Improving productivity in Fabric Notebooks with Inline Code Completion (Preview)
Now available in preview, Copilot Inline Code Completion is an AI-powered feature that helps data scientists and engineers write high-quality Python code faster and with greater ease.
Inspired by GitHub Copilot, this feature offers intelligent code suggestions as you type, with no commands needed. By understanding the context of your notebook, Copilot Inline Code Completion integrates with your workflow, reducing repetitive tasks, streamlining development, and making coding more intuitive and productive.
What is Inline Code Completion?
Copilot Inline Code Completion is powered by an AI model trained on millions of lines of code. It recognizes patterns in your notebook and suggests relevant code snippets, helping you:
- Write complex functions with minimal effort.
- Work faster when exploring new and unfamiliar libraries.
- Reduce syntax errors with intelligent auto-completions.
How it works
Before using inline suggestions, make sure Copilot completions is enabled in your notebook. You can turn this on using the toggle at the bottom of the screen.
- As you type, the system references relevant content from your notebook.
- It analyzes the preceding Python code to generate relevant completions.
- Suggested completions appear in light gray text; tab to accept or modify/reject as needed.
- The AI continues to learn and improve based on user patterns and feedback.
Note: Once enabled, Copilot Inline Code Completion will result in additional capacity unit consumption (CU). For more information, please refer to Copilot consumption – Microsoft Fabric.
Key features & benefits
- Smart suggestions: Copilot predicts your next lines so you can maintain your momentum.
- Fewer errors: Reduce typos and syntax errors, so you can focus on the logic.
- Minimal setup: Fabric Notebooks come with built-in inline code suggestions. No installs required, simply enable the feature and start typing.
Context-aware and evolving
Currently, Copilot Inline Code Completion supports Python and generates suggestions based on preceding cells in your notebook. Additionally, completions incorporate information from your Lakehouse schemas with a few considerations:
- If your Lakehouse contains a large number of tables or columns, only a subset can be used to inform suggestions.
- If new tables are created dynamically through Spark code, the model will not recognize them in real time.
We’re committed to expanding the contextual awareness of Copilot over time, balancing performance and relevance.
Getting started
Inline Code Completion is now available in Fabric Notebooks. Simply start coding and let Fabric Copilot improve your development experience. We would love to hear from you as we continue to refine and expand this feature. Please submit your feedback via Fabric Ideas – Microsoft Fabric Community.
For more information
Overview of Copilot for Data Science and Data Engineering in Microsoft Fabric (preview)
Privacy, security, and responsible use of Copilot for Data Science
