Jupyter notebook is an excellent application used by many companies and developers to quickly combine code, documentation, and visuals in an interactive document. We can easily edit and share the notebook based on the need. In this blog, I will explain how to get started with docker jupyter notebook and will go over:
- What is a jupyter notebook?
- What are the advantages and disadvantages of a jupyter notebook?
- What all jupyter notebooks are available.
- We will install a few useful notebooks and try basic commands.
- A few extra tips.
Now let’s get started with what a jupyter notebook is.
What is a jupyter notebook?
As per jupyter.org, The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. Uses include data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Let’s further understand a few advantages and disadvantages of the jupyter notebook.
Advantages of jupyter notebook
Jupyter notebook provides many advantages; below, I have listed a few of them.
- We can easily visualize the data in the jupyter notebook itself there is no need to install any separate tool for data visualization.
- Code can be shared easily with jupyter notebooks. you can easily view code, execute it, and display the output directly in your notebook itself.
- Jupyter Notebooks come in handy if we wish to prepare documentation. We can easily create the documentation with the notebook.
- Jupyter notebooks are not static it means we can edit the code, delete the code and even rerun the code based on the need.
Limitations of jupyter notebook
Although the jupyter notebook has plenty of advantages, it has a few limitations as well; some of them are:
- Sometimes It is very hard to test long tasks.
- Running Jupiter notebook standalone is Less secure.
- If you run any cell multiple times, a cell will be out of order.
- There is no support for any IDE integration, lining, or code-style correction.
Now we understand the advantages and disadvantages of jupyter notebooks; let’s further check what jupyter notebooks are available in jupyterhub.
How many docker Jupyter notebooks are available?
There are many ready-to-use docker jupyter notebooks are available in dockerhub. You can use these available notebooks to deploy the jupyter instance quickly.
To get the list of available jupyter notebooks, go to Dockerhub and search for the jupyter notebooks.
There are approx. 12k ready-to-use notebooks available. Out of these the most used notebooks are:
- jupyter/scipy-notebook
- jupyter/datascience-notebook
- jupyter/tensorflow-notebook
- jupyter/all-spark-notebook
- jupyterhub/jupyterhub
This tutorial will install some of the above notebooks and try some basic commands. Let’s first start with a scipy jupyter notebook.
Install scipy docker jupyter notebook
To install the jupyter notebook using docker, make sure docker is installed in your system. Let’s verify that the docker is running:
➜ docker --version Docker version 20.10.3, build 48d30b5
Now pull the jupyter image from the dockerhub. It might take a few minutes to download the image from dockerhub.
➜ docker pull jupyter/scipy-notebook Using default tag: latest latest: Pulling from jupyter/scipy-notebook 345e3491a907: Pull complete 57671312ef6f: Pull complete 5e9250ddb7d0: Pull complete e1fadee31091: Pull complete 70fa05f53554: Pull complete 4f4fb700ef54: Pull complete 80d0a768e52d: Pull complete b8e1ae373de6: Pull complete c13247cfb65f: Pull complete eddf77815124: Pull complete 35ffc5e5dc79: Pull complete 97e18716b9a2: Pull complete cdca71acba1b: Pull complete c8469b528abe: Pull complete fa53d08fc996: Pull complete 99cac836faeb: Pull complete 5f8cc05626db: Pull complete c40336035c20: Pull complete e03bfd4d9306: Pull complete 24020b1ee2d6: Pull complete Digest: sha256:bb88f28940581b4729d01f18c62fb1e215f99ca0ab2977ecc9631417420b0161 Status: Downloaded newer image for jupyter/scipy-notebook:latest docker.io/jupyter/scipy-notebook:latest
We have pulled a jupyter-SciPy notebook. So with the help of this notebook, we can perform scipy operations in this notebook.
For people who are not aware of scipy, it is an open-source python library mainly used for scientific and technical computing.SciPy contains optimization, linear algebra, integration, interpolation, image processing, ODE solvers, and other tasks common in science and engineering. To get more information about scipy, visit this link.
Now let’s run the docker image.
docker run -p 8888:8888 jupyter/scipy-notebook
WARN: Jupyter Notebook deprecation notice https://github.com/jupyter/docker-stacks#jupyter-notebook-deprecation-notice.
Executing the command: jupyter notebook
[I 14:45:35.105 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret
[W 2021-06-09 14:45:38.121 LabApp] 'ip' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 14:45:38.122 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 14:45:38.123 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 14:45:38.125 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[I 2021-06-09 14:45:38.147 LabApp] JupyterLab extension loaded from /opt/conda/lib/python3.9/site-packages/jupyterlab
[I 2021-06-09 14:45:38.148 LabApp] JupyterLab application directory is /opt/conda/share/jupyter/lab
[I 14:45:38.163 NotebookApp] Serving notebooks from local directory: /home/jovyan
[I 14:45:38.164 NotebookApp] Jupyter Notebook 6.4.0 is running at:
[I 14:45:38.166 NotebookApp] http://f7e880dcefd7:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682
[I 14:45:38.167 NotebookApp] or http://127.0.0.1:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682
[I 14:45:38.170 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 14:45:38.221 NotebookApp]
To access the notebook, open this file in a browser:
file:///home/jovyan/.local/share/jupyter/runtime/nbserver-7-open.html
Or copy and paste one of these URLs:
http://f7e880dcefd7:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682
or http://127.0.0.1:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682As instructed from the above output, let’s go to
http://127.0.0.1:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682 to access jupyter notebook.
If you are getting below the screen, it means your installation is successful
Create notebook
To create a new notebook, Goto New>Python3
The below screen will be opened in a new window with a notebook name untitled.
If you wish to change the notebook name, click on the untitled and change name as per your need. For this demo, I am renaming the notebook as naivetech-demo1.
Run Jupyter notebook
Now let’s type your first command, “print(“hello-world”),” and click on the run button to run the notebook.
Type a comment in the notebook followed by the ### sign to add a comment.
Click on Markdown and Run the cell.
Now let’s try a few more commands in the jupyter notebook.
Similarly, you can try a few other tutorials.
Save notebook
If you wish to save your notebook. Goto file> Download as > pdf
You can download the notebook in various formats and share it with other people.
Stop a jupyter notebook
If you wish to stop the jupyter notebook, open another window in the command line.
Check how many containers are running.
➜ docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES f7e880dcefd7 jupyter/scipy-notebook "tini -g -- start-no…" About an hour ago Up About an hour 0.0.0.0:8888->8888/tcp eloquent_mestorf
Get the container id from the above command and type the below command to stop the jupyter container.
➜ ~ docker kill f7e880dcefd7 f7e880dcefd7
Try to access the below URL again. It won’t be accessible anymore.
http://127.0.0.1:8888/?token=f2e0ebe6f5cdf2ae60217acb8f4e01a30f785e85ee255682
Now we are done with the scipy notebook. Let’s proceed further and install a data science notebook
Install Jupyter data science jupyter notebook
The data science notebook comes with preinstalled python, sklearn, pandas, NumPy, and a few other essential libraries.
Run the below command to set up a jupyter data science notebook.
➜ docker run -p 8888:8888 jupyter/datascience-notebook
WARN: Jupyter Notebook deprecation notice https://github.com/jupyter/docker-stacks#jupyter-notebook-deprecation-notice.
Executing the command: jupyter notebook
[I 16:15:47.280 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret
[W 2021-06-09 16:15:53.193 LabApp] 'ip' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 16:15:53.194 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 16:15:53.194 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[W 2021-06-09 16:15:53.194 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release.
[I 2021-06-09 16:15:53.320 LabApp] JupyterLab extension loaded from /opt/conda/lib/python3.9/site-packages/jupyterlab
[I 2021-06-09 16:15:53.327 LabApp] JupyterLab application directory is /opt/conda/share/jupyter/lab
[I 16:15:53.399 NotebookApp] Serving notebooks from local directory: /home/jovyan
[I 16:15:53.399 NotebookApp] Jupyter Notebook 6.4.0 is running at:
[I 16:15:53.399 NotebookApp] http://d749379a59b1:8888/?token=8dbe08adfba01139080942335d9764accfe19a4d43ca35dc
[I 16:15:53.400 NotebookApp] or http://127.0.0.1:8888/?token=8dbe08adfba01139080942335d9764accfe19a4d43ca35dc
[I 16:15:53.400 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 16:15:53.503 NotebookApp]
To access the notebook, open this file in a browser:
file:///home/jovyan/.local/share/jupyter/runtime/nbserver-8-open.html
Or copy and paste one of these URLs:
http://d749379a59b1:8888/?token=8dbe08adfba01139080942335d9764accfe19a4d43ca35dc
or http://127.0.0.1:8888/?token=8dbe08adfba01139080942335d9764accfe19a4d43ca35dcFollow the instruction mentioned in the console output to access the web UI.
Now let’s create a new python notebook
Now let’s try to run a simple data science model
And you can see data science packages readily available in this installation. We don’t need to set up anything else apart from this to get started. This is very useful if you want to quickly try out a few models without worrying about tools and the dependent packages.
Let’s kill this data science jupyter notebook and try another notebook
➜ docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES d749379a59b1 jupyter/datascience-notebook "tini -g -- start-no…" 15 minutes ago Up 15 minutes 0.0.0.0:8888->8888/tcp elated_galois ➜ docker kill d749379a59b1 d749379a59b1
Install Jupyter TensorFlow notebook
Tensorflow is an open-source AI library that uses data flow graphs to build models. It allows developers to create large-scale neural networks with multiple layers. TensorFlow is used primarily for Classification, Perception, Understanding, Discovering, and Prediction.
Run the below command to set up the TensorFlow notebook.
docker run -p 8888:8888 jupyter/tensorflow-notebook Unable to find image 'jupyter/tensorflow-notebook:latest' locally latest: Pulling from jupyter/tensorflow-notebook 345e3491a907: Already exists 57671312ef6f: Already exists 5e9250ddb7d0: Already exists e1fadee31091: Already exists 70fa05f53554: Already exists 4f4fb700ef54: Already exists 80d0a768e52d: Already exists b8e1ae373de6: Already exists c13247cfb65f: Already exists eddf77815124: Already exists 35ffc5e5dc79: Already exists 97e18716b9a2: Already exists cdca71acba1b: Already exists c8469b528abe: Already exists fa53d08fc996: Already exists 99cac836faeb: Already exists 5f8cc05626db: Already exists c40336035c20: Already exists e03bfd4d9306: Already exists 24020b1ee2d6: Already exists 3ace684ab257: Pull complete Digest: sha256:41a30c35ad7a1aa118a0690547d0e26c605d2dd8a7876a198255054f24731080 Status: Downloaded newer image for jupyter/tensorflow-notebook:latest WARN: Jupyter Notebook deprecation notice https://github.com/jupyter/docker-stacks#jupyter-notebook-deprecation-notice. Executing the command: jupyter notebook [I 16:39:09.963 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret [W 2021-06-09 16:39:19.670 LabApp] 'ip' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release. [W 2021-06-09 16:39:19.671 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release. [W 2021-06-09 16:39:19.671 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release. [W 2021-06-09 16:39:19.671 LabApp] 'port' has moved from NotebookApp to ServerApp. This config will be passed to ServerApp. Be sure to update your config before our next release. [I 2021-06-09 16:39:19.734 LabApp] JupyterLab extension loaded from /opt/conda/lib/python3.9/site-packages/jupyterlab [I 2021-06-09 16:39:19.734 LabApp] JupyterLab application directory is /opt/conda/share/jupyter/lab [I 16:39:19.780 NotebookApp] Serving notebooks from local directory: /home/jovyan [I 16:39:19.781 NotebookApp] Jupyter Notebook 6.4.0 is running at: [I 16:39:19.782 NotebookApp] http://a36a0722dca8:8888/?token=a6c0f54750e9fcbd253d30cc4403d69020d5f2c3e9f17de6 [I 16:39:19.783 NotebookApp] or http://127.0.0.1:8888/?token=a6c0f54750e9fcbd253d30cc4403d69020d5f2c3e9f17de6 [I 16:39:19.785 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
Go to http://127.0.0.1:8888/?token=a6c0f54750e9fcbd253d30cc4403d69020d5f2c3e9f17de6 to access the TensorFlow notebook.
Now let’s create a new python notebook.
For this demo, I will be using mnist data set to train the model. To get more information about the mnist dataset, follow this link:
Try importing TensorFlow and train some models using the mnist dataset.
Conclusion
Finally, we have come to the end of this fantastic tutorial. We started with the basics of the jupyter notebook, and we went deep dive and installed scipy, data science, and the TensorFlow library. We have also seen some of the advantages and disadvantages of the jupyter notebook. I hope you like this tutorial. Please do let me know in the comment box, and I will be more than happy to get your feedback.
Happy learning:)
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