Notebooks

Jupyter Notebooks in Athena

Overview

Athena Notebooks bring the power of Jupyter notebooks directly into Athena, with added features to enhance your data analysis and coding experience.

Notebooks are an incredibly powerful tool for anyone working with data. They allow you to create and share documents that contain live code, equations, visualizations, and narrative text. Here’s a brief overview. You can code interactively, use rich text elements, visualize data, collaborate and share all in a versatile format.

Additional features

Code Completion with Llama3

One of the standout features of Athena Notebooks is the integration of a low latency LLM for code completion. This means you get smart suggestions as you type:

Intuitive Suggestions: Simply start writing a line of code or a comment about what you want to achieve, and press the Tab key. Mixtral will offer you completion suggestions based on your input.

Setup Instructions: For new users, there's a sample Jupyter notebook within Athena that guides you through setting up and making the most of Athena code completion capabilities.

Personal Notebook Environments

Every notebook environment in Athena is personal to the user, ensuring that your work remains private and tailored to your needs. This personalized approach allows for a more organized and secure way to handle your data analysis tasks.

Inactivity Timeout and Auto-save Feature

Athena Notebooks are designed to be resource-efficient, with an inactivity timeout feature:

  • Timeout After Inactivity: If you navigate away from the Athena Notebooks module or close the tab, the notebook will cease active operation after 2 minutes. This includes shutting down the kernel to conserve resources.

  • Auto-save Functionality: Despite the inactivity timeout, you don't have to worry about losing your work. The state of your notebook, including all code, text, and output cells, is saved automatically.

  • Runtime State: It's important to note that while the content of your notebook is preserved, the runtime state (variables in memory, loaded data, etc.) is not. If you return to your notebook before the session ends, you can pick up where you left off without losing this runtime state.