install libswscale-dev
apt -y install libv4l-dev
apt -y install libgtk2.0-dev
apt -y install libgtk-3-dev
apt -y install libxvidcore-dev
apt -y install libx264-dev
#------------------------------------------------------

./inst_stack.sh

• This creates a virtual Python 3 environment '/home/pi/.venv/jns' and activates it temporarily
• It then updates pip3 to the latest version available from the Python package repository before it processes the requirements.txt file line by line.
• This is a workaround to prevent pip from failing if one or more requirements listed fail to install.

#!/bin/bash
# script name:     inst_stack.sh
# last modified:   2018/01/14
# sudo:            no

script_name=$(basename -- "$0")
env="/home/pi/.venv/jns"

if [ $(id -u) = 0 ]
then
   echo "usage: ./$script_name"
   exit 1
fi

# create virtual environment
if [ ! -d "$venv" ]; then
  python3 -m venv $env
fi

# activate virtual environment
source $env/bin/activate

pip3 install pip==9.0.0
pip3 install -U pip
pip3 install -U setuptools

cat requirements.txt | xargs -n 1 pip3 install

./conf_jupyter.sh

With this script you generate a jupyter notebook configuration directory and in it a file called jupyter_notebook_config.py that holds the configuration settings for your notebook / lab server. You also create a folder notebooks in the home directory of user pi as the notebook_dir for your server. In the configuration file, you apply the following changes:

• tell jupyter not to sart a browser upon start - we access the server from a remote machine on the same network
• set the IP address to '*'
• set the port for the notebook server to listen to 8888
• enable mathjax for rendering math in notebooks
• set the notebook_dir to ~/notebooks
• use the password hash for the default server password jns

NOTE: This setup still uses password authentication. If you prefer token-based authentication, you have to change settings in the config file /home/pi/.jupyter/jupyter_notebook_config.py. Documentation of possible configuration settings can be found here.

After the basic configuration the script activates the bash kernel and activates extensions for Jupyter Notebook and JupyterLab. At the JupyterLab end this requires intstallation of node followed by installation of the underlying JS infrastructure which is a bit time-consuming but ultimately allows you to use ipywidgets, bqplot and potentially other extensions.

#!/bin/bash
# script name:     conf_jupyter.sh
# last modified:   2018/05/29
# sudo:            no

script_name=$(basename -- "$0")
env="/home/pi/.venv/jns"

if [ $(id -u) = 0 ]
then
   echo "usage: ./$script_name"
   exit 1
fi

# activate virtual environment
source $env/bin/activate

# generate config and create notebook directory
# if notebook directory exists, we keep it (-p)
# if configuration file exeists, we overwrite it (-y)

jupyter notebook -y --generate-config
cd $home
mkdir -p notebooks

target=~/.jupyter/jupyter_notebook_config.py

# set up dictionary of changes for jupyter_config.py
declare -A arr
app='c.NotebookApp'
arr+=(["$app.open_browser"]="$app.open_browser = False")
arr+=(["$app.ip"]="$app.ip ='*'")
arr+=(["$app.port"]="$app.port = 8888")
arr+=(["$app.enable_mathjax"]="$app.enable_mathjax = True")
arr+=(["$app.notebook_dir"]="$app.notebook_dir = '/home/pi/notebooks'")
arr+=(["$app.password"]="$app.password = 'sha1:5815fb7ca805:f09ed218dfcc908acb3e29c3b697079fea37486a'")

# apply changes to jupyter_notebook_config.py

for key in ${!arr[@]};do
    if grep -qF $key ${target}; then
        # key found -> replace line
        sed -i "/${key}/c ${arr[${key}]}" $target
    else
        # key not found -> append line
        echo "${arr[${key}]}" >> $target
    fi
done

# install bash kernel
python3 -m bash_kernel.install

# install extensions
jupyter serverextension enable --py jupyterlab
jupyter nbextension enable --py widgetsnbextension --sys-prefix
jupyter nbextension enable --py --sys-prefix bqplot

# activate clusters tab in notebook interface
/home/pi/.venv/jns/bin/ipcluster nbextension enable --user

# install nodejs and node version manager n
# if node is not yet installed
if which node > /dev/null
    then
        echo "node is installed, skipping..."
    else
        # install nodejs and node version manager n
        cd ~/jns
        # fix for issue #22
        # install nodejs and node version manager n
        # see: https://github.com/mklement0/n-install
        curl -L https://git.io/n-install | bash -s -- -y lts
fi

# install jupyter lab extensions
bash -i inst_lab_ext.sh

The script inst_lab_ext.sh - introduced by @Kevin--R to fix issue#23 has the following content:

#!/bin/bash
# script name:     inst_lab_ext.sh
# last modified:   2018/05/29
# sudo:            no

script_name=$(basename -- "$0")
env="/home/pi/.venv/jns"

if [ $(id -u) = 0 ]
then
   echo "usage: ./$script_name"
   exit 1
fi

. /home/pi/.bashrc
jupyter lab clean
jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
jupyter labextension install bqplot --no-build
jupyter labextension install jupyterlab_bokeh --no-build
jupyter lab build

Since you used a virtual environment to install Python modules, you need to activate this environment before you can start your server:

source /home/pi/.venv/jns/bin/activate

The prompt will change to indicate successfull activation preceding pi@hostname: with the envireonment name - in case pf this setup (jns). With hostname set to zerow it looks like this:

(jns) pi@zerow:~ $

After installation completes, you will still need to activate the change made to ~\.bashrc when node was installed before doing anything that requires node.

You can be accomplish this by any of the following:

• reboot
• logout and log back in
• call . ~/.bashrc from the command line

That's the reason for this warning during node installation:

  IMPORTANT: OPEN A NEW TERMINAL TAB/WINDOW or run `. /home/pi/.bashrc`
             before using n and Node.js.

You can see this by running the following commands after your installation completes:

pi@test-pi:~/jns $ echo $PATH
/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/games:/usr/games
pi@test-pi:~/jns $ . ~/.bashrc
pi@test-pi:~/jns $ echo $PATH
/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/games:/usr/games:/home/pi/n/bin
pi@test-pi:~/jns $ 

If you look at your $PATH environmental variable and see /home/pi/n/bin you are ready to use node.

Also note that if you uninstall node with n-uninstall /home/pi/n/bin will remain in your $PATH environmental variable until you reboot or logout and log back in.

To start your server just type jupyter notebook or jupyter lab

To access your server form a webbrowser on a computer running on the same network as your Raspberry Pi, just open a browser and use the Pi's IP address / port 8888 as the url.

xxx.xxx.xxx.xxx:8888

Change `xxx.xxx.xxx.xxx' to the IP address of the Raspberry Pi.

During the configuration the default password for the server was set to jns. You can change this by typing:

(jns) pi@zerow:~ $ jupyter notebook password
Enter password:  ****
Verify password: ****

sudo ./inst_tex.sh

• TeX (and Pandoc) are used under the hood to convert Jupyter notebooks to other formats including PDF.
• Whilst not strictly necessary if no PDF export is rquired, I still recommend to run this step.

#!/bin/bash
# script name:     inst_tex.sh
# last modified:   2018/03/11
# sudo:            yes

script_name=$(basename -- "$0")

if ! [ $(id -u) = 0 ]; then
   echo "usage: sudo ./$script_name"
   exit 1
fi

#------------------------------------------------------
apt install -y texlive-xetex
apt install -y latexmk
#------------------------------------------------------

sudo ./inst_julia.sh

• Julia is a relatively new high-level, high-performance dynamic programming language for numerical computing trying to combine the ease of Python with the speed of C. Thanks to the efforts of the Raspberry Pi community Julia 0.6.0 is available in the Raspbian Stretch Repository. It is really worth a try as the language is a rising star in scientific computing.

• IJulia is the kernel required for Jupyter Notebook / JupyterLab. Backgroud information on Julia on the Raspberry Pi can be found here.

#!/bin/bash
# script name:     inst_julia.sh
# last modified:   2018/03/19
# sudo:            yes

env=/home/pi/.venv/jns
script_name=$(basename -- "$0")

if ! [ $(id -u) = 0 ]; then
   echo "usage: sudo ./$script_name"
   exit 1
fi

env=/home/pi/.venv/jns

apt -y install julia

su pi <<EOF
source $env/bin/activate
julia -e 'Pkg.add("IJulia");'
julia -e 'using IJulia;'
EOF

• I found the SQLite kernel quite useful in some experiments with SQLite3 databases in Jupyter Notebooks.

sudo ./inst_sqlite.sh

#!/bin/bash
# script name:     conf_jupyter.sh
# last modified:   2018/08/12
# sudo:            no

script_name=$(basename -- "$0")
env="/home/pi/.venv/jns"

if [ $(id -u) = 0 ]
then
   echo "usage: ./$script_name"
   exit 1
fi

# activate virtual environment
source $env/bin/activate

# clone SQLite kernel repository
git clone https://github.com/brownan/sqlite3-kernel.git

# install kernel
python ./sqlite3-kernel/setup.py install
python -m sqlite3_kernel.install
rm -rf sqlite3-kernel/

./inst_pi_hardware.sh

Setting up Python support for GPIO pins, the PICAMERA module and Sense HAT hardware in your virtual environment is almost as simple as you would commonly do without such environment.

#!/bin/bash
# script name:     inst_pi_hardware.sh
# last modified:   2018/01/14
# sudo: no

script_name=$(basename -- "$0")
env="/home/pi/.venv/jns"

if [ $(id -u) = 0 ]
then
   echo "usage: ./$script_name"
   exit 1
fi

# activate virtual environment
source $env/bin/activate

git clone https://github.com/RPi-Distro/RTIMULib

cd ./RTIMULib/Linux/python/

python3 setup.py build
python3 setup.py install

cd /home/pi/jns

rm -rf RTIMULib

pip3 install sense-hat
pip3 install picamera
pip3 install gpiozero

Credits for the following solution go to mt08xx:

• create an executable file named 'start_jupyter.sh' in '/home/pi' used to start the server
• create a file named 'jupyter.service' in '/etc/systemd/sytsem'
• start the service

To do this run:

sudo ./service.sh

The file has the following content:

#!/bin/bash
# script name:     service.sh
# last modified:   2018/08/12
# credits:         mt08xx
# sudo:            yes

script_name=$(basename -- "$0")

if ! [ $(id -u) = 0 ]; then
   echo "usage: sudo ./$script_name"
   exit 1
fi

# create jupyter.sh in /home/pi and make it executable
cat << 'ONE' > /home/pi/jupyter_start.sh && chmod a+x /home/pi/jupyter_start.sh
#!/bin/bash
. /home/pi/.venv/jns/bin/activate
jupyter lab
#jupyter notebook
ONE

cat << 'TWO' | sudo tee /etc/systemd/system/jupyter.service
[Unit]
Description=Jupyter

[Service]
Type=simple
ExecStart=/home/pi/jupyter_start.sh
User=pi
Group=pi
WorkingDirectory=/home/pi/notebooks
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target
TWO

# start jupyter
systemctl daemon-reload
systemctl start jupyter
systemctl enable jupyter

• Next time you boot your Pi, the service is stared automatically.
• To stop the service for system updates run:

sudo systemctl stop jupyter

This script is just convenience - it executes the individual steps described above in the order necessary. You may want to comment out optional features that you do not need. By default all features are activated.

#!/bin/bash
# script name:     inst_jns.sh
# last modified:   2018/08/12
# sudo:            yes

script_name=$(basename -- "$0")

if ! [ $(id -u) = 0 ]; then
   echo "usage: sudo ./$script_name"
   exit 1
fi

# make necessary preparations
./prep.sh

# install TeX OPTIONAL
./inst_tex.sh

# install support for Pi hardware OPTIONAL
sudo -u pi ./inst_pi_hardware.sh

# install Python packages 
sudo -u pi ./inst_stack.sh

# configure the server OPTIONAL
sudo -u pi ./conf_jupyter.sh

# install Julia and the IJulia kernel OPTIONAL
./inst_julia.sh

# install the SQLite3 kernel OPTIONAL
./inst_sqlite.sh

# set up service to start the server on boot OPTIONAL
./service.sh

• just run sudo apt update && sudo apt -y upgrade

• activate the virtual environment with source /home/pi/.venv/jns/bin/activate

• list outdated packages with pip3 list --outdated

• Update package with pip3 install -U package where package is the name of package you want to update.