How to Upgrade Jupyter Notebook to Python 3.7 or Higher

Learn how to effectively upgrade Jupyter Notebook to use Python `3.7` or newer with our step-by-step guide. Simplify your coding environment!
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Upgrading Jupyter Notebook to Python 3.7 or Higher

If you’re a data scientist or developer using Jupyter Notebook, you may find yourself needing to upgrade your Python version. This is particularly important when you have a newer version of Python installed, but Jupyter Notebook is running an older version. Here’s how to tackle the issue of updating Jupyter Notebook to Python 3.7 or higher.

The Problem

You’ve installed Python version 3.7.3 on your system, but when you check your Jupyter Notebook version, it displays as 3.6.8. This mismatch can lead to compatibility issues, and you may want all your projects to run with the same Python version. Despite trying to update Jupyter with commands like conda update jupyter and conda upgrade notebook, you're left with the older version within Jupyter Notebook.

Here’s a simple breakdown of the issue:

Installed Python Version: 3.7.3

Jupyter Notebook Python Version: 3.6.8

Attempts: Updates via conda didn’t solve the issue

How can you ensure that Jupyter Notebook works with your desired version of Python? Let’s explore the solution.

The Solution

The process of upgrading your Jupyter Notebook to use Python 3.7 or higher can be done with just a few simple commands. Follow these steps to ensure a smooth upgrade.

Step 1: Install Necessary Packages

Use the Anaconda Prompt (make sure it’s running in your desired virtual environment) to run the following command:

[[See Video to Reveal this Text or Code Snippet]]

This command serves two purposes:

It installs the ipython package, which is an enhanced interactive Python shell.

It ensures the jupyter package is also installed and linked correctly with your active Python version.

Step 2: Restart Jupyter Notebook

After running the installation command, remember to restart your Jupyter Notebook. Closing and reopening the notebook is vital as it allows the new configurations and updates to take effect.

Step 3: Verify the Version

To confirm that the upgrade was successful, run the following code in a new Jupyter Notebook cell:

[[See Video to Reveal this Text or Code Snippet]]

This should display 3.7.x, where x represents the sub-version of Python 3.7 that's currently installed.

Final Checks

If you still face issues: Make sure your virtual environment is activated correctly each time you run Jupyter Notebook.

Check for any additional dependencies that may need updating to ensure smooth functioning.

Conclusion

Upgrading Jupyter Notebook to work with Python 3.7 or a higher version is quite straightforward with the help of conda commands. This process not only keeps your development environment up to date but also improves compatibility with libraries and tools that require newer Python features.

Don’t hesitate to reach out if you run into any difficulties or have questions regarding the upgrade process! Happy coding with your upgraded Jupyter Notebook!