Jupyter Notebook on Local Machines

Overview   Installing conda   Managing Packages with conda   Installing conda packages into an existing environment   How do I know if a package is available?   Installing Jupyter   Launching Jupyter   Running Jupyter Notebook Server  

Overview  

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.

At Dartmouth, Jupyter is commonly used to interactively develop Python and R programs, but it is a versatile and extensible environment that is capable of running a broad array of languages, including C/C++, Java, Go, Matlab, and many more.

You can read more about the project at https://www.jupyter.org.

Installing conda  

The most straightforward way to install and start using a Jupyter environment is through the Anaconda distribution, which is an open-source Python distribution that includes the conda package manager that makes installing, maintaining, and upgrading Python and R environments straightforward.

Detailed installation instructions found at Anaconda.com are linked below:

Managing Packages with conda  

We are only listing a few of the more useful commands here. You can add --help to the end of any conda command to get some help on how to use it.

Complete documentation for conda can be found at https://conda.io/projects/conda/en/latest/.

  • conda create - make a new environment
  • conda env remove - remove an existing environment
  • conda info -envs - show environments
  • conda install <package name> - add a package to an environment
  • conda remove <package name> - remove a package from an environment
  • conda list - show packages installed in an environment
  • conda search <package name> - show available packages
  • conda activate <environment name> - activate (use) an environment
  • conda deactivate - deactivate an environment

Installing conda packages into an existing environment  

Using the conda install command, you can request multiple packages on the command line and specify (or not) a version for each one. Here is an example of installing a specific version of the numpy package and whatever is current for the ldap3 package into the myenv environment.

Note: part of what conda does dependencies so you would also be installing a couple dozen packages required by numpy and jupyter, if you run this command:

conda install numpy=1.16.2 jupyter

How do I know if a package is available?  

Use the conda search command for this or search for the package on Anaconda.org. You will find that a vast majority of the Python packages are supported by Anaconda or one of the community maintained channels.

Installing Jupyter  

Since Jupyter is merely a Python package, you can use conda to simply install Jupyter as follows:

conda install jupyter

This will install the latest Anaconda supported versions of Jupyter and Python along with all the necessary dependencies.

Launching Jupyter  

  • Windows. From the Start menu, search for and open “Anaconda Prompt”:
Installing Jupyter on Windows

  • macOS. Open Launchpad, then click the terminal icon.

  • Linux. Open a terminal window.

Running Jupyter Notebook Server  

Now that you have a terminal or Anaconda Prompt window open, to launch a Jupyter notebook server type jupyter notebook.

This will automatically open a new web browser window or tab and show the Notebook Dashboard.

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