virtualenv is a third-party command-line tool that creates isolated Python environments. Each environment is a directory with its own Python interpreter and `site-packages`, so packages installed in it do not affect the system Python or other environments. virtualenv predates the standard library's venv module and remains the more featureful of the two.

What is the difference between virtualenv and venv?

venv is a module in the Python standard library (added in Python 3.3); virtualenv is a separate package installed from PyPI. Both create isolated Python environments with the same general layout, but virtualenv is faster (it caches and reuses seed packages instead of bootstrapping pip on every create), supports more Python interpreters, including Python 2 and PyPy, and offers more configuration knobs. venv is enough for most projects on Python 3.3 or later and avoids the extra dependency.

Should I use virtualenv or venv?

For a new project on Python 3.3 or later, prefer venv: it ships with Python, requires no extra install, and covers the standard create-and-activate workflow. Reach for virtualenv when you need its faster environment creation, support for Python 2 or PyPy, or features venv does not expose. For a fully managed workflow, uv creates and manages environments automatically as part of `uv run` and `uv sync`, removing most manual steps either tool requires.

Does virtualenv install Python?

No. virtualenv only creates a new environment that points at an existing Python interpreter; it does not download or install Python itself. Use a tool like pyenv or uv to install Python versions, then use virtualenv (or venv) to create environments that target them.

virtualenv: Python Virtual Environment Tool

by Tim Hopper

Virtual Environments

virtualenv creates isolated Python virtual environments. Virtual environments are self-contained directories that contain a Python installation for a particular version of Python, plus additional packages.

When to use virtualenv

virtualenv fits projects that need broader Python version support than the standard library’s venv module offers, or that benefit from its faster environment creation through cached seed packages. Most modern projects on Python 3.3 or later can use venv, which ships in the standard library and covers the same core workflow without an extra dependency. For new work, uv creates and manages virtual environments automatically as part of its run and sync commands, removing most of the manual steps either tool requires.

Core Functionality

Creates isolated Python environments with their own site directories
Installs pip into virtual environments for package management
Provides activation scripts to easily switch between environments
Supports multiple Python interpreters and versions

Design Philosophy

virtualenv solves dependency conflicts and version management by providing isolation between Python environments. Each environment maintains its own independent set of Python packages that won’t interfere with the global Python installation or other virtual environments.

What virtualenv Doesn’t Handle

Installing Python versions (use tools like pyenv or uv for this)
Project dependency management (use pip or other package managers)
Packaging and distribution of Python applications
Environment activation across different shell sessions

Pros

Lightweight and focused on one core task
Stable
Well-integrated with pip and the Python ecosystem

Cons

Manual environment activation required
No automatic dependency management
Can be confusing for beginners
Limited project management features
No built-in support for project requirements files
Requires understanding of Python environments

Learn More

Last updated on May 5, 2026

venv Wheel

Please submit corrections and feedback...