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Using Jupyter Notebook for packages /libraries management

This allows for efficient integration and self-service workflows using PIP.

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Written by Omnisient Product
Updated this week

Starting 30 September 2024, you will now be able to install your own packages/libraries for use in Jupyter Notebook, and the platform will no longer pre-install the packages on your behalf. This allows for faster integrations with the exact libraries and versions you wish to work with.

NOTE:

The installs do not persist across your different notebooks and will have to be run in a block at the beginning of the notebook.

How to Install Packages in Jupyter Notebook using PIP

Jupyter Notebook allows you to install and manage Python packages efficiently using PIP. This can speed up integrations and empower users with self-service capabilities. You can even install specific versions of libraries to ensure compatibility with your projects.

Step-by-step Guide

  1. Open your Jupyter Notebook:

    • Launch Jupyter Notebook from the Omnisient web app

  2. Insert a new code cell:

    • Click on a new cell or press B to create a new code block.

  3. Install a package using PIP:

    • In the code cell, type the following command to install any package:

      !pip install <package_name>

    • For example, to install the pandas package, use:

      !pip install pandas

  4. Install a specific version of a package:

    • If you want to install a particular version of a package, specify the version number in your command. For example:

      !pip install pandas==1.3.3

  5. Run the cell:

    • Press Shift + Enter to execute the command and install the package.

    • Jupyter will display the installation progress in the output below the code cell.

  6. Verify the installation:

    • You can verify that the package was installed successfully by importing it into a new cell:

      import pandas as pd

Available Libraries

See a full list of available libraries and packages.

Best Practices

  • Check package compatibility: Before installing, make sure the package version is compatible with your environment or other libraries you are using.

Troubleshooting

  • Permission denied error: If you encounter a permission issue, try adding the --user flag to your command:

    pythonCopy code!pip install --user <package_name>

  • Package not found: If PIP is unable to find the package, make sure that the package name is spelled correctly, or that it exists in the Python Package Index (PyPI).

By following these steps, you can quickly install and manage the libraries you need for your projects, empowering faster integrations and more flexible, self-service development workflows.

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