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README

Jupyter Notebook & Lab Server on Raspberry Pi

Intro

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.

What is new?

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 - including 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.

What do you need to follow along?

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...

Installation

IMPORTANT NOTE on fresh installations

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.

First boot with fresh SD card

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

To increase the size of swap_file to 2048MB run:

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

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/scripts just created with git:

cd ~/jns/scripts

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/scripts.

You might not want all features on your system. Feel free to edit inst_jns.sh' to suit your requirements.


Install required Raspbian packages with apt
<pre><code class="lang-bash">sudo ./prep.sh</code></pre>
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.
<pre><code class="lang-bash">#!/bin/bash 
script name:     prep.sh
 last modified:   2018/09/09
 sudo:            yes

script_name=$(basename -- &quot;$0&quot;)
if ! [ $(id -u) = 0 ]; then    echo &quot;usage: sudo ./$script_name&quot;    exit 1 fi
apt update &amp;&amp; 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</code></pre>
Install required Python 3 packages with pip
<pre><code class="lang-bash">./inst_stack.sh</code></pre>

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.

 <pre><code class="lang-bash">#!/bin/bash script name:     inst_stack.sh
 last modified:   2018/01/14
 sudo: no

script_name=$(basename -- &quot;$0&quot;) env=&quot;/home/pi/.venv/jns&quot;
if [ $(id -u) = 0 ] then    echo &quot;usage: ./$script_name&quot;    exit 1 fi
if [ ! -d &quot;$venv&quot; ]; then   python3 -m venv $env fi
activate virtual environment
source $env/bin/activate
pip3 install pip==9.0.0 pip3 install setuptools pip3 install -U pip
cat requirements.txt | xargs -n 1 pip3 install</code></pre>
Configure Jupyter
<pre><code class="lang-bash">./conf_jupyter.sh</code></pre>

With this script you generate a jupyter notebook configuration directory and in it a file called jupyternotebookconfig.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/jupyternotebookconfig.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.


<pre><code class="lang-bash">#!/bin/bash 
script name:     conf_jupyter.sh
 last modified:   2018/09/09
 sudo:            no

script_name=$(basename -- &quot;$0&quot;) env=&quot;/home/pi/.venv/jns&quot;
if [ $(id -u) = 0 ] then    echo &quot;usage: ./$script_name&quot;    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 $home mkdir -p notebooks
target=~/.jupyter/jupyternotebookconfig.py
set up dictionary of changes for jupyter_config.py
declare -A arr
app=&#39;c.NotebookApp&#39;
arr+=([&quot;$app.openbrowser&quot;]=&quot;$app.openbrowser = False&quot;)
arr+=([&quot;$app.ip&quot;]=&quot;$app.ip =&#39;*&#39;&quot;)
arr+=([&quot;$app.port&quot;]=&quot;$app.port = 8888&quot;)
arr+=([&quot;$app.enablemathjax&quot;]=&quot;$app.enablemathjax = True&quot;)
arr+=([&quot;$app.notebookdir&quot;]=&quot;$app.notebookdir = &#39;/home/pi/notebooks&#39;&quot;)
arr+=([&quot;$app.password&quot;]=&quot;$app.password = &#39;sha1:5815fb7ca805:f09ed218dfcc908acb3e29c3b697079fea37486a&#39;&quot;)
apply changes to jupyternotebookconfig.py
for key in ${!arr[@]};do     if grep -qF $key ${target}; then         # key found -&gt; replace line         sed -i &quot;/${key}/c ${arr[${key}]}&quot; $target     else         # key not found -&gt; append line         echo &quot;${arr[${key}]}&quot; &gt;&gt; $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 &gt; /dev/null
    then
        echo &quot;node is installed, skipping...&quot;
    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 ./instlabext.sh</code></pre>
The script <pre><code class="lang-instlabext">.sh</code></pre> - introduced by @Kevin--R to fix issue#23 has the following content:
<pre><code class="lang-bash">#!/bin/bash 
script name:     instlabext.sh
 last modified:   2019/04/06
 sudo:            no

script_name=$(basename -- &quot;$0&quot;) env=&quot;/home/pi/.venv/jns&quot;
if [ $(id -u) = 0 ] then    echo &quot;usage: ./$script_name&quot;    exit 1 fi
. /home/pi/.bashrc . $env/bin/activate 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 labextension install jupyter-leaflet --no-build jupyter lab build</code></pre>
Start and access your server
Activate the virtual environment
Since you used a virtual environment to install Python modules, you need to activate this environment before you can start your server:
<pre><code class="lang-bash">source /home/pi/.venv/jns/bin/activate</code></pre>

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:


<pre><code class="lang-bash">(jns) pi@zerow:~ $</code></pre>
Before you proceed
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: <pre><code class="lang-">IMPORTANT: OPEN A NEW TERMINAL TAB/WINDOW or run

. /home/pi/.bashrc

              before using n and Node.js.</code></pre> You can see this by running the following commands after your installation completes: <pre><code class="lang-bash">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 $</code></pre> If you look at your $PATH environment 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 environment variable until you reboot or logout and log back in.


Start the server
To start your server just type

jupyter notebook or jupyter lab


Access the server
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.
<pre><code class="lang-bash">xxx.xxx.xxx.xxx:8888</code></pre>

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

Login

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: **

Install TeX (optional)

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 #------------------------------------------------------

Install Julia and the IJulia kernel (optional)

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.

Alternative 1: Julia 1.1.0 (RECOMMENDED)

sudo ./inst_julia-1.1.0.sh

NOTE tha the installer assumes that Julia IS NOT yet installed. If it is and you want to proceed with installing Julia-1.1.0, I suggest to remove the existing Julia installation before you proceed.

```
1.1.0
```
binaries were cross-compiled by Mr Satoshi Terasaki (for more information follow this link) and Mr Satoshi thankfully hosts his binaries here.

We need to download a large file from Google Drive and need to install the right binary based on the CPU architecture. The download contains binaries for both architectures.

The Download Helper

As per comments in the script this is literally a 1:1 copy of code found on stack overflow - adjustments were only necessary to set the FILE_ID and the DESTINATION as required in the context of this repository. The helper is called by the installer script and is not meant to be exceuted manually.

#!/home/pi/.venv/jns/bin/python
# 
last modified 2019/05/26
 # Python helper script to download Julia 1.1.0 binaries
 not meant to be executed manually
 https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
 #
FILE_ID = '1fj6pNAJgmUD7bsSXqh8ocC1wESx8jkRh' DESTINATION = './julia-1.1.0-arm32bit.zip'
import requests
def downloadfilefromgoogledrive(id, destination):     URL = "https://docs.google.com/uc?export=download"
session = requests.Session()
response = session.get(URL, params = { 'id' : id }, stream = True)     token = getconfirmtoken(response)
if token:         params = { 'id' : id, 'confirm' : token }         response = session.get(URL, params = params, stream = True)
saveresponsecontent(response, destination)
def getconfirmtoken(response):     for key, value in response.cookies.items():         if key.startswith('download_warning'):             return value
return None
def saveresponsecontent(response, destination):     CHUNK_SIZE = 32768
with open(destination, "wb") as f:         for chunk in response.itercontent(CHUNKSIZE):             if chunk: # filter out keep-alive new chunks                 f.write(chunk)
if name == "main":     fileid = FILEID     destination = DESTINATION     downloadfilefromgoogledrive(file_id, destination)

The Installer

Note that the code assumes that julia is not present.

installs necessary dependencies as suggested by Mr Terasaki
uses the downlaod helper to downlaod his binaries
detects the CPU architecture and installs the matching julia binary
creates a soft link in
```
/usr/local/bin
```
installs the the IJulia kernel

#!/bin/bash
script name:     inst_julia-1.1.0.sh
last modified:   2019/05/26
sudo:            yes
SCRIPT_NAME=$(basename -- "$0") JNS_USER='pi' HOMEDIR="/home/$JNSUSER" ENV="$HOME_DIR/.venv/jns"
JULIAHOME=$HOMEDIR/julia/
if ! [ $(id -u) = 0 ]; then    echo "usage: sudo ./$SCRIPT_NAME"    exit 1 fi
# 
apt install dependencies
 # apt install -y build-essential  apt install -y libatomic1 apt install -y gfortran  apt install -y perl  apt install -y wget apt install -y m4 apt install -y cmake  apt install -y pkg-config apt install -y libopenblas-base libopenblas-dev apt install -y libatlas3-base libatlas-base-dev apt install -y liblapack-dev apt install -y libmpfr-dev libgmp3-dev apt install -y libgfortran3
# 
download and install julia based on architecture
 # su pi <<ONE     cd $HOME_DIR     . $ENV/bin/activate     ./dnld_julia-1.1.0-arm32bit.py     unzip ./julia-1.1.0-arm32bit.zip          ARCHITECTURE=$(python -c 'import os; print(str(os.uname()[4]));')     if (("$ARCHITECTURE" == "armv7l"))     then         mv ./julia1.1.0-arm32bit/rpi3/julia-1.1.0.zip $HOME_DIR     else         mv ./julia1.1.0-arm32bit/rpizero/julia-1.1.0.zip $HOME_DIR     fi
unzip julia-1.1.0.zip     mv julia-1.1.0 julia     rm -rf julia1.1.0-arm32bit     rm ./julia-1.1.0-arm32bit.zip     rm ./julia-1.1.0.zip     rm -rf __MACOSX/ ONE
# 
add symbolic link for julia executable
 #
ln -s $JULIA_HOME/bin/julia /usr/local/bin/julia
# 
 install IJulia kernel
 #
su pi <<TWO     julia -e 'using Pkg; Pkg.add("IJulia");'     julia -e 'using IJulia;' TWO

Alternative 2: Julia 0.6.0 provided with Raspbian Stretch (NOT RECOMMENDED)

This is NOT RECOMMENDED as Julia 0.6.0 is no longer maintained. I keep the installer here for reference only.

sudo ./inst_julia-0.6.0.sh

#!/bin/bash
script name:     inst_julia-0.6.0.sh
last modified:   2019/05/23
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

Install R-3.6.0 and the IRkernel (optional)

Since the R binaries that come with Raspbian Stretch are quite dated, I decided to install R from source. Compilation takes a while. So be patient when running the script.

Note that this installer checks whether R is alredy present and if it is, skips compilition and just installs the IRkernel.

sudo ./inst_R-3.6.0.sh

#!/bin/bash
script name:     inst_R-3.6.0.sh
last modified:   2019/05/19
sudo:            yes
SCRIPT_NAME=$(basename -- "$0") JNS_USER='pi' HOMEDIR="/home/$JNSUSER" ENV="$HOME_DIR/.venv/jns"
R_VERSION="R-3.6.0" RDOWNLOADURL="http://mirrors.psu.ac.th/pub/cran/src/base/R-3/$R_VERSION.tar.gz" R_EXEC=$(which R) RHOME="$HOMEDIR/R"
if ! [ $(id -u) = 0 ]; then    echo "usage: sudo ./$SCRIPT_NAME"    exit 1 fi
cd $HOME_DIR
# 
 apt install additional packages
 # apt install -y libreadline-dev apt install -y libbz2-dev
# 
 download R source and compile
  if R is not yet present  
 # su pi <<ONE     if [ -z ${R_EXEC} ]; then         if [-z ${R_HOME}]; then             mkdir $R_HOME         fi         wget $RDOWNLOADURL         tar -xvf "$R_VERSION.tar.gz"         rm "$R_VERSION.tar.gz"         cd ./$R_VERSION          ./configure --with-x=no --disable-java --prefix=$R_HOME         make && make install         cd $HOME_DIR         rm -rf $R_VERSION     fi ONE
# 
 create soft link in /usr/local/bin
 # ln -s $R_HOME/bin/R /usr/local/bin/R ln -s $R_HOME/bin/Rscript /usr/local/bin/Rscript
su pi <<TWO     . $ENV/bin/activate     echo "install.packages('IRkernel', repos='http://cran.rstudio.com/')" | R --no-save     echo "IRkernel::installspec()" | R --no-save TWO

Install the SQLite kernel (optional)

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

./inst_sqlite.sh

#!/bin/bash
script name:     inst_sqlite.sh
last modified:   2018/09/09
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
cd sqlite3-kernel
python setup.py install
python -m sqlite3_kernel.install
cd ..
rm -rf sqlite3-kernel/

Install Python support for Raspberry Pi hardware (optional)

./instpihardware.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:     instpihardware.sh
last modified:   2018/10/04
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
pip install RTIMULib pip install sense-hat pip install picamera pip install gpiozero
Install openCV (optional)

bash #!/bin/bash

script name: inst_opencv.sh

last modified: 2018/11/27

sudo: yes

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

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

#------------------------------------------------------ apt install -y libjasper1 libjasper-dev apt install -y libjpeg-dev libtiff5-dev libpng12-dev apt install -y libilmbase12 apt install -y libopenexr22 apt install -y libgstreamer1.0-0 apt install -y libavcodec-extra57 apt install -y libavformat-dev apt install -y libilmbase12 apt onstall -y libavcodec-dev apt install -y libswscale-dev apt install -y libv4l-dev apt install -y libgtk2.0-dev apt install -y libgtk-3-dev apt install -y libxvidcore-dev apt install -y libx264-dev #------------------------------------------------------

su - pi <<'EOF' source /home/pi/.venv/jns/bin/activate pip install opencv-python-headless EOF

## Start the server at boot with systemd (optional) 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/system'
start the service

To do this run:

bash sudo ./conf_service.sh

The file has the following content:

bash #!/bin/bash

script name: conf_service.sh

last modified: 2018/09/09

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/jupyterstart.sh && chmod a+x /home/pi/jupyterstart.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:

bash sudo systemctl stop jupyter

## Put it all together

This script is just convenience - it executes the individual steps described above in the order necessary. Note that installation of additinal languages and their respective kernels as well as installtion of opnencv is deactivated by default as not all users may need this functionality. I recommend to run

inst_jns.sh

as is and install additional functionality using the individual scripts.
inst_sqlite.sh
inst_R-3.6.0.sh
inst_julia-0.6.0.sh
inst_julia-1.1.0.sh

bash #!/bin/bash

script name: inst_jns.sh

last modified: 2019/05/26

sudo: yes

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

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

#-----------------------------------------------

MANDATORY

#-----------------------------------------------

make necessary preparations

./prep.sh

install Python packages

sudo -u pi ./inst_stack.sh

configure server

sudo -u pi ./conf_jupyter.sh

#-----------------------------------------------

OPTIONAL, RECOMMENDED

#-----------------------------------------------

install TeX

./inst_tex.sh

install support for Pi hardware

sudo -u pi ./instpihardware.sh

set up service to start the server on boot

./conf_service.sh

#-----------------------------------------------

OPTIONAL, DISABLED BY DEFAULT

#-----------------------------------------------

install Julia 0.6.0 and the IJulia kernel NOT RECOMMENDED

./inst_julia-0.6.0.sh

install Julia 1.1.0 and the IJulia kernel

./inst_julia-1.1.0.sh

install R 3.6.0 and the IRkernel

./inst_R-3.6.0.sh

install the SQLite3 kernel

sudo -u pi ./inst_sqlite.sh

install opencv

./inst_opencv.sh

``


Keep your installation up to date
Raspbian operating system

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


Python 3 packages

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.

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