How To Set Up a Jupyter Notebook to Run IPython on Ubuntu 16.04

How To Set Up a Jupyter Notebook to Run IPython on Ubuntu 16.04
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Ubuntu 16.04


IPython is an interactive command-line interface to Python. Jupyter Notebook offers an interactive web interface to many languages, including IPython.

This article will walk you through setting up a server to run Jupyter Notebook as well as teach you how to connect to and use the notebook. Jupyter notebooks (or simply notebooks) are documents produced by the Jupyter Notebook app which contain both computer code (e.g. Python) and rich text elements (paragraph, equations, figures, links, etc.) which aid in presenting reproducible research.

By the end of this guide, you will be able to run Python 2.7 code using Ipython and Jupyter Notebook running on a remote server. For the purposes of this tutorial, Python 2 (2.7.x) is used since many of the data science, scientific computing, and high-performance computing libraries support 2.7 and not 3.0+.


To follow this tutorial, you will need the following:

All the commands in this tutorial should be run as a non-root user. If root access is required for the command, it will be preceded by sudo. Initial Server Setup with Ubuntu 16.04 explains how to add users and give them sudo access.

Step 1 — Installing Python 2.7 and Pip

In this section we will install Python 2.7 and Pip.

First, update the system’s package index. This will ensure that old or outdated packages do not interfere with the installation.

  1. sudo apt-get update

Next, install Python 2.7, Python Pip, and Python Development:

  1. sudo apt-get -y install python2.7 python-pip python-dev

Installing python2.7 will update to the latest version of Python 2.7, and python-pip will install Pip which allows us to manage Python packages we would like to use. Some of Jupyter’s dependencies may require compilation, in which case you would need the ability to compile Python C-extensions, so we are installing python-dev as well.

To verify that you have python installed:

  1. python --version

This will output:

Python 2.7.11+

Depending on the latest version of Python 2.7, the output might be different.

You can also check if pip is installed using the following command:

  1. pip --version

You should something similar to the following:

pip 8.1.1 from /usr/lib/python2.7/dist-packages (python 2.7)

Similarly depending on your version of pip, the output might be slightly different.

Step 2 — Installing Ipython and Jupyter Notebook

In this section we will install Ipython and Jupyter Notebook.

First, install Ipython:

  1. sudo apt-get -y install ipython ipython-notebook

Now we can move on to installing Jupyter Notebook:

  1. sudo -H pip install jupyter

Depending on what version of pip is in the Ubuntu apt-get repository, you might get the following error when trying to install Jupyter:

You are using pip version 8.1.1, however version 8.1.2 is available. You should consider upgrading via the 'pip install --upgrade pip' command.

If so, you can use pip to upgrade pip to the latest version:

  1. sudo -H pip install --upgrade pip

Upgrade pip, and then try installing Jupyter again:

  1. sudo -H pip install jupyter

Step 3 — Running Jupyter Notebook

You now have everything you need to run Jupyter Notebook! To run it, execute the following command:

  1. jupyter notebook

If you are running Jupyter on a system with JavaScript installed, it will still run, but it might give you an error stating that the Jupyter Notebook requires JavaScript:

Jupyter Notebook requires JavaScript. Please enable it to proceed. ...

To ignore the error, you can press Q and then press Y to confirm.

A log of the activities of the Jupyter Notebook will be printed to the terminal. When you run Jupyter Notebook, it runs on a specific port number. The first notebook you are running will usually run on port 8888. To check the specific port number Jupyter Notebook is running on, refer to the output of the command used to start it:

[I NotebookApp] Serving notebooks from local directory: /home/sammy [I NotebookApp] 0 active kernels [I NotebookApp] The Jupyter Notebook is running at: http://localhost:8888/ [I NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

If you are running Jupyter Notebook on a local Linux computer (not on a Droplet), you can simply navigate to localhost:8888 to connect to Jupyter Notebook. If you are running Jupyter Notebook on a Droplet, you will need to connect to the server using SSH tunneling as outlined in the next section.

At this point, you can keep the SSH connection open and keep Jupyter Notebook running or can exit the app and re-run it once you set up SSH tunneling. Let’s keep it simple and stop the Jupyter Notebook process. We will run it again once we have SSH tunneling working. To stop the Jupyter Notebook process, press CTRL+C, type Y, and hit ENTER to confirm. The following will be displayed:

[C 12:32:23.792 NotebookApp] Shutdown confirmed [I 12:32:23.794 NotebookApp] Shutting down kernels

Step 4 — Connecting to the Server Using SSH Tunneling

In this section we will learn how to connect to the Jupyter Notebook web interface using SSH tunneling. Since Jupyter Notebook is running on a specific port on the Droplet (such as :8888, :8889 etc.), SSH tunneling enables you to connect to the Droplet’s port securely.

The next two subsections describe how to create an SSH tunnel from 1) a Mac or Linux and 2) Windows. Please refer to the subsection for your local computer.

SSH Tunneling with a Mac or Linux

If you are using a Mac or Linux, the steps for creating an SSH tunnel are similar to the How To Use SSH Keys with DigitalOcean Droplets using Linux or Mac guide except there are additional parameters added in the ssh command. This subsection will outline the additional parameters needed in the ssh command to tunnel successfully.

SSH tunneling can be done by running the following SSH command:

  1. ssh -L 8000:localhost:8888 your_server_username@your_server_ip

The ssh command opens an SSH connection, but -L specifies that the given port on the local (client) host is to be forwarded to the given host and port on the remote side (Droplet). This means that whatever is running on the second port number (i.e. 8888) on the Droplet will appear on the first port number (i.e. 8000) on your local computer. You should change 8888 to the port which Jupyter Notebook is running on. Optionally change port 8000 to one of your choosing (for example, if 8000 is used by another process). Use a port greater or equal to 8000 (ie 8001, 8002, etc.) to avoid using a port already in use by another process. server_username is your username (i.e. sammy) on the Droplet which you created and your_server_ip is the IP address of your Droplet. For example, for the username sammy and the server address, the command would be:

  1. ssh -L 8000:localhost:8888 sammy@

If no error shows up after running the ssh -L command, you can run Jupyter Notebook:

  1. jupyter notebook

Now, from a web browser on your local machine, open the Jupyter Notebook web interface with http://localhost:8000 (or whatever port number you chose).

SSH Tunneling with Windows and Putty

If you are using Windows, you can also easily create an SSH tunnel using Putty as outlined in How To Use SSH Keys with PuTTY on DigitalOcean Droplets (Windows users).

First, enter the server URL or IP address as the hostname as shown:

Set Hostname for SSH Tunnel

Next, click SSH on the bottom of the left pane to expand the menu, and then click Tunnels. Enter the local port number to use to access Jupyter on your local machine. Choose 8000 or greater (ie 8001, 8002, etc.) to avoid ports used by other services, and set the destination as localhost:8888 where :8888 is the number of the port that Jupyter Notebook is running on. Now click the Add button, and the ports should appear in the Forwarded ports list:

Forwarded ports list

Finally, click the Open button to connect to the server via SSH and tunnel the desired ports. Navigate to http://localhost:8000 (or whatever port you chose) in a web browser to connect to Jupyter Notebook running on the server.

Step 5 — Using Jupyter Notebook

This section goes over the basics of using Jupyter Notebook. By this point you should have Jupyter Notebook running, and you should be connected to it using a web browser. Jupyter Notebook is very powerful and has many features. This section will outline a few of the basic features to get you started using the notebook. Automatically, Jupyter Notebook will show all of the files and folders in the directory it is run from.

To create a new notebook file, select New > Python 2 from the top right pull-down menu:

Create a new Python 2 notebook

This will open a notebook. We can now run Python code in the cell or change the cell to markdown. For example, change the first cell to accept Markdown by clicking Cell > Cell Type > Markdown from the top navigation bar. We can now write notes using Markdown and even include equations written in LaTeX by putting them between the $$ symbols. For example, type the following into the cell after changing it to markdown:

# Simple Equation

Let us now implement the following equation:
$$ y = x^2$$

where $x = 2$

To turn the markdown into rich text, press CTRL+ENTER, and the following should be the results:

results of markdown

You can use the markdown cells to make notes and document your code. Let’s implement that simple equation and print the result. Select Insert > Insert Cell Below to insert and cell and enter the following code:

x = 2
y = x*x
print y

To run the code, press CTRL+ENTER. The following should be the results:

simple equation results

You now have the ability to include libraries and use the notebook as you would with any other Python development environment!


Congratulations! You should be now able to write reproducible Python code and notes using markdown using Jupyter notebook running on a Droplet. To get a quick tour of Jupyter notebook, select Help > User Interface Tour from the top navigation menu.

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About the authors

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Tammy Fox


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`Hi ! Thanks for the tutorial. :)

I have the same issue as jonschull…

I have followed the explanation step by step.

I entered:

jupyter notebook --no-browser

On the terminal, everything seems to be working and I receive the following message:

Copy/paste this URL into your browser when you connect for the first time,
   to login with a token:

I copy-pasted the link in my browser to access Jupyter Notebook… but I receive the following

“Firefox ne peut établir de connexion avec le serveur à l’adresse localhost:8890” (cannot establish connection)

Could someone explain to me what I am doing wrong?



This site can’t be reached refused to connect.

On my local machine I type ** ssh -L 9000: jschull@ ** this connects happily to my remote machine: Last login: Wed May 3 04:38:37 2017 from

so I type

jupyter notebook --no-browser

Jupyter says **jschull@enable-upy:~$ jupyter notebook --no-browser [I 04:43:28.093 NotebookApp] Writing notebook server cookie secret to /run/user/1000/jupyter/notebook_cookie_secret [I 04:43:28.453 NotebookApp] Serving notebooks from local directory: /home/jschull [I 04:43:28.453 NotebookApp] 0 active kernels [I 04:43:28.453 NotebookApp] The Jupyter Notebook is running at: http://localhost:8888/?token=f1c6936414f78b7f26a817e00b582d16628cd5b34bd48f50 [I 04:43:28.454 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). [C 04:43:28.454 NotebookApp]

Copy/paste this URL into your browser when you connect for the first time,
to login with a token:

So using chrome on my Mac, I go to

Sadly the browser says **This site can’t be reached refused to connect. **

This makes me sad too ;-/


Great tutorial so far! But i get an error.

I have done everything above, but when i try to create a SSH Tunnel, it returns with an error: “Permission denied (publickey).” I am pretty new to unix systems. I tried to create the tunnel first as my new user and afterwards as root user. Both get the same error.

I have followed all steps from this previous tutorial: https://www.digitalocean.com/community/tutorials/initial-server-setup-with-ubuntu-16-04

I have added public key authentication for my user also. I have no idea why it is not working.

On installing jupyter i got this error,
Command “/usr/bin/python -u -c “import setuptools, tokenize;file=‘/tmp/pip-build-1lNXre/scandir/setup.py’;f=getattr(tokenize, ‘open’, open)(file);code=f.read().replace(‘\r\n’, ‘\n’);f.close();exec(compile(code, file, ‘exec’))” install --record /tmp/pip-nMINfY-record/install-record.txt --single-version-externally-managed --compile” failed with error code 1 in /tmp/pip-build-1lNXre/scandir/

how to resolve it please tell me.

Why does pip install ipython not work on ubuntu on do? Why does it need to be installed using apt-get instead of pip? Thanks.


I am unable to run the notebook. Terminal returns: No web browser found: could not locate runnable browser.

Executed all the instructions correctly, installed the needed packages as well as SSH tunnelling.

Please help!

Thanks Ed


This works great. In my notebook I was reading some local csv files into a dataframe, but I’m having a little trouble figuring out how to configure the path when I’m running the notebook on my droplet but accessing it with a local browser. Do I need to include the http address or the port or something?


Hi Andrew,

Thanks, it’s work. I’ve use conda package.

BTW is there any tips or tutorial how to access the jupyter notebook via domain or url ?

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