Dear VS Code users,
The March release of SonarLint for VS Code is available and it is packed with new functionality.
We have heard from many data scientists that they would like to detect issues in their Jupyter Notebooks. SonarLint now scans Python/IPython code in Jupyter Notebooks and ensure the code written by data scientists is:
- Reliable, i.e. produces the effects for what is has been written for.
- Clear and maintainable, i.e. other data scientists can easily understand it and collaborate by adding new code in an existing notebook.
The analysis of Jupyter notebooks works like for any other source file supported by SonarLint: you simply open the notebook and issues in your code will be squiggled in the code editor and listed in the Problems view. You can use SonarLint rule descriptions to better understand the issues and and correct them with quick fixes.
This is the first release that supports Jupyer Notebooks, we hope this will be useful and at the same time we welcome your feedback so that we can improve and make SonarLint better and better for data analysis.
Good news also for Go developers, thanks to your feedback we’ve decided to prioritize this feature and Go analysis is now available for all our VS Code users!
Speaking about feedback, we’ve added a new “Help and feedback” view in the SonarLint view container, that contains handy links that you can use should you have any questions or encounter any issues using SonarLint.
You can read more about this version in the release notes here.
Enjoy and don’t hesitate to share your feedback!