Unlocking Smarter Code Navigation and Lightning-Fast IntelliSense: Python in VS Code March 2026 Update

Welcome to the March 2026 update for the Python extension in Visual Studio Code! This release introduces two powerful enhancements designed to supercharge your development workflow. First, you can now search for Python symbols across installed packages directly within your workspace, making it easier to explore libraries without leaving the editor. Second, an experimental Rust-based parallel indexer promises up to 10x faster performance for large projects. These features are opt-in and customizable, giving you control over your environment. Dive into the details below to see how they can transform your coding experience.

1. How does the new symbol search work for installed packages?

When you’re working with a new codebase or an unfamiliar library, finding where a function or class is defined can be time-consuming. With the March 2026 release, Pylance extends its Workspace Symbol search (accessible via Cmd/Ctrl+T) to include symbols from packages installed in your active virtual environment. This means you can locate definitions in third-party libraries without opening external documentation or leaving VS Code. For libraries without py.typed files, only symbols exported through __init__.py or __all__ are included, keeping results relevant. This feature is opt-in by default to protect performance, and you can fine-tune how deeply Pylance indexes each package using the Python › Analysis: Package Index Depths setting.

2. How do I enable symbol search in my virtual environment?

Activating this feature is straightforward. Open your settings (Cmd+, or Ctrl+,) and search for “Include Venv In Workspace Symbols.” Check the box under the Python › Analysis section. Once enabled, your workspace symbol searches will automatically include definitions from site-packages in your active virtual environment. This allows you to navigate into library code directly from your search results. If you want to limit indexing depth to avoid slowdowns on large projects, adjust the Package Index Depths setting to control how many sub-module levels Pylance explores. This gives you a tailored balance between comprehensive search and performance.

3. What is the experimental Rust-based parallel indexer?

Pylance’s indexing engine powers features like completions, auto-imports, and workspace symbol search. In this release, we’re introducing an experimental setting that switches the indexer to a new Rust-based parallel implementation running outside the main process. In internal tests, this indexer achieves an average 10× speed improvement on large Python projects. That translates to faster completions after opening a workspace and a more responsive IntelliSense experience overall. The setting is intentionally experimental to validate performance and reliability across diverse project setups before making it the default. It’s most impactful on larger codebases; small projects may see little difference.

4. How can I try the Rust-based parallel indexer?

To enable this experimental feature, open your settings (Cmd+, or Ctrl+,) and search for “Parallel Indexing.” Check the box labeled Enable Parallel Indexing (Experimental) under Python › Analysis. Alternatively, you can add the following to your settings.json file: "python.analysis.enableParallelIndexing": true. After enabling, reload VS Code (Cmd/Ctrl+Shift+P → Reload Window) to ensure the new indexer starts cleanly. Remember, this is a trial feature—your feedback helps us decide if and when it becomes the default.

5. What performance gains should I expect with the new indexer?

Our testing shows that the Rust-based parallel indexer delivers an average 10× speed increase on large Python projects. This means noticeably faster auto-completions and workspace symbol searches after you open a project. However, the actual gain depends on your project size and complexity. For smaller projects, you might not notice a significant difference because the existing indexer is already fast enough. The primary benefit shines in projects with many files, deep package dependencies, or large virtual environments. If you work on such projects, enabling this setting could dramatically improve your daily coding flow. We encourage you to try it and let us know how it works in your environment.

6. Are there any configuration options to fine-tune the new features?

Yes, both features offer customization to match your needs. For the symbol search in packages, the Package Index Depths setting (Python › Analysis: Package Index Depths) controls how many sub-module levels Pylance indexes per package, preventing performance hits from deep recursion. For the parallel indexer, there’s only the single enable/disable toggle for now, but future releases may offer finer controls based on user feedback. Both settings can be accessed via the VS Code Settings UI or directly in your settings.json. Remember that the symbol search feature is opt-in to avoid impacting all users, while the indexer is experimental, so your adjustments help shape future defaults.

7. How can I provide feedback on these features?

Your input is crucial! If you try either feature—especially the experimental Rust-based indexer—please share your experience with the team. You can report issues, suggest improvements, or share performance observations via the Python extension GitHub repository or the Pylance feedback channel. Let us know if you notice faster completions, any slowdowns, or unexpected behavior. Your feedback helps us refine these tools for the entire VS Code Python community.