Launching the Notebook Server
To start a notebook server using a command-line interface, open the Terminal/Anaconda prompt, and navigate to the directory where you’d like to create notebook files (
.ipynb). You can confirm the present working directory using
Next, enter the following command in your terminal/Anaconda prompt
The command above will start the Notebook server in the current directory. Typically you’d want to start the server in the directory where your existing-notebooks reside. However, you can navigate through your file system to where the notebooks are present.
Unable to Start the Jupyter Notebook Server?
Try troubleshooting the problem with the help of this post –
What to do when things go wrong? Notebook Server Walkaround
When you run the
jupyter notebook command (try it yourself!), the server home should open in your browser. By default, the notebook server runs at
http://localhost:8888. If you aren’t familiar with this,
localhost means your computer and
8888 is the port the server is communicating on. As long as the server is still running, you can always come back to it by going to
http://localhost:8888 in your browser.
If you start another server, it’ll try to use port
8888, but since it is occupied, the new server will run on port
8889. Then, you’d connect to it at
http://localhost:8889. Every additional notebook server will increment the port number like this.
If you tried starting your own server, it should look something like this:
Create a New Notebook
Over on the right, you can click on “New” to create a new notebook, text file, folder, or terminal. The list under “Notebooks” shows the kernels you have installed. Here I’m running the server in a Python 3 environment, so I have a Python 3 kernel available. You might see Python 2 here. I’ve also installed kernels for Scala 2.10 and 2.11 which you see in the list. See
this documentation for how to install kernels if you ever need to do so. Jupyter Notebook Server Tabs
The tabs at the top show
Files, Running, and Cluster. Files shows all the files and folders in the current directory. Clicking on the Running tab will list all the currently running notebooks. From there you can manage them.
Clusters previously was where you’d create multiple kernels for use in parallel computing. Now that’s been taken over by ipyparallel so there isn’t much to do there. Notebook Conda Package
You should consider installing the Notebook Conda package to help manage your environments. Run the following terminal command:
conda install nb_conda
After successful installation of the
nb_conda package, if you run the notebook server from a conda environment, you’ll also have access to the “Conda” tab shown below. Here you can manage your environments from within Jupyter. You can create new environments, install packages, update packages, export environments, and much more.
Shutting down Jupyter
You can shutdown individual notebooks by marking the checkbox next to the notebook on the server home and clicking “Shutdown.” Make sure you’ve saved your work before you do this though! Any changes since the last time you saved will be lost. You’ll also need to rerun the code the next time you run the notebook.