How to Supercharge Your Python Coding in VS Code: Two Powerful Features from the March 2026 Update

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Introduction

If you've been working with Python in Visual Studio Code, you know how important it is to navigate code quickly and get responsive IntelliSense. The March 2026 release of the Python extension (and its companion Pylance) introduces two game-changing features that can significantly boost your productivity:

• Search Python Symbols in Installed Packages – Find functions and classes from libraries you've installed, right from your workspace search.
• Experimental Rust-Based Parallel Indexer – A new indexing engine that speeds up completions and auto-imports, especially on large projects.

This guide walks you through exactly how to enable and use both features. By the end, you'll be navigating third-party code like a pro and enjoying a snappier development experience.

What You Need

Before diving in, make sure you have:

• Visual Studio Code (latest version recommended)
• Python extension for VS Code (install from the marketplace if you haven't)
• Pylance extension (it usually comes with the Python extension, but ensure it's enabled)
• A Python project with a virtual environment (venv, conda, etc.) that has some packages installed (for the symbol search feature)
• Basic familiarity with VS Code settings (the settings.json file or the Settings UI)

Part 1: Enable Search for Python Symbols in Installed Packages

When you're exploring an unfamiliar library or working in a new codebase, you often need to jump to the definition of a function or class that lives inside an installed package. In previous versions, workspace symbol search (Ctrl+T or Cmd+T) only covered your own code. Now, Pylance can include symbols from the site-packages of your active virtual environment.

Step 1: Open VS Code Settings

• Press Ctrl+, (Windows/Linux) or Cmd+, (macOS) to open the Settings editor.
• Alternatively, use the command palette (Ctrl+Shift+P / Cmd+Shift+P) and search for "Preferences: Open Settings (UI)".

Step 2: Find the New Setting

• In the Settings search bar, type Include Venv In Workspace Symbols.
• You should see the setting under Python › Analysis.

Step 3: Enable the Feature

• Check the box next to Python › Analysis: Include Venv In Workspace Symbols.
• If you prefer editing JSON, you can add this to your settings.json:

"python.analysis.includeVenvInWorkspaceSymbols": true

Step 4: Use Workspace Symbol Search

• Press Ctrl+T (Windows/Linux) or Cmd+T (macOS) to open the workspace symbol search.
• Start typing the name of a function or class that you know is defined in an installed package (e.g., DataFrame from pandas).
• You'll now see results from your own code and from the installed packages in your active virtual environment.

Step 5: Adjust Index Depth (Optional)

By default, Pylance only indexes top-level symbols from packages that don't provide py.typed files. If you need deeper indexing into sub-modules, you can fine-tune per package using the Python › Analysis: Package Index Depths setting.

• Open Settings again and search for Package Index Depths.
• Add entries in the format {"name": "package_name", "depth": 2} (depth 1 means one level of submodules).

Remember: indexing too deeply may affect performance, so only increase depth for packages you frequently explore.

Part 2: Enable the Experimental Rust-Based Parallel Indexer

The second feature is an experimental, under-the-hood improvement: Pylance's indexer is now available as a Rust-based parallel implementation that runs outside the main VS Code process. In tests, this indexer is on average 10× faster on large Python projects, meaning:

• Faster completions after opening a workspace
• Snappier auto-import suggestions
• Quicker workspace symbol search (the feature from Part 1 also benefits)

Step 1: Open VS Code Settings

• Same as before: Ctrl+, or Cmd+,.

Step 2: Find the Parallel Indexing Setting

• In the Settings search bar, type Parallel Indexing.
• Look for the option Enable Parallel Indexing (Experimental) under Python › Analysis.

Step 3: Enable It

• Check the box to enable the feature.
• Alternatively, add this to your settings.json:

"python.analysis.enableParallelIndexing": true

Step 4: Reload VS Code

• To ensure the new indexer starts cleanly, reload the window:
• Open the command palette (Ctrl+Shift+P / Cmd+Shift+P) and run Developer: Reload Window.

Step 5: Test the Difference

• Open a large Python project (or any project with many files and dependencies).
• After reload, start typing code – you should notice completions appearing much faster than before.
• If your project is small, you may not see a huge difference, but larger codebases will benefit significantly.

Important Tips and Considerations

• Symbol Search is opt-in: Because indexing installed packages can consume CPU and memory, the feature is disabled by default. Only enable it when you need to explore third-party code.
• Parallel Indexer is experimental: This feature is still being validated across different environments. If you encounter issues (e.g., slower performance, crashes), disable it and provide feedback to the team.
• Provide feedback: The Python extension team wants to hear about your experience, especially with the parallel indexer. You can report issues or suggestions via the Pylance GitHub repo.
• Combine both features: The parallel indexer also speeds up workspace symbol search, so enabling both can give you a best-of-both-worlds experience on large projects.
• Monitor performance: If you notice VS Code becoming sluggish after enabling these features, consider disabling one or both, or adjusting package index depths.

With these two new capabilities, the March 2026 release of the Python extension makes VS Code an even more powerful environment for Python development. Give them a try and let us know what you think!

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