Visual Studio Code Python Extension: Key Updates in March 2026

Welcome to the March 2026 update of the Python extension for Visual Studio Code! This release brings two major enhancements designed to improve your code navigation and overall IntelliSense performance. First, you can now search for symbols within packages installed in your active virtual environment directly from the workspace symbol search. Second, an experimental Rust-based parallel indexer promises significantly faster indexing, especially for larger projects. Each feature is opt-in to maintain the best balance between functionality and performance. Continue reading to learn how these new tools can streamline your Python development workflow.

1. How do I search for symbols in installed Python packages using VS Code?

With the March 2026 release, Pylance can now include symbols from packages located in your active virtual environment's site-packages directory when you perform a Workspace Symbol search (triggered by Cmd/Ctrl+T). To enable this feature, open your settings (Cmd+, or Ctrl+,), search for Include Venv In Workspace Symbols, and check the box under Python > Analysis. Once activated, you can quickly jump to function or class definitions inside third-party libraries without leaving the editor or consulting external documentation. For libraries lacking a py.typed marker, only symbols exported via __init__.py or __all__ are included to keep results focused and relevant. This feature is opt-in by design because indexing installed packages can affect performance, so you only enable it when you need deeper code exploration.

2. How can I control the depth of package indexing for performance?

To fine-tune how deeply Pylance searches into sub‑modules of installed packages, use the Python > Analysis: Package Index Depths setting. This setting lets you specify per‑package the maximum recursion level for indexing. For example, if a library has a complex nested structure but you only need top‑level symbols, you can set a shallow depth to reduce resource usage. By default, indexing is limited to a sensible depth, but increasing it can provide more thorough results at the cost of slower performance. Adjusting this setting gives you granular control over the trade‑off between search completeness and editor responsiveness, especially when combined with the new venv symbol search feature.

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

The experimental Rust-based parallel indexer is a completely reworked engine behind Pylance’s completions, auto‑imports, and workspace symbol search. It runs out‑of‑process and uses parallel processing to speed up indexing. In internal testing, this new indexer demonstrated an average 10× improvement on large Python projects, meaning faster completions after opening a workspace and a more responsive IntelliSense experience overall. The indexer is still experimental because the team wants to validate its performance and reliability across a wide variety of project setups before making it the default. It’s particularly beneficial for sizable codebases, while small projects may not notice a significant difference.

4. How do I enable the experimental parallel indexer?

To enable the experimental Rust-based parallel indexer, open VS Code settings (Cmd+, or Ctrl+,), search for Parallel Indexing, and check Enable Parallel Indexing (Experimental) under Python > Analysis. Alternatively, you can add the following to your settings.json: "python.analysis.enableParallelIndexing": true. After enabling, reload VS Code (Cmd/Ctrl+Shift+P → Reload Window) to ensure the new indexer starts cleanly. This setting has the most impact on larger projects. The team encourages you to try it and provide feedback on your experience—whether you notice faster completions or any unexpected behavior—to help refine the feature before a future default rollout.

5. What feedback is needed for the experimental indexer?

The development team is actively seeking user feedback on the experimental Rust-based parallel indexer. Since this feature reworks a core part of Pylance’s performance, they want to validate it across many different environments—different operating systems, project sizes, and Python configurations. If you experience significantly faster completions, slower performance, or any errors, please report your findings through the VS Code GitHub repository or the Pylance issue tracker. Your input will help determine when the indexer becomes the default. For now, you can easily toggle it on or off to compare performance. Remember that after enabling, a full reload is required to reset the indexer, and the effect is most pronounced on larger codebases.

6. What other improvements are included in this release?

Beyond the two highlighted features, the March 2026 release includes a variety of smaller enhancements and bug fixes in both the Python extension and Pylance. You can review the complete list of changes in the respective changelogs on GitHub. These updates further refine code editing, IntelliSense accuracy, and overall stability. For developers who rely on Python in VS Code, this release represents a significant step forward in both code exploration capabilities and indexing performance—especially for those working with large codebases or unfamiliar libraries. Check the official changelogs for details on all resolved issues and minor feature improvements.