11/24/2021»»Wednesday

Install Jupyter Notebook Docker

Minimal notebook doesn’t have much inside. If you want to use your jupyter notebook for data science or tensorflow experiments, I recommend switching the minimal jupyter image jupyter/minimal-notebook with jupyter/tensorflow-notebook. First iteration. First we need to know what are we running and whether we can run it locally. Interactive notebook formats. ↔︎ Jupyter notebook. Page layout formats → InDesign ICML. Wiki markup formats. ↔︎ MediaWiki markup ↔︎ DokuWiki markup ← TikiWiki markup ← TWiki markup ← Vimwiki markup → XWiki markup → ZimWiki markup ↔︎ Jira wiki markup. Slide show formats → LaTeX Beamer → Slidy → reveal.js.

Start JupyterLab#

Start a JupyterLab container based on the official Jupyter docker stacks (debian), with sudo privileges to install anything you need (e.g. pip or apt packages)

You can start a container using the JupyterLab template in the Catalog web UI (make sure the Templates checkbox is checked)

When instantiating the template you can provide a few parameters, such as:

  • Password to access the notebook
  • Optionally you can provide a git repository to be automatically cloned in the JupyterLab (if there is a requirements.txt packages will be automatically installed with pip)
  • Docker image to use for the notebook (see below for more details on customizing the docker image)

The DSRI will automatically create a persistent volume to store data you will put in the /home/jovyan/work folder (the folder used by the notebook interface). You can find the persistent volumes in the DSRI web UI, go to the Administrator view > Storage > Persistent Volume Claims.

With this template you can use any image based on the official Jupyter docker stack: https://github.com/jupyter/docker-stacks

Install Anaconda For Windows

  • ghcr.io/maastrichtu-ids/jupyterlab: for data science and knowledge graphs, with Java and SPARQL kernels, and autocomplete for Python
  • jupyter/scipy-notebook: some packages for science are preinstalled
  • jupyter/datascience-notebook: with Julia kernel
  • jupyter/tensorflow-notebook: with tensorflow package pre-installed
  • jupyter/r-notebook: to work with R
  • jupyter/pyspark-notebook: if you want to connect to a Spark cluster
  • jupyter/all-spark-notebook: if you want to run Spark locally in the notebook

You can also build your own image, feel free to use this repository as example to extend a JupyterLab image: https://github.com/MaastrichtU-IDS/jupyterlab

Use git in JupyterLab#

You can always use git from the terminal.

Before pushing back to GitHub or GitLab, you will need to configure you username and email in VSCode terminal:

git config --global user.email [email protected]

You can run this command to ask git to save your password for 15min:

Or store the password in a plain text file:

git config --global credential.helper 'store --file ~/.git-credentials'

Install Jupyter Notebook Docker Image

Jupyter notebookInstall jupiter notebook docker download

We recommend to use SSH instead of HTTPS connection when possible, checkout here how to generate SSH keys and use them with your GitHub account.

You can also enable and use the JupyterLab Git extension to clone and manage your git repositories.

It will prompt you for a username and password if the repository is private.

Notebook

The Python docker library is among the top 100 Python libraries, with more than 29,160,484 downloads. This article will show you everything you need to get this installed in your Python environment.

How to Install docker on Windows?

  1. Type 'cmd' in the search bar and hit Enter to open the command line.
  2. Type “pip install docker” (without quotes) in the command line and hit Enter again. This installs docker for your default Python installation.
  3. The previous command may not work if you have both Python versions 2 and 3 on your computer. In this case, try 'pip3 install docker' or “python -m pip install docker“.
  4. Wait for the installation to terminate successfully. It is now installed on your Windows machine.

Here’s how to open the command line on a (German) Windows machine:

First, try the following command to install docker on your system:

Second, if this leads to an error message, try this command to install docker on your system:

Third, if both do not work, use the following long-form command:

The difference between pip and pip3 is that pip3 is an updated version of pip for Python version 3. Depending on what’s first in the PATH variable, pip will refer to your Python 2 or Python 3 installation—and you cannot know which without checking the environment variables. To resolve this uncertainty, you can use pip3, which will always refer to your default Python 3 installation.

How to Install docker on Linux?

You can install docker on Linux in four steps:

  1. Open your Linux terminal or shell
  2. Type “pip install docker” (without quotes), hit Enter.
  3. If it doesn’t work, try 'pip3 install docker' or “python -m pip install docker“.
  4. Wait for the installation to terminate successfully.

The package is now installed on your Linux operating system.

How to Install docker on macOS?

Install Jupiter Notebook Docker Windows 10

Similarly, you can install docker on macOS in four steps:

  1. Open your macOS terminal.
  2. Type “pip install docker” without quotes and hit Enter.
  3. If it doesn’t work, try 'pip3 install docker' or “python -m pip install docker“.
  4. Wait for the installation to terminate successfully.

The package is now installed on your macOS.

How to Install docker in PyCharm?

Given a PyCharm project. How to install the docker library in your project within a virtual environment or globally? Here’s a solution that always works:

  • Open File > Settings > Project from the PyCharm menu.
  • Select your current project.
  • Click the Python Interpreter tab within your project tab.
  • Click the small + symbol to add a new library to the project.
  • Now type in the library to be installed, in your example 'docker' without quotes, and click Install Package.
  • Wait for the installation to terminate and close all pop-ups.

Install Jupiter Notebook Docker Download

Here’s the general package installation process as a short animated video—it works analogously for docker if you type in “docker” in the search field instead:

Make sure to select only “docker” because there may be other packages that are not required but also contain the same term (false positives):

How to Install docker in a Jupyter Notebook?

To install any package in a Jupyter notebook, you can prefix the !pip install my_package statement with the exclamation mark '!'. This works for the docker library too:

This automatically installs the docker library when the cell is first executed.

How to Resolve ModuleNotFoundError: No module named ‘docker’?

Install Jupyter Notebook DockerInstall jupyter notebook docker free

Say you try to import the docker package into your Python script without installing it first:

Because you haven’t installed the package, Python raises a ModuleNotFoundError: No module named 'docker'.

To fix the error, install the docker library using “pip install docker” or “pip3 install docker” in your operating system’s shell or terminal first.

See above for the different ways to install docker in your environment.

Improve Your Python Skills

If you want to keep improving your Python skills and learn about new and exciting technologies such as Blockchain development, machine learning, and data science, check out the Finxter free email academy with cheat sheets, regular tutorials, and programming puzzles.

Join us, it’s fun! 🙂

Jupyter Notebook

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

Install Jupyter Notebook Docker

To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.

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His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.

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