Mastering Python Environment Management in VS Code: Your Complete Q&A Guide
Managing Python environments in Visual Studio Code just became a whole lot simpler. The new Python Environments Extension (now generally available after a preview period) brings all your environment tools—venv, conda, pyenv, poetry, pipenv, and system Python—under one intuitive interface. No more switching between command-line tools or wrestling with configuration files. Whether you're working on a solo project or a sprawling monorepo, this extension handles discovery, creation, and switching of environments automatically, with optional speed boosts from `uv`. Below, we answer your most pressing questions about how it works, what changed, and how to get started.
What exactly does the Python Environments Extension do for me?
The Python Environments Extension gives you a single, unified workflow for managing all your Python environments directly inside VS Code. It automatically discovers environments created by popular managers like venv, conda, pyenv, poetry, pipenv, and any system-wide Python installations. The extension uses a fast Rust-based scanner called PET (Python Environment Tool) to locate environments reliably on any platform. Once discovered, you can create, delete, switch, and manage environments from one dedicated UI—no more toggling between terminals or memorizing CLI commands. For most users, the extension works out of the box: just open a Python file, and your environments are automatically listed and ready to use.
How does the extension discover my environments, and can I customize the search?
Discovery is powered by PET, the same proven engine already used in the standard Python extension. It scans your PATH, standard installation directories, and any configurable search paths. For environments in non-standard locations, you have two customization options: workspace-level search paths using glob patterns, and global search paths that apply across all your projects (useful for shared directories outside your workspace). The scanner is fast because it's written in Rust, so even large projects with many environments are handled seamlessly. If you've ever struggled with environments not showing up, the extension makes it trivial to point it to the right folders.
How do I enable the extension, and when will it become the default?
The extension is rolling out to all users over the next few weeks, gradually replacing the older environment management experience. If you want it immediately, you can opt in by setting python.useEnvsExtension to true in your VS Code settings. No additional installation is required—it works alongside the existing Python extension and requires zero setup. Just open a Python file, and the extension takes over. For those who prefer to wait, the transition will happen automatically as the rollout completes. Either way, your existing environments and workflows remain intact.
Can I create new environments directly from VS Code, and what are Quick Create and Custom Create?
Absolutely. The extension offers two ways to create environments: Quick Create and Custom Create. Quick Create is the one-click option: click the + button in the Environment Managers view, and the extension builds a new environment using your default manager, the latest Python version, and any workspace dependencies it finds in requirements.txt or pyproject.toml. You get a working environment in seconds. For more control, use Custom Create (found via the Command Palette as Python: Create Environment). Here you can choose your environment manager (venv or conda directly; for pyenv, poetry, and pipenv, discovery happens after you create them with their CLI tools), specify the Python version, name the environment, and decide which dependency files to install from. This flexibility means you stay in your editor for the entire setup process.
What is uv, and how does it speed up environment creation?
uv is a fast, Rust-based tool for creating virtual environments and installing packages. If it's installed on your system, the Python Environments Extension will use it automatically when creating venv environments—by default, via the setting python-envs.alwaysUseUv: true. This significantly speeds up environment creation and package installation, especially for large projects with many dependencies. You don't need to change your workflow; the extension detects uv and uses it transparently. If you prefer to stick with the standard venv tool, you can disable this behavior by toggling the setting off.
How does the extension help with monorepos or multi-folder projects?
The extension introduces Python Projects, a feature that lets you map specific environments to particular folders or files. This is a game-changer for monorepos, where different sub-projects may require different Python versions or dependencies. Instead of manually switching environments every time you move between folders, you define which environment belongs to which directory. The extension automatically activates the correct environment when you open a file in that folder. This eliminates the common headache of environment misalignment and makes working on large, multi-directory projects much smoother.
What managers are supported for direct creation vs. discovery only?
The extension supports venv and conda for creating environments directly from the VS Code UI—you can set up a new environment without leaving the editor. For pyenv, poetry, and pipenv, the extension discovers environments that you've already created using their respective command-line tools. In practice, this means you can manage environments from all major managers in one place, but the full create-from-UI experience is currently limited to venv and conda. Environments from any manager, once discovered, can be switched to and managed (e.g., delete, rename if supported) from the same interface.
What if I have environments in non-standard locations? How do I configure search paths?
If your environments live outside the default locations (for example, in a shared network drive or a custom project structure), you can add them to the search scope. Use workspace-level settings to specify glob patterns that match your environment directories (e.g., .myenvs/*). For directories that are shared across multiple workspaces, use global search paths in your user settings. The extension will scan these additional locations and display any environments it finds. This flexibility ensures that no matter where you keep your environments, the extension can find them automatically—no manual selection required each time you open a project.