For years, Python developers have navigated a fragmented ecosystem for packaging and environment management. We stitch together pip for installation, venv or virtualenv for isolation, pyenv for version management, and tools like Poetry or pip-tools for dependency resolution. While these tools differ in scope, maintaining them creates friction, especially in CI/CD pipelines where every second counts.

Enter uv. Created by Astral (the team behind the incredibly fast Ruff linter), uv is an extremely fast Python package manager written in Rust. It is designed to be a unified successor to pip, poetry, pyenv, and more. In this post, we will look at why you should care and how to migrate your workflow.

Why Switch to uv?

The primary value proposition of uv is performance, but its long-term value is unification.

  • Speed: uv is 10-100x faster than pip and pip-tools. It uses a global cache and Copy-on-Write (CoW) on supported filesystems, meaning creating virtual environments is near-instantaneous.
  • Deterministic Resolution: Like Poetry, it generates lock files to ensure consistent deployments.
  • Python Version Management: It can download and manage Python versions for you, effectively replacing pyenv.
  • Pip Compatibility: It offers a drop-in replacement interface for standard pip commands.

Getting Started and Installation

Installing uv is a standalone process. It does not depend on Python being installed on your system beforehand.

# On macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

Practical Workflows: Migrating from Legacy Tools

Let's look at how uv replaces specific tools in your daily development cycle.

1. Replacing pip and venv

Traditionally, you would create a virtual environment and install packages. With uv, this is streamlined and significantly faster.

# Old way:
# python -m venv .venv
# source .venv/bin/activate
# pip install requests

# The uv way:
uv venv
# uv automatically detects the venv in subsequent commands
uv pip install requests

2. Replacing Pyenv (Python Version Management)

One of the most powerful features of uv is its ability to bootstrap Python itself. You no longer need to manage complex path variables or compile Python from source.

# Install a specific version of Python
uv python install 3.12

# Create a virtual environment using that specific version
uv venv --python 3.12

3. Replacing Poetry (Project Management)

If you are used to Poetry's pyproject.toml workflow, uv supports a very similar command structure for initializing projects and adding dependencies. This updates your pyproject.toml and manages the lock file (uv.lock) automatically.

# Initialize a new project
uv init my-app
cd my-app

# Add a dependency (replaces 'poetry add')
uv add fastapi

# Add a dev dependency
uv add --dev pytest

# Run a command in the environment (replaces 'poetry run')
uv run pytest

Performance at Scale

The performance difference becomes staggering when installing heavy machine learning libraries like PyTorch or TensorFlow. uv utilizes a global cache, so if you have installed a specific version of a library in any project on your machine, uv simply links it to the new environment rather than re-downloading or re-copying it.

Migration Strategy

If you have an existing requirements.txt, you can start using uv immediately without changing your project structure:

uv pip install -r requirements.txt

If you are migrating from Poetry or Pipenv, you can export your dependencies to standard formats and then let uv take over resolution:

# Generate a locked requirements file using uv's resolver
uv pip compile pyproject.toml -o requirements.txt

By unifying the toolchain, uv simplifies the "getting started" documentation for your repositories and drastically reduces CI build minutes.